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Breakout Session on Applications Summary of Discussions

Breakout Session on Applications Summary of Discussions. Focus/Agenda. Applications (some discussion) Benchmarks ( a bit of discussion) Best practices (no discussion) Common interfaces between Belief Revision and Description Logic communities

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Breakout Session on Applications Summary of Discussions

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  1. Breakout Session on ApplicationsSummary of Discussions

  2. Focus/Agenda • Applications (some discussion) • Benchmarks (a bit of discussion) • Best practices (no discussion) • Common interfaces between Belief Revision and Description Logic communities • How the DL community can use the results of BR community

  3. Main Identified Applications • Ontology-Based Data Access • Inconsistency tolerance and repairing • Updating • Data exchange/integration • Changes on the meaning of concepts (e.g., philosophical concepts, definition of things) • Similarity (change detection/versioning) • Traceability, provenance (why something changed the way it did, what BR operations where used)

  4. Wishlist • Iterated Belief Change • Material for case studies, use cases etc • Benchmarks • Workshop to compare efficiency of evolution algorithms (for given “quality guarantees”, e.g., satisfied postulates) • Incentives for efficient, formal, well-studied evolution algorithms

  5. Interaction Between Communities DL Community BR Community Most work done by philosophers, implementations are rare Who cares about implementations? We are interested in the properties of operators, understanding the mental processes behind change • We want tools and implemented stuff • Who cares about postulates? • We want efficient ontology evolution algorithms (pragmatic approach, concrete operations)

  6. Conclusion • BR community should: • Search for users and use cases • Focus on efficiency and implementations (hard?) • Approximate belief change(?) • DL community should: • Avoid ad-hoc or manual solutions for revising ontologies • Try to ground solutions in the solid theoretical frameworks provided by belief revision (don’t reinvent the wheel) • Study the properties of evolution algorithms (through the belief revision framework) • Opportunities for cross-fertilization (bridge the gap)

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