Collective intelligence and digital archives : (Record no. 87361)

000 -LEADER
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003 - CONTROL NUMBER IDENTIFIER
control field CITU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240515091807.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION
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007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781786300607
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781119384694
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Edition number 23
Classification number 006.3/824
245 00 - TITLE STATEMENT
Title Collective intelligence and digital archives :
Remainder of title towards knowledge ecosystem /
Statement of responsibility, etc edited by Samuel Szoniecky, Nasreddine Bouhaï
264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc London, UK :
Name of publisher, distributor, etc Wiley,
Date of publication, distribution, etc c2017
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references
505 0# - CONTENTS
Formatted contents note Table of Contents<br/>Chapter 1 Ecosystems of Collective Intelligence in the Service of Digital Archives 1<br/>Samuel SZONIECKY<br/><br/>1.1 Digital archives 1<br/><br/>1.2 Collective intelligence 3<br/><br/>1.3 Knowledge ecosystems 5<br/><br/>1.4 Examples of ecosystems of knowledge 7<br/><br/>1.4.1 Modeling digital archive interpretation 7<br/><br/>1.4.2 Editing archives via the semantic web 10<br/><br/>1.4.3 A semantic platform for analyzing audiovisual corpuses 12<br/><br/>1.4.4 Digital libraries and crowdsourcing: a state-of-the-art 14<br/><br/>1.4.5 Conservation and promotion of cultural heritage 16<br/><br/>1.4.6 Modeling knowledge for innovation 18<br/><br/>1.5 Solutions 20<br/><br/>1.6 Bibliography 21<br/><br/>Chapter 2 Tools for Modeling Digital Archive Interpretation 23<br/>Muriel LOUÂPRE and Samuel SZONIECKY<br/><br/>2.1 What archives are we speaking of? Definition, issues and collective intelligence methods 25<br/><br/>2.1.1 Database archives, evolution of a concept and its functions 25<br/><br/>2.1.2 The exploitation of digital archives in the humanities 27<br/><br/>2.1.3 The specific case of visualization tools 32<br/><br/>2.2 Digital archive visualization tools: lessons from the Biolographes experiment 34<br/><br/>2.2.1 Tools for testing 37<br/><br/>2.2.2 Tools for visualizing networks: DBpedia, Palladio 38<br/><br/>2.2.3 Multi-purpose tools (Keshif, Table) 40<br/><br/>2.3 Prototype for influence network modeling 44<br/><br/>2.3.1 Categorization of relationships 45<br/><br/>2.3.2 Assisted influence network entry 47<br/><br/>2.4 Limits and perspectives 50<br/><br/>2.4.1 Epistemological conflicts 51<br/><br/>2.4.2 The digital “black box”? 55<br/><br/>2.4.3 From individual expertise to group intelligence 56<br/><br/>2.5 Conclusion 57<br/><br/>2.6 Bibliography 58<br/><br/>Chapter 3 From the Digital Archive to the Resource Enriched Via Semantic Web: Process of Editing a Cultural Heritage 61<br/>Lénaïk LEYOUDEC<br/><br/>3.1 Influencing the intelligibility of a heritage document 61<br/><br/>3.2 Mobilizing differential semantics 62<br/><br/>3.3 Applying an interpretive process to the archive 63<br/><br/>3.4 Assessment of the semiotic study 67<br/><br/>3.5 Popularizing the data web in the editorialization approach 70<br/><br/>3.6 Archive editorialization in the Famille™ architext 73<br/><br/>3.7 Assessment of the archive’s recontextualization 79<br/><br/>3.8 Bibliography 81<br/><br/>Chapter 4 Studio Campus AAR: A Semantic Platform for Analyzing and Publishing Audiovisual Corpuses 85<br/>Abdelkrim BELOUED, Peter STOCKINGER and Steffen LALANDE<br/><br/>4.1 