When Linguistics Meets Web Technologies. Recent Advances in Modelling Linguistic Linked Open Data

Total Page:16

File Type:pdf, Size:1020Kb

When Linguistics Meets Web Technologies. Recent Advances in Modelling Linguistic Linked Open Data Semantic Web 0 (0) 1 1 IOS Press 1 1 2 2 3 3 4When Linguistics Meets Web Technologies. 4 5 5 6 6 7Recent advances in Modelling Linguistic 7 8 8 9Linked Open Data 9 10 10 11a b c d 11 12Anas Fahad Khan , Christian Chiarcos , Thierry Declerck , Daniela Gifu , 12 e f b h 13Elena González-Blanco García , Jorge Gracia , Maxim Ionov , Penny Labropoulou , 13 i j k i 14Francesco Mambrini , John P. McCrae , Émilie Pagé-Perron , Marco Passarotti , 14 l m 15Salvador Ros Muñoz , Ciprian-Octavian Truica˘ 15 16a Istituto di Linguistica Computazionale «A. Zampolli», Consiglio Nazionale delle Ricerche, Italy 16 17E-mail: [email protected] 17 18b Applied Computational Linguistics Lab, Goethe-Universität Frankfurt am Main, Germany 18 19E-mail: [email protected], 19 20E-mail: [email protected] 20 21c DFKI GmbH, Multilinguality and Language Technology, Saarbrücken, Germany 21 22E-mail: [email protected] 22 23d Faculty of Computer Science, Alexandru Ioan Cuza University of Iasi, Romania 23 24E-mail: [email protected] 24 25e Laboratory of Innovation on Digital Humanities, IE University, Spain 25 26E-mail: [email protected] 26 27f Aragon Institute of Engineering Research, University of Zaragoza, Spain 27 28E-mail: [email protected] 28 29g Applied Computational Linguistics Lab, Goethe-Universität Frankfurt am Main, Germany 29 30E-mail: [email protected] 30 31h Institute for Language and Speech Processing, Athena Research Center, Greece 31 32E-mail: [email protected] 32 33i CIRCSE Research Centre, Università Cattolica del Sacro Cuore, Milan, Italy 33 34E-mail: [email protected], 34 35E-mail: [email protected] 35 36j Insight SFI Research Centre for Data Analytics, Data Science Institute, National University of Ireland Galway, 36 37Ireland 37 38E-mail: [email protected] 38 39k Wolfson College, University of Oxford, United Kingdom 39 40E-mail: [email protected] 40 41l Laboratory of Innovation on Digital Humanities, National Distance Education University UNED, Spain 41 42E-mail: [email protected] 42 43m Computer Science and Engineering Department, Faculty of Automatic Control and Computers, University 43 44Politehnica of Bucharest, Romania 44 45E-mail: [email protected] 45 46 46 47 47 48 48 49 49 50Abstract. This article provides an up-to-date and comprehensive survey of models (including vocabularies, taxonomies and 50 ontologies) used for representing linguistic linked data (LLD). It focuses on the latest developments in the area and both builds 51 51 1570-0844/0-1900/$35.00 © 0 – IOS Press and the authors. All rights reserved 2 AF. Khan et al. / When Linguistics Meets Web Technologies. Recent advances in Modelling Linguistic Linked Open Data 1upon and complements previous works covering similar territory. The article begins with an overview of recent trends which 1 2have had an impact on linked data models and vocabularies, such as the growing influence of the FAIR guidelines, the funding 2 3of several major projects in which LLD is a key component, and the increasing importance of the relationship of the digital 3 4humanities with LLD. Next, we give an overview of some of the most well known vocabularies and models in LLD. After this 4 5we look at some of the latest developments in community standards and initiatives such as OntoLex-Lemon as well as recent 5 work which has been in carried out in corpora and annotation and LLD including a discussion of the LLD metadata vocabularies 6 6 META-SHARE and lime and language identifiers. In the following part of the paper we look at work which has been realised in 7 7 a number of recent projects and which has a significant impact on LLD vocabularies and models. 8 8 9Keywords: linguistic linked data, FAIR, corpora, annotation, language resources, OntoLex-Lemon, Digital Humanities, metadata, 9 10models 10 11 11 12 12 13 13 141. Introduction tion discussing projects, Section 5, and the conclusion, 14 15Section 6. 15 16The growing popularity of linked data, and espe- 16 17cially of linked open data (that is, linked data with an 17 18open license), as a means of publishing language re- 2. Setting the Scene: An Overview of Relevant 18 19sources (lexica, corpora, data categories, etc.) necessi- Trends for LLD 19 20tates a greater emphasis on models for linguistic linked 20 21data (LLD) since these are key to what makes linked The trends we have decided to focus on in this 21 22data resources so reusable and so interoperable (at a overview are the FAIRification of data in Section 2.1, 22 23semantic level). The purpose of this article is to pro- the importance of projects to LLD models in Section 23 24vide a comprehensive and up-to-date survey of mod- 2.2, and finally the increasing importance of Digital 24 25els used for representing linguistic linked data. It will Humanities use cases in Section 2.3. 