Covid-on-the-Web: Exploring the COVID-19 scientific literature through visualization of linked data from entity and argument mining Article Swipe
Aline Menin
,
Franck Michel
,
Fabien Gandon
,
Raphaël Gazzotti
,
Elena Cabrio
,
Olivier Corby
,
Alain Giboin
,
Santiago Marro
,
Tobias Mayer
,
Serena Villata
,
Marco Winckler
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1162/qss_a_00164
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1162/qss_a_00164
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.
Related Topics
Concepts
Computer science
Visualization
Data science
Context (archaeology)
SPARQL
Set (abstract data type)
Information visualization
Data visualization
Linked data
Argument (complex analysis)
RDF
World Wide Web
Information retrieval
Semantic Web
Data mining
Paleontology
Biochemistry
Chemistry
Biology
Programming language
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1162/qss_a_00164
- https://direct.mit.edu/qss/article-pdf/2/4/1301/2007990/qss_a_00164.pdf
- OA Status
- gold
- Cited By
- 5
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3208698975
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3208698975Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1162/qss_a_00164Digital Object Identifier
- Title
-
Covid-on-the-Web: Exploring the COVID-19 scientific literature through visualization of linked data from entity and argument miningWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-01-01Full publication date if available
- Authors
-
Aline Menin, Franck Michel, Fabien Gandon, Raphaël Gazzotti, Elena Cabrio, Olivier Corby, Alain Giboin, Santiago Marro, Tobias Mayer, Serena Villata, Marco WincklerList of authors in order
- Landing page
-
https://doi.org/10.1162/qss_a_00164Publisher landing page
- PDF URL
-
https://direct.mit.edu/qss/article-pdf/2/4/1301/2007990/qss_a_00164.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://direct.mit.edu/qss/article-pdf/2/4/1301/2007990/qss_a_00164.pdfDirect OA link when available
- Concepts
-
Computer science, Visualization, Data science, Context (archaeology), SPARQL, Set (abstract data type), Information visualization, Data visualization, Linked data, Argument (complex analysis), RDF, World Wide Web, Information retrieval, Semantic Web, Data mining, Paleontology, Biochemistry, Chemistry, Biology, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2022: 3, 2021: 1Per-year citation counts (last 5 years)
- References (count)
-
27Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3208698975 |
|---|---|
| doi | https://doi.org/10.1162/qss_a_00164 |
| ids.doi | https://doi.org/10.1162/qss_a_00164 |
| ids.mag | 3208698975 |
| ids.openalex | https://openalex.org/W3208698975 |
| fwci | 0.39012971 |
| type | article |
| title | Covid-on-the-Web: Exploring the COVID-19 scientific literature through visualization of linked data from entity and argument mining |
| biblio.issue | 4 |
| biblio.volume | 2 |
| biblio.last_page | 1323 |
| biblio.first_page | 1301 |
| topics[0].id | https://openalex.org/T11710 |
| topics[0].field.id | https://openalex.org/fields/13 |
| topics[0].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[0].score | 0.996999979019165 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1312 |
| topics[0].subfield.display_name | Molecular Biology |
| topics[0].display_name | Biomedical Text Mining and Ontologies |
| topics[1].id | https://openalex.org/T10215 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9944999814033508 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1702 |
| topics[1].subfield.display_name | Artificial Intelligence |
| topics[1].display_name | Semantic Web and Ontologies |
| topics[2].id | https://openalex.org/T11986 |
| topics[2].field.id | https://openalex.org/fields/18 |
| topics[2].field.display_name | Decision Sciences |
| topics[2].score | 0.9732999801635742 |
| topics[2].domain.id | https://openalex.org/domains/2 |
| topics[2].domain.display_name | Social Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1802 |
| topics[2].subfield.display_name | Information Systems and Management |
| topics[2].display_name | Scientific Computing and Data Management |
| is_xpac | False |
| apc_list.value | 800 |
| apc_list.currency | USD |
| apc_list.value_usd | 800 |
| apc_paid.value | 734 |
| apc_paid.currency | EUR |
| apc_paid.value_usd | 791 |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.7591016292572021 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C36464697 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7335755825042725 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q451553 |
| concepts[1].display_name | Visualization |
| concepts[2].id | https://openalex.org/C2522767166 |
