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The wiki page for the HCLSIG is at:

This page was created prior to the formation for the original HCLSIG.

Health Care

In Health Care and Medicine, managing information is important in

  • Creating and Managing an WikiPedia:Electronic_Health_Record (eHR) for patients in Health Care
  • Managing large medical terminologies and vocabularies like the WikiPedia:Unified_Medical_Language_System (UMLS), GALEN and SNOMED-CT, the WikiPedia:Systematized_Nomenclature_of_Medicine
  • All stages of the WikiPedia:Drug_discovery pipeline, from target selection through to clinical trials, rely on the effective management of large amounts of information

Life Sciences

In the Life Sciences, large amounts of information need to be managed, for example

  • Understanding vast amounts of data generated by WikiPedia:Sequencing of biological molecules WikiPedia:DNA , WikiPedia:RNA and WikiPedia:Protein, for example in the WikiPedia:Human_Genome_Project
  • Managing high-throughput WikiPedia:Microarray experiments, which measure WikiPedia:Gene expression
  • Mining public repositories of biomedical literature on the Web, for example in WikiPedia:PubMed, and in all stages of scientific, technical and medical publishing
  • Managing large thesauri used by biologists, such as the WikiPedia:National_Cancer_Institute Thesaurus and the WikiPedia:Gene_Ontology
  • Classifying organisms in WikiPedia:Taxonomy, such as the WikiPedia:National_Center_for_Biotechnology_Information (NCBI) Taxonomy, as in the study of WikiPedia:Phylogenetics and WikiPedia:Evolution
  • Understanding the Biological Pathways involved in WikiPedia:Metabolism

The use of WikiPedia:RDF and WikiPedia:Web_Ontology_Language (OWL) produced by the SemanticWeb intitiative, has already helped in some of these areas (both Health Care and Life Sciences) and shows promise for the future. See the summary report from the W3C Workshop on Semantic Web for Life Sciences in 2004 for further details on this activity


The development and deployment of ontologies is a fundamental part of the Semantic Web. The Ontology Working Group of the HCLS is focused on this area. Some example biomedical ontologies (RDF, OWL and OBO formats) being developed and used includes:

Data Sources in RDF

Use Cases and Demonstrations

  • The myGrid project at University of Manchester, UK makes extensive use of RDF, OWL and LSID to enable grid-based computing in its workflow application for biomedical scientists called Taverna. Semantic Web technology plays a role at all stages of the experimental cycle from discovery, selection, composition, execution and results management of many biomedical Web Services.
  • The BioMOBY project uses RDF and LSID to describe its services, and has many use cases and examples.
  • BioDASH is a Semantic Web prototype of a Drug Development Dashboard that associates disease, compounds, drug progression stages, molecular biology, and pathway knowledge.
  • YeastHub is a semantic web use case for integrating data in the life sciences domain.
  • ProofOfConcept is the set of use cases we are trying to develop for the Call For Participation: W3C Workshop on Semantic Web for Life Sciences
  • Andrew Cates has built some BusinessCases, ProofOfConcept and GrantApplications and asks that people stop by and edit them.
  • LifeSciencesQueries points to some queries that can be used to test query engines.

Languages, Standards and Applications