25 26focus on the latest developments and will both build 26 27upon as well as trying to complement previous works 2.1. FAIR New World 27 28covering similar territory by avoiding too much repeti- 28 29With the growing importance of Open Science ini- 29 tion and overlap with the latter. 30tiatives, and especially those promoting the FAIR 30 In the following section, Section 2, we give an 31guidelines (where FAIR stands for Findable, Accessi- 31 overview of a number of trends from the last few years 32ble, Interoperable and Reusable) [1] – and the conse- 32 which have had, or which are likely to have, a signifi- 33quent emphasis on the modelling, creation and publi- 33 cant impact on the definition and/or use of LLD mod- 34cation of language resources as FAIR digital resources 34 els. We relate these trends to the rest of the article by 35– shared models and vocabularies have begun to take 35 highlighting relevant sections of the article (in bold). 36on an increasingly prominent role. Although the lin- 36 This overview of trends will help to locate the present 37guistic linked data community has been active in pro- 37 work within a wider research context, something that 38moting shared RDF vocabularies and models for years, 38 39is extremely useful in an area as active as linguistic this new emphasis on FAIR is likely to have a con- 39 40linked data, as well as assisting readers in navigating siderable impact in several ways, not least in terms of 40 41the rest of the article. Next, in Section 2.4, we com- the necessity for these models to demonstrate a greater 41 42pare the present article with other related work, includ- coverage, and to be more interoperable one with an- 42 43ing an earlier survey of LLD models, in order to help other. We will look at one series of FAIR related rec- 43 44clarify the topics and approach of the present work. ommendations for models in Section 3 and see how 44 45Section 3 gives an overview of the most widely used they might be applied to the case of LLD. However in 45 46models in LLD. Then in Section 4, we look at recent the rest of the subsection we will take a closer look 46 47developments in community standards and initiatives. at the FAIR principles themselves and show why their 47 48These include the latest extensions of the OntoLex- widespread adoption is likely to lead to a greater role 48 49Lemon model in Section 4.1, a discussion of relevant for LLD models and vocabularies in the future. 49 50work in copora and annotations in Section 4.2, and a In The FAIR Guiding Principles for scientific data 50 51section on metadata Section 4.3. Finally there is a sec- management and stewardship [1], the article which 51 AF. Khan et al. / When Linguistics Meets Web Technologies. Recent advances in Modelling Linguistic Linked Open Data 3 1first articulated the well known FAIR principles, the – I1. (meta)data use a formal, accessible, shared, 1 2authors clearly state that the criteria proposed by these and broadly applicable language for knowledge 2 3principles are intended both "for machines and peo- representation. 3 4ple" and that they provide "‘steps along a path’ to ma- – I2. (meta)data use vocabularies that follow FAIR 4 5chine actionability", where the latter is understood to principles. 5 6describe structured data that would allow a "computa- 6 7tional data explorer" to determine: It is important to note that the emphasis placed 7 8on machine actionability in FAIR resources (that 8 9– The type of a "digital research object" is, on enabling computational agents to find rele- 9 10– Its usefulness with respect to tasks to be carried vant datasets and resources and to take "appropriate 10 11out action" when they find them) gives Semantic Web 11 12– Its usability especially with respect to licensing vocabularies/registries a substantial advantage over 12 13issues, represented in a way that would allow the other (non-Semantic Web native) standards in the 13 14agent to take "appropriate action". field of linguistics like the Text Encoding Initiative 14 3 15The current popularity of the FAIR principles and, (TEI) guidelines [2], the Lexical Markup Framework 15 16in particular, their promotion by governments and re- (LMF) [3] or the Morpho-syntactic Annotation Frame- 16 17search funding bodies, such as the European Commis- work (MAF) [4]. 17 18sion,1 through several national and international ini- For a start, none of these other standards possess 18 19tiatives reflects a wider recognition of the potential of a ‘native’, widely-used, widely technically supported 19 20structured and machine actionable data in changing knowledge representation language for describing the 20 21how research is carried out, and especially in helping semantics of vocabulary terms in a machine readable 21 22to support open science practices.
