Creating a User-centred Metadata Schema for Digital Comics
A study submitted in partial fulfillment of the requirements for the degree of Master of Science in Information Management
at
THE UNIVERSITY OF SHEFFIELD
by
Jeongha Son
September 2014 Abstract
Background. Due to the lack of research and commercial interest of digital comic metadata schemas, readers could face difficulties in finding digital comics. Therefore, a domain specific metadata schema should be considered and developed for supporting information seeking process digital comics.
Aims. The research aimed to create user-centred metadata for digital comics by investigating the information seeking process of digital comic users.
Methods. The research used a mixed methods approach including a combination of domain analysis and questionnaire. Domain analysis techniques were used to collect potential metadata elements for describing digital comics. A number of developed metadata schemas, commercial digital comic related websites and library catalogs were investigated. A questionnaire was also designed to investigate the information seeking process of digital comics’ users and was piloted with five digital comic readers. The URL link of the revised online questionnaire was distributed mainly by e-mail (the University of Sheffield student volunteer lists) to recruit digital comic readers (non-probability sampling). Finally, sixty-five digital comic readers took part in the survey.
Results. Firstly, using the domain analysis technique a total of sixty-nine elements were collected. These were divided mainly in to two parts (elements for general description and elements for series, volume and episode (issue) description) to describe the hierarchical structures of digital comics. Secondly, a number of findings were made about digital comic users by analysing the result of the questionnaire. Digital comic users are such active users; they like to share information. They often engage in searching for finding episodes and character information. They use title, topic, genre and main character information for formulating queries. Images of comics and story descriptions are important in identifying and extracting information. Finally, users do not often give consideration to the physical description of digital comics.
Conclusion. A set of fifty-five metadata elements as an optimal user-centred metadata schema is proposed where all elements are optional and repeatable depending on features and structures of the digital comic. For enhancing the feasibility of the metadata, the metadata schema should be revised and controlled vocabularies need to be established. Further work could include a larger number of participants and in-depth interview would be desirable.
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Acknowledgements
I gratefully acknowledge my supervisor, Prof. Paul Clough for continuing to offer his expertise, advice and support throughout this project.
I would like to thank the sixty-five digital comic readers who participated in my research.
I would also like to thank Dr. George Turner and Geoffrey Yau who supported me in developing my English academic writing skills.
Finally, I would like to dedicate this project to my parents, Heeyoung Son and Dongju Shin, for being so understanding and supportive while I completed my work; also to my sweetest sister, Jeongyeon Son and my dearest brother, Bids.
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Contents
Abstract ...... 1 Acknowledgements ...... 2
Chapter1. Introduction ...... 7 1.1. Context and Motivation ...... 7 1.2. Definition of Terms ...... 9 1.2.1. Comics and Digital Comics ...... 9 1.2.2. Metadata and Metadata Schema ...... 9 1.2.3. User-centred Metadata ...... 10 1.3. Aim and Objectives ...... 11 1.4. Structure of Dissertation ...... 12
Chapter2. Literature Review ...... 13 2.1. Comics and Digital Comics ...... 13 2.2. Comics in Information and Knowledge Management Discipline ...... 15 2.3. Information Resource Description ...... 16 2.4. User-centred Metadata ...... 18 2.5. Digital Comic Metadata Schema ...... 20
Chapter3. Methodology ...... 22 3.1. Overview of Metadata Design Process ...... 23 3.2. Domain Analysis ...... 24 3.2.1. Data Collection ...... 25 3.2.2. Data Analysis of Domain Analysis ...... 27 3.3. Questionnaire ...... 28 3.3.1. Self-completion Questionnaire ...... 29 3.3.2. Online Questionnaire Design ...... 30 3.3.3. Pilot Test ...... 32 3.3.4. Distribution and Participant ...... 33 3.3.5. Data Analysis of the Questionnaire ...... 34 3.3.6. Ethical Considerations ...... 35
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3.4. Limitations of the Methodology ...... 35
Chapter4. Results ...... 36 4.1. Results of Domain Analysis ...... 36 4.1.1. Mock up Metadata Framework ...... 36 4.2. Results of Questionnaire ...... 45 4.2.1. Participant Demographical Information ...... 46 4.2.2. Digital Comic Reading Experience ...... 47 4.2.3. Digital Comic Information Seeking Experience ...... 49 4.2.4. Summary of Information Seeking Process of Digital Comic Users ...... 65
Chapter5. Discussion ...... 68 5.1. Discussion of Findings ...... 68 5.1.1. Discussion of Mock-up Elements ...... 68 5.1.2. Discussion of Information Seeking Process of Digital Comic Users ...... 68 5.2. Proposed User-centred Metadata Schema...... 71 5.2.1. Proposed Metadata Schema ...... 72 5.2.2. Proposed Metadata Schema and Implementation ...... 74 5.2.3. Proposed Metadata Schema and Example ...... 76
Chapter6. Conclusion ...... 80 6.1. Accomplishment Aim and List of Objectives ...... 81 6.2. Limitation and Future Work ...... 82
Bibliography ...... 84
Appendix 1 Proposal for Research Ethics Review ...... 93 Appendix 2 Research Ethics Approval Letter ...... 98 Appendix 3 Online Questionnaire Consent Form ...... 99 Appendix 4 Online Questionnaire Part.1 ...... 101 Appendix 5 Online Questionnaire Part.2 ...... 102 Appendix 6 Online Questionnaire Part.3 ...... 103
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Figures and tables
Figures
Figure 1 Research onion ...... 22 Figure 2 Overview of metadata design process ...... 23 Figure 3 Self-completion online questionnaire ...... 30 Figure 4 Notion of the questionnaire design ...... 31 Figure 5 Respondents’ profile by gender ...... 46 Figure 6 Respondents’ profile by age group ...... 46 Figure 7 Respondents' profile by native language ...... 46 Figure 8 Respondents' profile by current level of study ...... 47 Figure 9 Reading experiences of respondents (types of digital comic) ...... 47 Figure 10 Reading experiences of respondents (period) ...... 48 Figure 11 Reading experiences of respondents (frequency) ...... 48 Figure 12 Reading experiences of respondents (purpose) ...... 49 Figure 13 Notion of the questionnaire design (unit 1 of part 3) ...... 49 Figure 14 Purpose of searching for information about digital comics of respondents ...... 50 Figure 15 Information sources of respondents to find the information about digital comics ...... 51 Figure 16 Notion of the questionnaire design (unit 2 of part 3) ...... 52 Figure 17 Directory preferences of respondents ...... 56 Figure 18 Notion of the questionnaire design (unit 3 of part 3) ...... 57 Figure 19 Notion of the questionnaire design (unit 4 of part 3) ...... 60 Figure 20 Levels of difficulty on the digital comic searching process of respondents ...... 63 Figure 21 Respondents’ reasons of facing difficulties in searching for information related to digital comics ...... 64
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Tables
Table 1 Alphabet codes ...... 28 Table 2 Mock up metadata (general elements) ...... 37 Table 3 Mock up metadata (status) ...... 42 Table 4 Mock up metadata (series) ...... 42 Table 5 Mock up metadata (volume) ...... 43 Table 6 Mock up metadata (issue (episode)) ...... 44 Table 7 Ranks of general elements in the question about formulating and executing queries ...... 52 Table 8 Ranks of series elements in the question about formulating and executing queries ...... 54 Table 9 Ranks of volume elements in the question about formulating and executing queries ...... 55 Table 10 Ranks of issue (episode) elements in the question about formulating and executing queries ...... 55 Table 11 Ranks of general elements in the question about examining and identifying the results ...... 57 Table 12 Ranks of series elements in the question about examining and identifying the results ...... 59 Table 13 Ranks of volume elements in the question about examining and identifying the results ...... 59 Table 14 Ranks of issue (episode) elements in the question about examining and identifying the results ...... 59 Table 15 Ranks of general elements in the question about extracting information ...... 60 Table 16 Ranks of series elements in the question about extracting information ...... 62 Table 17 Ranks of volume elements in the question about extracting information ...... 62 Table 18 Ranks of Issue (episode) elements in the question about extracting information . 62 Table 19 Top twenty elements between three processes ...... 65 Table 20 Proposed user-centred metadata schema ...... 72 Table 21 General description metadata schema implementation ...... 74 Table 22 Example of the proposed metadata ...... 77
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Creating a User-centred Metadata Schema for Digital Comics
Chapter1. Introduction
1.1. Context and Motivation
With the combination of words and sequential arts, comics are a great means of expression. They engage and entertain millions of people around the world in which ideas and stories for comics have to be developed within a very short time (Seago, 2014). Thus, they should be easy to read and at the same time offer pleasure and amusement. Despite their casual nature, the features of comics (e.g. combination of word and image, lay out, visual language and speech bubbles) should be considered as a genuine art form (Abbott, 1986; Sabin, 2001; Seago, 2014).
Recently, comics have undergone radical changes; many comics are widely published or re- published as digital content on the web with advanced digital delivery methods. One of the biggest comic publishers Marvel Comics found that the company sold more comics online than through the traditional retail environment (Kozlowski, 2014). The company launched digital archives for back issues in 2007 (BBC News, 2007) and has also been serving current digital content not only through its online website but also via mobile applications.
To manage and organise the enormous amount of digital comic contents efficiently on the web, the information resource description is required, which is often referred to as metadata (the clear definitions of metadata and metadata schema are provided on 1.2.2.) Especially in the digital environment, metadata is crucial because it provides accessibility of digital content and assists in content discovery in the large sizes of the digital content data stores. In addition, metadata supports users’ information seeking tasks in many ways such as finding, identifying selecting and obtaining content (IFRA, 2009).
The one example of supporting the digital comic users’ information seeking process via metadata functionality could be gathering. Metadata can assist to collate specific content
7 together such as by writers, genres and publishers if the element fields have relevant value. The majority of comic readers tend to select comics for reading depending upon the genres and writers (Han, 2005). Thus, comics under the same genre and writer should be collected.
Despite the growing interest in digital comics both commercially and culturally; a metadata element set for the digital comics has not been given much consideration from the view of researchers. Due to the lack of research and commercial interest of digital comic metadata schemas, it is possible to say that readers could face difficulties in finding digital comics. Harding (2014) found that there was no standardised metadata framework between the current eight comic metadata store systems, with several key metadata fields lacking.
In fact, a number of standardised metadata schemas have been released for maintaining digital contents such as Dublin Core Metadata Elements Set (DC) and Moving Picture Experts Group (MPEG). In spite of authority and high usage of these metadata schemas in the digital environment, the metadata framework which focuses on digital comics should be considered and developed. This is not only to preserve special features of digital comic contents but also because the information needs and seeking behaviours of comic-related users are different in comparison with other digital contents users.
IFRA (2009) established that metadata elements need to support four user generic tasks which are find, identify, select and obtain. Thus, a set of elements on these metadata should be carefully considered in order to support information-seeking process of digital comic users based on domain specific knowledge about digital comics.
To sum up, the standardised user-centred metadata schema for digital comics is crucially required. Thus, first, the digital comic domain needs to be examined to understand the features. Afterward, digital comic users’ information seeking process is essential in the investigation in order to create the metadata schema which provides intelligent and comprehensive way to represent and catalog digital comics.
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1.2. Definition of Terms
1.2.1. Comics and Digital Comics
It is essential to draw up a definition for comics as many terms exist to describe the format between researchers. Comics can be referred to differently depending on the country consuming it, the length of the stories or the thickness of the book; cartoon strips, graphic novels and comic books. Comics is the US term for sequential art, however, comic books may look like magazines published regularly (Caddy, 2009). On the other hand, the length of a graphic novel is similar to that of a book and consists of sequential art, and they can be a collection of short stories from several comic books. There are other terms originating from eastern countries such as manga from Japan or manhwa from South Korea (Sugiyama, 2004; Berndt, 2012).
Ways of highlighting characters and depictions subjective viewpoints could differ depending on the cultural backgrounds of countries it is produced in (Cohn, 2011). However, several essential features of comics help distinguish itself from other art forms, especially the identical visual similarity; the combination of words and sequential arts. In this dissertation for this reason, only the visual format which is a combination of words and sequential art will be considered to cover all types of Comics.
Moreover, with advanced technologies, the visual format is available in digital forms with online accessibility; such forms will be regarded as digital comics in this dissertation.
1.2.2. Metadata and Metadata Schema
Metadata The metadata is structured data or information about other data or information resource such as a book, video, digital image and digital comic (Miller, 2011).
“Metadata are structured, encoded data that describe characteristics of information- bearing entities to aid in the identification, discovery, assessment, and management of the described entities. (American Library Association, 2010)”
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There are three main types of metadata such as; first, descriptive or intellectual metadata (describing resources for discovery and identification), second, structural metadata (defining ways of creating compound objects) and administrative metadata (helping manage a resource) (NISO, 2004). Mainly, descriptive or intellectual metadata will be focused on this dissertation.
A metadata schema A metadata schema is a set of data elements. A metadata schema can also be referred to as a metadata scheme or a metadata element set (Miller, 2011).
“A metadata schema provides a formal structure designed to identify the knowledge structure of a given discipline and to link that structure to the information of the discipline through the creation of an information system that will assist the identification, discovery and use of information within that discipline. (American Library Association, 2010)”
1.2.3. User-centred Metadata
In this dissertation, the definition of user-centred metadata is that the metadata schema which reflects on how digital comic users seek (search and browse) information of related digital comics in this domain. The information seeking process of digital comic readers will be investigated and reflected in the metadata schema.
