1. Terminology Metadata Salvatore Mungal Duke University Extension of the Service Meta Model Faro, Portugal, 16 th November 2008

2. 2 Agenda ●Background ●Review Proposed Model ●Next Steps ●Question/Discussion

3. 3 Team Members ●Brian Davis (3rd Millennium) ●Frank Hartel (NCI) ●Tom Johnson (Mayo) ●George Komatsoulis (NCI) ●Hua Min (Fox Chase) ●Sal Mungal (Duke) ●Scott Oster (OSU) ●Mike Riben (MD Anderson) ●Denise Warzel (NCI)

4. 4 Background - caBIG TM Background - caBIG TM : –The cancer Biomedical Informatics Grid (caBIG TM ) is an information technology program that develops software tools to support cancer research efforts by establishing a common infrastructure that can be used to share data and applications across organizations. –Interoperability is a key factor in caBIG’s infrastructure and is very dependent on terminologies.

5. 5 Background - caBIG TM Background – caBIG TM /Metadata: –The growing demand for service-oriented access to terminologies in the caBIG community is anticipated to result in increased publication of respective services on caGrid. –Efficient discovery, administration and query of these resources require definition and use of consistent and reliable metadata from the cancer Data Standards Repository (caDSR) that can be queried at the service level.

6. 6 Background - Goals Goals: –Identify metadata queryable at the index service level –Narrow focus for first model revision… discoveryInitial model defined to satisfy discovery use cases Support development of enhanced grid discovery client Resolve runtime services for terminologies of interest Additional metadata available through runtime services –Allow/anticipate future expansion

7. 7 Background – Use Cases Use Case Collection –Identification –Internationalization –Intended/Allowed Usage –Provenance –Administration

8. 8 Background - Use Cases Samples –Browsing Ontologies –Viewing Differences –Administering the NCBO Ontology Library –Web of Trust

9. 9 (1) Browsing An ontology developer is interested in creating an ontology for a domain (e.g., radiographic anatomy). –Determine if there are already similar ontologies in that domain. –Evaluates assigned categories for registered ontologies. –Discovers match for “anatomy” If there is a match: –Views available titles and descriptions –Finds listings for “human” and “mouse” anatomy, but not “radiology” –Looks at the human anatomy ontology to see if it fits the need  Attributes: category, title (preferred Name), description Background - Use Cases

10. 10 (2) Viewing Differences An ontology developer wants to view what has changed between two versions of an ontology. –Retrieve listing of registered terminology services –Sort by URI, then version –Select and resolve grid services for differing versions –Invokes runtime services to resolve and compare content  Attributes: uri (id), version Background - Use Cases

11. 11 (3) Discovery A user wants to contact the providers for new ontologies registered within the last quarter. –Query registered ontologies by registration date –Pull point of contact information (source, curator, registration authority) from listed items  Attributes: registration date, registration authority, source, curator Background - Use Cases

12. 12 (4) Web of Trust Quality of ontologies: –User is aware that there are several anatomy ontologies, and is unclear which to use. –Trusts certain ontology sources (anatomists) more than others –Views ontology source to determine content origin –Views intended and example use to consider alignment with application –Considers caBIG certification level  Attributes: source, intended use, example use, certification level Background - Use Cases

13. 13 Background – Model Focus of work on … –Model alignment External … Incorporate feedback from review and alignment with relevant specifications and standards. Internal … Take better advantage of previously registered models and classes. –Incorporating specific feedback on model classes and attributes.

