# Presentation: 149113

## SEEDS Technology Infusion Study

**Second SEEDS Public Workshop**
**Capability Vision and Technology Infusion Process****Breakout Session Summary**

## Breakout Agenda

**Background (15 min)**
- Overview of SEEDS technology study, ESE vision, etc.
- Reference material for working session
**Capability discussion (40 min)**
- Write down individual thoughts on capabilities
- Group discussion – highlight one per person
**Breakout session instructions (5 min) - 2 groups: mission / applications focus**
**Breakout session (2 hr + 15 min break)**
- Barriers
- Related prototypes
- Trends
- Capabilities
- Vision development forum
- Vision representation
- Technology infusion barriers
- Technology infusion strategies

## Breakout Results Summary

**Good participation...thank you!**
- 35+ active participants
**Identified many important elements of (inputs to) a SEEDS vision**
- 49+ capabilities
- 12+ specific features
- 18+ current barriers to reaching ESE goals
- 26+ prototypes of relevant technologies
- 32+ technology/science/application trends
- 5 barriers to technology infusion
- 2 recommendations on vision representation
**Details of input and recommendations on following slides**
- Lightly summarized results
- Input from “mission” and “applications” focus groups is provided on separate slides where applicable

## Capabilities – Group Discussion Results

**What new or improved capabilities are needed in ESE data systems over the next 10 years? **
-  Access
- Info not Data
- Expert guidance for users (“Ask Jeeves”), Interactive access,
- Better web services, Semantic web, domain semantics,
- Catalog-to-data seamless access, content-based search
-  Data Services
- Tools to identify and resolve missing data
- Reduce search result set
- Automated intelligent QA
- Support seamless data fusion
- Data models to support emerging data collection (nano-tech, non-gridded)
-  Distribution
- Store compressed data objects, subset on compressed file to deliver
- Subscribe and deliver to where you are (mobile access, eg to PDA)
- Output multi-formats (format transparent to user)
-  Tools
- Building tailored processing chains (on-the-fly)
- High level data manipulation language for custom data products (from multi sources)
- Event recognition without reprocessing or new metadata
- Adapt tools to commercial products, COTS environments
-  Automated Ops, System “always up”
-  Design
- Simplicity, avoid “gratuitous complexity”
- Alternatives to firewall, security transparency

## Barriers

**What technical problems hinder your work? **
**Considerations**
- Hard to combine disparate data for more sophisticated models, interdisciplinary research, and applications
- Cannot obtain data within 45 minutes of overpass to support weather model initialization
- Cannot easily access NASA data sources from commercial software products
**Check**
- Does your list cover all missing technical capabilities that prevent us from achieving the 2025 ESE vision/goals now?

## Barriers – Applications Focus Results

**What technical problems hinder your work?**
- Slow data access- limited bandwidth or data chunks too big
- Security issues
- Awkward implementations of policy
- Irrational/simplistic policies (e.g., block all access)
- Immature authentication technologies esp. for distributed systems
- Data access and services not tailored to different users – “one size fits all” design results in restrictive policies
- Rapid change of technology and cost of porting/migrating apps
- Disparate data models across various communities
- COTS product and infrastructure issues
- Platform/OS incompatibilities
- COTS product interdependencies
- Slow to support new mission data formats
- COTS products not providing advertised functionality
- Poor system designs
- Generalized solutions do not meet special needs
- Specialized solutions so not meet general needs
- Knowledge gap between Earth science and computer science
- Need new computational Earth science field?

