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Metadata for Semantic and Social Applications
etadata is a key aspect of our evolving infrastructure for information management, social computing, and scientific collaboration. DC-2008M will focus on metadata challenges, solutions, and innovation in initiatives and activities underlying semantic and social applications. Metadata is part of the fabric of social computing, which includes the use of wikis, blogs, and tagging for collaboration and participation. Metadata also underlies the development of semantic applications, and the Semantic Web — the representation and integration of multimedia knowledge structures on the basis of semantic models. These two trends flow together in applications such as Wikipedia, where authors collectively create structured information that can be extracted and used to enhance access to and use of information sources. Recent discussion has focused on how existing bibliographic standards can be expressed as Semantic Metadata for Web vocabularies to facilitate the ingration of library and cultural heritage data with other types of data. Harnessing the efforts of content providers and end-users to link, tag, edit, and describe their Semantic and information in interoperable ways (”participatory metadata”) is a key step towards providing knowledge environments that are scalable, self-correcting, and evolvable. Social Applications DC-2008 will explore conceptual and practical issues in the development and deployment of semantic and social applications to meet the needs of specific communities of practice. Edited by Jane Greenberg and Wolfgang Klas DC-2008 -
Provenance and Annotations for Linked Data
Proc. Int’l Conf. on Dublin Core and Metadata Applications 2013 Provenance and Annotations for Linked Data Kai Eckert University of Mannheim, Germany [email protected] Abstract Provenance tracking for Linked Data requires the identification of Linked Data resources. Annotating Linked Data on the level of single statements requires the identification of these statements. The concept of a Provenance Context is introduced as the basis for a consistent data model for Linked Data that incorporates current best-practices and creates identity for every published Linked Dataset. A comparison of this model with the Dublin Core Abstract Model is provided to gain further understanding, how Linked Data affects the traditional view on metadata and to what extent our approach could help to mediate. Finally, a linking mechanism based on RDF reification is developed to annotate single statements within a Provenance Context. Keywords: Provenance; Annotations; RDF; Linked Data; DCAM; DM2E; 1. Introduction This paper addresses two challenges faced by many Linked Data applications: How to provide, access, and use provenance information about the data; and how to enable data annotations, i.e., further statements about the data, subsets of the data, or even single statements. Both challenges are related as both require the existence of identifiers for the data. We use the Linked Data infrastructure that is currently developed in the DM2E project as an example with typical use- cases and resulting requirements. 1.1. Foundations Linked Data, the publication of data on the Web, enables easy access to data and supports the reuse of data. The Hypertext Transfer Protocol (HTTP) is used to access a Uniform Resource Identifier (URI) and to retrieve data about the resource. -
Thesauruses and Ontologies
Thesauruses and ontologies Silvia Arano Citación recomendada: Silvia Arano. Thesauruses and ontologies [en linea]. "Hipertext.net", num. 3, 2005. <http://www.hipertext.net> [Consulted: 12 feb. 2007]. 