1. April 28, 2004 NASA Taxonomy Development Stitching Together Vocabularies for a Unified Information Architecture Jayne Dutra, Jet Propulsion Laboratory California Institute of Technology Joint Workshop on Multiple Taxonomies April 28, 2004

2. April 28, 2004 2 Life Cycle of Electronic Content in the Real Time Enterprise Site Maps Search Engines NASA Portals Content Integration Networks Finding the right information at the right time to solve the problem at hand Create Content Assets Discover Logical & Intuitive Filters Taxonomy Classify

3. April 28, 2004 3 Taxonomy Basics What is the NASA Taxonomy? A classification scheme meant to encompass all of NASA web content (NASA web space) including internal as well as external material. It is a means for tagging content so it can be used and reused in different contexts.

4. April 28, 2004 4 Project Goals: Enable Knowledge Discovery and Reuse Make it easy for various audiences to find relevant information from NASA programs quickly –Provide easy access for NASA resources found on the Web for reuse – text, data, tools –Provide search results targeted to user interests –Enable the ability to move content through the enterprise to where it is needed most –Improve NASA’s ability to compete and perform through better efficiencies of work processes Comply with E-Government Act of 2002 Be ready to participate in federal XML projects

5. April 28, 2004 5 NASA Taxonomy Best Practices The Long and Winding Road Design process that: –Incorporates existing federal and industry terminology standards like NASA AFS, NASA CMS, FEA BRM, NAICS, and IEEE LOM. –Provides for NASA XML namespace registry (DISA) – it becomes a NASA standard –Complies with metadata standards like Z39.19, ISO 2709, and Dublin Core. Methodology increases interoperability and extensibility It also makes visible the gaps in our IA

6. April 28, 2004 6 IA from the Top Down Using the NASA Taxonomy This is a generic taxonomy from which specializations can be derived for specific purposes –General by design –Not all facets need to be used in each instance –A facet is repeatable –The taxonomy is modular and dynamic Provides a means to map elements from different schema Provides good discrimination of terms with some big buckets

7. April 28, 2004 7 Early Task Objectives Understand current strategies and practices for creating, collecting, and organizing information across NASA. Observe how information is used and organized, the audiences for this information, and the information needs of these audiences. Elicit goals, hopes, and concerns for an information architecture solution. Start building a community of interest.

8. April 28, 2004 8 Audience Uses Vary Widely Better understand the program in total, and obtain scheduling information, project status and best practices. Access procurement rules and examples, and procurement action synopses. Engineering specifications. Scholarly research, competitive intelligence, and general aerospace research. Catalogue science data products after missions Develop educational products, support current products, learn, etc. Topic research and fact finding, topic background research, and downloading curriculum support materials. In the classroom as stand alone items, hands-on learning opportunities, class projects, to expand on a student’s learning potential. Find NASA contact information on services, information about student opportunities, information about career opportunities, and latest educational news. Admin Sci Tech Public

9. April 28, 2004 9 Extend Taxonomy Value Space as Needed Access Requirements Audiences Business Purpose Competencies Content Types Industries Instruments Locations Missions and Projects Organizations Subject Categories Dates Collections http://nasataxonomy.jpl.nasa.govhttp://n NASA Taxonomy Facets (Top Level)

10. April 28, 2004 10 NASA Challenges Extremely distributed information environment –Different legacy systems at each Center No formal approval process at the management level – and many changes in staffing Many different communities –Perhaps need to define large communities and develop ontologies specific to broader knowledge domains Funding is sparse and also distributed

11. April 28, 2004 11 Highly decentralized IT work force Sponsor funded programs and projects drive laboratory –For example, standards for NASA missions may drive technical decisions –Competitive funding model encourages silos –JPL CIO lacks governance over sponsor funded activities Wide “gap” between IT for “Business” and IT for “Missions” –Missions tend to “roll their own” infrastructure –IT staff tends to be local to the project Taxonomy Challenges at JPL Macrocosms and Microcosms

12. April 28, 2004 12 Results of 2003 JPL Information Repositories Study Fragmented and non- interoperable repositories Inefficient and broken processes and applications Parallel and redundant efforts both in building information systems and managing data Limited tools and services that cut across program and line organizations Data Repositories Identified Engineering86 Science8 Business/Admin.28 Infrastructure28 Outreach1 Total157