## Barriers - Mission Focus Results

**What technical problems hinder your work?**
- Security - firewalls, next gen networks (will security hinder data access?)
- Management of multiple goals - quick response and equity considerations (competing goals without software to support conflict resolution)
- Bandwidth - (point-to-point as well as space-ground); capacity lacking to fuse from multiple sources to satisfy higher-level needs; commercial tech drivers fall exceed NASA need
- Technology evolution - align, adapt; too many goals => difficult to satisfy all uses
- Automated systems are too manual
- Near-line archives inadequate for needs; volumes too high
- User model unknowable (changing); want interface to access knowledge; need easier to interface to subset of interest; need to rus user scripts on server side

## Related Prototypes

**What leading-edge prototypes do you think demonstrate capabilities that should be made pervasive in the SEEDS era?**
**Considerations**
- MODster & DODster: Distributed, Decentralized MODIS Data & Services
- Standards Framework in Support of Dynamic Assembly of NewDISS Components
- Universal Interchange Technology for Earth Science Data and Services (UNITE)

## Related Prototypes – Application Focus Results

**What leading-edge prototypes do you think demonstrate capabilities that might be made pervasive in the SEEDS era?**
- SRB + Data Grid
- OGC Web services testbed
- ESML
- Echo
- OpenDAP (DODS)  ... and all other ESIP activities presented in plenary
- Conquest
- Resource Description Framework
- XML Topic Maps
- Grid prototypes
- Fortezza cards
- RapidFire
- D2K data mining package
- GloViz @ EDC
- Global Broadcast System
- Data pools

## Related Prototypes - Mission Focus Results

**What leading-edge prototypes do you think demonstrate capabilities that should be made pervasive in the SEEDS era?**
-  Data Grid, service broker
-  EOSDIS as a prototype - interdisciplinary definitions, lessons learned, user patterns, examples of tough problems solved
-  Near-archive data mining
-  Interview science teams, DAACs, how is SEEDS improved?
-  NVO - National Virtual Observatory
-  Microsoft Terraserver has analogous system
-  REALM - lessons learned form Sam Goward/UM
- Simulation modeling in Hollywood
- TV News ability to pull video footage for breaking news reports
- Commercial digital archives
- Sony game playing distributed architecture and visualization

## Trends

**What current trends do you think foretell the most important changes to user requirements and system designs in the SEEDS era? **
**Considerations**
- LAN services  Internet services
- Data poor  Data rich (volume & variety)
- Central processing  End-user processing
- Single discipline science  Multi-disciplinary science/apps
- High-latency data for research  Low-latency data for apps (e.g., weather)

## Trends – Application Focus Results

**What current trends do you think foretell the most important changes to user requirements and system designs in the SEEDS era? **
- Offline  near line  on-line interactive
- Simple data access  value-added services
- Focused research community  broad application user communities
- Leading edge technology focus  usable technology focus
- Dumb sensors  Smart sensors
- Single downlink  direct broadcast
- Centralized  distributed (cluster computing, grid computing)
- Higher end-user computing capability
- Single purpose systems  multipurpose systems (research + applications) a la NPOESS
- Planned data products  on demand data product generation
- Slow networks  fast networks
- Wired  Wireless apps

## Trends – Mission Focus Results

**What current trends do you think foretell the most important changes to user requirements and system designs in the SEEDS era? **
-  Cheaper on-line storage
-  Bandwidth may get more expensive compared to storage
-  Processing on-board satellites
-  Outsourcing services/equipment
-  Look to commercial service  providers (use developing standards to plug-in)
-  More server-side processing
-  Distributed (mobile) services
- Smaller specialized services (chained together)
- Computation: SETI computational model (leverage unused CPU cycles); Sony/game playing models
- Visualization: ESE data role in entertainment/real time games (Sony)
- Coupled data (real-time stream) with large model outputs
- Charging for data
- Space technologies slow to evolve compared to intelligent ground technologies

## Capabilities (Revisited) – Application Focus Results

**What new or improved capabilities are needed in ESE data systems over the next 10 years? **
- Ability to produce higher level products over distributed systems (e.g., distributed FFT) and other new architectures
-  Refined security mechanisms
-  Levels of service on servers to handle broader set of users
-  Flexible/adaptable interfaces – systems provide value to engage end-users earlier
-  Automated near-real-time event detection
-  Faster data ingest
-  Separate ingest from distribution

## Capabilities (Revisited) – Mission Focus Results

**What new or improved capabilities (not already captured in the group discussion) are needed in ESE data systems over the next 10 years? **
-  Improved security management
-  Tools for management of multiple (conflicting) goals
-  Shipping code
-  Outsourcing of network services
-  Optimized mission planning
-  Get on the Grid

