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Ontolog Forum

Ontology Summit 2012: (Track-4) "Large-scale domain applications" Community Input

Track Co-Champions: Dr. Steve Ray and Dr. Trish Whetzel

Mission Statement

This track will help to ground the discussions in the other tracks and bring key challenges to light by describing current large-scale systems and systems of systems that either use, or could use, ontologies in their deployment. "Large-scale" can mean either very large data sets, very complex data sets, federated systems, highly distributed systems, or real-time, continuous data systems. Examples of large data sets might include scientific observations and studies; complex data sets could be technical data packages for manufactured products, or electronic health records; federated systems could include information sharing to combat terrorism, highly distributed systems includes items such as the smart electrical grid (aka Smart Grid), and real-time systems include network management systems. Of course, some big systems might include all five aspects.   

see also: OntologySummit2012_Applications_Synthesis


Enter your input below ... (please identify yourself and date your entry)

Entry by Steve Ray, 2/21/2012

  • Observations / Lessons learned:
    • UML to OWL is a common requirement for legacy systems
      • Need better tools to help interpret legacy systems, transform into semantic systems.
      • Starting from scratch is rare.
    • Ontology patterns are very helpful, and encourage model reuse
    • Look for the 80-20 rule of semantic development
    • Semantic techniques work best when not compromised by implementation tradeoffs
    • Semantic methods are faster to implement and easier to maintain
    • Semantic approaches are particularly suited to systems with many complex constraints, rules, laws, with frequent changes
  • Needs:
    • Need better standards for common elements:
      • Datatypes (Are xsd types enough? I think not)
      • Ontology patterns (e.g. whole/part patterns)
      • Collect ontological primitives from observation data
    • Need repositories (When is OOR going to be ready for production use?)
      • Repositories of ontological patterns could be more useful than repositories of ontologies
    • Need industrial strength semantic services resident in the cloud
    • Need better visualization tools and approaches

  • ...