Recommended publications
  • Distant Reading, Computational Stylistics, and Corpus Linguistics the Critical Theory of Digital Humanities for Literature Subject Librarians David D
    CHAPTER FOUR Distant Reading, Computational Stylistics, and Corpus Linguistics The Critical Theory of Digital Humanities for Literature Subject Librarians David D. Oberhelman FOR LITERATURE librarians who frequently assist or even collaborate with faculty, researchers, IT professionals, and students on digital humanities (DH) projects, understanding some of the tacit or explicit literary theoretical assumptions involved in the practice of DH can help them better serve their constituencies and also equip them to serve as a bridge between the DH community and the more traditional practitioners of literary criticism who may not fully embrace, or may even oppose, the scientific leanings of their DH colleagues.* I will therefore provide a brief overview of the theory * Literary scholars’ opposition to the use of science and technology is not new, as Helle Porsdam has observed by looking at the current debates over DH in the academy in terms of the academic debate in Great Britain in the 1950s and 1960s between the chemist and novelist C. P. Snow and the literary critic F. R. Leavis over the “two cultures” of science and the humanities (Helle Porsdam, “Too Much ‘Digital,’ Too Little ‘Humanities’? An Attempt to Explain Why Humanities Scholars Are Reluctant Converts to Digital Humanities,” Arcadia project report, 2011, DSpace@Cambridge, www.dspace.cam.ac.uk/handle/1810/244642). 54 DISTANT READING behind the technique of DH in the case of literature—the use of “distant reading” as opposed to “close reading” of literary texts as well as the use of computational linguistics, stylistics, and corpora studies—to help literature subject librarians grasp some of the implications of DH for the literary critical tradition and learn how DH practitioners approach literary texts in ways that are fundamentally different from those employed by many other critics.† Armed with this knowledge, subject librarians may be able to play a role in integrating DH into the traditional study of literature.
    [Show full text]
  • KB-Driven Information Extraction to Enable Distant Reading of Museum Collections Giovanni A
    KB-Driven Information Extraction to Enable Distant Reading of Museum Collections Giovanni A. Cignoni, Progetto HMR, [email protected] Enrico Meloni, Progetto HMR, [email protected] Short abstract (same as the one submitted in ConfTool) Distant reading is based on the possibility to count data, to graph and to map them, to visualize the re- lations which are inside the data, to enable new reading perspectives by the use of technologies. By contrast, close reading accesses information by staying at a very fine detail level. Sometimes, we are bound to close reading because technologies, while available, are not applied. Collections preserved in the museums represent a relevant part of our cultural heritage. Cataloguing is the traditional way used to document a collection. Traditionally, catalogues are lists of records: for each piece in the collection there is a record which holds information on the object. Thus, a catalogue is just a table, a very simple and flat data structure. Each collection has its own catalogue and, even if standards exists, they are often not applied. The actual availability and usability of information in collections is impaired by the need of access- ing each catalogue individually and browse it as a list of records. This can be considered a situation of mandatory close reading. The paper discusses how it will be possible to enable distant reading of collections. Our proposed solution is based on a knowledge base and on KB-driven information extraction. As a case study, we refer to a particular domain of cultural heritage: history of information science and technology (HIST).
