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dc.contributor.authorMolli, Pascal
dc.contributor.authorBreslin, John G.
dc.contributor.authorVidal, Maria-Esther
dc.date.accessioned2018-07-26T12:48:12Z
dc.date.available2018-07-26T12:48:12Z
dc.date.issued2016
dc.identifier.citationMolli, Pascal, Breslin, John G., & Vidal, Maria-Esther. (2016). Challenges for semantically driven collaborative spaces. Paper presented at the Semantic Web Collaborative Spaces: Second International Workshop, SWCS 2013, Montpellier, France, May 27, 2013, Third International Workshop, SWCS 2014, Trentino, Italy, October 19, 2014, Revised Selected and Invited Papersen_IE
dc.identifier.isbn978-3-319-32667-2
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10379/7427
dc.description.abstractLinked Data initiatives have fostered the publication of more than one thousand of datasets in the Linking Open Data (LOD) cloud from a large variety of domains, e.g., Life Sciences, Media, and Government. Albeit large in volume, Linked Data is essentially read-only and most collaborative tasks of cleaning, enriching, and reasoning are not dynamically available. Collaboration between data producers and consumers is essential for overcoming these limitations, and for fostering the evolution of the LOD cloud into a more participative and collaborative data space. In this paper, we describe the role that collaborative infrastructures can play in creating and maintaining Linked Data, and the benefits of exploiting knowledge represented in ontologies as well as the main features of Semantic Web technologies to effectively assess the LOD cloud’s evolution. First, the advantages of using ontologies for modelling collaborative spaces are discussed, as well as formalisms for assessing semantic collaboration by sharing annotations from terms in domain ontologies. Then, Semantic MediaWiki communities are described, and illustrated with three applications in the domains of formal mathematics, ontology engineering, and pedagogical content management. Next, the problem of exploiting semantics in collaborative spaces is tackled, and three different approaches are described. Finally, we conclude with an outlook to future directions and problems that remain open in the area of semantically-driven collaborative spaces.en_IE
dc.description.sponsorshipPascal Molli has been supported by the ANR Kolflow Project (ANR-10-CORD-0021), University of Nantes. John G. Breslin has been supported by Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 (Insight). Maria-Esther Vidal thanks the DID-USB (Decanato de Investigaci´on y Desarrollo de la Universidad Sim´on Bol´ıvar).en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherSpringeren_IE
dc.relation.ispartofSemantic Web Collaborative Spacesen
dc.subjectLinking Open Data (LOD)en_IE
dc.subjectCollaborationen_IE
dc.subjectCollaborative data spaceen_IE
dc.titleChallenges for semantically driven collaborative spacesen_IE
dc.typeConference Paperen_IE
dc.date.updated2018-03-13T15:44:45Z
dc.identifier.doi10.1007/978-3-319-32667-2 1
dc.local.publishedsourcehttps://www.springer.com/gp/book/9783319326665en_IE
dc.description.peer-reviewedNot peer reviewed
dc.contributor.funderScience Foundation Irelanden_IE
dc.internal.rssid12631548
dc.local.contactJohn Breslin, Electrical & Electronic Eng, Room 3047, Engineering Building, Nui Galway. 2622 Email: john.breslin@nuigalway.ie
dc.local.copyrightcheckedYes
dc.local.versionPUBLISHED
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/
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