# Presentation: 654926

## 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

- Karen Moe, NASA/ESTO
- Chris Lynnes, NASA/GSFC
- Earth Science Data Systems Working Group Meeting
- October 21-23, 2008
- Philadelphia, PA

## 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

## 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

## Tech Infusion Working Group*

**Tech Infusion Working Group***

## 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

## Interoperability Readiness Levels

**Interoperability Readiness Levels**
**(Full working group)**

## 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

##  IRL - Capability Enablement

- Low IRLs
- Little or no interoperability.
- Significant human interpretation and intervention required.
- Extensive custom coding.

- High IRLs
- Extensive interoperability.
- Little human interpretation and intervention required.
- Simple configuration rather than custom coding.

## IRL Examples

| IRL | Capability Enablement | Discovery | Access
 | Understanding
 | Data
 |
| --- | --- | --- | --- | --- | --- |
| 8 | Human-triggered incorporation of novel data and services into applications. | Services discoverable in global registries of services with complete syntactic information. | Discipline/ Domain-specific ontology support using recognized semantic tools. | Semantic agreement on content based upon community-accepted ontologies. | Standard data types in syntactically self-describing formats, quality, applicability, etc. information partly semantically captured. |
|  |  |  |  |  |  |
| 3 | Programmatic use of data from different sources via extensive custom code. | Catalog accessible but undocumented and changing. Manual search. | One-off specialized implementations (no standardization of API or functionality), poor documentation. | Extensive human-human interaction required to gain full meaning of data. | Data in documented formats with full content information available as free text. |

## Subgroup Lead:
Steve Olding, GSFC/Everware-CBDI

- Steve Olding, GSFC/Everware-CBDI

**Process and Strategies**

## Process and Strategies Subgroup

- TIWG welcome pack
- Technology survey / registry
- Updating the capability vision
- Technology radar
- Contribute to Interoperability Readiness Levels

## 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

## 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

**Notes:**
The capability vision serves two purposes: it helps focus the efforts of NASA and the Earth science community, and it provides a yardstick by which we can measure our progress.

Focusing our efforts is critical to ensure that available resources are applied where they are needed most.  What capabilities are most needed to achieve NASA’s Earth science goals?  What technologies, standards, and reusable components are most needed to achieve those capabilities?  This capability vision for Earth science information systems will help NASA managers, data system developers, and science researchers work together to evolve the next generation of data systems for Earth science research.  

With the capability vision as a roadmap, we can also measure progress toward achieving the vision as we enhance and evolve current systems.  This will facilitate coordinated efforts across the community and provide stakeholders with better insight to, and understanding of, our accomplishments. 

## Technology Radar

**Technology Radar**

- *206 items tagged with “tiwg”: *113 tagged “tiwg and radar”: breakout #1 @ 2:30

- * As of Oct 09, 2008

## Subgroup Lead:
Ken Keiser
Information Technology and Systems Center
University of Alabama in Huntsville

- Ken Keiser
- Information Technology and Systems Center
- University of Alabama in Huntsville

**Services Interoperability and Orchestration**

## Services Interoperability and Orchestration Subgroup

- Review technologies for services orchestration
- Practical Data Interoperability for Earth Scientists
- Continue to monitor and review ECHO and other services registries
- Review and update web services roadmap
- Review AIST Needs
- Contribute to Interoperability Readiness Levels

