Technology Infusion Working Group Co-Chairs: Karen Moe, NASA/ESTO Chris Lynnes, NASA/GSFC

1. Technology Infusion Working Group Co-Chairs: Karen Moe, NASA/ESTO Chris Lynnes, NASA/GSFC Earth Science Data Systems Working Group Meeting October 21-23, 2008 Philadelphia, PA

2. Agenda • Mission & Scope • Summary of Activities & Accomplishments • Interoperability Readiness Levels • Process & Strategies • Services Orchestration and Interoperability • Semantic Web • Sensor Web • Data Stewardship • ESIP & AGU • Breakout Session Agenda

3. Tech Infusion Working Group • Mission • Enable NASA’s Earth Science community to reach its research, application, and education goals more quickly and cost effectively through widespread adoption of key emerging information technologies • Scope • Information technologies that... • Provide capabilities critical to the ESD mission & vision • Have been substantially developed (TRL6-9) but have not been widely deployed • Cannot be obtained simply through reuse of mature subsystems or software • May be slow to adopt because of the unique characteristics of Earth science (e.g., high data volumes)‏ • Approach • Improve community understanding of the technology infusion process • Identify barriers and solutions to technology adoption • Use case studies to evaluate effectiveness of infusion processes • Identify and evaluate new and emerging technologies • Develop roadmaps for adoption of key technologies

4. TIWG 2008 Activities • Maintained 4 active subgroups and added a new special focus area • Infusion Process and Strategies • Subgroup lead: Steve Olding (GSFC/Everware-CBDI) • Web Services • Subgroup lead: Ken Keiser (UAH)‏ • Semantic Web • Subgroup lead: Peter Fox (NCAR)‏ • Sensor Web • Subgroup lead: Karen Moe (ESTO)‏ and Michael Goodman (NSSTC/MSFC)‏ • Data Stewardship • Focus area lead: Ruth Duerr (NSIDC)‏ • Conducted weekly telecons • 1st Thursday: Full working group • 2nd Thursday: Process and Strategies • 3rd Thursday: Web Services • 4th Tuesday: Sensor Web • 4th Thursday: Semantic Web

5. Interoperability Readiness Levels (Full working group)

6. Interoperability Readiness Levels • Nine Levels of Interoperability • Inspired by Technology Readiness Levels and Reuse Readiness Levels • Each interoperability level represents an increased ability for a system to interoperate with other systems • Based on four key interoperability dimensions • Capability Enablement • Describes the overall capability enabled at a particular IRL • Key Interoperability Dimensions • Discovery • Access • Understanding • Data • ‘Bonus’ Interoperability Dimension • Standards (Individual, Organizational, Associational, National, International) • Key Characteristics • Degree of human intervention required • Amount of custom coding vs. configuration • Available on Google Docs – http://tinyurl.com/tiwg-irl • Poster – Wednesday 4:00 PM

7. IRL - Capability Enablement Capability Enablement Level 9 Automatic discovery and incorporation of novel data and services into applications with no human intervention Level 8 Human-triggered incorporation of novel data and services into applications Level 7 Incorporation of novel data and services into applications with minimal configuration Level 6 Incorporation of novel data and services into applications with substantial configuration Level 5 Incorporation of novel data and services into applications with minimal custom code Level 4 Programmatic access to data services from different sources via extensive custom code Level 3 Programmatic use of data from different sources via extensive custom code Level 2 Human use of data from different sources using different code for each Level 1 Data from different sources cannot be used together High IRLs Extensive interoperability. Little human interpretation and intervention required. Simple configuration rather than custom coding. Low IRLs Little or no interoperability. Significant human interpretation and intervention required. Extensive custom coding.