1. Introduction During the past few years, the information representation and retrieval sector in the area of Documentation and Biblioteconomy has had to assume the important repercussions of the Internet and its associated technologies, and in particular, the World Wide Web (WWW). Technological modifications arising from these important changes are leading to the gradual digitalisation of the information representation and retrieval sector, affecting information artefacts, representation and retrieval tools and user requirements. In the light of this growing context of digitalisation, diverse information representation and retrieval tools exist, which must be studied in addition to diverse fields of knowledge in which these tools have originated: Linguistics, Artificial Intelligence, Documentation, Linguistic Engineering... Hence, in specialised literature, analyses are performed on information representation and retrieval tools, taxonomies, classification systems, computational lexicons, lexical databases, thesauruses, titles lists, knowledge bases, conceptual maps, ontologies, synonym rings and semantic networks, among others. Among this wide spectrum of information representation and retrieval tools are thesauruses and ontologies, which are most often linked in bibliography, even though they come from completely different disciplinary areas. However, the conceptualisation applied by authors to the terms "thesaurus" and "ontology" is quite diverse, and sometimes authors confuse, oppose, complement or overlap both these concepts. The overall objective of the present article [ 1] is to establish the relationship between the concepts of thesaurus and ontology in the Documentation and Biblioteconomy field. Two specific objectives have been established for this purpose. -
Rdfa in XHTML: Syntax and Processing Rdfa in XHTML: Syntax and Processing
RDFa in XHTML: Syntax and Processing RDFa in XHTML: Syntax and Processing RDFa in XHTML: Syntax and Processing A collection of attributes and processing rules for extending XHTML to support RDF W3C Recommendation 14 October 2008 This version: http://www.w3.org/TR/2008/REC-rdfa-syntax-20081014 Latest version: http://www.w3.org/TR/rdfa-syntax Previous version: http://www.w3.org/TR/2008/PR-rdfa-syntax-20080904 Diff from previous version: rdfa-syntax-diff.html Editors: Ben Adida, Creative Commons [email protected] Mark Birbeck, webBackplane [email protected] Shane McCarron, Applied Testing and Technology, Inc. [email protected] Steven Pemberton, CWI Please refer to the errata for this document, which may include some normative corrections. This document is also available in these non-normative formats: PostScript version, PDF version, ZIP archive, and Gzip’d TAR archive. The English version of this specification is the only normative version. Non-normative translations may also be available. Copyright © 2007-2008 W3C® (MIT, ERCIM, Keio), All Rights Reserved. W3C liability, trademark and document use rules apply. Abstract The current Web is primarily made up of an enormous number of documents that have been created using HTML. These documents contain significant amounts of structured data, which is largely unavailable to tools and applications. When publishers can express this data more completely, and when tools can read it, a new world of user functionality becomes available, letting users transfer structured data between applications and web sites, and allowing browsing applications to improve the user experience: an event on a web page can be directly imported - 1 - How to Read this Document RDFa in XHTML: Syntax and Processing into a user’s desktop calendar; a license on a document can be detected so that users can be informed of their rights automatically; a photo’s creator, camera setting information, resolution, location and topic can be published as easily as the original photo itself, enabling structured search and sharing. -
CODATA Workshop on Big Data Programme Book
Sponsor I CODACODATA S UU Co-Sponsors Organizer Workshop on Big Data for International Scientific Programmes CONTENTS I. Sponsoring Organizations International Council for Science (ICSU) I. Sponsoring Organizations 2 The International Council for Science (ICSU) is a the international scientific community to II. Programme 7 non-governmental organization with a global strengthen international science for the benefit of membership of national scientific bodies society. (121members, representing 141 countries) and international scientific unions (31 members). ICSU: www.icsu.org III. Remarks and Abstracts 13 ICSU mobilizes the knowledge and resources of Committee on Data for Science and Technology (CODATA) IV. Short Biography of Speakers 28 I CODACODATA S UU V. Conference Venue Layout 41 CODATA, the ICSU Committee on Data for Science challenges and ‘hot topics’ at the frontiers and Technology, was established in 1966 to meet of data science (through CODATA Task a need for an international coordinating body to Groups and Working Groups and other improve the management and preservation of initiatives). VI. General Information 43 scientific data. CODATA has been at the forefront 3. Developing data strategies for international of data science and data policy issues since that science programmes and supporting ICSU date. activities such as Future Earth and Integrated About Beijing 43 Research on Disaster Risk (IRDR) to address CODATA supports ICSU’s mission of ‘strengthening data management needs. international science for the benefit of society’ by ‘promoting improved scientific and technical data Through events like the Workshop on Big Data for About the Workshop Venue 43 management and use’. CODATA achieves this International Scientific Programmes and mission through three strands of activity: SciDataCon 2014, CODATA collaborates with 1. -
OGC Testbed-14: Semantically Enabled Aviation Data Models Engineering Report
OGC Testbed-14 Semantically Enabled Aviation Data Models Engineering Report Table of Contents 1. Summary . 4 1.1. Requirements & Research Motivation . 4 1.2. Prior-After Comparison. 4 1.3. Recommendations for Future Work . 5 1.4. What does this ER mean for the Working Group and OGC in general . 6 1.5. Document contributor contact points . 6 1.6. Foreword . 6 2. References . 8 3. Terms and definitions . 9 3.1. Semantics . 9 3.2. Service Description. 9 3.3. Service-Oriented Architecture (SOA) . 9 3.4. Registry . 9 3.5. System Wide Information Management (SWIM) . 9 3.6. Taxonomy . 9 3.7. Web Service . 10 4. Abbreviated Terms . 11 5. Overview . 12 6. Review of Data Models . 13 6.1. Information Exchange Models . 13 6.1.1. Flight Information Exchange Model (FIXM). 13 6.1.2. Aeronautical Information Exchange (AIXM) Model. 13 6.1.3. Weather Information Exchange Model (WXXM) . 14 6.1.4. NASA Air Traffic Management (ATM) Model . 14 6.2. Service description models . 19 6.2.1. Service Description Conceptual Model (SDCM) . 19 6.2.2. Web Service Description Ontological Model (WSDOM). 23 6.2.3. SWIM Documentation Controlled Vocabulary (FAA) . 25 7. Semantic Enablement Approaches . 27 8. Metadata level semantic enablement . 33 8.1. Issues with existing metadata standards . 34 8.1.1. Identification of Resources. 34 8.1.2. Resolvable URI. 34 8.1.3. Multilingual Support . 35 8.1.4. External Resource Descriptions . 35 8.1.5. Controlled Vocabulary Management . 36 8.1.6. Keywords Types . 37 8.1.7. Keyword Labeling Inconsistencies . -
Contents the Three Languages Theory In
Ie Contents The Three LanguagesTheory in Information Retrieval Part-controlled Vocabulary for Literature Studies UDC: International Medium Edition - English Text Class Number Searching in an Experimental Online Catalog UDC 168 + International Classification Vol. 13 (1986) Nr. 3 025.4 + 001.4 (05) INTERNATIONAL CLASSIFICATION Devoted to Concept Theory, Systematic Ter minology and Organization of Knowledge Editors Dr. phil. Ingetraut Dahlberg, 0-6000 Frank furt 50, Woogstr. 36a, Editor-in-chief Prof. Dr. med. Dr. phil. Alwin Diemer, Philo sophisches Institut der Universitat Dusseldorf, D-4000 Dusseldorf 1, Universitatsstr. 1, FRG. Prof. Jean M. Perreault, University Library, University of Alabama, P. O. B. 2600 Hunts Contents ville, Alabama 35807, USA Prof. Arashanipalai Neelameghan, clo Unes Editorial co PGI. 7, Place de Fontenoy, F-75700 Paris New Uses for Old Schemes 125 co-sponsored by - FID/CR (Federation Internationale de Do Articles cumentation, Committee on Classification Re G.Deschatelets: The three languages theory in information retrieval. 126 search, address see Dr. I. Dahlberg K.Harris: Part-controlled vocabulary for literature studies ..... 133 A.Chatterjee, G.G.Choudhury: UDC: International Medium Edition - Consulting Editors Mrs. Jean Aitchison, 12, Sollershott West, English text ....... ,. .. ....... ... .... 137 K.Markey: Class number searching in an experimental online catalog 142 Letchworth, Herts., SG6 3PX, England Prof. Asterio T. Campos, Departamento de Bi Reports and Communications . ... .. 151 blioteconomia, Universidade de Brasilia, Bra CSNA Annual Meeting 1986 - COMPSTAT 1986 - Fall Meeting of SEK DA-NK, silia OF, Brazil Gesellschaft flir Klassifikation - Stability in Classification - Dr. A.1. Cernyj, VINITI, Moscow A-219 Bal Standardization in Computerized Lexicography - Going for Gold - tijskaja u1. -
