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dc.contributor.authorEllefi, Mohamed Ben
dc.contributor.authorBellahsene, Zohra
dc.contributor.authorBreslin, John G.
dc.contributor.authorDemidova, Elena
dc.contributor.authorDietze, Stefan
dc.contributor.authorSzymanski, Julian
dc.contributor.authorTodorov, Konstantin
dc.date.accessioned2018-08-21T09:21:53Z
dc.date.available2018-08-21T09:21:53Z
dc.date.issued2018-07-12
dc.identifier.citationEllefi, Mohamed Ben, Bellahsene, Zohra, Breslin, John G., Demidova, Elena, Dietze, Stefan, Szymanski, Julian, & Todorov, Konstantin. (2018). RDF dataset profiling – a survey of features, methods, vocabularies and applications. Semantic Web, 1-29. doi: 10.3233/SW-180294en_IE
dc.identifier.issn1570-0844
dc.identifier.issn2210-4968
dc.identifier.urihttp://hdl.handle.net/10379/7555
dc.description.abstractThe Web of Data, and in particular Linked Data, has seen tremendous growth over the past years. However, reuse and take-up of these rich data sources is often limited and focused on a few well-known and established RDF datasets. This can be partially attributed to the lack of reliable and up-to-date information about the characteristics of available datasets. While RDF datasets vary heavily with respect to the features related to quality, provenance, interlinking, licenses, statistics and dynamics, reliable information about such features is essential to enable dataset discovery and selection in tasks such as entity linking, distributed query, search or question answering. Even though there exists a wealth of works contributing to the task of dataset profiling in general, these works are spread across a wide range of communities. In this survey, we provide a first comprehensive overview of the RDF dataset profiling features, methods, tools and vocabularies. We organize these building blocks of dataset profiling in a taxonomy and illustrate the links between the dataset profiling and feature extraction approaches and several application domains. This survey is aimed towards data practitioners, data providers and scientists, spanning a large range of communities and drawing from different fields such as dataset profiling, assessment, summarization and characterization. Ultimately, this work is intended to facilitate the reader to identify the relevant features for building a dataset profile for intended applications together with the methods and tools capable of extracting these features from the datasets as well as vocabularies to describe the extracted features and make them available.en_IE
dc.description.sponsorshipThis paper was partially supported by COST (European Cooperation in Science and Technology) under Action IC1302 (KEYSTONE), Science Foundation Ireland under Grant Number SFI/12/RC/2289 (INSIGHT), the German Federal Ministry of Education and Research (BMBF) under Data4UrbanMobility (02K15A040), the Datalyse project69 (FSN-AAP Big Data n3), and the European Research Council under ALEXANDRIA (ERC 339233).en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherIOS Pressen_IE
dc.relation.ispartofSemantic Web Journalen
dc.subjectLinked Data assessmenten_IE
dc.subjectRDF dataset profilingen_IE
dc.subjectDataset featuresen_IE
dc.subjectDataset profiling vocabulariesen_IE
dc.titleRDF dataset profiling – a survey of features, methods, vocabularies and applicationsen_IE
dc.typeArticleen_IE
dc.date.updated2018-03-08T13:03:32Z
dc.identifier.doi10.3233/SW-180294
dc.local.publishedsourcehttps://dx.doi.org/10.3233/SW-180294en_IE
dc.description.peer-reviewedpeer-reviewed
dc.contributor.funderEuropean Cooperation in Science and Technologyen_IE
dc.contributor.funderScience Foundation Irelanden_IE
dc.contributor.funderGerman Federal Ministry of Education and Researchen_IE
dc.contributor.funderBundesministerium für Bildung und Forschungen_IE
dc.contributor.funderEuropean Research Councilen_IE
dc.internal.rssid13995790
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/EC/FP7::SP2::ERC/339233/EU/Foundations for Temporal Retrieval, Exploration and Analytics in Web Archives/ALEXANDRIAen_IE
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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