8. IRL Examples

9. Subgroup Lead: Steve Olding, GSFC/Everware-CBDI Process and Strategies

10. Welcome Pack and Technology Registry • TIWG welcome pack • Improve information for new working group members • TIWG background • Capability vision overview • Subgroup details • Work plans • Telecon schedule • Access to mailing lists • http://tinyurl.com/tiwg-welcome • Technology registry • Database technologies • Grid technologies • Data Interoperability technologies • Web Service / SOA technologies • Semantic Web technologies • Earth Visualization and Virtual Globe technologies • Data Analysis and Visualization • Portal technologies

11. Capability Vision • Continued to review and maintain the Capability Vision • Use the Capability Vision to identify technologies to study • Align technology roadmaps to the Vision • Breakout session #2 – Tuesday at 5:30 pm

12. Technology Radar *206 items tagged with “tiwg”: *113 tagged “tiwg and radar”: breakout #1 @ 2:30 * As of Oct 09, 2008

13. Subgroup Lead: Ken Keiser Information Technology and Systems Center University of Alabama in Huntsville Services Interoperability and Orchestration

14. Technologies for Services Orchestration • SciFlo: Choreographing Scientific Web Services • Presentation and demonstration by Brian Wilson (JPL) to monthly telecon • Mining Web Services project with ITSC@UAH (BPEL-based)‏ • Presentation by Chris Lynnes (GSFC) to monthly telecon • Service Orchestration at GMU CSISS (BPEL-based)‏ • Presentation and demonstration by Peisheng Zhao (GMU) to monthly telecon • Practical Guide for Service Orchestration • Web services background • SOA background • Composition tools • Orchestration engines • Example Earth science service orchestration projects

15. Practical Data Interoperability for Earth Scientists • What Is Data Interoperability? • Why Bother? • Technology Assessment • What Is It Good For? • Limitations • Proficiency Level • Languages Supported • Obtaining and Installing • Examples of Use • Data Formats • netCDF/CF-1, HDF, GeoTIFF, KML, ESRI Shapefile, OPeNDAP • Data Interchange Tools • ESML, GDAL/OGR • V1.0 released October 2008 • http://tinyurl.com/tiwg-2008docs

16. Monitor and Review Services Registries • Global Earth Observing System-of-Systems (GEOSS), Service Registries • Presentation by Doug Nebert (USGS) to monthly telecon • ECHO, Enabling Interoperability with NASA Earth Science Data and Services • Presentation by Andy Mitchell at ESIP Technical Workshop

17. Providers advertise web services via Atom feeds (scast) Aggregate in feed readers & on ESIP Fed. web page Scasts discoverable in the Cloud (Google search) Advertise all kinds of services: SOAP, REST, OGC WxS OpenSearch, <your service> Adverts contain typed links to: Service interface (e.g. WSDL) Server endpoint Documentation for humans Advantages / Adoption: Auto service invocation Easy authoring, extensible Scalable, no central repository Search & aggregation come for free Atom Service-Casting Breakout #4 Wednesday @ 2:30 PM

18. Subgroup Lead: Peter Fox (HAO/ESSL/NCAR)‏ Semantic Web Sub-Group

19. Updated Hype Cycle for Semantic Web 2008 Hype Cycle for Emerging Semantic Web Technologies (v0.7)‏ 2008 Revisions: • Added missing technologies e.g. triple stores • Re-assess positions on hype cycle e.g. SPARQL • Added estimated time to mainstream adoption Visibility Semantic Web Services Triple stores, e.g. Jena, Sesame, Mulgara, Oracle Spatial XML Semantic Wiki Ontology editor, SWOOP Concept map, Cmap Query Lang, SPARQL Smart search, e.g. NOESIS Estimated years to mainstream adoption in Earth science RDF OWL 1.0 Protégé Mid-level ES domain ontologies, e.g GEON Tagging / annotation Rules/Logic, SWRL < 2 years 2-5 years DL Reasoners, e.g. Pellet, Racer SKOS, FOAF Species Validators Query Lang, OWL-QL 5-10 years Upper level ontologies, e.g ABC, DOLCE, SUMO Mid-level ES domain ontologies, e.g SWEET OWL 1.1 > 10 years Obsolete before plateau Natural Language Ontologies Query Lang, Commercial and embedded QL Managing modular ontologies (ES and general)‏ Time Slope of Enlightenment Plateau of Productivity Technology trigger Peak of Inflated Expectations Trough of Disillusionment

