Linked Open Data Validity -- A Technical Report from ISWS 2018

Mehwish Alam 1 Tayeb Abderrahmani Ghorfi 2 Esha Agrawal 3 Omar Alqawasmeh 4 Amina Annane 5 Claudia d'Amato 6 Amr Azzam 7 Andrew Berezovskyi 8 Russa Biswas 9 Mathias Bonduel 10 Quentin Brabant 1 Cristina-Iulia Bucur 11 Elena Camossi 12 Valentina Anita Carriero 13 Shruthi Chari 14 David Chaves Fraga 15 Fiorela Ciroku 16 Michael Cochez 17 Vincenzo Cutrona 18 Rahma Dandan 19 Pedro del Pozo Jimnez 15 Danilo Dess 20 Valerio Di Carlo 21 Ahmed El Amine Djebri 22 Marieke van Erp 23 Faiq Miftakhul Falakh 24 Alba Fernndez Izquierdo 15 Giuseppe Futia 25 Aldo Gangemi 26 Simone Gasperoni 27 Arnaud Grall 28 Lars Heling 9 Pierre-Henri Paris 29 Noura Herradi 30 Subhi Issa 30 Samaneh Jozashoori 31 Nyoman Juniarta 1 Lucie-Aime Kaffee 32 Ilkcan Keles 33 Prashant Khare 34 Viktor Kovtun 31 Valentina Leone 35 Siying Li 36 Sven Lieber 37 Pasquale Lisena 38 Tatiana Makhalova 39 Ludovica Marinucci 40 Thomas Minier 41 Benjamin Moreau 28 Alberto Moya Loustaunau 42 Durgesh Nandini 43 Sylwia Ozdowska 44 Amanda Pacini de Moura 45 Swati Padhee 46 Guillermo Palma 47 Valentina Presutti 13 Roberto Reda 35 Ettore Rizza 48 Henry Rosales-Mndez 42 Sebastian Rudolph 9 Harald Sack 9 Luca Sciullo 35 Humasak Simanjuntak 49 Carlo Stomeo 50 Thiviyan Thanapalasingam 34 Tabea Tietz 9 Dalia Varanka 51 Maria-Esther Vidal 52 Michael Wolowyk 53 Maximilian Zocholl 54
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
22 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
28 GDD - Gestion de Données Distribuées
LS2N - Laboratoire des Sciences du Numérique de Nantes
29 CEDRIC - ISID - CEDRIC. Ingénierie des Systèmes d'Information et de Décision
CEDRIC - Centre d'études et de recherche en informatique et communications
Abstract : Linked Open Data (LOD) is the publicly available RDF data in the Web. Each LOD entity is identfied by a URI and accessible via HTTP. LOD encodes globalscale knowledge potentially available to any human as well as artificial intelligence that may want to benefit from it as background knowledge for supporting their tasks. LOD has emerged as the backbone of applications in diverse fields such as Natural Language Processing, Information Retrieval, Computer Vision, Speech Recognition, and many more. Nevertheless, regardless of the specific tasks that LOD-based tools aim to address, the reuse of such knowledge may be challenging for diverse reasons, e.g. semantic heterogeneity, provenance, and data quality. As aptly stated by Heath et al. Linked Data might be outdated, imprecise, or simply wrong": there arouses a necessity to investigate the problem of linked data validity. This work reports a collaborative effort performed by nine teams of students, guided by an equal number of senior researchers, attending the International Semantic Web Research School (ISWS 2018) towards addressing such investigation from different perspectives coupled with different approaches to tackle the issue.
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https://hal.inria.fr/hal-02087112
Contributor : Fabien Gandon <>
Submitted on : Monday, April 1, 2019 - 5:58:39 PM
Last modification on : Monday, January 13, 2020 - 5:46:07 PM

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  • HAL Id : hal-02087112, version 1
  • ARXIV : 1903.12554

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Mehwish Alam, Tayeb Abderrahmani Ghorfi, Esha Agrawal, Omar Alqawasmeh, Amina Annane, et al.. Linked Open Data Validity -- A Technical Report from ISWS 2018. 2019. ⟨hal-02087112⟩

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