1. Creating, Maintaining, and Integrating Understandable Knowledge Bases
Deborah L. McGuinness
Associate Director and Senior Research Scientist
Knowledge Systems Laboratory
Stanford University
Stanford, CA 94305
Joint work with
Steve Wilder Jessica Jenkins Honglei Zeng Zhou Qing Gleb Frank

2. Research Directions (Formation and Evolution)
Analysis of KBs
Deducible contradictions
Possible contradictions
Incomplete specifications
Potential modeling issues
Merging KBs
Special Purpose Representation & Reasoning
Defaults
Part-Whole
Explanation
Structural Similarities/Differences
Hybrid Reasoning Environments
Disjointness exploitation
Object Markup(in coordination with DAML) for
Object presentation (salient features)
More effective usage

3. Chimaera – A Merging and Diagnostic Ontology Environment
Web-based tool utilizing the KSL Ontolingua platform that supports:
merging multiple ontologies found in distributed environments
analysis of single or multiple ontologies
attention focus in problematic areas
simple browsing and mixed initiative editing

4. Our KB Analysis Task Review KBs that:
Are developed using differing standards
May be syntactically but not semantically validated
May use differing modeling representations
May have different purposes
May be incomplete
Produce KB logs (in interactive environments)
Identify provable problems
Suggest possible problems in style and/or modeling
Are extensible by being user programmable

7. Integration Interactively impact agenda
Analysis of glycolysis on sabina’s input for example
Synonym list suggestions
Update “must” or “should” or possible portions of agenda
Disjointness options
Explain suggestions
Present results of modifications (with explanations)
Batch mode analysis

8. How KB Merging Tools Can Help
Combine input KBs with name clashes
Treat each input KB as a separate name space
Support merging of classes and relations
Replace all occurrences by the merged class or relation
Test for logical consistency of merge (e.g. instances/subclasses of multiple disjoint classes)
Actively look for inconsistent extensions
Match vocabulary (using syntax and semantics)
Find name clashes, subsumed names, synonyms, acronyms, structural similarity, necessary and sufficient conditions for subsumption, etc.
Focus attention
Portions of KB where new relationships are likely to be needed
E.g., sibling subclasses from multiple input KBs
Derive relationships among classes and relations
Disjointness, equivalence, subsumption, inconsistency, ...

11. Chimaera I Usage
HPKB program – analyze diverse KBs, support KR novices as well as experts
Cleaning semi-automatically generated simple KBs
Browsing and merging multiple controlled vocabularies (e.g., internal vocabularies and UN/SPSC (std products and services codes))
Reviewing internal vocabularies (VerticalNet, Cisco)

12. Status / Directions
Chimaera provides merging and diagnostic support for ontologies in many formats
It can be used offline in batch mode or interactively as an integrated browser/editor
It is becoming extensible with rule language
It improves merging performance over existing tools
It has been used by people of various training backgrounds in government and commercial applications and is available for use.
Will be able to explain its suggestions
Support collaborative development
Handling deeper representations
-movie, tutorial, papers(KR2000, AAAI2000, ICCS 2000), link to live system, etc.
Ontologies are becoming more central to applications, they are larger, more distributed, and longer-lived
Environmental support (in particular merging and diagnostic support) is more critical for the broader user base

13. Extras

14. Motivation: Ontology Integration Trends
Integrated in most search applications (Yahoo, Lycos, Xift, …)
Core component of E-Commerce applications (Amazon, eBay, Virtual Vineyards, REI, VerticalNet, CommerceOne, etc.)
Integrated in configuration applications (Dell, PROSE, etc.)

15. Motivation: Ontology Evolution
Controlled vocabularies abound (SIC-codes, UN/SPSC, RosettaNet, OpenDirectory,…)
Distributed ownership/maintenance
Larger scale (Open Directory >23.5K editors, ~250K categories, 1.65M sites)
Becoming more complicated - Moving to classes and slots (and value restrictions, enumerated sets, cardinality)

16. The Need For KB Merging
Large-scale knowledge repositories will contain KBs produced by multiple authors in multiple settings
KBs for applications will be built by assembling and extending multiple modular KBs from repositories
KBs developed by multiple authors will frequently
Express overlapping knowledge in a common domain
Use differing representations and vocabularies
For such KBs to be used together as building blocks -
Their representational differences must be reconciled

17. The KB Merging Task Combine KBs that:
Were developed independently (by multiple authors)
Express overlapping knowledge in a common domain
Use differing representations and vocabularies
Produce merged KB with
Non-redundant
Coherent
Unified
vocabulary, content, and representation

19. Merging Tools Merging can be arbitrarily difficult
KBs can differ in basic representational design
May require extensive negotiation among authors
Tools can significantly accelerate major steps
KB merging using conventional editing tools is
Difficult Labor intensive Error prone
Hypothesis: tools specifically designed to support KB merging can significantly
Speed up the merging process
Make broader user set productive
Improve the quality of the resulting KB