20. Semantic Web Roadmap - Gap Analysis • Yellow - okay, or some effort, not proven • Orange - fair, definite gap, effort needed • Red - none or poor, serious gap, effort required  Improved Information Sharing  Increased Collaboration & Interdisciplinary Science  Acceleration of Knowledge Production  Revolutionizing how science is done Results Outcome  Geospatial semantic services established  Geospatial semantic services proliferate  Scientific semantic assisted services  Autonomous inference of science results Output  Some common vocabulary based product search and access  Semantic geospatial search & inference, access  Semantic agent-based searches  Semantic agent-based integration Assisted Discovery & Mediation Capability  Local processing + data exchange  Basic data tailoring services (data as service), verification/ validation • Interoperable geospatial services(analysis as service), results explanation service  Metadata-driven data fusion (semantic service chaining), trust Interoperable Information Infrastructure  SWEET core 1.0 based on GCMD/CF  SWEET core 2.0 based on best practices decided from community  Reasoners able to utilize SWEET 4.0  SWEET 3.0 with semantic callable interfaces via standard programming languages Technology Vocabulary  RDF, OWL, OWL-S  Geospatial reasoning, OWL-Time  Numerical reasoning  Scientific reasoning Languages/ Reasoning Current Near Term (0-2 yrs)‏ Mid Term (2-5 yrs)‏ Long Term (5+ yrs)‏

21. Semantic Web Roadmap - Gap Analysis • Distance measure: • NASA = • Earth science = • Country =  Improved Information Sharing  Increased Collaboration & Interdisciplinary Science  Acceleration of Knowledge Production  Revolutionizing how science is done Results Outcome  Geospatial semantic services established  Geospatial semantic services proliferate  Scientific semantic assisted services  Autonomous inference of science results Output  Some common vocabulary based product search and access  Semantic geospatial search & inference, access  Semantic agent-based searches  Semantic agent-based integration Assisted Discovery & Mediation Capability  Local processing + data exchange  Basic data tailoring services (data as service), verification/ validation • Interoperable geospatial services(analysis as service), results explanation service  Metadata-driven data fusion (semantic service chaining), trust Interoperable Information Infrastructure  SWEET core 1.0 based on GCMD/CF  SWEET core 2.0 based on best practices decided from community  Reasoners able to utilize SWEET 4.0  SWEET 3.0 with semantic callable interfaces via standard programming languages Technology Vocabulary  RDF, OWL, OWL-S  Geospatial reasoning, OWL-Time  Numerical reasoning  Scientific reasoning Languages/ Reasoning Current Near Term (0-2 yrs)‏ Mid Term (2-5 yrs)‏ Long Term (5+ yrs)‏

22. SWEET 2.0 • SWEET 2.0 is a restructuring of SWEET • Smaller chunks, more modular. • Make it easy for the community to come and plug into ontology, clearer where to plug in something new. We want it to be a community ontology. • Layered structure. The most general, math, at the top, then science, then planetary science, and applications at the bottom.

23. Data Type and Service Ontology • Joint activity with ESIP Federation semantic web cluster • Sessions at January and July ESIP meetings • Workshop held in Greenbelt, May 15-16 • Further session in TIWG breakouts this week • Breakout # 4, Wednesday @ 1:30 PM

24. Subgroup Leads: Karen Moe (ESTO) and Michael Goodman (NSSTC/MSFC)‏ Sensor Web Sub-Group

25. Use Case Template • Use Case Title, POC, Goal • Summary • “Actors” - people & systems external to sensor web for this use case • Pre-conditions, Triggers • Basic Flow - step-by-step plot of what happens • Post Conditions - state at conclusion of use case • Resources - data, models, services, sensors References • http://en.wikipedia.org/wiki/Use_cases#Use_case_templates • http://tinyurl.com/sensorweb-usecases • Requires sign-in as user sensorweb and password esdswg1

26. Sensor Web Use Themes Earth Observation Systems • Remotely-sensed • In situ Earth System Models • Oceans • Ice • Land • Atmosphere • Solid Earth • Biosphere Policy Decisions Decision Support Assessments Decision Support Systems Management Decisions Data assimilation Forecasting Reduce model uncertainty Autonomous Data Production Predictions Societal Benefits High Performance Computing, Communication, & Visualization DATA Standards & Interoperability Observations End Users Ongoing feedback to optimize value and reduce gaps User Support Autonomous Sensor Operations GEOSS Architecture Workflow generation Access to sensors Campaign / mission design Rapid response Autonomous tasking Cal / Val Sensor management Data downlink