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1.3. Aim and Objectives
Aim The aim of this research is to create a user-centred metadata schema for digital comics. To achieve the aim of this research, there is a set of specific research objectives that need to be met and are as follows:
Object 1. To review related literature in the areas of: Comic and digital comics Comics in information and knowledge management discipline Information Resource Description (metadata) User-centred metadata Method of Accomplishment: Desk research in order to produce a comprehensive literature review on the digital comics, importance of standardised information resource description in information and knowledge management discipline and the possible way of designing user-centred metadata.
Object2. To collect and list potential metadata elements on literatures, library catalogs and commercial digital comic websites Method of accomplishment: Domain analysis in order to analyse empirical data on how digital comics are currently being described in three different sectors: literatures that proposed digital comic metadata schema, library catalogs which developed specialised rule of catalog comics and websites which storing and providing digital comics.
Object3. To investigate the information seeking process of digital comic readers in online environments Method of accomplishment: quantitative survey to understand digital comic users’ information needs and behaviours related to digital comics. This data will help to improve the understanding of the purpose behind digital comic searching, as well as how people search and identify digital comics, and as to what kind of information are useful for them for these tasks.
Object4. To design an optimal user-centred metadata schema for digital comics
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Method of accomplishment: Desk research in order to analyse the statistical results of the questionnaire, as well as produce the standardised user-centred metadata which reflect the features of digital comic domain and information seeking process of digital comic users.
1.4. Structure of Dissertation
This dissertation is divided into six chapters.
Chapter 1 provides a context and research motivation for carrying out this project, along with the research aim and objectives.
Chapter 2 provides a critical review of related literature in comics and digital comics, comics in information and knowledge management discipline, information resource description and user-centred metadata.
Chapter 3 provides details in the methodology design of this research which is the combination of domain analysis to collect potential elements for a digital comic metadata schema and quantitative survey to investigate the information-seeking process of digital comic users.
Chapter 4 represents details of the collected metadata elements and provides results of questionnaire.
Chapter 5 provides discussion for the description elements for digital comics, information seeking behaviour of digital comic users. Also, the proposed the user-centred metadata for digital comics will be represented.
Finally, Chapter 6 provides the conclusion, the limitation of this research and recommendations for further studies.
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Chapter2. Literature Review
This literature review will consist of five sections. The first part will discuss the current status of comics and digital comics all over the world. In the second part, there will be an analysis on how comics and digital comics are recognised in the disciple of information management. The third part will examine the purpose of information resource descriptions (metadata) and an existing metadata schema which is DC, as well as the limitations of exiting metadata schemas will be identified. The fourth will discuss existing metadata schemas which are designed to support users’ information seeking process. The last part will discuss the current research related digital comic metadata schemas and the limitation of the research. The limitation will form the basis of discussion about the requirement of user-centred metadata for digital comics.
2.1. Comics and Digital Comics
With advanced technologies, paper comics have been transferred to digital formats in order to allow for more accessibility for users (George et al., 2011; Ponsard & Fries, 2009) and reduce the cost of publishing and distribution (Kozlowski, 2014).
Comics: The Combination of words and sequential arts
Comics have become a major part of popular culture (Scott et al., 2010; Morozumi et al, 2009). Comic publishers such as Marvel Comics and DC comics release an increasingly large number of issues. Also, Manga, the Japanese term for comics, has a high popularity in Japan since the 1950’s (Morozumi et al., 2009). Manga has become a main part of the Japanese publishing industry and has also gained significant interest from worldwide readers. In Europe, comics are sometimes recognised more seriously as another form of art (Abbott, 1986; Sabin, 2001; Seago, 2013).
Digital comics
It is necessary to mention that when a sequential art format is available in digital form with online accessibility, the name of the art can also be different such as webtoons (eastern countries, specially South Korea), web comics and digital comics (Western countries).
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Morozumi et al. (2009) suggested that there are three ways to create digital comics; first, born digital; second, turned digital and third, a combination of the two.
First, webcomics can be classified under the first born digital category. Fenty et al. (2004) clarified the definition of webcomics; “…they are made first for the web, made by an independent creator … who all have no originally print version and no corporate sponsorship…”. However, depending on their cultural background Fenty et al.’s definition of webcomic could be misunderstood. Because the majority of webcomics attract a large readership in South Korea, they are born digital but they are not drawn by independent creators (Kim & Ha, 2013). The creators normally belong to the companies which have large digital comic platforms such as Naver (www.naver.com), Nate (www.nate.com) and Daum (www.daum.net). However, it is essential to point out that the tool for drawing the sequential art on the web can be the same for all types of webcomics such as Adobe Photoshop CC, Adobe Illustrator CC.
In contrast, second, back issues of Japanese manga and American superhero comics were distributed in print version but turned into digital format after a period of a few years in order to gain more young readers (BBC News, 2007).
Finally, some comics born of a combination of printed and digital format; current issues of Japanese manga and American superhero comics can be found in this format of example. However there are little differences between these two examples; American superhero comic tend to focus on digital comic market to reduce shipping costs (Kozlowski, 2014). But the Japanese manga market still relies heavily on the publishing industry because of the culture background. For this reason, the majority of manga in digital format are still kept in paper format with page numbers, even though physical page numbers may be unnecessary on the web.
Digital comic users
Ponsard & Fries (2009) discussed that enhancing digital comics’ accessibility could help a number of people with special needs by using a computer based interface. The research also categorises users into two groups: PC-oriented viewers and specialised viewers for mobile device like PDAs. As time passes, this clarification is valid but requires few changes with the development of digital technology.
The digital comic platforms moved from the web to Smart devices which can be represented by smartphones and tablet PCs (Kim & Ha, 2013). Moreover, the absence of
14 physical space might help to expand comic readership especially for female readers (George et al., 2011). In short, the development of technologies opens up the accessibility of the digital comic market to a wide range of users.
There is a lot of research in the motivations of comic reading (Wolf & Fiske, 1949) and the reading experiences of comics (Lash, 1948; Norton, 2003; Stevens & Bell, 2013). George et al. (2011) discussed that digital comic users can be more active than other contents users. Likewise, Kim & Ha (2013) found that comic readers rely on specific genres and authors when looking for comics and therefore the collection function of metadata should be stressed. In contrast, it is possible to say that there are no research investigating processes (e.g. find, identify, select and obtain digital comics) of users’ comics and digital comics searching on digital environments.
2.2. Comics in Information and Knowledge Management Discipline
Comics and digital comics have gained huge attention from academic disciplines; information literacy (Versaci, 2001; Jacobs, 2007; Schwarz, 2006), second language teaching (Cary, 2004; Ranker, 2007), education tools in the school environment (Bucher & Manning, 2004; Williams, 2008), mass media and cultural studies (Bongco, 2014; McAllister et al., 2001; Duncan & Smith, 2009). It is possible to mention that this phenomenon allows public libraries, school libraries and even academic libraries to collect comics under the name of graphic novels (book length comics (Rudiger & Schliesman, 2007)) because of user requirements.
Comics in library book shelves According to the Dewey Decimal Classification System, all types of comics should be gathered and shelved under the classification code 741.5 (Rebecca, 2006) but this solution does not reflect upon the practicalities of the real work place (Caddy, 2009). It is possible to say this problem has occurred due to the lack of understanding surrounding comics. Fletcher-Spear et al. (2005) argued that the comics should be considered as format not a genre. The statement pointed out comics could not be gathered together on the shelves simply because they share the same format.
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Catalog guidelines for Comics in Libraries Traditionally, the library cataloging has two main functions which are finding (identifying) item within large collections and collocating items under the similar subjects or same author (Cutter, 1910). Cataloging is one of way to describe information resource; it could be the most important factor to ensure the quality of information retrieval in libraries because cataloging is used for retrieval tools within large number of collections these days (Hider, 2012).
Many have researchers from information studies contributed towards the development of library collections and information resource description guidelines of comics for library use (Scott et al., 2010; Matz, 2004; Lee, 2004). For example, some libraries (e.g. University of Colorado Libraries and The Ohio State University Libraries) established special catalog guidelines for organising resource descriptions of graphic novels and Manga collections. According to the development of special catalog guidelines for comics, it is essential to highlight that the elements of comic bibliography descriptions cannot be organised in the way to catalog general collections because of the distinct features of comics.
2.3. Information Resource Description
Hider (2012) argued that information resource description is dominant to the field commonly known as information and knowledge organisation. It can be a set of elements each element describes an attribute of the information resource such as its title, subject and publication date. It is possible to say information resource description is the most important factor within large collections because it allows users to find, identify, select and obtain resources without having to examine every single item (IFLA, 2009).
Information Resource Description and Metadata It is essential to mention that information resource description is often referred to as metadata (Hider, 2012 and Heting, 2009). It is possible to argue that library catalogs could be the well-known kind of metadata (Miller, 2011).
The term “metadata” was used only in representing the resource description in the digital environment. Recently, the word embraces a broader meaning, Heting (2009: 41) pointed out two different ways of define the metadata; “…One is narrower in scope, implying
16 descriptions provided for networked information and digital resources by following a standard of framework (e.g. Dublin Core Metadata Element) that is specifically created for this purpose. The other definition is broader in coverage, including cataloging and indexing data created for any kind of documents through the use of traditional methods for describing and organising information.”.
Purpose of metadata A metadata is a set of elements those are needed to accomplish the five main purposes which are resource description; information retrieval; resource management; ownership and authenticity; and interoperability (Haynes, 2004).
Metadata is crucial to digital library development in assisting resource discovery. It is important to mention that metadata framework is vital for digital contents distribution and maintaining contents effectively (Oh et al, 2004). For this reason, in the information age, research related to metadata evaluation has received huge attention (Zhang & Li, 2008; Dushay & Hillmann, 2003; Sokvitne, 2000).
Metadata could support effective access to information resources; indicating to the prospective user to obtain items, helping the user decides whether they would be obtained and allowing the user to navigate it. It is important to highlight that the standardised metadata element sets between libraries (also digital libraries) could help to save amount of money because it allows for the sharing of records amongst libraries.
Types of metadata
Metadata frameworks can be divided into two standards which are general element sets and domain-specific element sets. DC, Functional Requirements for Bibliographic Records (FRBR), MAchine-Readable Cataloging (MARC) 21 intended to describe a wide selection of resource types for a selection of information communities (Miller, 2011). On the other, Moving Picture Experts Group Multimedia Metadata (MPEG-7 and MPEG-21), Data Documentation Initiative for social science data sets (DDI) could be a domain-specific element set to describe a specific type of resource to a given domain.
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It is important to mention that selecting (and designing) metadata frameworks should be carefully considered depending on the domain of collections, potential user groups and their information seeking behaviour.
Dublin Core Metadata Elements
In particular, DC was developed as a discovery standard for digital contents. The fifteen elements under the Dublin Core Metadata Elements (DCMI, 2014) which are title, subject, description, type, source, relation, coverage, creator, publisher, contributor, rights, date, format, identifier and language. All of elements could be extended, optional and repeatable (Miller, 2011). It is possible to say DC could be easily retrieved on the digital context.
Limitation of existing metadata schemas
It is important to design metadata schema to meet contextual requirements of potential users (Zhang & Li, 2008). However, several researchers argued that metadata development processes were frequently informal and dependent on professional experience rather than a more intentional process (Tonkin, 2007; Lee et al., 2013).
For example, despite the huge advantages of DC, some terms could be ambiguous (e.g. date) and unfamiliar for users (Fear, 2010).Moreover, users could perceive some of terms to be less useful (e.g. coverage). It can be suggested that the choosing the terms for the elements set should be careful to meet user requirements.
2.4. User-centred Metadata
Some metadata take human factors into account to support users’ searching tasks such as find, identify, select, and obtain (IFLA, 2009). However, there is little research for user centred approach and it has not received much attention from professional bodies.
Functional Requirements for Bibliographic Records
In 1997, the main focus of information resource description has been fundamentally changed for the digital environment. The International Federation of Library Associations and Institutions (IFLA) produced a final report FRBR. IFLA (2009) accredited that the importance of meeting user needs and expectation in the information resource description. Furthermore, it argued that metadata should support four generic user tasks which are the
18 find, identify, select and obtain entities. It is worth to mention that IFRA probably took the user-centred view which focuses on the study of human information behaviour, understanding of human needs, information context and content use (Chowdhury, 2010)
Domain specific user-centred Metadata Schemas
Some researchers have developed domain-specific user-centred metadata element sets such as for video game contents (Lee et al., 2013) and moving image collection (Zhang and Li, 2008). Lee et al. (2013) took domain analysis to collect potential elements on video game domain and interviewed 24 gamers to evaluate the metadata elements. Conducted interviews were used to understand their video game-related information needs and seeking behaviours. Ultimately, the developed metadata elements set for video games are very different than other types of digital contents description (e.g. Number of players, Point of view). However, it is possible to say that the metadata schema is more intelligent and comprehensive than other standardised metadata sets to represent video games.
Designing user-centred Metadata Schemas
Miller (2011: 254) established six questions to help design user-centred metadata schemas. First, how do users want to search and browse for the content of collection? Second, what information do users want to know? Third, how do users want to sort and group objects? Fourth, what are the common attributes or properties of the objects in the collection? Fifth, how do the values of those elements need to be entered and structured to enable those functions? Last, how do these elements conform and map to the standardised element set selected?