| concepts[2].level | 1 |
| concepts[2].score | 0.5844101309776306 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q2374463 |
| concepts[2].display_name | Data science |
| concepts[3].id | https://openalex.org/C2779343474 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5288516283035278 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q3109175 |
| concepts[3].display_name | Context (archaeology) |
| concepts[4].id | https://openalex.org/C41009113 |
| concepts[4].level | 4 |
| concepts[4].score | 0.510017454624176 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q54871 |
| concepts[4].display_name | SPARQL |
| concepts[5].id | https://openalex.org/C177264268 |
| concepts[5].level | 2 |
| concepts[5].score | 0.49457618594169617 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q1514741 |
| concepts[5].display_name | Set (abstract data type) |
| concepts[6].id | https://openalex.org/C185578843 |
| concepts[6].level | 3 |
| concepts[6].score | 0.47459906339645386 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q10609775 |
| concepts[6].display_name | Information visualization |
| concepts[7].id | https://openalex.org/C172367668 |
| concepts[7].level | 3 |
| concepts[7].score | 0.46421197056770325 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q6504956 |
| concepts[7].display_name | Data visualization |
| concepts[8].id | https://openalex.org/C69075417 |
| concepts[8].level | 3 |
| concepts[8].score | 0.44536346197128296 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q515701 |
| concepts[8].display_name | Linked data |
| concepts[9].id | https://openalex.org/C98184364 |
| concepts[9].level | 2 |
| concepts[9].score | 0.4406542479991913 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q1780131 |
| concepts[9].display_name | Argument (complex analysis) |
| concepts[10].id | https://openalex.org/C147497476 |
| concepts[10].level | 3 |
| concepts[10].score | 0.4269029498100281 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q54872 |
| concepts[10].display_name | RDF |
| concepts[11].id | https://openalex.org/C136764020 |
| concepts[11].level | 1 |
| concepts[11].score | 0.39772456884384155 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q466 |
| concepts[11].display_name | World Wide Web |
| concepts[12].id | https://openalex.org/C23123220 |
| concepts[12].level | 1 |
| concepts[12].score | 0.38765162229537964 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q816826 |
| concepts[12].display_name | Information retrieval |
| concepts[13].id | https://openalex.org/C2129575 |
| concepts[13].level | 2 |
| concepts[13].score | 0.38162416219711304 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q54837 |
| concepts[13].display_name | Semantic Web |
| concepts[14].id | https://openalex.org/C124101348 |
| concepts[14].level | 1 |
| concepts[14].score | 0.23336800932884216 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[14].display_name | Data mining |
| concepts[15].id | https://openalex.org/C151730666 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q7205 |
| concepts[15].display_name | Paleontology |
| concepts[16].id | https://openalex.org/C55493867 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q7094 |
| concepts[16].display_name | Biochemistry |
| concepts[17].id | https://openalex.org/C185592680 |
| concepts[17].level | 0 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[17].display_name | Chemistry |
| concepts[18].id | https://openalex.org/C86803240 |
| concepts[18].level | 0 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[18].display_name | Biology |
| concepts[19].id | https://openalex.org/C199360897 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[19].display_name | Programming language |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.7591016292572021 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/visualization |
| keywords[1].score | 0.7335755825042725 |
| keywords[1].display_name | Visualization |
| keywords[2].id | https://openalex.org/keywords/data-science |
| keywords[2].score | 0.5844101309776306 |
| keywords[2].display_name | Data science |
| keywords[3].id | https://openalex.org/keywords/context |
| keywords[3].score | 0.5288516283035278 |
| keywords[3].display_name | Context (archaeology) |
| keywords[4].id | https://openalex.org/keywords/sparql |
| keywords[4].score | 0.510017454624176 |
| keywords[4].display_name | SPARQL |
| keywords[5].id | https://openalex.org/keywords/set |
| keywords[5].score | 0.49457618594169617 |
| keywords[5].display_name | Set (abstract data type) |
| keywords[6].id | https://openalex.org/keywords/information-visualization |
| keywords[6].score | 0.47459906339645386 |
| keywords[6].display_name | Information visualization |
