1. 1 Introduction to the caDSR Presented to HL7 Vocab SIG January 24, 2005 Denise Warzel National Cancer Institute, Center for Bioinformatics caDSR Project Officer, Software Development

2. D. Warzel2 Presentation Outline caCORE Overview ISO/IEC 11179 Overview caDSR Implementation and tooling

3. D. Warzel3 caCORE Components Enterprise Vocabulary Data Standards Bioinformatics Objects caCORE is the open-source foundation upon which the NCICB builds its research information management systems

4. D. Warzel4 caCORE Infrastructure wiring Vocabulary for CDE specification Dictionary, thesaurus services Domain object metadata Common data elements Public APIs Common data elements (CDEs)

5. D. Warzel5 Presentation Outline caCORE Overview ISO/IEC 11179 OverviewISO/IEC 11179 Overview caDSR Implementation and tooling

6. D. Warzel6 Terms and Definitions for ISO/IEC 11179 Administered Item: A registry item for which administrative information is recorded in an Administration Record Data Element: A unit of data for which the definition, identification, representation, and permissible values are specified by means of a set of attributes. Data Element Concept: An idea that can be represented in the form of a data element, described independently of any particular representation. Value Domain: A set of attributes describing representational characteristics of instance data with or without enumerated permissible values. Data Element: A unit of data for which the definition, identification, representation, and permissible values are specified by means of a set of attributes. Data Element Concept: An idea that can be represented in the form of a data element, described independently of any particular representation. Value Domain: A set of attributes describing representational Characteristics of instance data with or without permissible values. Value Meaning: A member of the set of finite allowed inventory of notions that can be categorized for a conceptual domain. Permissible Value: An expression of a value meaning in a specific value domain Representation Class: A classification of data elements based upon the type of representational form. Conceptual Domain: A set of possible value meanings of a data element expressed without representation. Data Element Representation: The part of a data element having A value domain, datatype,and other representational specifications.

7. D. Warzel7 ISO/IEC 11179 Parts 1-6: Information technology – Specification and Standardization of data elements –A metamodel for ‘data element’ metadata –Standard by which to convey semantic, syntactic and lexical meaning Human and machine understandable Unambiguous What is ISO/IEC 11179?

8. D. Warzel8 ISO/IEC 11179 Information technology Standard ISO/IEC 11179 Part 1: Framework for the specification and standardization of data elements ISO/IEC 11179 Part 2: Classification for data elements ISO/IEC 11179 Part 3: Registry metamodel and basic attributes ISO/IEC 11179 Part 4: Rules and Guidelines for the Formulation of Data Elements ISO/IEC 11179 Part 5: Naming and Identification Principles for Data Elements ISO/IEC 11179 Part 6: Registration of data elements

9. D. Warzel9 Basic Metamodel Components Conceptual_Domain Data_Element_Concept 1..1 0..* +specifying 1..1 +having 0..* data_element_concept_conceptual_domain_relationship Data_Element 0..* 1..1 +providing_representation_to 0..* +represented_by 1..1 expression Value_Domain 0..* 1..1 +represented_with 0..* +providing_representation_for 1..1 representation 0..* 1..1 +representing 0..* +specified_by 1..1 specification Data Element ConceptConceptual Domain Data Element Value Domain Perception Representation

10. D. Warzel10 “What is this datum?” –Provides concrete guidance on the creation and maintenance of discrete data element attributes and metadata (semantics) enabling the formulation of data elements in a consistent, standard manner – “Metadata Repository/Registry” –Framework for Data element standardization and registration allow the creation of a shared data environment in much less time and with much less effort than it takes for conventional data management methodologies. Adoption of 1179 Allowed us to “Get on with it”Adoption of 1179 Allowed us to “Get on with it” Why ISO/IEC 11179?