Most of all, features of contents in the collection should be consider before selecting metadata elements. Hjørland (2002) argued that domain analysis approach could be taken to get domain-specific knowledge and it can be used in order to create metadata. However, understanding users’ information-seeking process is another crucial factor in designing intelligent metadata because the metadata framework interacts with end users. It could be possible that information seeking process frameworks can be used to examine what type of information user might want to know. Considering purpose and process of information searching it would be possible to guess what information users will use to formulate queries and so on.
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For example, in Marchionini’s information-seeking process model (1995:50) it could be possible to find the interacting points between users and metadata. The first process point would be “execute query” because when the user types the query, the system will look up the metadata inventories to find any matching or relevance items. Second point would be “examine results”, before accessing the items users will look at the metadata surrogates on the result pages. The third point would be “extract information”, after the user identifies relevance items the user will access and look at the detailed structured information of contents such as size of content, released date, copyright.
2.5. Digital Comic Metadata Schema
Describing digital comic information resource by some stand raised metadata schema such as DC, the level of interoperability will be increased between other systems but some special features of the concept of digital comics can be ignored. Moreover, it is important that the terms of metadata elements should be referred to features of digital comics and its users’ searching behaviour.
Existing Digital comic metadata schema
Despite high popularity of not only digital comic contents but also metadata framework evaluation on research fields, the combined research of both is uncommon. Harding(2014) reviewed eight systems of comic book metadata storage and established the relational database format for his dissertation work. In addition Morozumi et al. (2009) also developed the metadata framework for manga. With developed metadata schemas, they have only considered a particular field of comics; American superhero comics and Japanese manga, and for this reason the research does not cover all sequential art formats.
Digital comic user-centred metadata schema
Moreover, despite of the importance of human factors, currently developed digital comic metadata schemas do not account for the information seeking tasks of digital comic users. It is necessary to mention that previous research were looking into analysing the needs of the publisher or system manager(Harding, 2014) and structure of comics (Morozumi et al., 2009) In short, the exiting metadata research did not consider the different types of resource description elements that are suitable for the user’s needs during the information
20 seeking process. Metadata framework which covers all of these features for digital comics should be considered. It is important in approving the usability of metadata schema because of users’ information seeking behaviours. Moreover, it would allow a better way to represent digital comics online and help users to retrieve required information related to digital comics.
To sum up, there is only little research available for metadata framework for digital comics despite its high popularity in public and academic disciplines. Little research has been conducted, and the research does not cover all types of digital comics and does not consider the users’ perspective. It is possible to say that the user-centred metadata schema is required to represent and organise description of digital comics more intelligently and comprehensively.
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Chapter3. Methodology
Despite the importance of metadata schema in information and knowledge management, there is no standardised metadata development processes (Tonkin, 2007; Lee et al., 2013). It is difficult to judge which techniques and methods should be selected to create the metadata framework. Therefore, approaches should be taken depending on the aim and objectives of the research.
Describing resource information for the certain type of contents to manage them is always specific. For this reason designing digital comic metadata should be strongly focused on characteristics of the type of contents. According to Hjørland (2002), the domain analysis technique can be taken to design different domain metadata based on the understanding of the specific subject knowledge.
However, toward user-centred metadata which support the digital comic users’ information seeking process, more than one approach should be engaged with domain analysis to investigate the process. It is possible to say that survey, focus groups, observation, testing can be several ways to do this. Particularly, in discovering the patterns of comic readers’ information seeking behaviour quantitative research approach can be taken with survey strategies.
For this dissertation, the methodological approach in creating the metadata schema can be described as a combination of domain analysis and questionnaire (Figure 1). It is possible to say that these mixed methods approach could be the most suitable methods to achieve the aim and objectives of this dissertation and also consideration of practicability (e.g. time amount and ethical issues). A more detailed explanation of this will be shown as followed.
Figure 1 Research onion
From “Research Methods for Business Students”, by Saunders et al. (2009) cited in Hinkelmann & Witschel (2013)
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3.1. Overview of Metadata Design Process
Figure 2 Overview of metadata design process
The research aim and objectives can be achieved through four phases (Figure 2); phase1 literature review, phase, 2 digital comic domain analysis, phase 3 questionnaires and phase 4 user-centred metadata elements evaluation.
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For phase 1, studies of digital comics and information resource description (metadata and user-centred metadata), these two main topics are reviewed to discuss current the requirement of user-centred metadata schema for digital comics. By literature review, objective 1 was accomplished.
For phase 2, digital comic domain analysis was conducted to collect potential metadata elements on digital comic domain. Hjørland (2002) and Lee et al. (2013) argued that domain analysis approach can be taken in information science to gain domain specific knowledge in order to create metadata specifically. This phase is supported to achieve objective 2. Since a sufficient number of potential elements were gathered, elements were given clear definitions and framed as a mock up metadata schema.
For phase 3, after domain analysis, quantitative research strategy is deployed to investigate the information-seeking process of digital comic users using the questionnaire. Many well- known researchers argue that users’ information-seeking behaviours are consisted of several processes (Wilson, 1999; Savolainen, 1993; Marchonini, 1995). Thus it is important to mention that to gain the complete picture of information usage and needs of users, several parts of interactive cognitive process should be investigated. For this reason, the questionnaire approach was conducted because Wong et al. (2000) claimed that interview or survey data (e.g. questionnaire) could provide a partial picture of the interaction. This approach supported to achieve objective 3.
For phase 4, analysed collected data from the questionnaire was used for evaluating user- centred metadata elements set in order to accomplish the last objective 4. The (highly) required elements from users was considered as part of the final metadata schema, however, poorly required elements was not considered for the final schema.
3.2. Domain Analysis
Main purpose of domain analysis was to collect potential metadata elements in developed digital contents metadata schemas, several digital comic related websites and some library catalogs.
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3.2.1. Data Collection
Developed metadata schema First of all, several developed metadata schema were examined. It is important to mention that by looking at developed metadata schema was significantly helpful in collecting large numbers of elements. However, most of the metadata schema was concentrated in several types of digital comics such as American super hero comics and Japanese manga. List of metadata are listed below.
- Comic Book Metadata and Database Design, Harding (2014) The researcher proposed the standardised relational comic book metadata by investigating eight current American superhero comic book metadata storages to.
- Metadata Framework for Manga: A Multi-paradigm Metadata Description Framework for Digital Comics, Morozumi et al.(2009) Based on the understanding of the structure of digital comics (digital manga) and its contents, the researcher suggested the metadata schema for manga.
- User-centred Approach in Creating a Metadata Schema for Video Games and Interactive Media, Lee et al. (2013) This research aimed to create a user-centred metadata schema for video game. The article is not considered as related to the specific digital comic domain. However, the user groups of digital comic and video game has similar features which could define as active user groups and they interact with the contents for the purpose of leisure rather than work (George et al., 2011). For this reason, this user considered metadata schema as a factor that could be referenced for some part of the domain analysis.
Digital comic related websites Several digital comic websites were investigated to collect pragmatic real data which will now be described. Collected elements in this part were especially useful in order to understand how the domain was shaped, and as to what elements were listed to describe the different types of digital comics. List of the main websites are listed below.
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- Amazon http://www.amazon.co.uk/
- Comixology https://www.comixology.co.uk/
- Daum Webtoon http://webtoon.daum.net
- DC Comics http://www.dccomics.com/
- Lezhin Comics http://www.lezhin.com/
- Marvel http://marvel.com/comics
- Naver Webtoon http://comic.naver.com/index.nhn
- Vizmidea http://www.viz.com/
Library catalog Some universities which have large amount of comic collections, they would have specific rules when cataloging comics. It is possible to say that librarians have little understanding of the features of comics could not be contained in the ways in which general collections are cataloged. In addition, these cataloging rules could be built on the professional cataloging experience of librarians.
- Graphic Novels Cataloging Procedures, University of Colorado http://ucblibraries.colorado.edu/cataloging/cpm/graphicnovels.htm
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- Sangmyung University Cheonan Campus Library http://libnt.smuc.ac.kr/
- Special collections cataloging guidelines: Specific collections, Comic book copy cataloging, The Ohio State University http://library.osu.edu/staff/special-collections-cataloging/locs/comiccat.php
- Special collections cataloging guidelines: Specific collections, Appendix A Manga genre terms, The Ohio State University http://library.osu.edu/staff/special-collections-cataloging/locs/mangaprj.php#appa
From these sources, potential elements collected. Microsoft Excel was used to list the founded elements.
3.2.2. Data Analysis of Domain Analysis
The numbers of elements are relatively large (sixty-nine elements). Thus, it is essential to mention that collected elements were required to be well-managed and well-defined to prevent confusion. Moreover, some elements may sound similar but represent different information description (e.g. topic, subject and setting of comics). This factor could lead elements ambiguous and cause confusion to not only users but also metadata recorders.
In this reason, collected elements were processed in two steps; first, clear definitions have been given to the potential elements. Second, elements were grouped in several ways. For grouping, MARC 21 field description has been adopted. (“MARC 21 is the technical standard for the encoding of bibliographic information.”(OCLC, 2014) It could be argued that these numbers would give some degree of interoperability between current catalog systems especially recording MARC which is used in many libraries. Alphabet codes were used to represent features of elements. The description is provided on table 1.
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Table 1 Alphabet codes
Code MARC field Field description Example
A 00X Control Fields A01 Type
B 20X-24X Title and title-related fields B01 Main title
C 260 Publication and distribution fields C01Digital Released Date
D 3XX Physical description fields D01 Colour
E 508 Creation/Production credits fields E01 Writer
F01 Names of leading F 6XX Subject access fields characters
G 5XX Note fields G01 Language
H Supplement fields H01 Cover image (difficult be found in MARC) 4XX I Issue, Episode fields IB1 Issue (episode) title (490 or 830)
J01 Status J 490 or 830 (Series statement fields)
4XX Series description fields SB1 Series title S (490 or 830)
4XX Volume description fields VB1 Volume title V (490 or 830) (Series statement fields)
According to this table, sixty-nine elements were grouped and designed as a mock up metadata schema. The schema was used in the main part (Part.3) of the questionnaire.
3.3. Questionnaire
One of the major difficulties of this study is collecting real world data from users since the research aims to design user-centred metadata schema. Thus, to organise optimal metadata schema, a large number of digital comic readers should be engaged in this research to find patterns of users’ information seeking process. For this reason, a questionnaire was designed rather than performing interviews.
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Moreover, it is important to say that a questionnaire has highly significant benefits. First, it saves the amount of time and cost required and second, it is quicker to administer (Bryman, 2004). It is also convenient for researchers to get a response from larger pool of users when compared with interviews. By using e-mail list of the University of Sheffield volunteers it was possible to distribute the questionnaire URL link in very short time to more than one thousand people.
3.3.1. Self-completion Questionnaire
The questionnaire was a self-completion questionnaire; most of questions were designed as closed questions (e.g. multiple dichotomous questions (Pickard, 2013)) and the Likert scale.
With closed questions however, there are some disadvantages; it can be a loss of freedom in respondents’ answer and it is difficult to make forced-choice answers equally limited (Bryan, 2004). Despite these disadvantages, it is easy to process answers and second it enhances the comparability of answer (Bryan, 2004). Most of all, it is possible to say closed questions would be the most appreciated because users may not be aware of how they interacted during the information seeking process. Thus, by looking at example answers, respondents might clarify the meaning of questions and they could recall their thoughts, search for strategies during the digital comic information seeking process. Furthermore, it is quick and easy to answer.
In addition, the Likert scale is often utilised in a questionnaire. Basically, respondents were presented with a statement and were asked to indicate whether they “definitely use”, “probably use”, “probably not use”, “definitely not use” and “I don’t know” (Babbie, 1998). However, with the Likert scale, it is difficult to “make assertions about the equality of underlying attitude of differences, and that identical scores may have very different meanings (Oppenheim, 1992: 200)”. However, the Likert scale was an invaluable tool to measure the importance of each element and rank them during the different process.
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3.3.2. Online Questionnaire Design
The purpose of the first part was examining respondent demographical information; the second part was exploring the digital comic reading experience. The third part of the questionnaire was designed to follow on the notion of Marchionini’s (1995) information- seeking process model. It is divided into four sections with four different purposes including investigating purpose of searching, query formulating, result identifying and information requiring of users. In this part, the questionnaire mainly asked participations to rate the importance of each element (from the mock up metadata schema) using by Likert scale.
In the light of the electronic nature of the research, serious attention was given as to whether to use Google, Google Docs (docs.google.com) or Surveymonkey (www.surveymonkey.com) sites where the researcher builds a questionnaire and sends the participant a link to the questionnaire to complete (Figure 3). In the end Google Docs has been used for creating the form of questionnaire and the host of questionnaire. This Google tool was easy to handle and it allowed creating different sections and variety types of questions within different structure.
Figure 3 Self-completion online questionnaire
From “Social research methods”(p.86), by Bryman (2004). Oxford university press.
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The questionnaire has been divided clearly into three parts. (For a full list of the questions asked, see Appendix 4, 5 and 6.)
Part.1 Demographic Information There were four questions in this part, asking demographic information such as age group, gender, native language and level of study (occupation). This questionnaire was mainly distributed to students in the University of Sheffield. However, it was an online questionnaire in which anyone can access the questionnaire with the URL link so it was possible some participation outside of the institution could take part of survey. In this case, respondents needed to indicate their current occupation. The information from this part was used for participants’ demographic analysis.
Part.2 About your digital comic reading experience This section proposes to investigate reading experience of digital comic users. It was important to ask respondents what types of digital comics they have read to judge the research embrace readers of all types of digital comics such as American comic, Japanese manga and Korean webtoon. Moreover in this part, there were some questions asking for the frequency, purpose of reading and years of reading experience.