| keywords[7].id | https://openalex.org/keywords/data-visualization |
| keywords[7].score | 0.46421197056770325 |
| keywords[7].display_name | Data visualization |
| keywords[8].id | https://openalex.org/keywords/linked-data |
| keywords[8].score | 0.44536346197128296 |
| keywords[8].display_name | Linked data |
| keywords[9].id | https://openalex.org/keywords/argument |
| keywords[9].score | 0.4406542479991913 |
| keywords[9].display_name | Argument (complex analysis) |
| keywords[10].id | https://openalex.org/keywords/rdf |
| keywords[10].score | 0.4269029498100281 |
| keywords[10].display_name | RDF |
| keywords[11].id | https://openalex.org/keywords/world-wide-web |
| keywords[11].score | 0.39772456884384155 |
| keywords[11].display_name | World Wide Web |
| keywords[12].id | https://openalex.org/keywords/information-retrieval |
| keywords[12].score | 0.38765162229537964 |
| keywords[12].display_name | Information retrieval |
| keywords[13].id | https://openalex.org/keywords/semantic-web |
| keywords[13].score | 0.38162416219711304 |
| keywords[13].display_name | Semantic Web |
| keywords[14].id | https://openalex.org/keywords/data-mining |
| keywords[14].score | 0.23336800932884216 |
| keywords[14].display_name | Data mining |
| language | en |
| locations[0].id | doi:10.1162/qss_a_00164 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210195326 |
| locations[0].source.issn | 2641-3337 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2641-3337 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Quantitative Science Studies |
| locations[0].source.host_organization | https://openalex.org/P4310315718 |
| locations[0].source.host_organization_name | The MIT Press |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310315718 |
| locations[0].source.host_organization_lineage_names | The MIT Press |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://direct.mit.edu/qss/article-pdf/2/4/1301/2007990/qss_a_00164.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Quantitative Science Studies |
| locations[0].landing_page_url | https://doi.org/10.1162/qss_a_00164 |
| locations[1].id | pmh:oai:HAL:hal-03404580v1 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306402512 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | HAL (Le Centre pour la Communication Scientifique Directe) |
| locations[1].source.host_organization | https://openalex.org/I1294671590 |
| locations[1].source.host_organization_name | Centre National de la Recherche Scientifique |
| locations[1].source.host_organization_lineage | https://openalex.org/I1294671590 |
| locations[1].license | other-oa |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | Journal articles |
| locations[1].license_id | https://openalex.org/licenses/other-oa |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Quantitative Science Studies, 2021, ⟨10.1162/qss_a_00164⟩ |
| locations[1].landing_page_url | https://hal.science/hal-03404580 |
| locations[2].id | pmh:oai:doaj.org/article:8ef3f64af4fa4d6e9383c0d726507e0c |
| locations[2].is_oa | False |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Quantitative Science Studies, Vol 2, Iss 4 (2022) |
| locations[2].landing_page_url | https://doaj.org/article/8ef3f64af4fa4d6e9383c0d726507e0c |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5075965243 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-9345-3994 |
| authorships[0].author.display_name | Aline Menin |
| authorships[0].affiliations[0].raw_affiliation_string | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Aline Menin |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[1].author.id | https://openalex.org/A5032122043 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-9064-0463 |
| authorships[1].author.display_name | Franck Michel |
| authorships[1].affiliations[0].raw_affiliation_string | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Franck Michel |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[2].author.id | https://openalex.org/A5044946197 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-0543-1232 |
| authorships[2].author.display_name | Fabien Gandon |
| authorships[2].affiliations[0].raw_affiliation_string | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Fabien Gandon |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[3].author.id | https://openalex.org/A5007976719 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-5618-9776 |
| authorships[3].author.display_name | Raphaël Gazzotti |
| authorships[3].affiliations[0].raw_affiliation_string | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Raphaël Gazzotti |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[4].author.id | https://openalex.org/A5049137879 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-9374-7872 |