## Features

**What specific new features are needed in ESE data systems over the next 10 years to enable the capabilities you identified? **
**Considerations**
- ArcInfo and IDL plug-ins that provide direct access to DAAC holdings
- Near-real-time data delivery of low-quality data subsets (images) over a limited area (implies prioritized vs. FIFO processing)
- Ability to order a data product based on the content of another data product (e.g., high-res data over fires detected in low-res data)
**Check**
- Does your list address all needed capabilities?

## Features – Application Focus Results

**What specific new features are needed in ESE data systems over the next 10 years to enable the capabilities you identified? **
- Direct broadcast
- Parallel taps into raw  or processed data stream to deliver data to special-purpose plug-in application services w/ near-real-time capabilities
- Ability to do quality/timeliness trades (note: AVHRR available 2 hrs after overpass)
- Prioritization by user or user type
- Strong user identification
- Resource usage monitoring
- General data pools (limited depth pools for user algorithms)
- Data debit cards
- Intelligent data subsetting (much more than FTP)
- Partial data decompression
- Data fusion
- Semantic understanding of the data (esp. resolutions)
- Swath + Uniform grid + vector
- Co-registration
- Enabling third-party services/products that can be vetted by the users
- COTS tools understand metadata and can make certain automatic transformations/warnings
- Better insight into different qualities of similar datasets

## Features – Mission Focus Results

**What specific new features are needed in ESE data systems over the next 10 years to enable the capabilities you identified? **
-  Knowledge representation, extraction, and access tools
-  User interfaces much simpler (partner with commercial developers)
-  Modules that work together
-  Defining rules for transforming query to next level
-  Population knowledge repository - discipline-specific level
-  Classifier of data into knowledge
-  Ontology/namespace

## Vision Representation

**How should the vision for ESE data systems be represented?**
**Considerations**
- List of features/benefits
- Future user scenarios
- Thematic diagram/picture
- Goal system architecture
- Tell a story (video w/ animation, interviews, etc.)

## Vision Representation – Mission + Application Focus

**How should the vision for ESE data systems be represented?**
-  Recommend “Tell a story” (animated, short movie)
- Start with ESE 2020 vision animation but address the role of the observatory data systems
- Scenario storyboard with multiple user perspectives
- Mission user/scientist with “direct” access
- Graduate student researcher with access via value-added tools working within COTS
- Commercial customers with access via value-added providers
- Ordinary citizen making quiries (eg, directly from their tractor)
- Convey themes
-  SEEDS enables development of new products and services but does not make new products
- Metric of success - commercial use of SEEDS standards, technology solutions
- Demonstrate ability to connect data to sspecific user needs as needs evolve
- Different formats for different audiences
- All formats under “considerations” are viable

## Technology Infusion Barriers – Application Focus

**What are the barriers to infusing new technology into current ESE data systems?**
- Different priorities between developers and operations
- Lack of modularity
- Systems not open by design
- COTS interdependencies
- Intellectual property issues- will the source be available?  Bureaucratic release processes

## Technology Infusion Strategies

**What strategies can be used to ensure technologies are readily incorporated into operational ESE data systems?**
**Considerations**
- Collaborative funding for technology customers to incorporate successful research prototypes into operational systems
- Sponsor activities connecting technology developers with technology customers
- Explore partnering opportunities
- Standardize key interfaces
**(Note: topic not covered in the workshop due to time constraints)**

## Next Steps: Capability Needs Information Roadmap

- SEEDS Capability Vision

- ESE Strategic Plan

- Capability Needs

- Current & Projected Barriers

- NASA Funded Research (NRAs, BAAs)

- Tech Deployment Demos?

- Technology Approaches

- Scenarios

- Investment Themes

- Related Research (DARPA, etc)

- Trends

- Categorize

- Categorize

- Drives

- Contains

- Drive

- Employ/Explore

- Categorize

- Are Demo’ed In