Introduction to Ontology- Based Semantics Goals Service
Goals • To provide some insight into the usefulness of ontologies Introduction to Ontology- • To provide an understanding of the based Semantics features of RDFS and OWL and their use in automated reasoning Semantic Web, ontologies, RDF, OWL, • To provide an outline of the N3 syntax N3 • Use N3 to express RDFS and OWL – sufficient for later examples and exercises on service semantics With thanks to Declan O’Sullivan @ David Lewis @ David Lewis Service Semantics Functional Semantics • WSDL provides the syntax we need for interoperating with a service, but little in the way of semantics • What do ‘origin’ and ‘destination’ strings • Examining this example raises many questions about represent? functional and non-functional semantics – Country, city, airport, restrictions (airline, national, <message name=“getcheapestFlightRequest"> regional)? <part name=“origin" type="xsd:string"/> <part name=“destination" type="xsd:string"/> • What does ‘flight’ string represent? <part name=“date" type="xsd:date"/> – Airline, flight number, plane type? </message> <message name=“getcheapestFlightResponse"> • What does ‘time’ string represent? <part name=“flight" type="xsd:string"/> <part name=“time" type="xsd:time"/> – Departure time? <part name=“cost” type=“xsd:float”/> </message> – Note xsd:time probably is adequate - supports time- <portType name=“cheapestFlight"> zone information <operation name="getCheapestFlight"> <input message=“getcheapestFlightRequest"/> • What does ‘cost’ float represent? <output message=“getcheapestFlightResponse"/> </operation> -
Folksonomies - Cooperative Classification and Communication Through Shared Metadata
Folksonomies - Cooperative Classification and Communication Through Shared Metadata Adam Mathes Computer Mediated Communication - LIS590CMC Graduate School of Library and Information Science University of Illinois Urbana-Champaign December 2004 Abstract This paper examines user-generated metadata as implemented and applied in two web services designed to share and organize digital me- dia to better understand grassroots classification. Metadata - data about data - allows systems to collocate related information, and helps users find relevant information. The creation of metadata has generally been approached in two ways: professional creation and author creation. In li- braries and other organizations, creating metadata, primarily in the form of catalog records, has traditionally been the domain of dedicated profes- sionals working with complex, detailed rule sets and vocabularies. The primary problem with this approach is scalability and its impracticality for the vast amounts of content being produced and used, especially on the World Wide Web. The apparatus and tools built around professional cataloging systems are generally too complicated for anyone without spe- cialized training and knowledge. A second approach is for metadata to be created by authors. The movement towards creator described docu- ments was heralded by SGML, the WWW, and the Dublin Core Metadata Initiative. There are problems with this approach as well - often due to inadequate or inaccurate description, or outright deception. This paper examines a third approach: user-created metadata, where users of the documents and media create metadata for their own individual use that is also shared throughout a community. 1 The Creation of Metadata: Professionals, Con- tent Creators, Users Metadata is often characterized as “data about data.” Metadata is information, often highly structured, about documents, books, articles, photographs, or other items that is designed to support specific functions. -
What Are Controlled Vocabularies?