## 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

## Technologies for Services Orchestration*

**Technologies for Services Orchestration***

## 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

## 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

## Atom Service-Casting

- 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

- Breakout #4
- Wednesday
- @ 2:30 PM

## Web Services Roadmap 2005

**Web Services Roadmap 2005**

**Technology**

****** ****Geospatial services established**

****** ****Open geospatial services proliferate**

****** ****Production quality geospatial services**

****** ****Geospatial service catalog established (WSDL, UDDI)****‏**

****** ****Common geospatial schema adopted ****(GML, ESML)****‏**

****** ****Standard workflow language infused (BPEL)****‏**

****** ****Open geospatial ontology converges (OWL)****‏**

****** ****Local processing + data exchange**

****** ****Basic data tailoring services (data as service)****‏**

****** ****Interoperable geospatial services****(analysis as service)****‏**

****** ****Parameter-based product searches and access**

**Interoperable Information Infrastructure**

**Assisted Discovery & Mediation**

****** ****Metadata-driven data fusion (semantic service chaining)****‏**

****** ****Automatic service mediation**

****** ****Semantic geospatial search & access**

****** ****Common service protocol, description adopted ****(SOAP, WSDL)****‏**

**Capability**

**Results**

****** ****Improved Information Sharing**

****** ****Accelerated Research & System Cost Savings**

****** ****Increased Collaboration & Interdisciplinary Science**

****** ****Increased PI Participation in Information Production**

****** ****Increased Data Utilization**

****** ****Open service protocols established (HTTP, REST)****‏**

****** ****Intelligent Services**

****** ****Unified security & identity management ****(WS-Security, SAML)****‏**

****** ****Full geospatial logical searches and access**

****** ****Open data access established (OpenDAP, OGC)****‏**

**Data **

**Messaging**

**Output**

## Web Services Roadmap 2008 Update

**Outcome **

**Web Services Roadmap 2008 Update**

**Technology**

****** ****Geospatial services established**

****** ****Open geospatial services proliferate**

****** ****Production quality geospatial services**

****** ****Common geospatial schema adopted ****(GML)**

****** ****Local processing + data exchange**

****** ****Basic data tailoring services (data as service)**

****** ****Interoperable geospatial services****(analysis as service)**

****** ****Parameter-based product searches and access**

**Interoperable Information Infrastructure**

**Assisted Discovery & Mediation**

****** ****Metadata-driven data fusion (semantic service chaining)**

****** ****Automatic service mediation**

****** ****Semantic geospatial search & access**

****** ****Common service protocol, description adopted ****(SOAP, WSDL)**

**Capability**

**Results**

****** ****Improved Information Sharing**

****** ****Accelerated Research & System Cost Savings**

****** ****Increased Collaboration & Interdisciplinary Science**

****** ****Increased PI Participation in Information Production**

****** ****Increased Data Utilization**

****** ****Open service protocols established (HTTP, REST)**

****** ****Intelligent Services**

****** ****Full geospatial logical searches and access**

****** ****Open data access established (OpenDAP, OGC)**

**Data **

**Messaging**

**Output**

****** *****Automated***** Data Utilization**

****** ****Geospatial service catalog established (WSDL, UDDI, ???)**

****** ****Standard workflow languages infused (*****e.g.***** BPEL)**

****** ****Open geospatial ontology converges (OWL)**

****** ****Unified security & identity management ****(WS-Security, SAML)**

## Subgroup Lead:
Peter Fox (HAO/ESSL/NCAR)‏

- Peter Fox (HAO/ESSL/NCAR)‏

**Semantic Web Sub-Group**

## Semantic Web Subgroup

- Updated semantic web hype cycle
- Added gap analysis to semantic web roadmap
- Presented a combined  capability vision / semantic web roadmap presentation to ESTO, next step is to present to NASA HQ
- Semantic web cluster formed within the ESIP Federation
- Develop semantic web use cases
- A number of use cases were discussed at the January ESIP meeting
- Documented on ESIP wiki
- Data type and service ontology
- Sessions at January and July ESIP meetings
- Workshop held in Greenbelt, May 15-16
- Further session in TIWG breakout this week
- Breakout # 4, Wednesday @ 1:30
- Review SWEET 2.0
- Review AIST Needs
- Contribute to Interoperability Readiness Levels