27. Focus Area Lead: Ruth Duerr (NSIDC)‏ Data Stewardship Special Focus Area

28. Data Stewardship An Assessment of Data Identification Technologies - Outline • Introduction • Use cases • Assessment criteria • Why would one want to use a unique identifier • Characteristics of the ideal identifier • Technologies (pros and cons of each)‏ • Summary or Recommendations Technology Infusion Statement on Data Lifecycle • Proposed Activities • Develop white papers defining the scope of the technical aspects of the preservation problem • Conduct assessments to determine the state of the technology in relevant areas, assess their technical readiness levels, and identify the standards and technology gaps that need to be filled • Develop roadmaps for needed data life-cycle technologies • Make recommendations for technologies that are ready for use and help extend their use throughout the NASA Earth science community • Potential areas for near-term concentration include: • Data identification and lineage/provenance. • Metadata and semantics. • Standards. Breakout #3 Wednesday @ 10:30

29. ESIP Federation Summer MeetingAGU Fall MeetingESDSWG Meeting

30. ESIP Technical Workshop Best Practices in Services and Data Interoperability • Web Service Protocols, Experiences and Best Practices • Best Practices in REST, Pat Cappelaere • Best Practices in SOAP (discussion), Brian Wilson/Liping Di/Andy Mitchell • Web Mapping Service, Chris Lynnes • The OGC Web Coverage Service Specification and Its Implementation, Liping Di • Discovery • ECHO - Enabling Interoperability with NASA Earth Science Data and Services, Andy Mitchell • Atom Service-Casting to Advertise Web Services, Brian Wilson • Understanding and Orchestration • Ontologies for Earth System Science, Rob Raskin • SciFlo workflows, and ECHO Client for space/time granule query, Brian Wilson • GeoBrain BPELPower Workflow Engine, Liping Di • OPeNDAP • Hyrax Installation and Customization, James Gallagher

31. ESIP Breakout Sessions • Sensor Web Enablement • Karen Moe and Pat Cappelaere • Establishing a Common Ontology for Earth System Science • Rob Raskin • Data-type and Service Ontologies • Peter Fox • Data Stewardship • Ruth Duerr

32. AGU Fall Meeting • IN13:Information Technology Infusion - Successful Strategies In 2003 NASA established the Earth Science Data Systems Working Groups to provide an interactive forum to advance the use of Earth science remote sensing data. Technology Infusion was identified as a strategic component of future NASA data systems. The group created a vision of the NASA information system capabilities anticipated for the coming decade and tackled the barriers and solutions to infusing new technology to achieve the vision. Information technology has a significant impact throughout the life cycle of remote sensing systems, from sensor data processing to multi-sensor data production to data assimilation. To ignore changing technology is costly, so proactively planning for infusion and adaptation is a strategic necessity. This session seeks technology infusion experiences from both within and beyond NASA sponsored activities, and how the corresponding lessons learned can benefit present and future efforts. Examples of problems and solutions to technology infusion in remote sensing data systems are desired, specifically those dealing with data processing, system interoperability and service oriented architectures. • Conveners: • Karen MoeNASA Goddard Space Flight Center • Karl BenedictU of New Mexico • Chris LynnesNASA Goddard Space Flight Center • Matt HeavnerUniv of Alaska Southeast • 25 Submissions

33. Tuesday Breakout Session 1‏ Joint session with SPG, KML/GeoRSS 1:30-2:30 Technology radar update and collaboration tools 2:30-3:30 Breakout Session 2‏ TIWG Subgroup Soapbox Semantic web – Peter Fox Scalable data discovery – Brian Wilson Sensor web workflow – Liping Di Data: Why So Difficult? – Chris Lynnes Capability Vision Workshop intro. Wednesday Breakout Session 3 Data Life Cycle Workshop 10:30-12:00 Breakout Session 4‏ Data and Services Ontology Workshop 1:30-2:30 Atom Service Casting Workshop 2:30-3:30 Thursday Breakout Session 5‏ Capability Vision Workshop wrap-up 2009 Planning Subgroups, technology focus areas Nomination of co-chair & subgroup leads TIWG Breakout Agenda Details on Google Docs at http://tinyurl.com/philly2008