1. A Standard & Prototype Starting Point for An Open Ontology Repository: The Extended Metadata Registry Project John L. McCarthy XMDR Project Lawrence Berkeley National Laboratory Open Ontology Repository (OOR) Panel on Rationale, Expectations & Requirements March 27, 2008

2. page 2 of 15 XMDR Open Ontology Talk-v5.ppt Shared Goals & Challenges Open Ontology Repository Goals –collection of useful ontologies –help facilitate harmonization & synergy –standard representation/characterization? Extended Metadata Registry (XMDR) Project Goals –extend ISO-IEC 11179 ed. 2 Metadata Registry Standard for increasingly large & complex databases & software systems particularly for large organizations like EPA, NCI, DOD, … –incorporate & manage evolution of concept information codesets of valid values, terminologies, thesauri, ontologies using a shared metamodel for both metadata & concepts

3. page 3 of 15 XMDR Open Ontology Talk-v5.ppt XMDR Project Overview & Background Set of collaborative initiatives with shared goals & funding –EPA, NCI, DOD, LBNL, USGS, Ecoterm, UNEP, … (major 11179 users) XMDR project at LBNL began in 2003 principals have been meeting in Berkeley since 2004 –ISO-IEC JTC1/SC32/WG2 & ANSI L8 working on 11179 ed. 3 Joint Technical Committee 1, Subcommittee 32, Working Group 2 metadata registry standards work began in 1980’s re data dictionaries & codesets Open source reference implementation & testbed system –test implementations of proposed extensions to 11179 metamodel add more formal semantic metadata on concepts & relationships to data –assemble semantic metadata from diverse sources & structures terminologies, ontologies, etc. for environment, geography, health, … –explore emerging semantic technologies (e.g., RDF, OWL, CL, …) –demonstrate new capabilities e.g., ontology lifecycle management & harmonization

4. page 4 of 15 XMDR Open Ontology Talk-v5.ppt Challenge: Gain Common Understanding of meaning between Data Creators and Data Users UsersInformation SystemsData Creation Users EEA USGS DoD EPA environ agriculture climate human health industry tourism soil water air 123 345 445 670 248 591 308 123 345 445 670 248 591 308 3268 0825 1348 5038 2708 0000 2178 3268 0825 1348 5038 2708 0000 2178 textdata environ agriculture climate human health industry tourism soil water air 123 345 445 670 248 591 308 123 345 445 670 248 591 308 3268 0825 1348 5038 2708 0000 2178 3268 0825 1348 5038 2708 0000 2178 text ambiente agricultura tiempo salud hunano industria turismo tierra agua aero 123 345 445 670 248 591 308 123 345 445 670 248 591 308 3268 0825 1348 5038 2708 0000 2178 3268 0825 1348 5038 2708 0000 2178 textdata environ agriculture climate human health industry tourism soil water air 123 345 445 670 248 591 308 123 345 445 670 248 591 308 3268 0825 1348 5038 2708 0000 2178 3268 0825 1348 5038 2708 0000 2178 textdata Others... ambiente agricultura tiempo salud huno industria turismo tierra agua aero 123 345 445 670 248 591 308 123 345 445 670 248 591 308 3268 0825 1348 5038 3268 0825 1348 5038 2708 0000 2178 textdata Common interpretation of what data represents

5. page 5 of 15 XMDR Open Ontology Talk-v5.ppt Inference requires combination of Data, Metadata & Concept Systems IDDateTempHg A06-09-134.44 B06-09-139.32 X06-09-136.778 NameDatatypeDefinitionUnits IDtext Monitoring Station Identifiernot applicable DatedateDateyy-mm-dd Tempnumber Temperature (to 0.1 degree C) degrees Celcius Hgnumber Mercury contamination micrograms per liter Inference Search Query: “find water bodies downstream from Fletcher Creek where chemical contamination was over 10 micrograms per liter between December 2001 and March 2003” Data: Metadata: BiologicalRadioactive Contamination leadcadmium mercury Chemical Concept System (multi-lingual):

6. page 6 of 15 XMDR Open Ontology Talk-v5.ppt XMDR Goals (continued) Improve representation of relationships between data (e.g., data elements & value domains) and concept structures (e.g., ontologies, taxonomies, thesauri, terminologies, …) Register & manage complex semantic metadata (i.e., concepts) in more formal, systematic ways (e.g., description logic) to facilitate machine processing of semantics in order to –link together data elements & terms across multiple systems –discover relationships among data elements, terms & concepts –create and manage names, definitions, terms, etc. –support software inference, aggregation, and agent services Add more rigorous & formal specification for –concepts and concept systems (including ontologies) –relationships between metamodel components –formal axioms for conceptual & structural relationships Use concepts to unify different types of metadata –evolution requires increasing granularity & details –combine strengths of data dictionaries/registries and ontologies