## Hype Cycle for Semantic Web

- 2007 Hype Cycle for Emerging Semantic Web Technologies (v0.2)‏

**Technology**
**trigger**

**Peak of**
**Inflated**
**Expectations**

**Trough of**
**Disillusionment**

**Slope of**
**Enlightenment**

**Plateau of**
**Productivity**

- Time

- Visibility

- Natural Language Ontologies

- SKOS, FOAF

- Smart search, e.g. NOESIS

- Tagging / annotation

- OWL 1.1

- Reasoners, e.g. Pellet, Racer, DIG

- Managing, modular ontologies  (ES and general)‏

- Upper level ontologies, e.g ABC

- Concept map, Cmap

- Protégé

- XML

- OWL

- Mid-level ES ontologies, e.g SWEET

- Mid-level ES ontologies, e.g GEON

- Semantic Wiki

- RDF

- Ontology, e.g. SWOOP

- Semantic Web Services

- Query Lang, SPARQL

- Rules/Logic, SWRL

- Validators

## Updated Hype Cycle for Semantic Web

**Peak of**
**Inflated**
**Expectations**

**Trough of**
**Disillusionment**

**Slope of**
**Enlightenment**

**Plateau of**
**Productivity**

- Time

- Visibility

**Updated Hype Cycle for Semantic Web**

- SKOS,
- FOAF

- Smart search, e.g. NOESIS

- Tagging / annotation

- OWL 1.1

- DL Reasoners, e.g. Pellet, Racer

- Upper level ontologies, e.g ABC, DOLCE, SUMO

- Concept map, Cmap

- Protégé

- XML

- OWL 1.0

- Mid-level ES domain ontologies, e.g SWEET

- Mid-level ES domain ontologies, e.g GEON

- Semantic Wiki

- RDF

- Ontology editor, SWOOP

- Semantic Web Services

- Query Lang, SPARQL

- Rules/Logic, SWRL

- Species
- Validators

- Query Lang, OWL-QL

- Query Lang, Commercial and embedded QL

- Estimated years to mainstream adoption in Earth science

- < 2 years

- 2-5  years

- 5-10  years

- > 10  years

- Obsolete before plateau

- Triple stores, e.g. Jena, Sesame, Mulgara, Oracle Spatial

- 2008 Hype Cycle for Emerging Semantic Web Technologies (v0.7)‏

- Managing modular ontologies
- (ES and general)‏

**Technology**
**trigger**

- Natural Language Ontologies

- 2008 Revisions:
- Added missing technologies e.g. triple stores
- Re-assess positions on hype cycle e.g. SPARQL
- Added estimated time to mainstream adoption

**Notes:**
Explain reasoners, dl, 
ES = Earth Science 
OWL=Ontology Web Language
SPARQL vs. OWL-QL - SPARQL is query for RDF, OWL-QL is query for OWL
SKOS=Simple Knowledge Organization System - semantic vocabulary ontology, built on RDF, and is ideal for taxonomies
FOAF=Friend-Of-A-Friend - built on RDF - semantic vocabulary for identifying associations between entities (e.g. people)‏
NOESIS is the smart search framework from ITSC at Univ. Alabama, Huntsville, uses modified SWEET ontology, reasoning engine
SUMO=Suggested Upper Merged Ontology
DOLCE is a foundational ontology
ABC is a foundational ontology
GEON=Geosciences Network 
SWEET=Semantic Web for Earth and Environmental Terminologies - mid-level earth science ontology
SWOOP=ontology editor from UMBC
** Swoop - will be obsolete because development has ceased and not because it is/was not a good product
Protégé is an ontology editor from the Stanford biomedical ontology group.
DL=Description Logics
Pellet=reasoner
Racer =reasoner
Cmap is a concept mapping tool from IHMC
RDF=Resource Description Framework (graph-based model for resources), often coded in RDF/XML
XML=eXtensible Markup Language
Note: Years to adoption versus position on time axis: 

5-10 YR
Modular ontology management is still in a very heuristic stage of development and is art more than science. It is needed but will take at least 5 years before mainstream adoption.
Natural Language Ontologies - are just becoming of interest in science and earth science communities since they bear closer resemblance to the use cases and science terminology in use, rather than the often obscure OWL/RDF encodings, very few tools exist to work with them and they are still in the research topic space
Rules/Logic/SWRL is emerging and gaining visibility in semantic web (having a very long history in AI) efforts but no standards exist for their use in semantic web settings, and tool support is minimal, e.g. no Java representation (only prolog, etc.), and the most effective use is being seen in hybrid approaches, I.e. combining declarative (OWL) and logic but these efforts are just starting and are not mature. The emergence of query languages has further complicated their use.
2-5 YR
OWL-QL development had stalled but is being revived since many semantic web developers are finding that SPARQL (RDF) is insufficient in many applications.
SKOS and FOAF are now being used effectively in taxonomic applications with good success, even though the tool support (only one editor) is minimal
Tagging and Annotation (RDFa and others) are also being used increasingly in ES (with semantic schema)‏
SPARQL has generated a lot of interest and is likely to become a W3 Recommendation early in 2008 which will accelerate development.
Semantic Wiki are now being developed and gaining lots of visibility but are still immature since development tools are minimal
Species validators are stuck and need research efforts which will probably need to happen in at most 5 years
Upper and mid-level ontologies have been out of favor but recent efforts at modularizing and mapping between them have indicated strong promise for how to turn them into very powerful elements of the semantic web, many efforts are underway in both of these areas and the work is encouraging.
DL Reasoners are becoming more productive in a web services setting and are more reliable.
< 2 YR
Commercial and embedded Query Languages (Oracle, for e.g.) are likely to shift quickly into stable mature and used products.
OWL 1.1 is still pending Recommendation status with W3 consortium but is expected to pass soon and since it is built on OWL 1.0 is expected to quickly below mature and productive - provided tools (editors, etc.) are updated quickly to utilize its enhancements
Smart search is becoming very visible as a number of applications are emerging and use both OWL and RDF ontologies
Semantic Web Services are also gaining visibility but are immature since there are 4 submissions for language standards to W3 but no approved recommendations. Demand is great and work should be rapid but they will rely on both service and data type ontologies as well as domain ontologies to be effective. Also required is a semantic web service discovery/ registry mechanism and these efforts are not mature nor visible.
OWL 1.0, Protégé, Cmap, RDF, Triple stores and XML are productive and mature and in use in many ES areas.