Introduction 85<br/><br/>4.2 Context and issues 86<br/><br/>4.2.1 Archiving and appropriation of audiovisual data 89<br/><br/>4.2.2 General presentation of the Campus AAR environment 94<br/><br/>4.3 Editing knowledge graphs – the Studio Campus AAR example 96<br/><br/>4.3.1 Context 97<br/><br/>4.3.2 Representations of OWL2 restrictions 99<br/><br/>4.3.3 Resolution of OWL2 restrictions 101<br/><br/>4.3.4 Relaxing constraints 102<br/><br/>4.3.5 Classification of individuals 104<br/><br/>4.3.6 Opening and interoperability with the web of data 106<br/><br/>4.3.7 Graphical interfaces 107<br/><br/>4.4 Application to media analysis 108<br/><br/>4.4.1 Model of audiovisual description 109<br/><br/>4.4.2 Reference works and description models 110<br/><br/>4.4.3 Description pattern 111<br/><br/>4.4.4 The management of contexts 112<br/><br/>4.4.5 Suggestion of properties 113<br/><br/>4.4.6 Suggestion of property values 114<br/><br/>4.4.7 Opening on the web of data 115<br/><br/>4.5 Application to the management of individuals 116<br/><br/>4.5.1 Multi-ontology description 116<br/><br/>4.5.2 Faceted browsing 117<br/><br/>4.5.3 An individual’s range 117<br/><br/>4.6 Application to information searches 118<br/><br/>4.6.1 Semantic searches 118<br/><br/>4.6.2 Transformation of SPARQL query graphs 120<br/><br/>4.6.3 Transformation of OWL2 axioms into SPARQL 120<br/><br/>4.6.4 Interface 121<br/><br/>4.7 Application to corpus management 122<br/><br/>4.8 Application to author publication 123<br/><br/>4.8.1 Publication ontologies 125<br/><br/>4.8.2 Transformation engine 128<br/><br/>4.8.3 Final product 129<br/><br/>4.8.4 Opening on the web of data 129<br/><br/>4.8.5 Graphical Interface 130<br/><br/>4.9 Conclusion 131<br/><br/>4.10 Bibliography 132<br/><br/>Chapter 5 Digital Libraries and Crowdsourcing: A Review 135<br/>Mathieu ANDRO and Imad SALEH<br/><br/>5.1 The concept of crowdsourcing in libraries 136<br/><br/>5.1.1 Definition of crowdsourcing 136<br/><br/>5.1.2 Historic origins of crowdsourcing 137<br/><br/>5.1.3 Conceptual origins of crowdsourcing 140<br/><br/>5.1.4 Critiques of crowdsourcing. Towards the uberization of libraries? 140<br/><br/>5.2 Taxonomy and panorama of crowdsourcing in libraries 141<br/><br/>5.2.1 Explicit crowdsourcing 143<br/><br/>5.2.2 Gamification and implicit crowdsourcing 145<br/><br/>5.2.3 Crowdfunding 148<br/><br/>5.3 Analyses of crowdsourcing in libraries from an information and communication perspective 150<br/><br/>5.3.1 Why do libraries have recourse to crowdsourcing and what are the necessary conditions? 150<br/><br/>5.3.2 Why do Internet users contribute? Taxonomy of Internet users’ motivations 153<br/><br/>5.3.3 From symbolic recompense to concrete remuneration 154<br/><br/>5.3.4 Communication for recruiting contributors 155<br/><br/>5.3.5 Community management for keeping contributors 155<br/><br/>5.3.6 The quality and reintegration of produced data 156<br/><br/>5.3.7 The evaluation of crowdsourcing projects 157<br/><br/>5.4 Conclusions on collective intelligence and the wisdom of crowds 158<br/><br/>5.5 Bibliography 159<br/><br/>Chapter 6 Conservation and Promotion of Cultural Heritage in the Context of the Semantic Web 163<br/>Ashraf AMAD and Nasreddine BOUHAÏ<br/><br/>6.1 Introduction 163<br/><br/>6.2 The knowledge resources and models relative to cultural heritage 164<br/><br/>6.2.1 Metadata norms 164<br/><br/>6.2.2 Controlled vocabularies 171<br/><br/>6.2.3 Lexical databases 172<br/><br/>6.2.4 Ontologies 172<br/><br/>6.3 Difficulties and possible solutions 174<br/><br/>6.3.1 Data acquisition 175<br/><br/>6.3.2 Information modeling 185<br/><br/>6.3.3 Use 195<br/><br/>6.3.4 Interoperability 