11. D. Warzel11 ISO/IEC 11179 Administered Items Derivation_Rule

12. D. Warzel12 ISO/IEC Administered Item Administration Record and Common Attributes Unique Identifier Administrative Status Registration Status Creation Date Administrative Note(s) Effective Date Change Date(s) Change Description(s) Origin Until Date Created By Modified By Name(s) Definition(s) Stewardship Information Submitter Information Reference Document(s) Classifications

13. D. Warzel13 ISO/IEC 11179 NCICB Extensions Derivation_Rule The Concept Class Provides Semantic Linkage Form Concept Class

14. D. Warzel14 NCICB Concept Class Common Attributes Concept Class Administered Item attributes + Concept Unique Identifier Pointer to an externally defined concept Concept Definition Source Names the source terminology/ontology/vocabulary Concept Relationship Semantic Order of the concepts NOTE: ISO describes a ‘Concept Relationship’ as a semantic link among two or more concepts. There is a subtlety in our implementation. In caDSR use the concept relationships as more of a derivation rule, naming the order of the concepts - not semantic relationships in an ontologic or object model sense of ‘relationship’. Object Class, Property, Representation term, Qualifier terms, Value Domains

15. D. Warzel15 Why vocabularies/ontology important? Goal: “Semantically unambiguous, interoperability” Data Element curators are not necessarily vocabulary experts NCI had a terminology and vocabulary services group: EVS Semantic integration is achieved by tying Standard vocabulary identifier codes to the caDSR metadata The ISO 11179 provides the framework – we were looking for something that could be computed without a human having to read and interpret definitions By abstracting the curation of concepts in caDSR and instead relying on external vocabularies

16. D. Warzel16 EVS and caDSR Distinctions caDSR is a metadata repository –maintains metadata to permit a user to locate the correct data element defining the characteristics of a piece of datum, an instance of a specific concept, in sufficient detail to be collected and stored on a computer EVS is a terminology server –provides services for synonymy, mapping between vocabularies, hierarchical structures, Subconcepts, Superconcepts, Roles, Semantic type, etc.

17. D. Warzel17 Presentation Outline caCORE Overview ISO/IEC 11179 Overview caDSR Implementation and toolingcaDSR Implementation and tooling

18. D. Warzel18 caDSR Overview NCI Data Element Metadata repository and registry Based on the ISO/IEC 11179 Designed to integrate caCORE infrastructure Supports the development and deployment of Data Elements that are used as metadata descriptors, primarily for NCI-sponsored research, with an ever widening girth of end users Available as an open-source download

19. D. Warzel19 caDSR Tools Goals of caDSR Tools development: –Simplify development and creation of ISO/IEC 11179 compliant metadata by Data Element Curators and UML Modelers –Simplify consumption of Data Elements by end users and application developers –Enhance reuse of Data Elements for all –Enable semantic consistency across research domains –Support metadata life-cycle and governance processes

20. D. Warzel20 caDSR Home Page Curators DevelopersGeneral

21. D. Warzel21 Introduction to caDSR Tools –CDE Browser to Search for and Download –Form Builder to Create user specified collections of CDEs –CDE Curation Tool to Create Data Elements –Admin Tool to Curate and Administer caDSR - “Power Users” –Batch Load to import Administered Items Excel Loader (MS Excel) UML Loader (XMI) Case Report Form Loader (MS Excel) –Sentinel Tool (3.0) Generates end user ‘Alerts’ triggered by metadata changes Access, Develop, Manage, Consume

22. D. Warzel22 View, Search, Download –Shopping cart feature FormBuilder to Build / Download Forms and Data Elements “Context Browsing” Tree –By Classification Schemes –By Forms CDE Basic Search Criteria –Google-like search –Sortable search results by clicking on column headings CDE Browser “CONTEXT Browsing” “CONTEXT Browsing” Basic Search

23. D. Warzel23 Advanced Search Criteria –Leverages ISO attributes Find all with “18254-3” permissible value Find all with “Gene*” Find all with “Released” workflow status Find all with “Standard” Registration status Etc. CDE Browser Advanced Search

24. D. Warzel24 Form Builder Create and Manage Forms –Organize CDEs into modules within a Form –Attach pdf or word format –Classify Forms into groupings for specific end user communities –“Publish” “Un-Publish” for Browser Catalog visibility “Printer Friendly” version Download CDEs