| authorships[4].author.display_name | Elena Cabrio |
| authorships[4].affiliations[0].raw_affiliation_string | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Elena Cabrio |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[5].author.id | https://openalex.org/A5053350510 |
| authorships[5].author.orcid | https://orcid.org/0000-0001-6610-0969 |
| authorships[5].author.display_name | Olivier Corby |
| authorships[5].affiliations[0].raw_affiliation_string | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Olivier Corby |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[6].author.id | https://openalex.org/A5072843681 |
| authorships[6].author.orcid | https://orcid.org/0000-0003-1007-0101 |
| authorships[6].author.display_name | Alain Giboin |
| authorships[6].affiliations[0].raw_affiliation_string | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Alain Giboin |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[7].author.id | https://openalex.org/A5016059244 |
| authorships[7].author.orcid | https://orcid.org/0000-0001-6220-0559 |
| authorships[7].author.display_name | Santiago Marro |
| authorships[7].affiliations[0].raw_affiliation_string | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Santiago Marro |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[8].author.id | https://openalex.org/A5040582750 |
| authorships[8].author.orcid | https://orcid.org/0000-0002-4935-4710 |
| authorships[8].author.display_name | Tobias Mayer |
| authorships[8].affiliations[0].raw_affiliation_string | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[8].author_position | middle |
| authorships[8].raw_author_name | Tobias Mayer |
| authorships[8].is_corresponding | False |
| authorships[8].raw_affiliation_strings | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[9].author.id | https://openalex.org/A5016281730 |
| authorships[9].author.orcid | https://orcid.org/0000-0003-3495-493X |
| authorships[9].author.display_name | Serena Villata |
| authorships[9].affiliations[0].raw_affiliation_string | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[9].author_position | middle |
| authorships[9].raw_author_name | Serena Villata |
| authorships[9].is_corresponding | False |
| authorships[9].raw_affiliation_strings | WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics (2004 route des lucioles 06902 Sophia Antipolis - France) |
| authorships[10].author.id | https://openalex.org/A5089722326 |
| authorships[10].author.orcid | https://orcid.org/0000-0002-0756-6934 |
| authorships[10].author.display_name | Marco Winckler |
| authorships[10].countries | FR |
| authorships[10].affiliations[0].institution_ids | https://openalex.org/I1294671590, https://openalex.org/I1326498283 |
| authorships[10].affiliations[0].raw_affiliation_string | University Côte d’Azur, Inria, CNRS, I3S (UMR 7271), France |
| authorships[10].institutions[0].id | https://openalex.org/I1294671590 |
| authorships[10].institutions[0].ror | https://ror.org/02feahw73 |
| authorships[10].institutions[0].type | government |
| authorships[10].institutions[0].lineage | https://openalex.org/I1294671590 |
| authorships[10].institutions[0].country_code | FR |
| authorships[10].institutions[0].display_name | Centre National de la Recherche Scientifique |
| authorships[10].institutions[1].id | https://openalex.org/I1326498283 |
| authorships[10].institutions[1].ror | https://ror.org/02kvxyf05 |
| authorships[10].institutions[1].type | government |
| authorships[10].institutions[1].lineage | https://openalex.org/I1326498283 |
| authorships[10].institutions[1].country_code | FR |
| authorships[10].institutions[1].display_name | Institut national de recherche en sciences et technologies du numérique |
| authorships[10].author_position | last |
| authorships[10].raw_author_name | Marco Winckler |
| authorships[10].is_corresponding | False |
| authorships[10].raw_affiliation_strings | University Côte d’Azur, Inria, CNRS, I3S (UMR 7271), France |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://direct.mit.edu/qss/article-pdf/2/4/1301/2007990/qss_a_00164.pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Covid-on-the-Web: Exploring the COVID-19 scientific literature through visualization of linked data from entity and argument mining |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11710 |
| primary_topic.field.id | https://openalex.org/fields/13 |
| primary_topic.field.display_name | Biochemistry, Genetics and Molecular Biology |
| primary_topic.score | 0.996999979019165 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1312 |
| primary_topic.subfield.display_name | Molecular Biology |