7. page 7 of 15 XMDR Open Ontology Talk-v5.ppt Example concept system content currently loaded in XMDR Prototype via Lexgrid (from Mayo Clinic & Harold Solbrig) GEMET 2001.0 Multilingual Environmental Thesaurus National Biological Information Infrastructure biodiversity NCI Thesaurus_06.02d health concepts system ISO4217_1981 currency codes ISO3166_V-10 country codes (only 2 letter codes) Mouse_1.32 anatomy Defense Technology Information Center 1.0 Thesaurus Portions of EPA controlled vocabulary SIC and NAICS industrial classification codes via special purpose scripts Omega ontology

8. page 8 of 15 XMDR Open Ontology Talk-v5.ppt Additional candidate metadata content to test 11179 metamodel expressivity Current 11179 Data Element Registries caDSR (full NCI Cancer Data Standards Registry) EDR (EPA Environmental Data Registry) Candidate Additions to Concept Systems and Ontologies NASA SWEET (Semantic Web Earth & Environmental Terminologies) IETF RFC 3066 Language Codes USGS Geographic Names Information System Getty Thesaurus of Geographic Names I.T.I.S. - Integrated Taxonomic Information System Foundational Model of Anatomy EPA Chemical Substance Registry GO (Gene Ontology), ….Agrovoc, …and possibly others OMV Ontology Metadata Vocabulary (European NeON consortium & Stanford NCBO)

9. page 9 of 15 XMDR Open Ontology Talk-v5.ppt Omega Ontology illustrates challenges of loading large, complex new content Omega is a “terminological ontology” reorganization & synthesis of WordNet & Mikrokosmos adds higher level ontology to organize multiple ontologies Initial mapping and loading of Omega needs to be refined Multiple ontology languages present an additional challenge Entity relationships conform to Concept_System figure Entity ->Attribute conforms to Classification_Scheme figure Omega Attributes mapped to ISO/IEC11179 ed3 Facets (ignoring Omega datatype field) Required a week to process and load Omega Ontology 4 million files, so ~250,000/24 hrs

10. page 10 of 15 XMDR Open Ontology Talk-v5.ppt XMDR Prototype Modular Architecture: with current open source software selections Registry Store (Subversion) Search & Inference Queries (Jena, SPARQL) XMDR metamodel (OWL & xml schema) Full Text Index XMDR Prototype Architecture REST Style standard XMDR files Asserted LogicIndex Inferred LogicIndex Content Loading & Transformation (Lexgrid & custom) Human User Interface (XML pages & javascript) Metadata Sources concept systems, data elements USERS Web Browsers…..Client Software Application Program Interface (REST) Authentication Service Validation (XML Schema) Mapping Engine Reasoner (Pellet) Text Search (Lucene) Metamodel specs (UML & Editing) (Poseidon, Protege) XMDR data model & exchange format XML, RDF, OWL

11. page 11 of 15 XMDR Open Ontology Talk-v5.ppt DRAFT 11179 – ed. 3 metamodel Consolidated Class Hierarchy see xmdr.org wiki for more diagrams and details

12. page 12 of 15 XMDR Open Ontology Talk-v5.ppt http://xmdr.org/ XMDR Prototype Web Site has downloadable code & content

13. page 13 of 15 XMDR Open Ontology Talk-v5.ppt Technical Challenges and Issues for XMDR Implementation Testbed Complexity –representation of different types of relationships –non-binary relationships -- e.g., instrumentality (A used to do B to C) –extensibility for unknown future complexities (e.g., Omega)? –incorporate IKL variant of CLIF dialect of ISO Common Logic? Scalability & performance –currently includes tens of thousands of objects & millions of RDF triples –maybe indexing and/or distributed registries will help? External metadata sources, ontologies, terminologies –cannot simply be copied because they are proprietary & evolving Mapping (to data elements as well as between e.g. between concept systems) –wide variety of challeges (e.g., probabilistic & changing mappings) Manage evolving metamodel, concept systems & mappings –additions & changes in both content & structure over time, versioning Harmonize with ODM, MMF, CL, OMV, Web Services –need open source, standards-based approach (vs. proprietary)

14. page 14 of 15 XMDR Open Ontology Talk-v5.ppt Conclusion: Why should OOR & XMDR projects consider closer collaboration? Potential benefits for OOR Project… –modular, extensible, open source code base –initial set of ontologies & other concept systems –major collaborators (EPA, NCI, DOD, EEA, …) –real-world ontology applications –ISO/IEC standards-based approach –proven 11179 administrative metadata & procedures for managing stewardship & evolution of individual items –extensive & extensible OOR metamodel Potential benefits for the XMDR Project –ontology experts, experience and ideas (e.g., Natasha re OMV) –more ontologies to exercise expressivity & tools –help in refining ontology representation & mapping

15. page 15 of 15 XMDR Open Ontology Talk-v5.ppt Thanks & Acknowledgements Bruce Bargmeyer, principal investigator Frank Olken, initial concepts & metamodel extensions Kevin Keck, initial & current designer & implementor Karlo Berkett, implementation, user interface, data loading Harold Solbrig, Lexgrid, model development, etc! Fred Gey, concept mapping, etc. L8 and SC 32/WG 2 Standards Committees Major XMDR Project Sponsors and Collaborators –National Science Foundation (Grant #0637122) –U.S. Environmental Protection Agency –Department of Defense –National Cancer Institute –U.S. Geological Survey –And others!