25. D. Warzel25 To Create, Edit or Version: Data Element Concepts Value Domains Data Elements ISO 11179 Wizard –Construct ISO compliant Data Elements by building up the pieces Builds Names and Definitions from underlying components. “Get Associated” –Leverage ISO to retrieve related CDEs “Block Edit” “shopping cart” Assign classification schemes Versioning Curation Tool

26. D. Warzel26 Administration Tool System Administration User Accounts and Security Lists of Values (LOVs) used in content creation Create “Framework”: Conceptual Domains Classification Schemes (basis for organizing CDEs in Browser) Protocols

27. D. Warzel27 Sentinel Tool Create “Alerts” –User defined triggers based on data element metadata attributes –“notify me of any change to the Value Domain for any CDE on the Adverse Event Form Generates and emails a report of changes matching “Alert” criteria

28. D. Warzel28 Batch Loading Excel Loaders –Formatted MS Worksheet Administered Item Form UML Loader –XMI representation of a UML Class Diagram Class  Object Class Attribute  Property Data Element Concept, Value Domain and Data Element derived from the above

29. D. Warzel29 CDE Side-by-Side Compare –Build shopping cart, compare CDE metadata side by side –Download to excel spreadsheet

30. D. Warzel30 Current User Base Cancer Biomedical Informatics Grid (caBIG) – 820/466 * Center for Cancer Research (CCR) – 821/573 Clinical Data Interchange Standard Consortium (CDISC) - 3/0 Center for Cancer Imaging (CIP) - 238/151 Cancer Therapy Evaluation Program (CTEP) – 8027/2410 Division of Cancer Prevention (DCP) – 427/321 National Heart Lung and Blood Institute (NHLBI) – 0/0 Early Detection Research Network (EDRN) – 121/1 Divisions of Population Sciences and Cancer Control (PS & CC) 85/9 Specialized Programs of Research Excellence (SPOREs) – 719/197 Cancer Ontologic Research Environment (caCORE) – 1028/810 * Total CDEs/”Released” CDEs

31. D. Warzel31 Exploring National Institute of Neurological and Disorders and Syndromes (NINDS) National Icelandic Center for Oncology Cancergrid – UK

32. D. Warzel32 Operating Environments Database Repository –Oracle 98i Administration Tool –Oracle PL/SQL, Oracle 9i Application Server CDE Browser –Java, Oracle 9i Application Server CDE Curation Tool –Jakarta Tomcat

33. D. Warzel33 Contact Information caDSR Home Page –http://ncicb.nci.nih.gov/core/caDSR caDSR Training Home Page –http://ncicb.nci.nih.gov/NCICB/core/caDSR/Tr aining caDSR Training ListServe –caDSR_Training-L@list.nih.gov

34. D. Warzel34 Documentation/Recommended Reading Materials caDSR Homepage: –http://ncicb.nci.nih.gov/core/caDSR caCORE User Application Manual: –ftp://ftp1.nci.nih.gov/pub/cacore/NCICBapplications/NCICBAppManual.pdf caCORE Technical Guide: –ftp://ftp1.nci.nih.gov/pub/cacore/caCORE2.0_Tech_Guide.pdf – caDSR APIs caDSR API Guide: –ftp://ftp1.nci.nih.gov/pub/cacore/caDSR/caCORE2.0_caDSR_API.pdf caDSR Business Rules –http://ncicb.nci.nih.gov/NCICB/core/caDSR/BusinessRules caDSR Content Meetings –http://ncicb.nci.nih.gov/NCICB/core/caDSR/Content caDSR_Users List serv subscribe: –http://list.nih.gov –Send Request for caDSR Account to: ncicb@pop.nci.nih.gov

35. D. Warzel35 caDSR Tools Team NCICB –Peter Covitz –Denise Warzel ScenPro –Bill McCurry –Tom Phillips –Robert Harding – Jennifer Brush –Larry Hebel –Smita Hastak Oracle –Edmond Mulaire –Ram Chilukuri –Prerna Aggarwal –Dan Ladino –Christophe Ludet –Shaji Kakkodi –Jane Jiang SAIC –Kathleen Gundry –Tommie Curtis –Brenda Maeske