Part.3 About how you find information It is important to mention that the main part of the questionnaire is the Part.3. This part was divided to four units and these units have been logically ordered following by Marchonini’s (1995) information seeking process on electronic environment (Figure 4). It is possible to say this organisation might help to participant recall their information seeking process.
Figure 4 Notion of the questionnaire design
From " Information seeking in electronic environments " (p.50), by Marchionini (1995). Cambridge University Press.
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Baseline of Unit 1 is how users define the problem to search. This part asked users to indicate the purpose of searching and information resource. These were multiple dichotomous question, “which provides a list of possible responses and allows the respondents to select any number of choices from the list (Pickard, 2013:211)”.
Questions in Unit 2 asked for which information would be used to formulate and execute queries on the search box. The list of elements from the mock up metadata schema was represented and respondents scaled the usability of element using by the Likert scale. There was one more question related to the directory tabs (the multiple dichotomous question).
The question in Unit 3 asked to scale importance of each element on the mock up metadata schema to identify the digital comics on the result pages (the Likert scale).
There were three main questions in Unit 4 to investigate how users extract information and reflect on digital comic information searching. On the first question, respondents scaled each element on the mock up element schema and the possibility of element which require fulfilling their information needs (the Likert scale). With the second question, respondents were asked to indicate their level of information searching ability. Finally, the last question asked to check difficulties when looking for digital comics on the web (the multiple dichotomous question).
3.3.3. Pilot Test
It is important to say that a pilot test is vital before distribution. Slater (1990) claimed the pilot test is necessary to ensure clear and unambiguous terminology which can be relevant to the purpose of the research. It is essential to check whether all of the questions are easy to read and understand how the questions were purposed. In receiving feedback, five set of the questionnaire were printed and given to the two English speakers and three non- English speakers (one Korean speaker and two Chinese speakers).
The feedback from the pilot participants was generally negative. Most of pilot participants indicated the questionnaire was too long and some question sentences were ambiguous to answer. However, they suggested many ways of how the questionnaire might be improved.
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After taking these valuable comments the questionnaire has been redesigned to be more clear and straightforward as possible.
3.3.4. Distribution and Participant
The questionnaire was distributed on 25th of July, 2014 and finished on 22nd of August, with it mainly being distributed through emails (Picture 1) and Facebook, an online social network service. To end with, a total of sixty-five digital comic readers participated in the questionnaire.
The questionnaire targeted readers who have read any types of digital comic. However, there were several difficulties on this part; first, it was difficult in determining the size of the sample. Even though, between sample size and quality of results are in direct proportion (De Vaus, 2004) since the research aimed to find the patterns of information seeking behaviour of digital comic users by the quantitative method. Practically, it was difficult to get a large number of a sample. Second, there was the limitation of distributing the questionnaire URL link because it is impossible to send it to all of possible targets.
Thus, two ways of non-probability sampling has been taken which were convenience sampling and snowball sampling. To achieve the large number of participants there were three ways of distributions have been used.
First, an online link has been sent to all members of the University of Sheffield who were in the student volunteer e-mail list to invite them to participate in the questionnaire if they have read digital comics (Picture 1).
Second, the link also has been posted on the comic society, animation Society and Korean society of the University of Sheffield Facebook group pages to request participant because these were places where there was a high possibility of digital comic users who would click on the link.
Third, the link also has been sent to some of acquaintances of the researcher by e-mail or Facebook.
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Picture 1 e-mail questionnaire distribution
3.3.5. Data Analysis of the Questionnaire
The online questionnaire used quantitative methods which analysed data numerically and provided results which were objective. Since users summit their answered forms it is automatically processed and represented on the Google Spreadsheet. Once an acceptable number (sixty-five responses) of questionnaires had been returned, the spreadsheet was exported to Microsoft Excel to be analysed.
Many of the important questions from the questionnaire included closed questions and the Likert scale. Particularly, the Likert scale helped to weight elements, whether the element performance significant role on the users’ information seeking process. For the data analysis these scales were given meaningful order numbers such as 4 (definitely use), 3 (probably use), 2 (probably not use), 1 (definitely not use) and 0 (I don’t know). These numbers have been supported to rank importance of elements in each process. It is possible to say that the results were easily analysed statistically and reliably (Bryman, 2004).
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3.3.6. Ethical Considerations
This project has been classified as ‘low risk’. However, the research has been ethically approved before distributing the questionnaire by the Information School Ethics Panel, of the University of Sheffield (Proposal for research ethics review can be found as Appendix 1 and research ethics approval letter can be found as Appendix 2). Moreover, all responses have been strictly anonymous and remained confidential.
The research required human participants but the research have been carried out entirely in the electronic domain. In fact, the participants have been asked to provide certain demographical information such as age, gender, native language and level of study. But, it is possible to say that most of questions were not of a sensitive nature beyond personal opinion. The participants have been fully informed as to the nature of the research, its use and anonymity. Also, participants can opt out of the survey at any time.
The consent form has been provided the front page of questionnaire (this can be found as Appendix 3).
3.4. Limitations of the Methodology
It is important to highlight some limitations of this methodology framework.
There are several limitations on the domain analysis. First, even though, the variety common features among different types of digital comics, there were some difficulties in defining the common description elements for describing them. Second, the language barrier, such as manga and some other types of comics are written by non-English (or non- Korean). For this reason, the majority of domain articles, websites and library catalogs were written in English or Korean. It is possible to say the importance of some Japanese manga features may have been over looked.
The questionnaire was a self-completion questionnaire which was distributed by e-mail with a URL link to the form. There are several risks which could effect to the result of research. First, it was difficult ask a lot of questions, second the low response rate and finally, it might be difficult to get enough respondents (Bryman, 2004).
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Chapter4. Results
The various elements identified in the domain analysis will be displayed at the beginning of this chapter with definitions and code numbers. Following this, the questionnaire results which aimed to investigate information seeking behaviours of digital comic users will be analysed statistically.
4.1. Results of Domain Analysis
The total sixty-nine elements were identified from the domain analysis. Meanwhile they were each given a clear notion of definition - the lists of elements grouped using an alphabet code.
4.1.1. Mock up Metadata Framework
A list of the mock up metadata framework is provided in this section. All sixty-nine elements were divided into two main parts including general elements (40 elements) and additional elements for the digital comic which consists of series, volumes and episodes (29 elements) in order to describe several layers of some digital comics’ hierarchical structures.
The elements are noted with a definition next to them. In order to support some grade of interoperability between other standard metadata element sets, whenever possible the definitions of these elements from existing standards (e.g., FRBR, Getty Art & Architecture Thesaurus, OCLC and CIDOC CRM) were adopted. However, because of the unique nature of the object, some definitions had to be made as it was difficult to classify reusable definitions from existing standards.
General elements
The forty potential elements in table 2 can be used for generally describing digital comics. Also these elements could be used for all types of the combination of text and sequential arts such as graphic novels, manga, manhwa, webtoon and web comics.
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Table 2 Mock up metadata (general elements)
Code Element Definition
The category of the digital comic which could be different 1 A01 Type depends on publishing country or format of the digital comic.
Proper noun phrases or verbal phrases that are used to refer to B01 2 Main title a digital comic, assigned by the writer (or transcriber).
(modified from CIDOC CRM, 2013,p.15)
Original proper noun phrases or verbal phrases that are used to B02 Original 3 refer to a digital comic, assigned by the writer before title transcribing.
B03 Alternative Alternative titles of the digital comic, including the 4 title abbreviations.
Digital The date of the public/commercial release of the digital comic. 5 C01 Release (modified from IFLA, 2009, p.42) Date
The publisher of the digital comic is the individual, group, or organisation named in the digital comic as being responsible for 6 C02 Publisher the publication, distribution, issuing, or release of the comic. A digital comic may be associated with one or more publishers. (modified from IFLA, 2009, p. 42)
Publishing The place of publication of the digital comic is the city, town, or 7 C03 city other locality associated in the digital comic with the name of (country) the publisher. (modified from IFLA, 2009, p. 42)
Colour is the colour(s), tone(s), etc. (including black and white) 8 D01 Colour used in the production of the digital comic. (modified from IFLA, 2009,p.46)
9 D02 Format The particular form by which sequential arts are expressed.
Size of 10 D03 The memory size required to store the digital comic. comic
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The name of the person who wrote the story of digital comic or 11 E01 Writer who was responsible for the intellectual content story line. (modified from Getty Art & Architecture Thesaurus)
The name of the person who draws the sequential arts for the 12 E02 Illustrator digital comic.
Illustrator who drew The name of the person who draws the cover page of the 13 E03 the cover digital comic. image
Character The name of the person who created (made the concept of or 14 E04 creator designed the image of) the character.
Names of The given full name (if available) or aliases of the leading 15 F01 leading characters. characters
Appearance 16 F02 of leading Description of appearance and ability of leading characters. characters
Names of The given full name (if available) or aliases of the sub 17 F03 sub characters. characters
Appearance 18 F04 of sub Description of appearance and ability of sub characters. characters
The category of the digital comic characterized by content. 19 F05 Genre (modified from modified from Getty Art &Architecture Thesaurus)
Comic Historical events that are the setting for (or play an important related 20 F06 role in) the digital comic. This may be a named event, a historical historical period. (modified from Lee et al. (2006), p.229) events
Description of the character’s physical form (e.g. ghost, ninja, 21 F07 Subject robot etc.)
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22 F08 Topic The matter dealt with in the story of the digital comic.
Setting of The place and time in which the digital comic’s story is taking 23 F09 comics place.
The language in which the digital comic is expressed. (modified 24 G01 Language from IFLA, 2009, p. 36)
Story 25 G02 A written account of the storyline of the digital comic. description
Related media The name of work (e.g. animation, movie) that shares the story 26 G03 which line with the digital comic. The name of any work that the shares the digital comic is based on (e.g. name of film or animation). story
Type of 27 G04 The category of story ending of the digital comic. ending
The image or summary version of digital comic released and/or endorsed by the writer/illustrator/publisher of the digital comic 28 G05 Trailers for promotional purposes. (modified from Lee et al. (2006), p.235)
The name of extended or continuing storyline in the digital 29 G06 Story arc comic which gradually unfolds over several comics.
Character 30 G07 The status of a character which unfolds throughout a narrative. arc
A note about the target audience for the digital comic. Used Target primarily when the contents of an item are considered 31 G08 audience appropriate for a specific audience or intellectual level (e.g., elementary school students).(modified from OCLC, 2014)
The rate or ranking of the digital comic based on a comparative User 32 G09 assessment of the story line, illustration from readers or Ratings publishers.
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User 33 G10 Critical appraisals of the digital comic Review
Fan arts (e.g. The artwork such as a picture of image, a figure of character 34 G11 deviant created by the fan of the digital comic. ART)
Digitalised The date of digitalisation of the digital comic. (The date printed 35 G12 date comic turned into digital)
Cover Image of the cover (front) page - it can be the cover of 36 H01 image individual comics within collection.
Main comic Representing image of the entire digital comic. (it can be 37 H02 image picture of main characters)
The suggested manufacturer's retail price at time of initial 38 H03 Price release or current retail price. (modified from Lee et al. (2006), p.229)
Frame 39 H04 screenshots Still images taken from the digital comic. of comics
Text inside 40 H05 or outside Recorded full text of the digital comic of frame
In addition, Miller (2011) mentioned that all standard metadata schemas contain some kind of identifiers. An identifier is a string such as International standard book number, Uniform Resource Identifier (URL) or unique identifier number in the local database or system. This is important because it makes items unambiguous within a given context (DCMI, 2014; Miller, 2011).
A metadata schema for digital comics could contain search criteria such as a URL link to the digital comics for reading, a purchase URL link and a purchase URL link to the physical version. Despite the importance of an identifier, these are not in the list because a
40 definition of identifier and a given string could vary depending on systems and databases even for the same digital comics. However, an identifier for digital comics must be recorded.
Additional element for series, volume and episode (issue) Many digital comics consist of several series, volumes (a collection of several episodes) and issue (episodes). In general, these are consistently released. It could be suggested that for cataloging these types of digital comics adaption of the rules of serial cataloging should be considered. For this reason, more information descriptions are required. For example, to describe the episode of the digital comic, around five different types of title description fields might be required such as main title, original title, alternative title, series title, volume title and issue (episode) title (Picture 2).
Picture 2 the exmple of a digital comic structure
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J01 Status element describes the publication status for the comic issued. Users can recognise whether the comic is currently published or has ceased publication by this field. After J01 Status recording, there are three groups of elements (e.g. series, volume and issue (episode) will be described depending on the digital comic.
Table 3 Mock up metadata (status)
Code Element Definition
Publication status for the comic issued as a serial is the status of 1 J01 Status the comic with respect to its continuing publication. (modified from IFLA, 2009, p. 45)
These six elements can be used for additional description of the comic which has more than one series.
Table 4 Mock up metadata (series)
Code Element Definition The noun phrases or verbal phrases of the series that are used to refer to the series of the digital comic, assigned by the 1 SB1 Series title creator or writer (or transcriber). (modified from CIDOC CRM, 2013,p.15) The dates of the public/commercial release of the series f the Release comic. The date may be a single date of publication or 2 SC1 date of release, or a range of dates for the series publication. series (modified from IFLA, 2009, p.42)
Series The name of a new main character in the series or subject 3 SF1 subject words or important phrase that may be used in searching for (keywords) the series.