13. April 28, 2004 13 Information Architecture Gaps No common data model or service architecture to support cross repository search – many distributed systems Difficulty in getting visibility and senior management champions Difficulty in getting resources to address the issues Difficulty in getting IT funding centralized and strategically planned – CIO Office

14. April 28, 2004 14 Partnership with EA and CIO Governance (or Enterprise Architecture Management) –Enterprise Architecture Working Group –Principles, Guidelines and Portfolio Management –Common Methodologies to System Development Enterprise Information Architecture –Management of information across JPL information systems –Support development of an interoperable information infrastructure Project Architects –Funded by CIO, assigned project roles –Architecture alignment: principles and common infrastructure (data, technology, services and process)

15. April 28, 2004 15 Semantic Frameworks and Data Architecture JPL Data architects have more visibility and support than the Library So Why Are They Interested in Taxonomies? Data dictionaries are too narrow to interoperate Data architects are seeking “data harmonization” Semantic frameworks allow for mappings of data elements to larger vocabularies –Thesauri capability needed Zachman is helpful in defining roles

16. April 28, 2004 16 Current Status of “JPL Core” Metadata Core spec for project documents now proposed – test, validation, etc. Effort originally related to Records Retention requirements Still too technology specific (Docushare) Open Issues: –Identifying document types that work for users –JPL specific processes call for JPL specific vocabularies: need a JPL taxonomy –Retention not based solely on document type Atomic vocabulary components that are combined to determine retention schedules –Balance between enough tags to describe an object usefully and the amount of tags someone will actually fill out

17. April 28, 2004 17 Most Recent Work: Integrating Engineering Repositories Reuse work from taxonomy and information architecture tasks Identification of engineering repositories and technologies Engineering content tagged with topic, repository, product or discipline semantic markers Integration of content based on semantic properties Utilizes Web Services infrastructure and RDF to make content portable (Seamark tool) Goal: Embed content into mission development processes Content Integration Networks

18. April 28, 2004 18 Status of NASA Taxonomy CIO Board approval –Define review and approval process –Facilitate review and approval process Deliver metadata specification Formalize taxonomy as XML schema Delegate taxonomy stewardship –Within NASA CIO Office Plan follow-on work –Various implementations in NASA Web apps

19. April 28, 2004 19 Wrap Up and Discussion Thank you for your time! White Paper on Content Integration Networks for NASA Dutra, Xiao, 2/4/2004 https://pub-lib.jpl.nasa.gov/pub- lib/dscgi/ds.py/Get/File- 118/Content_Integration_Networks_WP_02 _11_04.doc

20. April 28, 2004 20 NASA taxonomy Back Up Slides

21. April 28, 2004 21 Selected and Built Test Collection CollectionSource URL No of Docs Lessons Learned Lessons Learned Databasehttp://llis.nasa.gov1,370 NTRSNTRS (NASA Technical Report Server)http://ntrs.nasa.gov213,900 SIRTFSIRTF (Space Infrared Telescope Facility) Project Library http://sirtifweb.jpl.n asa.gov4,054 James Webb Space Telescope (JWST) Project DocumentsWebb http://ngst.gsfc.nasa.gov/doclist/bytitle.ht ml634

22. April 28, 2004 22 NASA Taxonomy in Action Taxonomy Demo http://tb1.siderean.com:7880/test/test2query3.jsp Logon: NASA Password: facets –Hosted by Siderean www.siderean.com with Seamark softwarewww.siderean.com

23. April 28, 2004 23 Goals of Enterprise Data Management 1.Develop/acquire reusable data management infrastructure, tools and technologies to support information management 2.Capture system data definitions and models 3.Capture system data object formats 4.Support definition of local system architecture and relationship to lab-wide information architecture 5.Define lab-wide data standards for information capture and dissemination 6.Develop mappings between common and local data models 7.Update JPL software lifecycle to reference standards adoption 8.Define/develop standard interfaces to data systems

24. April 28, 2004 24 The Enterprise Framework (John Zachman)

25. April 28, 2004 25 The Enterprise Framework (John Zachman) Taxonomies and metadata make up the semantic model that informs data models and other IT infrastructure components.