There is a newer version of this record available.

Journal article Open Access

Representing COVID-19 information in collaborative knowledge graphs: a study of Wikidata

Houcemeddine Turki; Mohamed Ali Hadj Taieb; Thomas Shafee; Tiago Lubiana; Dariusz Jemielniak; Mohamed Ben Aouicha; Jose Emilio Labra Gayo; Mus'ab Banat; Diptanshu Das; Daniel Mietchen


JSON Export

{
  "files": [
    {
      "links": {
        "self": "https://zenodo.org/api/files/ccb3ecb1-5df6-4d51-9b60-14482b64776b/Representing%20COVID-19%20information%20in%20collaborative%20knowledge%20graphs_%20a%20study%20of%20Wikidata.docx"
      }, 
      "checksum": "md5:040b302ee5d891f09bc886661d7c6a03", 
      "bucket": "ccb3ecb1-5df6-4d51-9b60-14482b64776b", 
      "key": "Representing COVID-19 information in collaborative knowledge graphs_ a study of Wikidata.docx", 
      "type": "docx", 
      "size": 8471676
    }, 
    {
      "links": {
        "self": "https://zenodo.org/api/files/ccb3ecb1-5df6-4d51-9b60-14482b64776b/Representing%20COVID-19%20information%20in%20collaborative%20knowledge%20graphs_%20a%20study%20of%20Wikidata.odt"
      }, 
      "checksum": "md5:3882b71faac99d9c82fb262aaa5c3a69", 
      "bucket": "ccb3ecb1-5df6-4d51-9b60-14482b64776b", 
      "key": "Representing COVID-19 information in collaborative knowledge graphs_ a study of Wikidata.odt", 
      "type": "odt", 
      "size": 8337932
    }, 
    {
      "links": {
        "self": "https://zenodo.org/api/files/ccb3ecb1-5df6-4d51-9b60-14482b64776b/Representing%20COVID-19%20information%20in%20collaborative%20knowledge%20graphs_%20a%20study%20of%20Wikidata.pdf"
      }, 
      "checksum": "md5:93823893d931a99e139cf52c0b9fb1e4", 
      "bucket": "ccb3ecb1-5df6-4d51-9b60-14482b64776b", 
      "key": "Representing COVID-19 information in collaborative knowledge graphs_ a study of Wikidata.pdf", 
      "type": "pdf", 
      "size": 2987022
    }
  ], 
  "owners": [
    126367
  ], 
  "doi": "10.5281/zenodo.4028483", 
  "stats": {
    "version_unique_downloads": 3423.0, 
    "unique_views": 418.0, 
    "views": 437.0, 
    "version_views": 3576.0, 
    "unique_downloads": 2543.0, 
    "version_unique_views": 3212.0, 
    "volume": 10199984126.0, 
    "version_downloads": 4629.0, 
    "downloads": 3384.0, 
    "version_volume": 15296584761.0
  }, 
  "links": {
    "doi": "https://doi.org/10.5281/zenodo.4028483", 
    "conceptdoi": "https://doi.org/10.5281/zenodo.4028482", 
    "bucket": "https://zenodo.org/api/files/ccb3ecb1-5df6-4d51-9b60-14482b64776b", 
    "conceptbadge": "https://zenodo.org/badge/doi/10.5281/zenodo.4028482.svg", 
    "html": "https://zenodo.org/record/4028483", 
    "latest_html": "https://zenodo.org/record/5544840", 
    "badge": "https://zenodo.org/badge/doi/10.5281/zenodo.4028483.svg", 
    "latest": "https://zenodo.org/api/records/5544840"
  }, 
  "conceptdoi": "10.5281/zenodo.4028482", 
  "created": "2020-09-15T21:19:22.280231+00:00", 
  "updated": "2021-10-11T15:51:38.282831+00:00", 
  "conceptrecid": "4028482", 
  "revision": 16, 
  "id": 4028483, 
  "metadata": {
    "access_right_category": "success", 
    "doi": "10.5281/zenodo.4028483", 
    "description": "<p>Information related to the COVID-19 pandemic ranges from biological to bibliographic and from geographical to genetic. Wikidata is a vast interdisciplinary, multilingual, open collaborative knowledge base of more than 88 million entities connected by well over a billion relationships and is consequently a web-scale platform for broader computer-supported cooperative work and linked open data. Here, we introduce four aspects of Wikidata that make it an ideal knowledge base for information on the COVID-19 pandemic: its flexible data model, its multilingual features, its alignment to multiple external databases, and its multidisciplinary organization. The structure of the raw data is highly complex, so converting it to meaningful insight requires extraction and visualization, the global crowdsourcing of which adds both additional challenges and opportunities. The created knowledge graph for COVID-19 in Wikidata can be visualized, explored and analyzed in near real time by specialists, automated tools and the public, for decision support as well as educational and scholarly research purposes via SPARQL, a semantic query language used to retrieve and process information from databases saved in Resource Description Framework (RDF) format.</p>", 
    "language": "eng", 
    "title": "Representing COVID-19 information in collaborative knowledge graphs: a study of Wikidata", 
    "license": {
      "id": "CC-BY-4.0"
    }, 
    "relations": {
      "version": [
        {
          "count": 5, 
          "index": 0, 
          "parent": {
            "pid_type": "recid", 
            "pid_value": "4028482"
          }, 
          "is_last": false, 
          "last_child": {
            "pid_type": "recid", 
            "pid_value": "5544840"
          }
        }
      ]
    }, 
    "communities": [
      {
        "id": "africarxiv"
      }, 
      {
        "id": "covid-19"
      }
    ], 
    "keywords": [
      "Public health surveillance", 
      "Wikidata", 
      "Knowledge graph", 
      "COVID-19", 
      "SPARQL", 
      "Community curation", 
      "FAIR data", 
      "Linked Open Data"
    ], 
    "publication_date": "2020-09-14", 
    "creators": [
      {
        "orcid": "0000-0003-3492-2014", 
        "affiliation": "Faculty of Medicine of Sfax, University of Sfax, Sfax, Tunisia", 
        "name": "Houcemeddine Turki"
      }, 
      {
        "orcid": "0000-0002-2786-8913", 
        "affiliation": "Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia", 
        "name": "Mohamed Ali Hadj Taieb"
      }, 
      {
        "orcid": "0000-0002-2298-7593", 
        "affiliation": "La Trobe University, Melbourne, Victoria, Australia", 
        "name": "Thomas Shafee"
      }, 
      {
        "orcid": "0000-0003-2473-2313", 
        "affiliation": "Computational Systems Biology Laboratory, University of S\u00e3o Paulo, S\u00e3o Paulo, Brazil", 
        "name": "Tiago Lubiana"
      }, 
      {
        "orcid": "0000-0002-3745-7931", 
        "affiliation": "Department of Management in Networked and Digital Societies, Kozminski University, Warsaw, Poland", 
        "name": "Dariusz Jemielniak"
      }, 
      {
        "orcid": "0000-0002-2277-5814", 
        "affiliation": "Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia", 
        "name": "Mohamed Ben Aouicha"
      }, 
      {
        "orcid": "0000-0001-8907-5348", 
        "affiliation": "Web Semantics Oviedo (WESO) Research Group, University of Oviedo, Spain", 
        "name": "Jose Emilio Labra Gayo"
      }, 
      {
        "orcid": "0000-0001-9132-3849", 
        "affiliation": "Faculty of Medicine, Hashemite University, Zarqa, Jordan", 
        "name": "Mus'ab Banat"
      }, 
      {
        "orcid": "0000-0002-7221-5022", 
        "affiliation": "Institute of Child Health (ICH), Kolkata, India", 
        "name": "Diptanshu Das"
      }, 
      {
        "orcid": "0000-0001-9488-1870", 
        "affiliation": "School of Data Science, University of Virginia, Charlottesville, Virginia, United States of America", 
        "name": "Daniel Mietchen"
      }
    ], 
    "access_right": "open", 
    "resource_type": {
      "subtype": "article", 
      "type": "publication", 
      "title": "Journal article"
    }, 
    "related_identifiers": [
      {
        "scheme": "doi", 
        "identifier": "10.5281/zenodo.4028482", 
        "relation": "isVersionOf"
      }
    ]
  }
}
3,576
4,629
views
downloads
All versions This version
Views 3,576437
Downloads 4,6293,384
Data volume 15.3 GB10.2 GB
Unique views 3,212418
Unique downloads 3,4232,543

Share

Cite as