Series story 4 SG1 A written account of the storyline of the series of the comic. description
Main Representing image of the comic series (it can be picture of 5 SH2 image of main characters) series
Series 6 SJ1 The number of sequential position of the comic series number
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The word “volume” could refer to a separately bound portion of comics which can only be used for print versions of a comic. However, when printed comics are digitalised they still keep the format of the printed version. In this case, the collection of several episodes could be referred to as a volume. There are an additional ten elements for the comic which has more than one volume.
Table 5 Mock up metadata (volume)
Code Element Definition The noun phrases or verbal phrases of the volume that are used Volume to refer to the volume of the digital comic, assigned by the 1 VB1 title creator or writer (or transcriber). (modified from CIDOC CRM, 2013,p.15)
Release 2 VC1 date of The date of the public/commercial release of the volume. volume
The publisher of the volume of the digital comic is the individual, group, or organization named in the volume of the digital comic as being responsible for the publication, Publisher 3 VC2 distribution or release of the volume. The volume may be (volume) associated with one or more publishers (printed version and digital version could have different publisher. (modified from IFLA, 2009, p. 42)
Page count The number of page of the volume. 4 VD1 of volume
Volume The name of a new main character in the volume or subject 5 VF1 subject words or important phrase that may be used in searching for (keywords) the volume.
Volume 6 VG3 story A written account of the storyline of the volume of the comic. description
Main 7 VH1 image of Representing image of the volume of the comic volume
Cover 8 VH2 image of Image of the cover (front) page of the volume volume
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Volume 9 VJ1 The sequential volume number of the comic. number
Publishing 10 VJ2 frequency Expected publishing (releasing) frequency of volume of volume
It could be said that the word “page” (e.g. VD1 Page count of volume) can be odd for the digital contents because the word could refer to the physical piece of paper. However, when printed comics are digitalised they still keep the format of a printed version. Therefore, page number and page count could be the descriptive elements for the volume.
There are an additional twelve elements used to describe the episode or issue of comics. It cannot be assumed that terms of issue and episode represent the exact same meaning because it is rare that more than one episode is contained in one issue (distribute at one time) such as four cut digital cartoons. In this case, several IB1 episode titles should be recorded under the equal IC1 released data of issue. The list of elements is provided in table 6.
Table 6 Mock up metadata (issue (episode))
Code Element Definition The noun phrases or verbal phrases of the issue that are used Issue to refer to the issue of the digital comic, assigned by the creator 1 IB1 (episode) or writer (or transcriber). (modified from CIDOC CRM, title 2013,p.15) Release date of 2 IC1 The date of the public/commercial release of the issue. issue (episode) Publisher The publisher of the issue (comic magazine) of the digital comic (comic is the individual, group, or organization named in the issue of 3 IC2 magazines the digital comic as being responsible for the publication, or comic distribution or release of the issue (magazine). (modified from books) IFLA, 2009, p. 42)
Name of Name of comic magazine which contains the issue (episode) of 4 IC3 comic digital comic within and publishes frequently. magazine
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Page count 5 ID1 The number of pages within the issue. of episode
Issue The name of a new main character in the issue (episode) or (episode) 6 IF1 subject words or important phrase or events that may be used subject in searching for the issue (episode). (keywords) Issue (episode) A written account of the main theme of the storyline within the 7 IG1 story comic issue. description Cover image of 8 IH1 Image of the cover (front) page of the issue issue (episode) Main image of 9 IH2 Representing image of the main theme of the comic issue. issue (episode) Name of sound IH3 The name of a theme-tune that is delivered with the episode 10 provided online. with the episode
Issue 11 IJ1 (episode) The sequential issue number of the comic. number
Publishing frequency 12 IJ2 Expected publishing frequency of Issue of Issue (episode)
4.2. Results of Questionnaire
Results of the questionnaire are separated into three sections in this part. First, participant demographical information, second, digital comic reading experience of participant and third, process of digital comic information seeking experience. Moreover, the result of the last part is divided into four units; defining purpose of searching, formulating and executing queries, identify results and extracting information.
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4.2.1. Participant Demographical Information
The first four questions asked respondents about their gender, age group, native language and current level of study (occupation). Out of sixty-five respondents, sixty were ‘Male’ and twenty-five ‘Female’ (Figure 5). Most respondents (45) were between 18-25 years old and only two respondents were in the 36-45 group (Figure 6).
Female, Male, 25 40
Figure 5 Respondents’ profile by gender
36-45, 2 26-35, 17 18-25, 45
Figure 6 Respondents’ profile by age group
Twenty-eight participants indicated that they are Korean speakers. Seventeen respondents were English speakers and sixteen spoke Chinese. Also, two of the respondents indicated they used more than two languages as their native languages. (Figure 7)
30 28
25
20 17 16 15
10
5 1 1 1 1 0 Korean English Chinese Bulgarian Lithuanian Chinese, English, English French
Figure 7 Respondents' profile by native language
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Nearly half of the respondents (49%) were undergraduate level students. The majority of participants (97%) indicated that they were currently at university; however, four respondents confirmed that they were not students (i.e. business or admin staff and a comic writer). (Figure 8)
4 7 Undergraduate Postgraduate Taught 32 Postgraduate Research 22 Others
Figure 8 Respondents' profile by current level of study
4.2.2. Digital Comic Reading Experience
When asked which types of digital comic they have read, respondents provided multiple choices which covered all different types of digital comics. The majority of participants (54) read more than two types of digital comics. (Figure 9)
Webcomic 20
Newspaper comics 14
Editorial cartoon or political cartoon 12
Korean Webtoons 31
Japanese Manga 42
Comic Books 24
Graphic Novels 10
0 5 10 15 20 25 30 35 40 45 50
Figure 9 Reading experiences of respondents (types of digital comic)
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Approximately half of respondents (31) responded they have read digital comics for more than five years. It is possible to assume that one of third of respondents have read digital comics since they were teenagers because the majority of respondents (22) in the 18 to 25 group answered they have read digital comics for more than five years. (Figure 10)
More than five years 31
More than four years less than five years 7
More than three years less than four years 6
More than two years less than three years 5
More than one year less than two years 9
Less than one year 7
0 5 10 15 20 25 30 35
Figure 10 Reading experiences of respondents (period)
Twenty-nine respondents responded they read digital comics a few times a week. It is possible to assume that many of the participants keep an eye on a few digital comics in a week because many digital comics are released weekly. Moreover, respondents who answered ‘daily’ (9) could read different digital comics each day. (Figure 11)
Less frequently 11
A few times a month 16
A few times a week 29
Daily 9
0 5 10 15 20 25 30 35
Figure 11 Reading experiences of respondents (frequency)
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Most of the participants (61) responded that they are reading comics for leisure. However, there are some answers saying that they read digital comic for language study or to get ideas for their work (a comic writer). (Figure 12)
Leisure 61
Work 2
Others 7
0 10 20 30 40 50 60 70
Figure 12 Reading experiences of respondents (purpose)
4.2.3. Digital Comic Information Seeking Experience
The final section of the questionnaire consists of four units. The notion of the section was designed based on understanding of the information-seeking process of users in online environments (Marchionini, 1995).
Unit 1 Define problem and select source
Figure 13 Notion of the questionnaire design (unit 1 of part 3)
From "Information seeking in electronic environments " (p.50), by Marchionini (1995). Cambridge University Press.
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The first question in this unit asked respondents their purpose of searching for information about digital comics (multiple choices). The result of this question is provided in the bar chart below.
Other 2 to find information about related media 22 to decide whether to read a comic 34 to know about characters 32 to know about creators 15 to buy digital comics 9 to check current news about comics 21 to check user feedback 20 to read episodes 48
0 10 20 30 40 50 60
Figure 14 Purpose of searching for information about digital comics of respondents
Forty-eight responded that they searched for information about digital comics in order to read episodes. This can be classed as an example of known item searching (Lee at al., 2007). Users probably knew that the specific digital comic existed on the web and they were looking for the URL link to the digital comics. Identifiers such as URL links to the digital comics ought to be contained in the final metadata set.
In addition, more than half of respondents (34) indicated the purpose of searching was for deciding whether to read a digital comic. Therefore sufficient information needs to be provided within the descriptions about digital comics in order to support users in making decisions.
Nearly half of respondents (32) responded they were looking for information about specific characters. In addition, one participant answered that the purpose of searching was for identifying ranks or levels of characters in the digital comic. In the final metadata set, the information related characters should be considered.
However, many respondents (22) answered that they are looking for information not about the digital comic itself but the information related media. If the comics gained high
50 popularity, different types of media could be created based on the story or characters of the digital comic. For instance, there are several contents such as animation, films, video games and Audio CDs that were produced based on the famous Japanese manga Case Closed (Detective conan). In short, digital comic users might require information related to information of other media.
Twenty one users engaged in searching to check current news related to comics and also a number search for the user feedback of comics (20). However, it is essential to mention that only 4% of respondents answered that they engage in searching in order to buy digital comics. In recent times many comics have become available for free. For this reason, it can be said that the URL link to purchase digital comics is not essential.
The last question in this unit was examining what types of information source are used to find the information about digital comics (Figure 15). After users defining their needs of searching the next step is to select the information source to solve their information needs in the information seeking process. The most popular information source is friends; fifty people responded that they took recommendations from friends.
Social networking service (24), online communities for comics (31), the general search engine (36) and official comic publisher (15) were also recognised as good information sources to support searching. In addition, one respondent indicated adverts on other webcomic sites as an information source.
Social networking service 24 Search results on general search engines 36 Online communities for comics 31 Official comic publisher websites 15 Recommendations from friends 50 Other 1
0 10 20 30 40 50 60
Figure 15 Information sources of respondents to find the information about digital comics
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Unit 2 Formulating and executing queries
Figure 16 Notion of the questionnaire design (unit 2 of part 3)
From " Information seeking in electronic environments " (p.50), by Marchionini (1995). Cambridge University Press.
The first question of the second unit asked respondents to indicate using a Likert scale (definitely use, probably use, probably not use, definitely not use and I don’t know) the possibility of mock up elements which could be used to create a query formulation.
Meaningful order numbers were given for analysing the result of this question such as definitely use (4), probably use (3), probably not use (2), definitely not use (1) and I don’t know (0). The maximum total number for each element was 260 because sixty five digital comic users responded to this questionnaire. The list of elements is ordered by rankings, shown in tables below. Also, the total number and median (middle number) are represented.
Table 7 Ranks of general elements in the question about formulating and executing queries
Rank Code Name of Elements Total Median 1 B01 Main title 248 4 2 E01 Writer 187 3 3 B02 Original title 184 3 4 F08 Topic 182 3 5 B03 Alternative title 178 3 5 F01 Names of leading characters 178 3 7 F05 Genre 176 3 8 G02 Story description 174 3 9 F07 Subject 168 3
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9 G01 Language 168 3 11 A01 Type 167 3 12 G03 Related media which shares the story 166 3 13 E02 Illustrator 157 3 14 G10 User review 156 3 15 G09 User Ratings 154 3 16 F09 Setting of comics 150 2 17 F06 Comic related historical events 147 2 18 G05 Trailers 143 2 19 F03 Names of sub characters 139 2 19 G08 Target audience 139 2 21 G06 Story arc 134 2 22 E04 Character creator 130 2 23 G07 Character arc 126 2 24 C02 Publisher 122 2 25 E03 Illustrator who drew the cover image 120 2 25 H01 Cover image 120 2 27 F02 Appearance of leading characters 118 2 28 C03 Publishing city (country) 117 2 29 H02 Main comic image 116 2 30 G11 Fan arts 113 2 31 C01 Digital Release Date 112 1 32 G04 Type of ending 110 2 33 H03 Price 109 1 34 F04 Appearance of sub characters 106 1 34 H04 Frame screenshots of comics 106 1 36 H05 Text inside or outside of frame 103 1 37 D01 Colour 101 1 38 G12 Digitalised date 100 1 39 D02 Format 94 1 40 D03 Size of comic 91 1
Title and title related elements (B1 Main title, B2 Original title and B3 Alternative title) were extremely popular for formulating queries. The result could relate to the result of Unit 1 of first question. The majority of respondents (48) answered that the purpose of searching was to read episode which was a known item search. It could therefore be assumed that users remembered the titles of the digital comic they read when they formulated or reformulated titles as queries.
Commonly, the subject related fields were also highly ranked except F02 Appearance of leading characters. It could be suggested that users frequently formulate and execute queries based on understating the subject of comics. In addition, nearly half of respondents
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(32) indicated the purpose of searching is for finding information about characters according to the result of Unit 1 of the first question. It is possibly linked with the result of this question because four elements of the subject related elements are associated with characters such as F01 Names of leading characters, F02 Appearance of leading characters, F03 Names of sub characters and F04 Appearance of sub characters. In other words, subjects related fields should be emphasised when designing the metadata set.
The ranking of elements in the Creation/Production credits fields varied greatly. E01 Writer was ranked second and E02 Illustrator was ranked thirteenth but the other elements were ranked poorly.
The same can be said for the ranking of elements in the Note field. G02 Story description and G01 Language were ranked eighth and ninth respectively. G02 Related media which shares the story element also ranked highly (12th). Moreover, it is essential to argue that many users consider user feedback such as G10 User review and G11 User ratings of comics when they are formulating and reformulating quires.
The majority of elements from the publication and distribution fields and the physical description fields were poorly ranked compared to other fields in this unit. Therefore it can be said that in the digital environment, physical description of digital contents (e.g. D01 Colour, D02 Format and D03 Size (e.g. 1GB) of digital comic) were not considered as important elements. Also, the publication and distribution fields were lowly ranked. This could be because many digital comics such as webcomics and webtoon are published by independent creators.
