Covid-on-the-Web: Exploring the COVID-19 Scientific Literature through Visualization of Linked Data from Entity and Argument Mining
| Autor: | Olivier Corby, Raphaël Gazzotti, Alain Giboin, Fabien Gandon, Elena Cabrio, Tobias Mayer, Santiago Marro, Marco Winckler, Serena Villata, Franck Michel, Aline Menin |
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| Přispěvatelé: | Web-Instrumented Man-Machine Interactions, Communities and Semantics (WIMMICS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Institut National de Recherche en Informatique et en Automatique (Inria), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), ANR-19-P3IA-0002,3IA@cote d'azur,3IA Côte d'Azur(2019), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
media_common.quotation_subject entity linking 050905 science studies Entity linking Open research [INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY] SPARQL RDF Semantic Web visualization media_common Creative visualization 05 social sciences argument mining [INFO.INFO-WB]Computer Science [cs]/Web COVID-19 General Medicine computer.file_format Linked data linked data Data science [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR] Visualization 0509 other social sciences 050904 information & library sciences computer |
| Zdroj: | Quantitative Science Studies Quantitative Science Studies, MIT Press Direct, 2021, ⟨10.1162/qss_a_00164⟩ Quantitative Science Studies, 2021, ⟨10.1162/qss_a_00164⟩ HAL |
| ISSN: | 2641-3337 |
| Popis: | The unprecedented mobilization of scientists caused by the COVID-19 pandemic has generated an enormous number of scholarly articles that are impossible for a human being to keep track of and explore without appropriate tool support. In this context, we created the Covid-on-the-Web project, which aims to assist the accessing, querying, and sense-making of COVID-19-related literature by combining efforts from the semantic web, natural language processing, and visualization fields. In particular, in this paper we present an RDF data set (a linked version of the “COVID-19 Open Research Dataset” (CORD-19), enriched via entity linking and argument mining) and the “Linked Data Visualizer” (LDViz), which assists the querying and visual exploration of the referred data set. The LDViz tool assists in the exploration of different views of the data by combining a querying management interface, which enables the definition of meaningful subsets of data through SPARQL queries, and a visualization interface based on a set of six visualization techniques integrated in a chained visualization concept, which also supports the tracking of provenance information. We demonstrate the potential of our approach to assist biomedical researchers in solving domain-related tasks, as well as to perform exploratory analyses through use case scenarios. |
| Databáze: | OpenAIRE |
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