## Semantic Web Roadmap - Gap Analysis

**Semantic Web Roadmap - Gap Analysis**

**Notes:**
Eventually a white paper is needed to capture each of the elements in this roadmap with expanded explanations.
Horizontal axis: Time frame
Vertical Axis: three sets of groupings (bottom two from capability vision): Technology split into the domain independent portion (languages/ reasoning) and domain specific (vocabulary). Capability includes ONLY two of the seven capability components from slide 5 as an *example* of the different stages and needs for these capabilities (the NEXT slide expands the Capability axis to cover all seven components). Top rows are the Results in terms of output and outcomes where the advancement of the capability vision in support of science and education using semantic technologies is to be realized.
Note dependence on Tech Infusion Capability Vision
The color graphical representation indicated that as one moves across the horizontal axis, each element builds on TOP of the previous element (I.e. evolve)‏
In the same way that as one moves up (vertically) within a given timeframe that each element builds upon the former. E.g. vocabulary relies on languages/reasoning, etc.
For Results - we need to determine how to measure progress. Need to establish baseline metrics.
For presentation. Take one or two cells and explain the contents as one goes from left - > right or bottom to top. Noting the ultimate top-right statement!

## Semantic Web Roadmap - Gap Analysis

**Semantic Web Roadmap - Gap Analysis**

**Notes:**
Eventually a white paper is needed to capture each of the elements in this roadmap with expanded explanations.
Horizontal axis: Time frame
Vertical Axis: three sets of groupings (bottom two from capability vision): Technology split into the domain independent portion (languages/ reasoning) and domain specific (vocabulary). Capability includes ONLY two of the seven capability components from slide 5 as an *example* of the different stages and needs for these capabilities (the NEXT slide expands the Capability axis to cover all seven components). Top rows are the Results in terms of output and outcomes where the advancement of the capability vision in support of science and education using semantic technologies is to be realized.
Note dependence on Tech Infusion Capability Vision
The color graphical representation indicated that as one moves across the horizontal axis, each element builds on TOP of the previous element (I.e. evolve)‏
In the same way that as one moves up (vertically) within a given timeframe that each element builds upon the former. E.g. vocabulary relies on languages/reasoning, etc.
For Results - we need to determine how to measure progress. Need to establish baseline metrics.
For presentation. Take one or two cells and explain the contents as one goes from left - > right or bottom to top. Noting the ultimate top-right statement!

## Semantic Web Roadmap - Gap Analysis

**Semantic Web Roadmap - Gap Analysis**

**Notes:**
Eventually a white paper is needed to capture each of the elements in this roadmap with expanded explanations.
Horizontal axis: Time frame
Vertical Axis: three sets of groupings (bottom two from capability vision): Technology split into the domain independent portion (languages/ reasoning) and domain specific (vocabulary). Capability includes ONLY two of the seven capability components from slide 5 as an *example* of the different stages and needs for these capabilities (the NEXT slide expands the Capability axis to cover all seven components). Top rows are the Results in terms of output and outcomes where the advancement of the capability vision in support of science and education using semantic technologies is to be realized.
Note dependence on Tech Infusion Capability Vision
The color graphical representation indicated that as one moves across the horizontal axis, each element builds on TOP of the previous element (I.e. evolve)‏
In the same way that as one moves up (vertically) within a given timeframe that each element builds upon the former. E.g. vocabulary relies on languages/reasoning, etc.
For Results - we need to determine how to measure progress. Need to establish baseline metrics.
For presentation. Take one or two cells and explain the contents as one goes from left - > right or bottom to top. Noting the ultimate top-right statement!

