OntologySummit2012 Applications CommunityInput

= OntologySummit2012: (Track-4) "Large-scale domain applications" Community Input =

Track Co-Champions: Dr. SteveRay and Dr. TrishWhetzel

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

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Entry by SteveRay, 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