The three tables below represent the rank of other elements which are related to series, volume and issue (episode) in the question about formulating and executing queries.
Table 8 Ranks of series elements in the question about formulating and executing queries
Rank Code Name of Elements Total Median 1 SB1 Series title 191 3 2 SJ1 Series number 179 3 3 SF1 Series subject (keywords) 164 3 4 SG1 Series story description 157 2 5 SC1 Release date of series 145 2
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6 SH2 Main image of series 133 2
Table 9 Ranks of volume elements in the question about formulating and executing queries
Rank Code Name of Elements Total Median 1 VJ1 Volume number 191 3 2 VB1 Volume title 183 3 3 VF1 Volume subject (keywords) 164 3 4 VG3 Volume story description 158 3 5 VC2 Publisher (volume) 130 2 5 VJ2 Publishing frequency of volume 130 2 7 VC1 Release date of volume 124 2 8 VH2 Cover image of volume 120 2 9 VH1 Main image of volume 113 2 10 VD1 Page count of volume 97 1
Table 10 Ranks of issue (episode) elements in the question about formulating and executing queries
Rank Code Name of Elements Total Median 1 IJ1 Issue (episode) number 195 3 2 IB1 Issue (episode) title 191 3 3 IF1 Issue (episode) subject (keywords) 165 3 4 IG1 Issue (episode) story description 157 2 Name of comic magazine which 5 IC3 publish episode serially 152 2 Publishing frequency of Issue 6 IJ2 (episode) 136 2 Publisher (comic magazines or 7 IC2 comic books) 133 2 8 IC1 Release date of issue (episode) 131 2 9 IH2 Main image of issue (episode) 127 2 10 IH1 Cover image of issue (episode) 125 2 Name of sound that provided with 11 IH3 the episode automatically 106 2 12 ID1 Page count of episode 88 1
Titles and numbers of series, volumes and episodes were popular elements (SB1Series title, SJ1Series number, VJ1Volume number, VB1Volume title, IJ1 Issue (episode) number and IB1Issue (episode) title) for formulating queries. Moreover, each subject of series, volumes and episodes (SF1 Series subject (keywords), VF1 Volume subject (keywords) and IF1 Issue (episode) subject (keywords)) ranked after elements related to titles and numbers. However, page count elements were ranked last; there are two possible evidences in this
55 result. First, users do not tend to formulate queries with page count numbers. Second, in the digital environment, physical description elements are not significantly valuable.
Users could engage in searching by using directories rather than typing queries in the search box. The clicking directory tab could be one of the ways to executing queries. Thus, the second question in Unit 2 is which directories could be used during the search session (multiple choices). The result of the question is represented in the bar-chart below.
45 41 40 36 35 34 34 35 30 25 26 22 23 25 20 20 18 18 15 14 14 15 11 10 8 5 2 0
Figure 17 Directory preferences of respondents
Popular directories were Genre (41), top rated (34), series (35), A-Z list (34) and statues (34) (for on-going digital comics). One respondent noted Best-selling directory as another possible tool to use.
It could be that searching by queries and directories offer a different main purpose of use. The main purpose of using queries could be for searching for known items to read because title related fields were highly popular for formulating. However, directories could be for deciding whether to read, since the majority of respondents indicated they would use Genre and top rated directory tabs.
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Unit 3 Examining and identifying the results
Figure 18 Notion of the questionnaire design (unit 3 of part 3)
From "Information seeking in electronic environments " (p.50), by Marchionini (1995). Cambridge University Press.
The purpose of Unit 2 is to investigate which elements would be used for examining (identifying) the results after executing queries in the search box. The question respondents were asked was to indicate the elements which would possibly be useful for identifying results by using a Likert scale. Meaningful order numbers were given for examining the question (definitely use (4), probably use (3), probably not use (2), definitely not use (1) and I don’t know (0)). The ranks of general elements are provided in table 11.
Table 11 Ranks of general elements in the question about examining and identifying the results
Rank Code Name of Elements Total Median 1 B01 Main title 240 4 2 B02 Original title 210 3 3 G02 Story description 195 3 4 E01 Writer 194 3 4 F05 Genre 194 3 4 G01 Language 194 3 7 F01 Names of leading characters 192 3 8 B03 Alternative title 187 3 9 A01 Type 180 3 10 F08 Topic 179 3 11 F07 Subject 174 3 11 G03 Related media which shares the story 174 3 13 G10 User review 173 3 14 G09 User Ratings 170 3 14 H01 Cover image 170 3 16 F09 Setting of comics 169 3 17 E02 Illustrator 166 3
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18 H02 Main comic image 157 2 19 F06 Comic related historical events 156 3 20 F02 Appearance of leading characters 152 2 21 F03 Names of sub characters 150 2 22 G08 Target audience 146 2 23 E04 Character creator 137 2 23 G05 Trailers 137 2 25 C01 Digital Release Date 136 2 26 G06 Story arc 134 2 26 G07 Character arc 134 2 28 C02 Publisher 131 2 29 E03 Illustrator who drew the cover image 130 2 30 F04 Appearance of sub characters 127 2 31 D02 Format 126 2 31 G12 Digitalised date 126 2 31 H03 Price 126 2 34 D01 Colour 122 2 35 G04 Type of ending 121 2 36 C03 Publishing city (country) 115 2 37 G11 Fan arts 111 1 38 H04 Frame screenshots of comics 106 2 39 H05 Text inside or outside of frame 105 1 40 D03 Size of comic 98 1
Title and title related fields (B01, B02 and B03), E01 Writer, F02 Genre and F01 Names of leading characters were highly ranked for identifying digital comics on the result page. G10 User review, G09 User rating and G03 Related media which shares the story ranked was in top 15.
Also, the ranks of G02 Story description, H01 Cover image and H02 Main comic image increased (ranked 8th, 25th and 29th to 3rd, 14th and 18th) from Unit 2. Firstly, it is possible to assume that for formulating query by long description or image files could be difficult to ensure the result of search. Secondly, the rank of H01 Cover image and H02 Main comic image increased ten ranking places; perhaps the visual elements are a useful element for identifying the digital comics.
The three tables below show the results of examining and identifying process on series, volume and issue (episode).
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Table 12 Ranks of series elements in the question about examining and identifying the results
Rank Code Name of Elements Total Median 1 SB1 Series title 199 3 2 SJ1 Series number 194 3 3 SF1 Series subject (keywords) 177 3 4 SG1 Series story description 174 3 5 SH2 Main image of series 143 2 6 SC1 Released date of series 136 2
Table 13 Ranks of volume elements in the question about examining and identifying the results
Rank Code Name of Elements Total Median 1 VB1 Volume title 206 4 2 VJ1 Volume number 199 4 3 VG3 Volume story description 187 3 4 VF1 Volume subject (keywords) 183 3 5 VH2 Cover image of volume 149 2 5 VJ2 Publishing frequency of volume 149 2 7 VC2 Publisher (volume) 143 2 8 VH1 Main image of volume 141 2 9 VC1 Released date of volume 138 2 10 VD1 Page count of volume 107 2
Table 14 Ranks of issue (episode) elements in the question about examining and identifying the results
Rank Code Name of Elements Total Median 1 IB1 Issue (episode) title 203 3 2 IJ1 Issue (episode) number 197 4 3 IG1 Issue (episode) story description 183 3 Issue (episode) subject 4 IF1 (keywords) 176 3 5 IH1 Cover image of issue (episode) 147 2 Publisher (comic magazines or 6 IC2 comic books) 146 2 Name of comic magazine which 7 IC3 publish episode serially 144 2 8 IC1 Released date of issue (episode) 140 2 9 IH2 Main image of issue (episode) 139 2 Publishing frequency of Issue 10 IJ2 (episode) 133 2 Name of sound that provided 11 IH3 with the episode automatically 109 2 12 ID1 Page count of episode 107 1
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Titles of series, volumes and episodes were still important elements (SB1, SJ1, VJ1, VB1, IJ1 and IB1) to identify digital comics. However, some of the story description elements (VG1 and IG1) reached a higher position than story subject words (VF1 and IF1), suggesting users prefer sentence description than lists of words when they identify the results (series, volume and episode).
Unit 4. Extracting Information
Figure 19 Notion of the questionnaire design (unit 4 of part 3)
From "Information seeking in electronic environments " (p.50), by Marchionini (1995). Cambridge University Press.
The purpose of the Unit for is to investigate the importance of each element for extracting information of digital comics and how users felt about searching.
The first question of the unit asked respondents to indicate using a Likert scale (definitely need, probably need, probably not need, definitely not need and I don’t know) the possibility of using specified elements for extracting information.
Meaningful order numbers were given for analysing the result of this question. The elements list is ordered by rank and represented with total number and median.
Table 15 Ranks of general elements in the question about extracting information
Rank Code Name of Elements Total Median 1 B01 Main title 244 4 2 B02 Original title 220 4 3 G01 Language 212 4 4 E01 Writer 209 3 5 F05 Genre 207 4
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6 G02 Story description 202 3 7 H01 Cover image 199 3 8 F07 Subject 198 3 9 B03 Alternative title 197 3 10 F08 Topic 195 3 11 F01 Names of leading characters 194 3 12 G10 User review 189 3 13 A01 Type 188 3 13 F09 Setting of comics 188 3 15 G03 Related media which shares the story 185 3 15 G09 User Ratings 185 3 17 E02 Illustrator 183 3 18 H02 Main comic image 179 3 19 C02 Publisher 163 3 20 F06 Comic related historical events 159 3 21 C01 Digital Release Date 158 3 21 F03 Names of sub characters 158 3 23 G08 Target audience 155 2 24 F02 Appearance of leading characters 152 2 25 E04 Character creator 151 2 26 H03 Price 149 2 27 E03 Illustrator who drew the cover image 145 2 28 G06 Story arc 143 2 29 F04 Appearance of sub characters 142 2 30 G05 Trailers 137 2 30 G12 Digitalised date 137 2 32 G07 Character arc 136 2 33 C03 Publishing city (country) 134 2 33 D01 Colour 134 2 35 D02 Format 127 2 35 H04 Frame screenshots of comics 127 2 37 D03 Size of comic 122 2 38 H05 Text inside or outside of frame 119 2 39 G11 Fan arts 117 2 40 G04 Type of ending 111 2
There were no significance changes between the results of Unit 3 and Unit 4. The ranking of some elements increased such as G01 Language, H01 cover image and C02 Publisher. However, the rank of some elements decreased (G02 Story description, F01 Names of leading characters and G03 Related media which shares the story) Unexpectedly, G04 Type of ending and G11 Fan art were ranked last -lower than rankings of physical description elements such as D01 colour and D02 format.
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The three tables below show the results of the question which is related to series, volume and issue (episode).
Table 16 Ranks of series elements in the question about extracting information
Rank Code Name of Elements Total Median 1 SB1 Series title 214 4 2 SJ1 Series number 201 3 3 SG1 Series story description 196 3 4 SF1 Series subject (keywords) 192 3 5 SH2 Main image of series 165 3 6 SC1 Released date of series 156 3
Table 17 Ranks of volume elements in the question about extracting information
Rank Code Name of Elements Total Median 1 VB1 Volume title 218 4 2 VJ1 Volume number 207 4 3 VG3 Volume story description 200 3 4 VF1 Volume subject (keywords) 196 3 5 VH2 Cover image of volume 173 3 6 VC1 Released date of volume 162 3 7 VC2 Publisher (volume) 156 3 7 VH1 Main image of volume 156 3 9 VJ2 Publishing frequency of volume 150 2
Table 18 Ranks of Issue (episode) elements in the question about extracting information
Rank Code Name of Elements Total Median 1 IB1 Issue (episode) title 217 4 2 IJ1 Issue (episode) number 212 4 3 IG1 Issue (episode) story description 200 3 4 IF1 Issue (episode) subject (keywords) 191 3 5 IH1 Cover image of issue (episode) 174 3 Name of comic magazine which publish 6 IC3 episode serially 171 3 7 IH2 Main image of issue (episode) 166 3 8 IJ2 Publishing frequency of Issue (episode) 162 3 9 IC1 Released date of issue (episode) 159 3 Publisher (comic magazines or comic 10 IC2 books) 154 3 Name of sound that provided with the 11 IH3 episode automatically 114 2
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There is no significant difference in the ranking of elements. However, respondents require more elements for their information needs to extract digital comics than other processes (the sum of the total numbers increased from 5609 (Unit 2) and 6144 (Unit 3) to 6650 (Unit 4)). Also, the median values are higher than other Units.
The second question of Unit 4 is how users felt about the digital comic searching process in general. The results are shown in the pie chart below.
It is usually hard for me to find what I’m looking for 5 3
It is sometimes hard for me to find what I’m 22 looking for It is rarely hard for me to 35 find what I’m looking for
It is never hard for me to find what I’m looking for
Figure 20 Levels of difficulty on the digital comic searching process of respondents
Only 8% of respondents answered it was never hard to find the information they wanted. Despite a variety of searching support tools that are available on the web such as directories and special collection cataloging tools for digital comics, the majority of respondents indicated they had some level of difficulty when they look for information.
The purpose of the last question is to examine why users felt they faced difficulties in searching for information related to digital comics. The results are displayed in the bar chart below.