## Semantic Web Roadmap - Gap Analysis

**Semantic Web Roadmap - Gap Analysis**

**Notes:**
Eventually a white paper is needed to capture each of the elements in this roadmap with expanded explanations.
Horizontal axis: Time frame
Vertical Axis: three sets of groupings (bottom two from capability vision): Technology split into the domain independent portion (languages/ reasoning) and domain specific (vocabulary). Capability includes ONLY two of the seven capability components from slide 5 as an *example* of the different stages and needs for these capabilities (the NEXT slide expands the Capability axis to cover all seven components). Top rows are the Results in terms of output and outcomes where the advancement of the capability vision in support of science and education using semantic technologies is to be realized.
Note dependence on Tech Infusion Capability Vision
The color graphical representation indicated that as one moves across the horizontal axis, each element builds on TOP of the previous element (I.e. evolve)‏
In the same way that as one moves up (vertically) within a given timeframe that each element builds upon the former. E.g. vocabulary relies on languages/reasoning, etc.
For Results - we need to determine how to measure progress. Need to establish baseline metrics.
For presentation. Take one or two cells and explain the contents as one goes from left - > right or bottom to top. Noting the ultimate top-right statement!

## SWEET 2.0

**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.

## 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

## Subgroup Leads:
Karen Moe (ESTO) and
Michael Goodman (NSSTC/MSFC)‏

- Karen Moe (ESTO) and
- Michael Goodman (NSSTC/MSFC)‏

**Sensor Web Sub-Group**

## Sensor Webs are ...

- Distributed Earth observation systems
- Comprised of
- Satellite and in situ sensors
- Data systems
- Models
- Dynamically configured to produce products on demand
- By using emerging web technologies

**Notes:**
Sensor Observations to Applications
Sensors and sensor networks gain value from the use of their observations
Need to get data and information out of the sensor network and integrated with other sensor data, models, and decision support systems?
Need a framework that is flexible and that can be expanded (new sensors, models, tools need to be accommodated)

NASA Sensor Web Response

NASA AIST* funded 35 projects to 
develop key technology
demonstrate pilot systems
clarify the concepts
expand knowledge about sensor webs 

Goal is to bridge the gap between today’s remote sensing system capabilities and the sensor web vision

*Advanced Information Systems Technology Program

## Earth Observation Sensor Web Uses

- Improve science products
- Rapidly respond to events
- Enable cross mission, multi-sensor products
- Reduce model uncertainty via targeted data inputs
- Provide timely calibration/validation
- Improve science operations
- Plan sensor flight paths for unmanned air & surface vehicles
- Design field campaigns
- Simulate mission designs (ala OSSE)
- Enable collaboration and save operational costs
- Leverage multi-agency, international assets, eg. US GEO, GEOSS
- Reuse infrastructure enabling collaboration in totally different domains such as fires and floods
- Reduce staff via automation

- Derived from the NASA ESTO Sensor Web Meeting April 2008 (41 use cases)
- http://esto.nasa.gov/sensorwebmeeting

**Notes:**
OSSE - Observing System Simulation Experiment

## 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

**Notes:**
Use Case coverage
41 cases
Each science focus area has between 3 and 10 use cases
All NRC Decadal Survey challenge areas covered
All AIST goals for technology needs addressed

## Sensor Web Use Themes

**Autonomous **
**Sensor Operations**

**User **
**Support**

**Autonomous **
**Data Production**

**GEOSS Architecture**

**Predictions**

**Societal**
**Benefits**

**Observations**

**DATA**

- Ongoing feedback to optimize value and reduce gaps

- High Performance
- Computing,
- Communication,
- & Visualization

- Standards &
- Interoperability

**Rapid response**
**Autonomous tasking**
**Cal / Val**
**Sensor management**
**Data downlink**

**Workflow generation**
**Access to sensors**
**Campaign / mission**
**   ****design**

**Data assimilation**
**Forecasting**
**Reduce model**
**  ****uncertainty**

**End Users**

## Focus Area Lead:
Ruth Duerr (NSIDC)‏

- Ruth Duerr (NSIDC)‏

**Data Stewardship Special Focus Area**

## Data Stewardship

- 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.

- 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

- Breakout #3
- Wednesday
- @ 10:30

## Data Stewardship*

**Data Stewardship***

## ESIP Federation Summer MeetingAGU Fall MeetingESDSWG Meeting

**ESIP Federation Summer Meeting****AGU Fall Meeting****ESDSWG Meeting**

## 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

## 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

## 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 Moe***NASA Goddard Space Flight Center*
**Karl Benedict***U of New Mexico*
**Chris Lynnes***NASA Goddard Space Flight Center*
**Matt Heavner***Univ of Alaska Southeast*
- 25 Submissions

## TIWG Breakout Agenda

- 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

- Details on Google Docs at http://tinyurl.com/philly2008

## TIWG Breakout Agenda*

**TIWG Breakout Agenda***