197<br/><br/>6.4 Conclusion 201<br/><br/>6.5 Bibliography 202<br/><br/>Chapter 7 On Knowledge Organization and Management for Innovation: Modeling with the Strategic Observation Approach in Material Science 207<br/>Sahbi SIDHOM and Philippe LAMBERT<br/><br/>7.1 General introduction 207<br/><br/>7.2 Research context: KM and innovation process 210<br/><br/>7.2.1 Jean Lamour Institute 210<br/><br/>7.2.2 Technology and Knowledge Transfer Office (or CC-VIT) 211<br/><br/>7.3 Methodological approach 212<br/><br/>7.3.1 Observation and accumulation of knowledge for innovation 212<br/><br/>7.3.2 Strategic observation and extraction of knowledge: towards an ontological approach 215<br/><br/>7.3.3 Creation of a class hierarchy (of knowledge) 224<br/><br/>7.4 Conceptual modeling for innovation: technological transfer 225<br/><br/>7.4.1 Implementations 226<br/><br/>7.4.2 Corpus specificities 227<br/><br/>7.4.3 NLP engineering applied to the corpus 228<br/><br/>7.4.4 “Polyfunctionalities” favoring strategic observation 232<br/><br/>7.5 Conclusion: principal results and recommendations 233<br/><br/>7.6 Bibliography 235<br/><br/>List of Authors 239<br/><br/>Index 241
520 ## - SUMMARY, ETC.
Summary, etc This book presents the most up-to-date research from different areas of digital archives to show how and why collective intelligence is being developed to organize and better communicate new masses of information.<br/><br/>Current archive digitization projects produce an enormous amount of digital data (Big Data). Thanks to the proactive approach of large public institutions, this data is increasingly accessible. Despite the recent stabilization of technical and legal frameworks, the use of data has yet to be enriched by processes such as collective intelligence.<br/><br/>By exploring the field of digital humanities, audiovisual archives, preservation of cultural heritage, crowdsourcing and the recovery of scientific archives, this book presents and analyzes concrete examples of collective intelligence for use in digital archives.
545 0# - BIOGRAPHICAL OR HISTORICAL DATA
Biographical or historical note About the Author<br/>Samuel Szoniecky is Associate Professor at the University of Paris 8, France in the Department of Digital Humanities.<br/><br/>Nasreddine Bouhaï is Associate Professor at the University of Paris 8, France in the Department of Digital Humanities.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Swarm intelligence.
Authority record control number http://id.loc.gov/authorities/subjects/sh2001001702
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Digital libraries.
Authority record control number http://id.loc.gov/authorities/subjects /sh95008857
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Szoniecky, Samuel
Authority record control number http://id.loc.gov/authorities/names/ no2017161650
Relator term editor
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Bouhaï, Nasreddine
Authority record control number http://id.loc.gov/authorities/names/ no2017095392
Relator term editor
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://onlinelibrary.wiley.com/doi/book/10.1002/9781119384694
Link text Full text is available at Wiley Online Library Click here to view
942 ## - ADDED ENTRY ELEMENTS
Source of classification or shelving scheme
Item type EBOOK
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent Location Current Location Date acquired Source of acquisition Inventory number Full call number Barcode Date last seen Price effective from Item type
          COLLEGE LIBRARY COLLEGE LIBRARY 2024-05-15 ALBASA Consortium 50513 006.3824 C6858 2017 CL-50513 2024-05-15 2024-05-15 EBOOK