2. What Are Controlled Vocabularies? A controlled vocabulary is an organized arrangement of words and phrases used to index content and/or to retrieve content through browsing or searching. It typically includes preferred and variant terms and has a defined scope or describes a specific domain. 2.1. Purpose of Controlled Vocabularies The purpose of controlled vocabularies is to organize information and to provide terminology to catalog and retrieve information. While capturing the richness of variant terms, controlled vocabularies also promote consistency in preferred terms and the assignment of the same terms to similar content. Given that a shared goal of the cultural heritage community is to improve access to visual arts and material culture information, controlled vocabularies are essential. They are necessary at the indexing phase because without them catalogers will not consistently use the same term to refer to the same person, place, or thing. In the retrieval process, various end users may use different synonyms or more generic terms to refer to a given concept. End users are often not specialists and thus need to be guided because they may not know the correct term. The most important functions of a controlled vocabulary are to gather together variant terms and synonyms for concepts and to link concepts in a logical order or sort them into categories. Are a rose window and a Catherine wheel the same thing? How is pot-metal glass related to the more general term stained glass? The links and relationships in a controlled vocabulary ensure that these connections are defined and maintained, for both cataloging and retrieval. -
Taxonomy Directed Folksonomies
2nd Version Date : 19/06/2007 TAXONOMY DIRECTED FOLKSONOMIES Integrating user tagging and controlled vocabularies for Australian education networks Sarah Hayman and Nick Lothian education.au Adelaide Australia Meeting: 157 Classification and Indexing Simultaneous Interpretation: No WORLD LIBRARY AND INFORMATION CONGRESS: 73RD IFLA GENERAL CONFERENCE AND COUNCIL 19-23 August 2007, Durban, South Africa http://www.ifla.org/iv/ifla73/index.htm 1 Abstract What is the role of controlled vocabulary in a Web 2.0 world? Can we have the best of both worlds: balancing folksonomies and controlled vocabularies to help communities of users find and share information and resources most relevant to them? education.au develops and manages Australian online services for education and training. Its goal is to bring people, learning and technology together. education.au projects are increasingly involved in exploring the use of Web 2.0 developments building on user ideas, knowledge and experience, and how these might be integrated with existing information management systems. This paper presents work being undertaken in this area, particularly in relation to controlled vocabularies, and discusses the challenges faced. Education Network Australia (edna) is a leading online resource collection and collaborative network for education, with an extensive repository of selected educational resources with metadata created by educators and information specialists. It uses controlled vocabularies for metadata creation and searching, where users receive suggested related terms from an education thesaurus, with their results. We recognise that no formal thesaurus can keep pace with user needs so are interested in exploiting the power of folksonomies. We describe a proof of concept project to develop community contributions to managing information and resources, using Taxonomy-Directed Folksonomy. -
Download the 2021 IEEE Thesaurus
2021 IEEE Thesaurus Version 1.0 Created by The Institute of Electrical and Electronics Engineers (IEEE) 2021 IEEE Thesaurus The IEEE Thesaurus is a controlled The IEEE Thesaurus also provides a vocabulary of almost 10,900 descriptive conceptual map through the use of engineering, technical and scientific terms, semantic relationships such as broader as well as IEEE-specific society terms terms (BT), narrower terms (NT), 'used for' [referred to as “descriptors” or “preferred relationships (USE/UF), and related terms terms”] .* Each descriptor included in the (RT). These semantic relationships identify thesaurus represents a single concept or theoretical connections between terms. unit of thought. The descriptors are Italic text denotes Non-preferred terms. considered the preferred terms for use in Bold text is used for preferred headings. describing IEEE content. The scope of descriptors is based on the material presented in IEEE journals, conference Abbreviations used in the Thesaurus: papers, standards, and/or IEEE organizational material. A controlled BT - Broader term vocabulary is a specific terminology used in NT - Narrower term a consistent and controlled fashion that RT - Related term results in better information searching and USE- Use preferred term retrieval. UF - Used for Thesaurus construction is based on the ANSI/NISO Z39.19-2005(2010) standard, Guidelines for the Construction, Format, and Management of Monolingual Controlled Vocabulary. The Thesaurus vocabulary uses American-based spellings with cross references to British variant spellings. The scope and structure of the IEEE Thesaurus reflects the engineering and scientific disciplines that comprise the Societies, Councils, and Communities of the IEEE in *Refer to ANSI/NISO NISO Z39.19-2005 addition to the technologies IEEE serves.