| primary_topic.display_name | Biomedical Text Mining and Ontologies |
| related_works | https://openalex.org/W199330785, https://openalex.org/W2615202182, https://openalex.org/W2904139343, https://openalex.org/W2767591199, https://openalex.org/W98016204, https://openalex.org/W2101525042, https://openalex.org/W4388184885, https://openalex.org/W4322622679, https://openalex.org/W2770351630, https://openalex.org/W2522667419 |
| cited_by_count | 5 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2022 |
| counts_by_year[1].cited_by_count | 3 |
| counts_by_year[2].year | 2021 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 3 |
| best_oa_location.id | doi:10.1162/qss_a_00164 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210195326 |
| best_oa_location.source.issn | 2641-3337 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2641-3337 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Quantitative Science Studies |
| best_oa_location.source.host_organization | https://openalex.org/P4310315718 |
| best_oa_location.source.host_organization_name | The MIT Press |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310315718 |
| best_oa_location.source.host_organization_lineage_names | The MIT Press |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://direct.mit.edu/qss/article-pdf/2/4/1301/2007990/qss_a_00164.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Quantitative Science Studies |
| best_oa_location.landing_page_url | https://doi.org/10.1162/qss_a_00164 |
| primary_location.id | doi:10.1162/qss_a_00164 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210195326 |
| primary_location.source.issn | 2641-3337 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2641-3337 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Quantitative Science Studies |
| primary_location.source.host_organization | https://openalex.org/P4310315718 |
| primary_location.source.host_organization_name | The MIT Press |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310315718 |
| primary_location.source.host_organization_lineage_names | The MIT Press |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://direct.mit.edu/qss/article-pdf/2/4/1301/2007990/qss_a_00164.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Quantitative Science Studies |
| primary_location.landing_page_url | https://doi.org/10.1162/qss_a_00164 |
| publication_date | 2021-01-01 |
| publication_year | 2021 |
| referenced_works | https://openalex.org/W4288079217, https://openalex.org/W2970771982, https://openalex.org/W2620819475, https://openalex.org/W2088981396, https://openalex.org/W2026810221, https://openalex.org/W2100396541, https://openalex.org/W2344469150, https://openalex.org/W3030520728, https://openalex.org/W3109507892, https://openalex.org/W6604181502, https://openalex.org/W4246234517, https://openalex.org/W2175849758, https://openalex.org/W2965892119, https://openalex.org/W3186273103, https://openalex.org/W3184760519, https://openalex.org/W3086986628, https://openalex.org/W3030413700, https://openalex.org/W2019211393, https://openalex.org/W3102245839, https://openalex.org/W3116149091, https://openalex.org/W3171637127, https://openalex.org/W3147190425, https://openalex.org/W6776225533, https://openalex.org/W3020786614, https://openalex.org/W4381594492, https://openalex.org/W3209888570, https://openalex.org/W3024528803 |
| referenced_works_count | 27 |
| abstract_inverted_index.a | 23, 130, 147, 152, 160 |
| abstract_inverted_index.(a | 80 |
| abstract_inverted_index.In | 36, 69 |
| abstract_inverted_index.We | 172 |
| abstract_inverted_index.an | 13, 76 |
| abstract_inverted_index.as | 187, 189 |
| abstract_inverted_index.by | 7, 56, 128 |
| abstract_inverted_index.in | 71, 119, 159, 183 |
| abstract_inverted_index.of | 4, 16, 29, 53, 83, 110, 122, 125, 138, 141, 154, 169, 176 |
| abstract_inverted_index.on | 151 |
| abstract_inverted_index.to | 26, 46, 179, 190 |
| abstract_inverted_index.we | 39, 74 |
| abstract_inverted_index.RDF | 77 |
| abstract_inverted_index.The | 1, 115 |
| abstract_inverted_index.and | 30, 51, 66, 94, 97, 107, 146 |
| abstract_inverted_index.are | 20 |
| abstract_inverted_index.for | 22 |
| abstract_inverted_index.has | 11 |
| abstract_inverted_index.our | 177 |
| abstract_inverted_index.set | 79, 153 |
| abstract_inverted_index.six | 155 |
| abstract_inverted_index.the | 8, 41, 48, 60, 84, 98, 105, 111, 120, 126, 136, 167, 174 |
| abstract_inverted_index.use | 195 |
| abstract_inverted_index.via | 91 |
| abstract_inverted_index.Data | 100 |
| abstract_inverted_index.Open | 86 |
| abstract_inverted_index.aims | 45 |
| abstract_inverted_index.also | 165 |
| abstract_inverted_index.case | 196 |