14. 14 Background - Alignment Specifications/standards considered … –Dublin Core –ISO 11179-2/3/6: classification, registries, admin –LexGrid/LexBIG model –National Center for Biomedical Ontology (NCBO) BioPortal –Public Health Information Network (CDC/PHIN) –Simple Knowledge Organization System (SKOS core) –UMLS Rich Release Format (RRF) –CTS/CTS2

15. 15 Background – Model Alignment

16. 16 Background – Model Alignment

17. 17 Background – Model Alignment Findings … –No silver bullet –General alignment for defined items All SWG items and definitions represented conceptually in one or more specifications Adequate, but not perfect, alignment of semantics Some name changes –Some new attributes identified Supplement existing use case Generally not found to be required unless we add use cases

18. 18 Model - Overview

19. 19 Model - AdministeredComponent ●Administered Component - a common superclass based on the ISO 11179 standard providing typical attributes relevant to any component registered and maintained on the grid (e.g. id, preferredName, preferredDefinition)

20. 20 Model – Core Identification & Description ●localName (1..n) –Name used to refer to the terminology within a localized context; often a mnemonic. –ICD-9-CM, ICD-9 ●category (0..n) –Applicable domains or scientific fields. –e.g. anatomy, genomic, proteomic, phenotype…

21. 21 ●type (0..1) –Nature of content relative to the category. –application – describes domain in an application dependent manner –core – describes domain in an application independent manner –domain – describes the most important concepts in a domain –task – describes generic types of tasks or activities (e.g. selling, selecting) –upperLevel – describes general, domain independent concepts (e.g. space, time) ●structure (1) –Indicates complexity of maintained relationships –flat – no hierarchy –simple - supports a single inheritance mono- hierarchical structure. –complex - supports multiple relationships and/or relationship types Model – Core Identification & Description

22. 22 ●defaultLanguage (1) –Language for text unless otherwise specified –eng ●supportedLanguage (1..n) –Languages supported for text-based content –eng, spa, … ●supportedContentType (1..n) –Supported type of text or imbedded multimedia –e.g. mime type (text/plain, image) ●keyword (0..n) –Words or phrases of special significance. –patient record, nursing protocol, … Model – Core Identification & Description

23. 23 Model - Usage ●intendedUse (0..n) –Human-readable description of intended use. –data integration ●exampleUse (0..n) –Human-readable example of use. –Integration of protein data. ●isRestricted (1) –Indication of intellectual property boundaries. –true ●rights (0..n) –Human-readable description of IP rights. –NCI Thesaurus terms of use …

24. 24 Model - Provenance ●releaseDate (0..1) –Date of availability in released format. –2007-08-30 ●releaseFormat (0..1) –Format as released by the curator. –e.g. OWL, OBO, RRF source (0..1) –Origin or provider of content –National Center for Health Statistics (NCHS) ●releaseLocation (0..1) –Location of resource in the releaseFormat. –ftp://ftp1.nci.nih.gov/pub/cacore/EVS/NCI_ Thesaurus/Thesaurus_07.12a.OWL.zip ●releaseVersion (0..1) –Represented version identifier. –2007

25. 25 Model - Certification ●type –e.g. Good housekeeping or caBIG’s level of compliance ●value –e.g. Gold seal of approval or caBIG’s bronze, silver, gold

26. 26 Model - ReleasePackage ●name –meta distribution containing the terminology as released. eg. UMLS ●version –identifier of the composite ontology or meta distribution containing the terminology as released. eg. 2007AB

27. 27 Model - Contact ●A common class used to maintain contact information (e.g. name, address, phone) as defined by the ISO 11179 standard

28. 28 Model – Anticipated Alignment against available classes Superclasses Based on 11179

29. 29 Next Steps ●Currently, model harmonization with recommended superclasses is complete but additional changes are anticipated in the registration process using caBIG TM tools ●Change caGRID tooling to capture additional metadata when registering terminology ●Create custom discovery client for terminology services, to take advantage of additional metadata in support of the identified use cases

30. 30 Questions/Discussion ●Links: –https://cabig.nci.nih.gov/ –http://gforge.nci.nih.gov/projects/termeta –http://cdebrowser.nci.nih.gov/CDEBrowser/ICB/i nfrastructure/cacore_overview/cadsr –salvatore.mungal@duke.edu