    [Show full text]
  • IXA-Pipe) and Parsing (Alpino)
    Details from a distance? CLIN26 Amsterdam A Dutch pipeline for event detection Chantal van Son, Marieke van Erp, Antske Fokkens, Paul Huygen, Ruben Izquierdo Bevia & Piek Vossen CLOSE READING DISTANT READING NewsReader & BiographyNet Apply the detailed analyses typically associated with close (or at least non-distant) reading to large amounts of textual data ✤ NewsReader: (financial) news data ✤ Day-by-day processing of news; reconstructing a coherent story ✤ Four languages: English, Spanish, Italian, Dutch ✤ BiographyNet: biographical data ✤ Answering historical questions with digitalized data from Biography Portal of the Netherlands (www.biografischportaal.nl) using computational methods http://www.newsreader-project.eu/ http://www.biographynet.nl/ Event extraction and representation 1. Intra-document processing: Dutch NLP pipeline generating NAF files ✤ pipeline includes tokenization, parsing, SRL, NERC, etc. ✤ NLP Annotation Format (NAF) is a multi-layered annotation format for representing linguistic annotations in complex NLP architectures 2. Cross-document processing: event coreference to convert NAF to RDF representation 3. Store the NAF and RDF in a KnowledgeStore Event extraction and representation 1. Intra-document processing: Dutch NLP pipeline generating NAF files ✤ pipeline includes tokenization, parsing, SRL, NERC, etc. ✤ NLP Annotation Format (NAF) is a multi-layered annotation format for representing linguistic annotations in complex NLP architectures 2. Cross-document processing: event coreference to convert NAF to RDF 3.
    [Show full text]
  • ISSN: 1647-0818 Lingua
    lingua Volume 12, Número 2 (2020) ISSN: 1647-0818 lingua Volume 12, N´umero 2 { 2020 Linguamatica´ ISSN: 1647{0818 Editores Alberto Sim~oes Jos´eJo~aoAlmeida Xavier G´omezGuinovart Conteúdo Artigos de Investiga¸c~ao Adapta¸c~aoLexical Autom´atica em Textos Informativos do Portugu^esBrasileiro para o Ensino Fundamental Nathan Siegle Hartmann & Sandra Maria Alu´ısio .................3 Avaliando entidades mencionadas na cole¸c~ao ELTeC-por Diana Santos, Eckhard Bick & Marcin Wlodek ................... 29 Avalia¸c~aode recursos computacionais para o portugu^es Matilde Gon¸calves, Lu´ısaCoheur, Jorge Baptista & Ana Mineiro ........ 51 Projetos, Apresentam-se! Aplicaci´onde WordNet e de word embeddings no desenvolvemento de proto- tipos para a xeraci´onautom´atica da lingua Mar´ıaJos´eDom´ınguezV´azquez ........................... 71 Editorial Ainda h´apouco public´avamosa primeira edi¸c~aoda Linguam´atica e, subitamente, eis-nos a comemorar uma d´uziade anos. A todos os que colaboraram durante todos estes anos, tenham sido leitores, autores ou revisores, a todos o nosso muito obrigado. N~ao´ef´acilmanter um projeto destes durante tantos anos, sem qualquer financi- amento. Todo este sucesso ´egra¸cas a trabalho volunt´ario de todos, o que nos permite ter artigos de qualidade publicados e acess´ıveisgratuitamente a toda a comunidade cient´ıfica. Nestes doze anos muitos foram os que nos acompanharam, nomeadamente na comiss~aocient´ıfica. Alguns dos primeiros membros, convidados em 2008, continuam ativamente a participar neste projeto, realizando revis~oesapuradas. Outros, por via do seu percurso acad´emico e pessoal, j´an~aocolaboram connosco. Como sinal de agradecimento temos mantido os seus nomes na publica¸c~ao.