| abstract_inverted_index.data | 78, 113, 127, 142 |
| abstract_inverted_index.from | 59 |
| abstract_inverted_index.keep | 27 |
| abstract_inverted_index.set. | 114 |
| abstract_inverted_index.that | 19 |
| abstract_inverted_index.this | 37, 72 |
| abstract_inverted_index.tool | 34, 117 |
| abstract_inverted_index.web, | 62 |
| abstract_inverted_index.well | 188 |
| abstract_inverted_index.LDViz | 116 |
| abstract_inverted_index.based | 150 |
| abstract_inverted_index.being | 25 |
| abstract_inverted_index.human | 24 |
| abstract_inverted_index.paper | 73 |
| abstract_inverted_index.track | 28 |
| abstract_inverted_index.views | 124 |
| abstract_inverted_index.which | 44, 103, 134, 164 |
| abstract_inverted_index.SPARQL | 144 |
| abstract_inverted_index.assist | 47, 180 |
| abstract_inverted_index.caused | 6 |
| abstract_inverted_index.entity | 92 |
| abstract_inverted_index.linked | 81 |
| abstract_inverted_index.number | 15 |
| abstract_inverted_index.tasks, | 186 |
| abstract_inverted_index.visual | 108 |
| abstract_inverted_index.assists | 104, 118 |
| abstract_inverted_index.chained | 161 |
| abstract_inverted_index.created | 40 |
| abstract_inverted_index.efforts | 58 |
| abstract_inverted_index.enables | 135 |
| abstract_inverted_index.explore | 31 |
| abstract_inverted_index.fields. | 68 |
| abstract_inverted_index.linking | 93 |
| abstract_inverted_index.mining) | 96 |
| abstract_inverted_index.natural | 63 |
| abstract_inverted_index.perform | 191 |
| abstract_inverted_index.present | 75 |
| abstract_inverted_index.solving | 184 |
| abstract_inverted_index.subsets | 140 |
| abstract_inverted_index.through | 143, 194 |
| abstract_inverted_index.version | 82 |
| abstract_inverted_index.without | 32 |
| abstract_inverted_index.(LDViz), | 102 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.COVID-19 | 9 |
| abstract_inverted_index.Research | 87 |
| abstract_inverted_index.analyses | 193 |
| abstract_inverted_index.approach | 178 |
| abstract_inverted_index.argument | 95 |
| abstract_inverted_index.articles | 18 |
| abstract_inverted_index.concept, | 163 |
| abstract_inverted_index.context, | 38 |
| abstract_inverted_index.enormous | 14 |
| abstract_inverted_index.enriched | 90 |
| abstract_inverted_index.language | 64 |
| abstract_inverted_index.pandemic | 10 |
| abstract_inverted_index.project, | 43 |
| abstract_inverted_index.queries, | 145 |
| abstract_inverted_index.querying | 106, 131 |
| abstract_inverted_index.referred | 112 |
| abstract_inverted_index.semantic | 61 |
| abstract_inverted_index.support. | 35 |
| abstract_inverted_index.supports | 166 |
| abstract_inverted_index.tracking | 168 |
| abstract_inverted_index.combining | 57, 129 |
| abstract_inverted_index.different | 123 |
| abstract_inverted_index.generated | 12 |
| abstract_inverted_index.interface | 149 |
| abstract_inverted_index.potential | 175 |
| abstract_inverted_index.querying, | 50 |
| abstract_inverted_index.scholarly | 17 |
| abstract_inverted_index.“Linked | 99 |
| abstract_inverted_index.(CORD-19), | 89 |
| abstract_inverted_index.Dataset” | 88 |
| abstract_inverted_index.accessing, | 49 |
| abstract_inverted_index.biomedical | 181 |
| abstract_inverted_index.definition | 137 |
| abstract_inverted_index.impossible | 21 |
| abstract_inverted_index.integrated | 158 |
| abstract_inverted_index.interface, | 133 |
| abstract_inverted_index.literature | 55 |
| abstract_inverted_index.management | 132 |
| abstract_inverted_index.meaningful | 139 |
| abstract_inverted_index.provenance | 170 |
| abstract_inverted_index.scenarios. | 197 |
| abstract_inverted_index.scientists | 5 |
| abstract_inverted_index.techniques | 157 |
| abstract_inverted_index.appropriate | 33 |
| abstract_inverted_index.demonstrate | 173 |
| abstract_inverted_index.exploration | 109, 121 |
| abstract_inverted_index.exploratory | 192 |
| abstract_inverted_index.particular, | 70 |
| abstract_inverted_index.processing, | 65 |
| abstract_inverted_index.researchers | 182 |
| abstract_inverted_index.“COVID-19 | 85 |
| abstract_inverted_index.information. | 171 |
| abstract_inverted_index.mobilization | 3 |
| abstract_inverted_index.sense-making | 52 |
| abstract_inverted_index.Visualizer” | 101 |
| abstract_inverted_index.unprecedented | 2 |
| abstract_inverted_index.visualization | 67, 148, 156, 162 |
| abstract_inverted_index.domain-related | 185 |
| abstract_inverted_index.COVID-19-related | 54 |
| abstract_inverted_index.Covid-on-the-Web | 42 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 11 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.5299999713897705 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.59096229 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |