The DO-KB Knowledgebase: a 20-year journey developing the disease open science ecosystem.

Journal: Nucleic acids research
Published Date: Jan 5, 2024

Abstract

In 2003, the Human Disease Ontology (DO, https://disease-ontology.org/) was established at Northwestern University. In the intervening 20 years, the DO has expanded to become a highly-utilized disease knowledge resource. Serving as the nomenclature and classification standard for human diseases, the DO provides a stable, etiology-based structure integrating mechanistic drivers of human disease. Over the past two decades the DO has grown from a collection of clinical vocabularies, into an expertly curated semantic resource of over 11300 common and rare diseases linking disease concepts through more than 37000 vocabulary cross mappings (v2023-08-08). Here, we introduce the recently launched DO Knowledgebase (DO-KB), which expands the DO's representation of the diseaseome and enhances the findability, accessibility, interoperability and reusability (FAIR) of disease data through a new SPARQL service and new Faceted Search Interface. The DO-KB is an integrated data system, built upon the DO's semantic disease knowledge backbone, with resources that expose and connect the DO's semantic knowledge with disease-related data across Open Linked Data resources. This update includes descriptions of efforts to assess the DO's global impact and improvements to data quality and content, with emphasis on changes in the last two years.

Authors

  • J Allen Baron
    University of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
  • Claudia Sanchez-Beato Johnson
    University of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
  • Michael A Schor
    University of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
  • Dustin Olley
    Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
  • Lance Nickel
    University of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
  • Victor Felix
    Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
  • James B Munro
    University of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
  • Susan M Bello
    The Jackson Laboratory, 600 Main St, Bar Harbor, ME 04609, USA.
  • Cynthia Bearer
    University of Maryland School of Medicine, Baltimore, MD, USA.
  • Richard Lichenstein
    University of Maryland School of Medicine, Baltimore, MD, USA.
  • Katharine Bisordi
    University of Maryland School of Medicine, Baltimore, MD, USA.
  • Rima Koka
    University of Maryland School of Medicine, Baltimore, MD, USA.
  • Carol Greene
    University of Maryland School of Medicine, Baltimore, MD, USA.
  • Lynn M Schriml
    Department of Biochemistry and Molecular Medicine, George Washington University, Washington, DC 20037, USA, Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Center for Bioinformatics and Information Technology, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20892-9760, USA, NASA Jet Propulsion Laboratory, Pasadena, CA, USA, Division of Cancer Prevention, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20892-9760, USA, Wellcome Trust Sanger Institute, Cambridge, UK and McCormick Genomic and Proteomic Center, George Washington University, Washington, DC 20037, USA.

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