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

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_CommunityInput

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In implemented systems, ontologies are...

• Strong for:
  • Supporting change and aggregation
  • Enabling community aggregation, annotation
  • Automated data ingestion
  • Data validation
  • Ensuring consistency of terms across many data sets (Distributed systems)
  • Supporting reasoning
  • Self describing systems
  • Systems with many complex constraints, rules, laws, with frequent changes (Dynamically changing systems)
  • Data mining / semantic signature extraction
  • Rapid system building
• Weak for:
  • Being understandable by software engineers and customers
  • Query performance (compared to relational databases)

Needs

• Need better standards for common elements:
  • Datatypes
  • Ontology patterns (e.g. whole/part patterns)
  • Collect ontological primitives from observation data
• Need repositories
  • 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
• Need better tools to help interpret legacy systems, transform into semantic systems.
• Need to establish feedback mechanisms from end users to ontology designers directly from point of use.

Recommendations

• Look for the 80-20 rule of semantic development
• Use well defined and narrow use cases to demonstrate benefits of semantic approaches
• Having explicit vocabularies (classifiers) is a must in a distributed system;
• Community should be included in the development and evolution of vocabularies
• It is critical to capture and evolve domain knowledge in a form that the community is comfortable with
• Transition from implicit domain knowledge to explicit encoding requires community consensus - and an organization to manage the consensus
• Some have recommended exposing users to SKOS semantics; use more complicated constructs only on back end if necessary.

Other Observations / Lessons learned

• UML to OWL is a common requirement for legacy systems
  • Starting from scratch is rare.
• Ontology patterns are very helpful, and encourage model reuse
• Semantic techniques work best when not compromised by implementation tradeoffs
• Semantic methods are faster to implement and easier to maintain
• Semantic approaches particularly suited to systems with many complex constraints, rules, laws, with frequent changes
• Incremental implementation is possible through federation of datastores
• Ontologies are not always applied to enable reasoners - sometimes just as a more rigorous data modeling approach
• Engineers turned ontologists often don't have the necessary background/skills
• Existing infrastructure supports traditional software development far better than large-scale ontology development
• There are many ontologies of dubious quality
• Service-oriented architectures allow separation of code and ontology updates
• Reasoner and query engine performance is highly dependent upon the exact formulation of rules and queries
• No single technology/tool currently provides the best solution across all large system use cases

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maintained by the Track-4 champions: Steve Ray & Trish Whetzel ... please do not edit