COVIWD: COVID-19 Wikidata Dashboard

Darari, Fariz

doi:10.21609/jiki.v14i1.941

Jurnal SINTA 2

COVIWD: COVID-19 Wikidata Dashboard

Darari, Fariz^{University of Indonesia}

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 14 No. 1 (2021) · pp. 39–47

DOI: 10.21609/jiki.v14i1.941
ISSN: 2502-9274, 2088-7051
Published: 2021-02-28
Publisher: Faculty of Computer Science - Universitas Indonesia
Language: eng

Abstract

COVID-19 (short for coronavirus disease 2019) is an emerging infectious disease that has had a tremendous impact on our daily lives. Globally, there have been over 95 million cases of COVID-19 and 2 million deaths across 191 countries and regions. The rapid spread and severity of COVID-19 call for a monitoring dashboard that can be developed quickly in an adaptable manner. Wikidata is a free, collaborative knowledge graph, collecting structured data about various themes, including that of COVID-19. We present COVIWD, a COVID-19 Wikidata dashboard, which provides a one-stop information/visualization service for topics related to COVID-19, ranging from symptoms and risk factors to comparison of cases and deaths among countries. The dashboard is one of the first that leverages open knowledge graph technologies, namely, RDF (for data modeling) and SPARQL (for querying), to give a live, concise snapshot of the COVID-19 pandemic. The use of both RDF and SPARQL enables rapid and flexible application development. COVIWD is available at http://coviwd.org.

Keywords

Collaboration network of the authors

8 authors · 22 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

University of Indonesia
Affiliation unknown

Different organisations
Same organisation
Affiliation unknown
Thicker line = more joint articles · bigger circle = more articles

Show as table

Co-author	Organisation	Joint articles
Ruli Manurung	Affiliation unknown	1
Douglas Raevan Faisal	University of Indonesia	1
Muhammad Ilham Al Ghifari	University of Indonesia	1
Muhammad Zuhdi Zamrud	University of Indonesia	1
Marcellino Chris O'Vara	University of Indonesia	1
Berty Chrismartin Lumban Tobing	Affiliation unknown	1
On Lee	Affiliation unknown	1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.

Original metadata (oai_dc)

<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">COVIWD: COVID-19 Wikidata Dashboard</dc:title>
	<dc:creator>Darari, Fariz</dc:creator>
	<dc:subject xml:lang="en-US">COVID-19</dc:subject>
	<dc:subject xml:lang="en-US">Wikidata</dc:subject>
	<dc:subject xml:lang="en-US">Dashboard</dc:subject>
	<dc:subject xml:lang="en-US">Data Visualization</dc:subject>
	<dc:description xml:lang="en-US">COVID-19 (short for coronavirus disease 2019) is an emerging infectious disease that has had a tremendous impact on our daily lives. Globally, there have been over 95 million cases of COVID-19 and 2 million deaths across 191 countries and regions. The rapid spread and severity of COVID-19 call for a monitoring dashboard that can be developed quickly in an adaptable manner. Wikidata is a free, collaborative knowledge graph, collecting structured data about various themes, including that of COVID-19. We present COVIWD, a COVID-19 Wikidata dashboard, which provides a one-stop information/visualization service for topics related to COVID-19, ranging from symptoms and risk factors to comparison of cases and deaths among countries. The dashboard is one of the first that leverages open knowledge graph technologies, namely, RDF (for data modeling) and SPARQL (for querying), to give a live, concise snapshot of the COVID-19 pandemic. The use of both RDF and SPARQL enables rapid and flexible application development. COVIWD is available at http://coviwd.org.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2021-02-28</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/941</dc:identifier>
	<dc:identifier>10.21609/jiki.v14i1.941</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 14 No. 1 (2021): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 39-47</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v14i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/941/440</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 Jurnal Ilmu Komputer dan Informasi</dc:rights>
</oai_dc:dc>