    [Show full text]
  • VIANA: Visual Interactive Annotation of Argumentation
    VIANA: Visual Interactive Annotation of Argumentation Fabian Sperrle* Rita Sevastjanova∗ Rebecca Kehlbeck∗ Mennatallah El-Assady∗ Figure 1: VIANA is a system for interactive annotation of argumentation. It offers five different analysis layers, each represented by a different view and tailored to a specific task. The layers are connected with semantic transitions. With increasing progress of the analysis, users can abstract away from the text representation and seamlessly transition towards distant reading interfaces. ABSTRACT are actively developing techniques for the extraction of argumen- Argumentation Mining addresses the challenging tasks of identi- tative fragments of text and the relations between them [41]. To fying boundaries of argumentative text fragments and extracting develop and train these complex, tailored systems, experts rely on their relationships. Fully automated solutions do not reach satis- large corpora of annotated gold-standard training data. However, factory accuracy due to their insufficient incorporation of seman- these training corpora are difficult and expensive to produce as they tics and domain knowledge. Therefore, experts currently rely on extensively rely on the fine-grained manual annotation of argumen- time-consuming manual annotations. In this paper, we present a tative structures. An additional barrier to unifying and streamlining visual analytics system that augments the manual annotation pro- this annotation process and, in turn, the generation of gold-standard cess by automatically suggesting which text fragments to annotate corpora is the subjectivity of the task. A reported agreement with next. The accuracy of those suggestions is improved over time by Cohen’s k [11] of 0:610 [64] between human annotators is consid- incorporating linguistic knowledge and language modeling to learn ered “substantial” [38] and is the state-of-the-art in the field.
    [Show full text]
  • Enhancing Domain-Specific Entity Linking in DH
    heterogeneous spectrum of Digital Humanities re- search. • Black Box and reproducibility. As Hasibi et Enhancing Domain-Specific al. (2016) recently remarked, the TagMe Entity Linking in DH RESTful API remains a black box, as it is im- possible to check whether it corresponds to Federico Nanni the system described in the original paper. [email protected] Not knowing the reliability of the system University of Mannheim, Germany limits its use for distant reading analyses, i.e. quantitative studies that go beyond text ex- Yang Zhao ploration. [email protected] • Language Versions. Currently, TagMe is University of Mannheim, Germany only available in English, German and Italian but does not support other widespread lan- Simone Paolo Ponzetto guages such as Chinese, Arabic, Spanish, and [email protected] French, which are essential for enhancing its University of Mannheim, Germany use in the DH community. • Infrequent Updates. TagMe has been ini- Laura Dietz tially created on the English 2009 version of [email protected] Wikipedia and it has been updated only University of New Hampshire, United States of America twice (summer 2012, summer 2016). Imag- ine a setting where a scholar intends to ana- lyze a collection of mainstream news on the Middle East: before the most recent update For the purpose of information retrieval and text the system was not able to detect mentions exploration, digital humanities (DH) scholars have ex- of “Al-Nursa Front”, the former Syrian amined the potential of methods such as keyphrase ex- branch of al-Qaeda. traction (Hasan and Ng, 2014) and named entity • Wikipedia as Knowledge Base.
    [Show full text]
  • Prolegomena to the Automated Analysis of a Bilingual Poetry Corpus, with Particular Reference to an Annotated Edition of “The Cantos” of Ezra Pound
    University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2016 Prolegomena To The Automated Analysis Of A Bilingual Poetry Corpus, With Particular Reference To An Annotated Edition Of “the Cantos” Of Ezra Pound Robin Seguy University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the English Language and Literature Commons Recommended Citation Seguy, Robin, "Prolegomena To The Automated Analysis Of A Bilingual Poetry Corpus, With Particular Reference To An Annotated Edition Of “the Cantos” Of Ezra Pound" (2016). Publicly Accessible Penn Dissertations. 2576. https://repository.upenn.edu/edissertations/2576 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/2576 For more information, please contact [email protected]. Prolegomena To The Automated Analysis Of A Bilingual Poetry Corpus, With Particular Reference To An Annotated Edition Of “the Cantos” Of Ezra Pound Abstract Standing at the intersection of a theoretical investigation into the possibilities of applying the tools and methods of automated analysis to a large plurilingual poetry corpus and of a set of observables gleaned along the creation of a digitally annotated edition of The Cantos of Ezra Pound — a robust test-case for the TEI — the present dissertation can be read under different guises. One of them, for instance, would be that of a comedy, divina commedia or com�dia de Deus, in which the computer plays — Leibnizian harmonics! — the part of supreme intellect. A: The selva oscura is that of newly born “Digital Humanities” — burgeoning yet obscured already by two dominant paradigms. On the one hand, the constructivism inherited from poststructuralist theory; on the other, a na�ve return to the most trivial kind of linguistic realism.
    [Show full text]
  • Where Close and Distant Readings Meet
    Where Close and Distant Readings stress on mixed methods, as we are combining linguistic and literary criteria of selecting style markers to dis- Meet: Text Clustering Methods in criminate between blog genres (Leech & Short 2007,57-58). Literary Analysis of Weblog Genres Current research in the field of computational literary genre stylistics focuses on Most Frequent Words (e.g. Schöch Maciej Maryl and Pielström 2014; Jannidis & Lauer 2014) or functional [email protected] linguistic categories (or both) (e.g. Allison et. al 2011). Institute of Literary Research of the Polish Academy of Yet, this study applies similar methods to emergent and Sciences, Poland uncategorised forms of writing. The quantitative methods are incorporated into the qualitative research workflow in Maciej Piasecki order to create a productive feedback loop. [email protected] Wrocław University of Technology Corpus Ksenia Młynarczyk The corpus of blogs was collected with the use of [email protected] BlogReader - an extension of a corpus gathering system Wrocław University of Technology developed in CLARIN-PL (Oleksy et al. 2014) on a basis of open components: jusText andOnion (Pomikálek, 2011). From the initial set analysed by Maryl et al., 250 blogs were Problem: towards a non-topical classification of selected for processing as being long enough and included weblog genres clean text (comments were omitted). We intentionally left out blogs with exceptionally large or small amount of text The existing typologies of weblog genres - both popular in order to balance the sample. The selected subcorpus and academic - are based on the blog topic, e.g.
    [Show full text]
  • Litbank: Born-Literary Natural Language Processing 1 Introduction
    LitBank: Born-Literary Natural Language Processing∗ David Bamman University of California, Berkeley [email protected] 1 Introduction Much work involving the computational analysis of text in the humanities draws on methods and tools in natural language processing (NLP)—an area of research focused on reasoning about the linguistic struc- ture of text. Over the past 70 years, the ways in which we process natural language have blossomed into dozens of applications, moving far beyond early work in speech recognition (Davis et al., 1952) and machine translation (Bar-Hillel, 1960) to include question answering, summarization, and text generation. While the direction of many avenues of research in NLP has tended toward the development of end-to- end-systems—where, for example, a model learns to solve the problem of information extraction without relying on intermediary steps of part-of-speech tagging or syntactic parsing—one area where the individual low-level linguistic representations are important comes in analyses that depend on them for argumentation. Work in the computational humanities, in particular, has drawn on this representation of linguistic structure for a wide range of work. Automatic part-of-speech taggers have been used to explore poetic enjambment (Houston, 2014) and characterize the patterns that distinguish the literary canon from the archive (Algee- Hewitt et al., 2016). Syntactic parsers have been used to attribute events to the characters who participate in them (Jockers and Kirilloff, 2016; Underwood et al., 2018) and characterize the complexity of sentences in Henry James (Reeve, 2017). Coreference resolution has been used to explore the prominence of major and minor characters as a function of their gender (Kraicer and Piper, 2018).
    [Show full text]
  • Cultivating Capacity, Creating Change
    CCCC Convention Convention CCCC CULTIVATING CAPACITY, CREATING CHANGE CHANGE CREATING CAPACITY, CULTIVATING CCCC 2017 . PORTLAND March 15–18, 2017 • Portland, Oregon • Portland, 2017 15–18, March R.S.V.P. to one of our local parties to sample Portland treats and drinks. Go “all in” with one of our author workshops at the conference. Visit Booth #101 for details, and look for us this summer at the CCCC regional meetings! CULTIVATING CAPACITY, CREATING CHANGE #BSM4C2017 March 15–18, 2017 • Portland, Oregon macmillanlearning.com / BSM4C2017 Conference on College Composition and Communication cccc17 program cover.indd 1 2/5/17 11:24 PM cccc ad bw.pdf 1 2/12/16 12:02 AM Find opportunity and value with CCCC Take a closer look at the Conference on College Composition and Communication HAVE YOU READ THE LATEST BOOKS IN THE STUDIES IN WRITING AND RHETORIC SERIES? CCCC is the leading organiza- tion in writing studies, offering not only the largest meeting of writing specialists in the world every spring but also a relevant and strategic reposi- tory of resources, research, and networking channels to help you be your best. C •CCCC’s extensive grants and awards M program provides opportunities to be Y recognized for your scholarship, to CM apply for funds for your next research Public Pedagogy in Composition Studies, Ashley J. Holmes MY project, or to receive travel support to The Desire for Literacy: Writing in the Lives of Adult Learners, Lauren Rosenberg From Boys to Men: Rhetorics of Emergent American Masculinity, Leigh Ann Jones CY learn from and with your colleagues.
    [Show full text]
  • Digital Approaches Towards Serial Publications Joke Daems, Gunther Martens, Seth Van Hooland, and Christophe Verbruggen
    Digital Approaches Towards Serial Publications Joke Daems, Gunther Martens, Seth Van Hooland, and Christophe Verbruggen Journal of European Periodical Studies, 4.1 (Summer 2019) ISSN 2506-6587 Content is licensed under a Creative Commons Attribution 4.0 Licence The Journal of European Periodical Studies is hosted by Ghent University Website: ojs.ugent.be/jeps To cite this article: Joke Daems, Gunther Martens, Seth Van Hooland, and Christophe Verbruggen, ‘Digital Approaches Towards Serial Publications’, Journal of European Periodical Studies, 4.1 (Summer 2019), 1–7 Digital Approaches Towards Serial Publications Joke Daems*, Gunther Martens*, Seth Van Hooland^, and Christophe Verbruggen* *Ghent University and ^Université Libre de Bruxelles [email protected] For periodical studies to activate its potential fully, therefore, we will need dedicated institutional sites that furnish the necessary material archives as well as the diverse expertise these rich materials require. The expanding digital repositories, which often patch up gaping holes in the print archive, have begun to provide a broad array of scholars with a dazzling spectrum of periodicals. This dissemination of the archive, in turn, now challenges us to invent the tools and institutional structures necessary to engage the diversity, complexity, and coherence of modern periodical culture.1 This volume was inspired by the Digital Approaches Towards 18th–20th Century Serial Publications conference, which took place in September 2017 at the Royal Academies for Sciences and Arts of Belgium. The conference brought together humanities scholars, social scientists, computational scientists, and librarians interested in discussing how digital techniques can be used to uncover the different layers of knowledge contained in serial publications such as newspapers, journals, and book series.
    [Show full text]
  • The Distant Reading of Religious Texts: a “Big Data” Approach to Mind-Body Concepts In
    Article The Distant Reading of Religious Texts: A “Big Data” Approach to Mind-Body Concepts in Early China 5 Edward Slingerland,* Ryan Nichols, Kristoffer Neilbo, and Carson Logan This article focuses on the debate about mind-body concepts in early China to demonstrate the usefulness of large-scale, automated textual 10 analysis techniques for scholars of religion. As previous scholarship has argued, traditional, “close” textual reading, as well as more recent, human coder-based analyses, of early Chinese texts have called into question the “strong” holist position, or the claim that the early Chinese made no qualitative distinction between mind and body. In a series of follow-up 15 studies, we show how three different machine-based techniques—word collocation, hierarchical clustering, and topic modeling analysis—provide *Edward Slingerland, Department of Asian Studies, University of British Columbia, Vancouver, British Columbia, Canada. E-mail: [email protected]. Ryan Nichols, Department of Philosophy, California State University, Fullerton, CA. Kristoffer Nielbo, School of Culture and Society, Aarhus University, Aarhus, Denmark. Carson Logan, Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. Most of this work was funded by a Social Sciences and Humanities Research Council (SSHRC) of Canada Partnership Grant on “The Evolution of Religion and Morality” awarded to E.S., with some performed while K.N. was a visiting scholar at the Institute for Pure and Applied Mathematics (IPAM), which is supported by the National Science Foundation, and E.S. was an Andrew W. Mellon Foundation Fellow, Center for Advanced Study in the Behavioral Sciences, Stanford University. We would also like to thank the anonymous referees at JAAR for very helpful comments that have made this a much stronger paper.
    [Show full text]