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looking for websites to purchase digital comics 7
looking for websites providing digital comics 13
deciding which website or mobile application to 15 search
deciding what to read because of lack of 17 information
finding some information about digital comics 11 such as name of writer, character creator
finding a specific previous episodes that you 24 have read before
finding the name of a digital comic when you 33 only know the story of the digital comics
finding names of digital comics when you only know the appearance of characters on the 25 digital comics
finding the frames (strips) of digital comics that 17 you have seen before
finding the text inside the digital comics 18
Other 2
0 5 10 15 20 25 30 35
Figure 21 Respondents’ reasons of facing difficulties in searching for information related to digital comics
The majority of respondents indicated they have difficulties finding digital comics when they only know the story of the comic. It is essential to say that elements related to stories are highly important factors for all around searching tasks. According to the results of unit 1, unit 2 and unit 3, G02 story description and other fields which are related to story (e.g. E01 writer) were always highly ranked (Top 10).
Finding comics by appearance of characters is also difficult for more than two thirds of the users, who responded. Characters in comics are one of the most important factors for
64 comics’ users. More information related characters should be recorded to support users’ searches.
It is important to highlight that users indicated they had difficulties when they looked for specific episodes. It is possible there was a lack of episode description on current systems. Also, according to the result of the first question in Unit 4, many of the elements which are in the issue (episode) related fields (e.g. IB1 Issue (episode) title, IJ1Issue (episode) number, IG1Issue (episode) story description, IF1 Issue (episode) subject (keywords), IH1 Cover image of issue (episode), IC3 Name of comic magazine which publish episode serially, IH2 Main image of issue (episode), IJ2 Publishing frequency of Issue (episode) and IC1 Released date of issue (episode)) got higher total numbers than the lowest 25 ranked elements of the general description elements. For this reason, sufficient information related to issue (episode) should be given to users to fulfil their information requirements.
4.2.4. Summary of Information Seeking Process of Digital Comic Users
The table represent the top twenty elements between three processes.
Table 19 Top twenty elements between three processes
Define problem and select source Formulating and executing queries Examining and identifying the Results
1 B01 Main title 248 4 B01 Main title 240 4 B01 Main title 244 4 2 E01 Writer 187 3 B02 Original title 210 3 B02 Original title 220 4 Story 3 B02 Original title 184 3 G02 195 3 G01 Language 212 4 description 4 F08 Topic 182 3 E01 Writer 194 3 E01 Writer 209 3 Alternative F0 5 B03 178 3 F05 Genre 194 3 Genre 207 4 title 5 Names of G0 Story 5 F01 leading 178 3 G01 Language 194 3 202 3 2 description characters Names of H0 7 F05 Genre 176 3 F01 leading 192 3 Cover image 199 3 1 characters G0 Story Alternative F0 8 174 3 B03 187 3 Subject 198 3 2 description title 7 Alternative 9 F07 Subject 168 3 A01 Type 180 3 B03 197 3 title F0 9 G01 Language 168 3 F08 Topic 179 3 Topic 195 3 8 Names of 1 A01 Type 167 3 F07 Subject 174 3 F01 leading 194 3 1 characters Related media Related media 1 G0 G1 which shares 166 3 G03 which shares 174 3 User review 189 3 2 3 0 the story the story
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1 E02 Illustrator 157 3 G10 User review 173 3 A01 Type 188 3 3 1 G1 F0 Setting of User review 156 3 G09 User Ratings 170 3 188 3 4 0 9 comics Related 1 G0 G0 media which User Ratings 154 3 H01 Cover image 170 3 185 3 5 9 3 shares the story 1 Setting of Setting of G0 F09 150 2 F09 169 3 User Ratings 185 3 6 comics comics 9 Comic related 1 F06 historical 147 2 E02 Illustrator 166 3 E02 Illustrator 183 3 7 events 1 G0 Main image of H0 Main image Trailers 143 2 H02 157 2 179 3 8 5 comic 2 of comic Comic related 1 Names of sub F03 139 2 F06 historical 156 3 C02 Publisher 163 3 9 characters events Appearance Comic related 2 G0 Target F0 139 2 F02 of leading 152 2 historical 159 3 0 8 audience 6 characters events
There are total seventeen elements are in common (highlighted elements). They are B01 Main title, E01 Writer, B02 Original title, F08 Topic, B03 Alternative title, F01 Names of leading characters, F05 Genre, G02 Story description, F07 Subject, G01 Language, A01 Type, G03 Related media which shares the story, E02 Illustrator, G10 User review, G19 User Ratings, F09 Setting of comics and F06 Comic related historical events..
Some statement could make based on the result.
Users can access variety types of digital comic online. Digital comic readers can be called active readers because they like to share information related to digital comics between them not only on the web but also with their friends. Most digital comic users read digital comics for leisure. Some digital comic users read more than one digital comics weekly. Some digital comic users read since they were teenager. Some minority digital comic users read digital comics for working purpose such as second language studying.
Users often engage search for reading episode. (Users require links to the episode.) Users often engage search for to decide whether to read. Users often engage search for character information. Users often engage search for related media information such as video games and animations.
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Main information source of digital comic searching encountered social spaces such as recommendations from friends, social networking services and online communities.
Users mainly use the search box for searching known items. Title and Title related elements are extremely popular for query formulation. Topic, genre and names of leading characters are popular for query formulation. Titles and numbers of series, volumes and issue (episode) are popular elements for query formulation. Elements related to publication and distribution field and the physical description field are rarely used for query formulation.
Users often use the directory tabs for browsing digital comics to decide whether to read. Users often browse digital comics by genre, top rated, series, A-Z list and statues (for on-going digital comics).
Images of comics are important on the identifying digital comics and extracting information. Users require story descriptions of digital comics on the identifying digital comics and extracting information. In general, digital comic users require more information on the extracting information stage than the identifying information stage.
The majority of digital comic users had difficulties of finding information related to digital comics.
Users require more story description on current systems. Users require more character description on current systems. Users require more information related to episodes on current systems.
Users often do not consider about physical description of digital comics. The writer information is more important than the illustrator information for whole process.
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Chapter5. Discussion
5.1. Discussion of Findings
5.1.1. Discussion of Mock-up Elements
The total sixty-nine potential metadata elements were defined on the digital comic domain analysis. Some of elements (F01 Names of leading character and F02 Appearance of leading characters) were difficult to find matching fields in any existing metadata schemas (e.g. MARC 21, DC, etc.) even though they are frequently appeared across all resource of the digital comic domain. Therefore, the specialised digital comic metadata schema is required for store distinct characteristic of digital comics because a number of metadata schema developed without consideration on digital comics.
It can be suggested forty elements were for generally describing digital comics and additional twenty-nine were for series, volumes and issue (episode). It is possible to say that the digital comic which is contained any value of series, volumes and issue (episode) should have a hierarchical structure metadata for collating any related descriptions.
Morozumi et al. (2009) advocated the components of comics match straightforward to the hierarchical structure of the video content (e.g. group of video programs = title of comics, program = episode of comic etc.). Also, Harding (2014) defined the series and issues as important elements for the relational metadata design. Nevertheless, the collected metadata schema elements in this research and other proposed different metadata frameworks have many differences; the notion of metadata design for digital comics could be similar.
5.1.2. Discussion of Information Seeking Process of Digital Comic Users
Digital comic Users Pansard & Fries (2009) argued that digital comics allow more accessibility for users. Also, digital comic users also get more accessibility for variety different types of digital comics online. The majority of respondents indicated they have read different types of digital
68 comic even though there were some language and culture barriers. For example, the majority of English speakers (thirteen out of seventeen) answered they read Japanese manga and five out of seventeen English speakers indicated that they read webtoons which is a Korean comic. It can be suggested that the native languages and cultural background did not affect the selection of digital comics. Moreover, according to this finding, the standardised metadata for all types of sequential art on the web is necessary for users.
George et al. (2011) defined comic users as active readers. In general, sources of digital comic searching encountered social spaces such as recommendations from friends, social networking services and online communities. For this reason, users would be pleased if the metadata could give some types of intellective knowledge of digital comics which can be a higher level of information description (Bellinger et al., 2004) such as user rating, user feedback and recommendations of next reading.
Define problem and select source
Koll (2000) pointed that people seek information with a variety of needs, so it is important to investigate digital comic users’ the purpose of search. The majority of digital comic users engaged with the known item searching. For example, users start to search when they have a particular digital comic to read in their mind. In that case, the users might formulate queries on a known document (digital comic) attribute such as writer and title (Chu, 2009).
Besides, users involved in searching for many purpose, mainly, character information, related media and other readers’ opinion. Therefore sufficient information needs to be provided within the descriptions about digital comics in order to support information seeking process of digital comic users.
Formulating and executing queries Title and title related elements, writer, topic and names of leading characters were particularly popular for formulating queries. There are several assumptions that could be made to explain this. Firstly, the main purpose of searching was the known item search which use known document (digital comic) attribute as formulating quires which could be the listed elements. Secondly, they could be easy to formulate as queries because,
69 normally, these elements are shorter than other elements. Baeza-Yates & Ribeiro-Neto (2011) stated that queries on the web are short and consisting of one to three words.
There are many diverse directory tabs provided on digital comic websites which help support to browse comics by category (Kowalski, 1997). For example, a user who intends to find a science fiction comic to read would naturally browse the Genre category on the comic website. Therefore, the main purpose of using the search box (to search known items) and the directory tabs (to browse list of comic) could be different. The majority of users tend to browse comics by genre, top rated series, A-Z list and status.
Examining and identifying the Results
It is important to highlight that the sum of the mock up elements’ total number significantly increased from Unit 2 Formulating and executing queries (5609) to Unit 3 Examining and identifying the Results (6144). Moreover, elements which scored over 150 also increased (15 elements in Unit 2, 20 elements in Unit 3). There are several assumptions that could be made to explain this. Firstly, users could require more description elements when they are identifying the results than formulating the queries. Secondly, users might have difficulties in recalling some information or knowledge for formulating queries. In general, the majority of people find it hard to formulate queries for retrieving the information they want (Marchionini, 1989 and Blair et al., 1985). To support users in identifying digital comics, sufficient information should be shown on the results page.
Moreover, Visual elements such as cover image and main image of comic are useful for examining and identifying the results. However, on the limited screen size, all of images related comics cannot be displayed. Suh et al. (2009) claimed that thumbnail images can support users identify result more efficiently on the result page.
Extracting Information
Twenty-five elements from the mock up elements scored over 150 (15 elements in Unit 2 and 20 elements in Unit 3). Also, the sum of the total numbers increased again from 6144 to 6650 which means users request more information when they extract digital comics.
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Marchonini (1995: 57) stated the identified document is “… judged relevant, the information seeker may choose to continue assessing its relevance by extracting…”. For example, when the user identified several digital comics which can be relevant to the purpose of reading, the user re-examined the revised comics to fully meet the conditions of the user’s goal. Therefore, users will require more information than examining and identifying the results.
Series, Volume and Issue (Episode) It is important to highlight that users require information related to series, volume and issue (episode) frequently all stages of information seeking, particularly, issue (episode). First, the majority of users indicated that they engaged in searching for reading episode. Second, many of the elements which are in the issue (episode) related fields got higher total numbers than the lowest 25 ranked elements of the general description elements.
Despite the importance of these elements, users still had difficulties when they looked for specific episodes. It is possible there was a lack of episode description on current systems. Therefore, sufficient information related to issue (episode) should be given to users to fulfil their information requirements.
5.2. Proposed User-centred Metadata Schema
A total of forty out of sixty-nine elements were identified highly required from users through their digital comic information seeking process which consists of twenty-two elements in general description elements and eighteen in the series, volume and issue (episode) elements.
However, some of additional elements were necessary to be added on the final metadata schema because firstly, support some of important elements (e.g. G07 Character arc was added as the resource of character information), second, the elements if users required highly in particular part of the process.
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Finally, fifty-five metadata elements finally defined as the optimal user-centred metadata schema where all elements are optional and repeatable depending on features and structures of the digital comic.
5.2.1. Proposed Metadata Schema
The proposed and recommended metadata schema is provided in table 20. Identified elements which users highly required through the information seeking process are highlighted with light red.
Table 20 Proposed user-centred metadata schema
General description elements Code Name of Elements 1 A01 Type 2 B01 Main title 3 B02 Original title 4 B03 Alternative title 5 C01 Digital Release Date 6 C02 Publisher 7 E01 Writer 8 E02 Illustrator 9 F01 Names of leading characters 10 F02 Appearance of leading characters 11 F03 Names of sub characters 12 F05 Genre 13 F06 Comic related historical events 14 F07 Subject 15 F08 Topic 16 F09 Setting of comics 17 G01 Language 18 G02 Story description 19 G03 Related media which shares the story 20 G06 Story arc 21 G07 Character arc 22 G08 Target audience 23 G09 User Ratings 24 G10 User review 25 H01 Cover image 26 H02 Main comic image 27 Identifier
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Status 1 J01 Status Elements for series 1 SB1 Series title 2 SC1 Released date of series 3 SF1 Series subject (keywords) 4 SG1 Series story description 5 SH2 Main image of series 6 SJ1 Series number 7 Series Identifier Elements for Volume 1 VB1 Volume title 2 VC1 Released date of volume 3 VC2 Publisher (volume) 4 VF1 Volume subject (keywords) 5 VG3 Volume story description 6 VH1 Main image of volume 7 VH2 Cover image of volume 8 VJ1 Volume number 9 Volume Identifier Elements for Issue (Episode) 1 IB1 Issue (episode) title 2 IC1 Released date of issue (episode) 3 IC2 Publisher (comic magazines or comic books) 4 IC3 Name of comic magazine which publish episode serially 5 IF1 Issue (episode) subject (keywords) 6 IG1 Issue (episode) story description 7 IH1 Cover image of issue (episode) 8 IH2 Represent image of issue (episode) 9 IJ1 Issue (episode) number 10 IJ2 Publishing frequency of Issue (episode) 11 Issue (episode) Identifier
It is important to represent the several layers of the digital comics’ hierarchical structures which have any value of series, volume and issue (episode). To help understand the structure of digital comics there is example figure is represented below. (These elements related to series, volume and issue (episode) can be chosen depends on structure of the digital comic. If the digital comic do not have any value of series or volume it is not necessary to record)
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Picture 3 Exmple of a digital comic metadata figure
5.2.2. Proposed Metadata Schema and Implementation
Nevertheless, it is difficult to manage and organise digital comic information through other standardised metadata schemas, but it is still important to prove the implementation feasibility by using existing metadata schemas.
For this part, there will be an implementation of the proposed twenty-eight general description metadata elements based on two existing standards which are MARC 21 and DC. These two metadata schemas have significantly different features; MARC 21 subdivided bibliography descriptions into more than two-hundred fields (OCLC, 2014), on the other hand, DC only has fifteen fields in total. Compared to MARC21, DC is extremely simple and flexible. Moreover all of fields are optional and repeatable (Miller, 2011). However, both are commonly used metadata schemas within current cataloging systems.
General description metadata schema implementation
Table 21 General description metadata schema implementation
Name of Implementation on MARC Code Implementation on DC Elements (relevance field in MARC) 007 1 A01 Type Physical Description Fixed Field- Type General Information 2 B01 Main title 245 Title
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Title Statement 246 3 B02 Original title Title Varying Form of Title 246 4 B03 Alternative title Title Varying Form of Title Digital Release 260 5 C01 Date Date Publication, Distribution, etc. 260 6 C02 Publisher Publisher Publication, Distribution, etc. 508 7 E01 Writer Creation/Production Credits Creator Note 508 8 E02 Illustrator Creation/Production Credits Creator Note 600 Names of leading 9 F01 Subject Added Entry - Personal Subject characters Name 600 or 656 Appearance of Subject Added Entry - Personal 10 F02 leading Subject Name or Index Term - characters Occupation 600 Names of sub 11 F03 Subject Added Entry - Personal Subject characters Name 600 or 656 Subject Added Entry - Personal 12 F05 Genre Subject Name or Index Term - Occupation Comic related 653 13 F06 Subject historical events Index Term - Uncontrolled 656 14 F07 Subject Subject Index Term - Occupation 650 15 F08 Topic Subject Added Entry - Topical Subject Term 651 16 F09 Setting of comics Subject Added Entry - Coverage Geographic Name 546 17 G01 Language Language Language Note 520 18 G02 Story description Description Summary, etc. Related media 500 19 G03 which shares the Relation General Note story 500 20 G06 Story arc Relation General Note 500 21 G07 Character arc Relation General Note
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521 22 G08 Target audience Description Target Audience Note 520 23 G09 User Ratings Description General Note 520 24 G10 User review Description General Note (Can be described as 856 25 H01 Cover image single entity and link by Electronic Location and Access relation field) (Can be described as Main comic 856 26 H02 single entity and link by image Electronic Location and Access relation field) 020 Identifier International Standard Book 27 (e.g. the link to Number (if available) or Identifier the digital comic) 856 Electronic Location and Access
Elements related to any value of the series, volume and issue (episode) can be described on MARC 21, in 4XX series statement fields and in 8XX Series added entries and holdings. On DC, each item of series, volume and issue (episode) can be described as separated single item and these hierarchical structures could be represented as links using by record in the “Relation” field.
However, it could be difficult to represent information about some digital comics which have four layers of hierarchical structure (General→ Series→ Volume→ Episode) on MARC 21 fields and DC.
5.2.3. Proposed Metadata Schema and Example
The example of proposed metadata is provided in table 22. It is important to highlight that some of information on the example table was adapted and modified from the list of sites below.
- Amazon, One Piece, Vol. 71: Coliseum of Scoundrels eBook http://www.amazon.com/
- Vizmedia, One Piece http://www.viz.com/manga/digital/one-piece
- Wikia, One Piece
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http://onepiece.wikia.com
- Wikipedia, One Piece http://en.wikipedia.org/wiki/One_Piece
Table 22 Example of the proposed metadata
General description elements Code Name of Elements Example A01 Type Manga B01 Main title One Piece B02 Original title ワンピース B03 Alternative title Wan Pīsu C01 Digital Release Date 9/07/ 2011 C02 Publisher VIZ Media: Shonen Jump E01 Writer Eiichiro, Oda E02 Illustrator Eiichiro, Oda F01 Names of leading Monkey D. Luffy characters F02 Appearance of leading Monkey D. Luffy is recognized by his trademark straw hat, characters portrayed as a carefree and happy-go-lucky character with great ambitions. F03 Names of sub characters Roronoa Zoro F03 Names of sub characters Nami F03 Names of sub characters Usopp F05 Genre Action F05 Genre Adventure F07 Subject Pirates F08 Topic Comedy F09 Setting of comics Ocean G01 Language English G02 Story description Monkey D. Luffy sets off on a journey from the East Blue Sea to find the One Piece and become King of the Pirates. G03 Related media which One Piece: Defeat The Pirate Ganzack! (video game) shares the story G03 Related media which One Piece: Character Song Carnival!! (music) shares the story G03 Related media which Clockwork Island Adventure (film) shares the story G06 Story arc Pirate Alliance Saga G06 Story arc Fishman Island Saga G06 Story arc Summit War Saga G09 User Ratings 4.9 out of 5 stars (Amazon) G10 User review “…It was a great read and I can't wait for the next one!...” (M.Lemus, 06/09/2013) H02 Main comic image http://www.toei-anim.co.jp/tv/onep/img/mainvisual/logo.png Identifier http://www.viz.com/manga/digital/one-piece
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Status J01 Status On going Elements for series SB1 Series title Pirate Alliance Saga SC1 Released date of series 03/09/2014 SF1 Series subject (keywords) Punk Hazard SF1 Series subject (keywords) Dressrosa SG1 Series story description The Monkey D. Luffy finally entered the island of Raftel, but after receiving a call from Punk Hazard, they became entangled in the illegal experiments of Caesar Clown. SH2 Main image of series http://img3.wikia.nocookie.net/__cb20140727111256/onepie ce/images/thumb/5/5f/Pirate_Alliance_Saga.png/640px- Pirate_Alliance_Saga.png Elements for Volume VB1 Volume title Coliseum of Scoundrels VC1 Released date of volume 03/09/2014 VC2 Publisher (volume) VIZ Media: Shonen Jump VF1 Volume subject (keywords) Doflamingo’s Smile factory VG3 Volume story description Monkey D. Luffy have infiltrated the kingdom of Dressrosa in order to destroy Doflamingo’s Smile factory. VH2 Cover image of volume http://s3.amazonaws.com/wsl-viz/manga/thumbs/thumb- 10853-ONP_71_web.jpg VJ1 Volume number 71 Volume Identifier ISBN 978-1421569451 Volume Identifier http://www.viz.com/manga/digital/one-piece-volume- 71/2694 Elements for Issue (Episode) IB1 Issue (episode) title Adventure in the Country of Love, Passion, and Toys IC1 Released date of issue 11/03/2013 (episode) IC2 Publisher (comic magazines Shonen Jump or comic books) IC3 Name of comic magazine Weekly Shonen Jump which publish episode serially IF1 Issue (episode) subject Momonosuke (keywords) IF1 Issue (episode) subject Doflamingo (keywords) IG1 Issue (episode) story After Monkey D. Luffy and Law arrived on Dressrosa, Monkey description D. Luffy messed around with Momonosuke, who seemed to have another vague memory of Doflamingo. IJ1 Issue (episode) number 701 IJ2 Publishing frequency of Weekly Issue (episode)
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5.2.4. Problems and Challenges
There are some problems and challenges on the user-centred metadata set.
First, some of elements such as genre, subject and topic require controlled vocabularies in order to maintain the consistency in the granularity of data across all records. Characteristics of natural language such as synonym and homograph issue could hinder effective digital comic searching (Chu, 2010) because it could mismatch between the user query terms and information resource description term. By using controlled vocabularies for some elements can overcome variations that result from richness of natural language. Some libraries have considered some terms for comic cataloging. However, in the research field, there is little attention directed towards developments for controlled vocabularies for digital comics.
Second, source of information could be variable. Many descriptive elements can be recorded by observing information from the digital comics itself but some of elements require additional research on the digital comic using secondary source (e.g. user review, user rating and related media which shares the story).
Third, characters in the comics are one of the most valuable elements for users because many users engage searching for information related characters. However, it is difficult in making judgements for a main character in the digital comic. Moreover, some digital comics have very large character casts (e.g. One Piece etc.), and character casts can vary depending on the series, volume and issue (episode). More instruction should be provided in the future in order to ensure that catalogers can describe character elements in a consistent manner.
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Chapter6. Conclusion
Without a standardised way for organising and describing digital comics, it will be impossible to search and find the digital comics we want, or the episode we had once read. To propose this domain specific user-centred metadata schema, two method techniques had been taken; digital comic domain analysis and quantitative survey of digital comic users.
First, after reviewing the literature, several developed metadata schemas, digital comic related websites and library catalogs were examined to collect potential elements for describing digital comics. A total of sixty-nine elements were gathered and structures of digital comics were observed as the result of the domain analysis.
Second, collected elements were developed as a mock up metadata schema and each of elements were given clear definitions.
Third, to investigate the information seeking process of digital comic users, the questionnaire was designed based on the notion of Marchonini’s (1995) information seeking process. The mock up metadata schema was placed in several sections to estimate the value of each element.
Fourth, the link of questionnaire was distributed by e-mail and the Facebook (non- probability sampling).
Five, since sixty-five respondents were gathered the result of questionnaire was analysed numerically. Six, there were some important findings made about the information seeking behaviour of digital comic such as purpose of searching digital comics, popular elements for formulate quires, information requirements on identifying and extracting information and difficulties on searching digital comic information.
Finally, by reflecting on the information seeking process of digital comic users the mock up metadata schema was sorted and established the final metadata which consist of fifty-five elements.
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6.1. Accomplishment Aim and List of Objectives
To achieve the aim of this research, there were four of specific research objectives that needed to be met. By reflecting on the research processes, this part summarises these achievements.
Aim The research aimed to create a user-centred metadata for digital comics. The final set of fifty-five metadata elements were provided for descripting digital comics developed from a user-centred approach.
Objectives
Object 1. To review related literature in the areas of: Comic and digital comics Comics in information and knowledge management discipline Information Resource Description (metadata) User-centred metadata To review these four areas a sufficient number of literatures were engaged. The literature review is provided on Chapter2. The literature review supported the designing the methodology in order to create user-centred metadata for digital comics.
Object2. To collect and list potential metadata elements on literatures, library catalogs and commercial digital comic websites The total three developed metadata schemas, a sufficient number of digital comic related websites and four library catalogs were examined to collect potential elements for describing digital comics. The total sixty-nine elements were gathered the list of collected elements is provided as the mock up metadata schema on Chapter 4.1.1.
Object3. To investigate the information seeking process of digital comic readers in online environments To investigate the information seeking process of digital comic users, the questionnaire was designed based on the notion of Marchonini’s (1995) information seeking process. There were numbers of findings were made about information seeking process of digital comic
81 readers. The summary of information seeking process of digital comic readers is provided in Chapter 4.2.4.
Object4. To design an optimal user-centred metadata schema for digital comics The potential elements were sorted by reflecting findings of digital comic users’ the information seeking and established the user-centred metadata schema. The schema is represented on Chapter 5.2.1.
6.2. Limitation and Future Work
Methodology
There are several limitations on the methodology.
First, for the domain analysis, even though there are distinct common features for the different types of digital comics, it is still difficult to find common description elements for them. Therefore, larger number of sources should be engaged.
Second, on the questionnaire, a larger sample of digital comic users should be engaged to find more exact patterns of information seeking behaviour and decrease sampling error. For future research, a large-scale user survey should be conducted to achieve a deeper understanding of users’ information usage and needs.
Third, it is possible to suggest more research techniques to in-depth study such as structured interview of digital comic users or investigating Human Computer Interaction (HCI) during searching process.
Data analysis
Despite the large number of collected data, there was a limitation on data handling due to limited space and the tool that used for data analysing. It would be interesting to see that the information seeking process patterns is dependent on the native language of the reader and the types of comic that the user reads.
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Proposed metadata schema
There are several challenges on the proposed metadata schema.
First, some elements fields require controlled vocabularies which have not developed on this field.
Second, many of elements require secondary sources to record, those elements are required to fulfil information needs of digital comic users but recording these elements are time consuming. Also, if catalogers have no expertise on digital comics they would have difficulties in understanding what the elements mean.
Third, it is important to consider how the metadata schema can be implemented on current systems. There were two implementation suggestions made on Chapter 5.2.2 but more understanding and considerations are required in how to apply the schema. It is important to revise the structure of this metadata schema for future implementation of any digital comic metadata schemas.
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Appendix 1 Proposal for Research Ethics Review
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Appendix 2 Research Ethics Approval Letter
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Appendix 3 Online Questionnaire Consent Form
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Appendix 4 Online Questionnaire Part.1
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Appendix 5 Online Questionnaire Part.2
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Appendix 6 Online Questionnaire Part.3
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