Goal
#

Requirements

Technology Needs

Potential Approaches

A

Improve mission performance through automation and autonomy

1.A.1
On board processing for command and control

1. Increased Millions of Instructions per Second (MIPS)
2. Distributed processing within & across multiple spacecraft
3. Reconfigurable hardware (HW)
4. Distributed decision making
5. Intelligent routing

1. Reprogrammability (reconfigurable computing)
2. Pattern/feature/event recognition; artificial intelligence (AI)
3. Access to ancillary data via uplink
4. Enable real time applications
5. User-tailored near real-time product generation

E

Improve access/retrieval and scalability of the storage and management of large data volumes

1.E.1
Improve fault handling (detection and correction)

1. Develop components and architectures for fault tolerant on-board and inter-satellite network
2. Low power radiation-tolerant devices and components
3. Selective redundancy
4. Radiation-hardened technologies
5. Technologies for testing components on ground
6. On-orbit diagnosis techniques (ground or space)

F

Improve performance, flexibility & adaptability of data processing and networking

1.F.1
On-board high speed networks and buses; spacecraft as a node in a constellation

1. Wired/wireless
2. Protocols/interface across processor elements and sensors based on LAN architecture
3. Interfaces to smart sensors

1. Inter-satellite WAN architecture
2. Protocols/interface across processor elements and sensors based on WAN architecture

1. Parallel processing on-board
2. Distributed processing within & across multiple spacecraft
3. Reconfigurable HW

1. Object-oriented Design (OOD) and modular HW design
2. Standardized interfaces approach
3. Unattended operations
4. Technology reuse
5. Commodity processors and software

1. High density storage
2. Accelerate data retrieval (e.g. parallel processing)
3. Reduce data volume by event and feature detection
4. Lossy and/or lossless compression

L

Reduce life cycle cost of ground and space operations and processing

1.L.1
Use and creation of standards to improve reliability of HW and software (SW)

Goal
#

Requirements

Technology Needs

Potential Approaches

C

Enable seamless, ubiquitous communication networks

2.C.1
Enable reconfigurable intersatellite network links

1. Flexible intersatellite network architecture
2. Ultra-low weight/power transceiver modules
3. High capacity Low Earth Orbiting (LEO) - Geosynchronous Earth Orbiting (GEO) links for small spacecraft
4. Integrated digital communications, data, and network modules

D

Increase transmission efficiency of large data volumes

2.D.1
On-board high fidelity data compression and/or error correction/containment techniques

1. Semantic content for prioritization of data transmission
2. On-board storage strategies
3. Buffer management techniques (e.g., AI)

1. High power, high efficiency sources
2. High gain/EIRP antenna/telescope
3. Low weight, low power, compact high data rate components/ subsystems

L

Reduce life cycle cost of ground and space operations and processing

2.L.1
Reduce cost of direct downlink of user-tailored near real-time products

1. Phased array antenna
2. Multiple, low cost, portable ground stations with Internet node interface

Goal
#

Requirements

Technology Needs

Potential Approaches

E

Improve access/retrieval and scalability of the storage and management of large data volumes

3.E.1
Long-term, high-density, high-speed access archival media and formats to preclude obsolescence and data degradation

1. Evolvable storage media and format
2. Storage, archive, and retrieval standards
3. Robust, self-describing formats to support generational upgrades of data

1. Improved data compression ratio for storage
2. Storage architecture that supports adaptive access patterns (georeferenced, temporal, atmospheric profiles, etc.)
3. Distributed storage architecture (tertiary and secondary storage) with embedded intelligence for access and processing

1. Compression, subsetting, reprojection
2. Transparent retrieval of data from multiple archives

F

Improve performance, flexibility and adaptability of data processing and networking

3.F.1
Create an extensible, evolvable framework supporting interoperability standards to create interdisciplinary models and/or custom data processing systems

1. Self-describing data and service representation (e.g., Metadata definition and standards, Markup languages)
2. Technical access and transformation of data and services (e.g., adaptive interfaces, agents)
3. Improve descriptive information in metadata for use as basis of search
4. Shared schemata, interoperability software tools and metadata for data and services
5. Techniques to represent semantics, ontologies and thesauri that promote interchangeability
6. Enable automated search of catalogs
7. Define an Application Program Interface (API) for a general-use interface to Earth Science data products and applications (e.g., Web portal technologies)

1. Incremental improvement of initial conditions of models
2. New data acquisition from diverse sources (e.g., archived or new measurement)
3. Predictive processing to avoid rereading an entire dataset

1. Evolvable metadata over time (e.g., time-dependent calibration datasets)
2. Automatic generation, population, and propagation of lineage information throughout life cycle of data
3. Maintain algorithm & data/metadata traceability & evolvability

3.F.6
High performance processing for data production

1. Computing clusters
2. Reconfigurable computing
3. Embedded computing
4. Optical computing
5. Distributed computing

3.F.7
Exploit commercial database technologies for spatial, temporal and spectral data handling

3.F.8
Automatic code generation of processing algorithms

K

Improve system management and operations

3.K.1
Improve system engineering & architectural design of end-to-end system for data production (e.g., starting with initial production of data by instrument)

3.K.2
Improved data product and workflow management for integrated data products (e.g., multiple instruments integrated into one product)

L

Reduce life cycle cost of ground and space operations and processing

3.L.1
Tools enabling space/ground data processing trades and real-time reconfiguration

1. Dynamic resource allocation
2. Tools/environments for modeling and simulation of end-to-end data flow

Goal
#

Requirements

Technology Needs

Potential Approaches

F

Improved performance, flexibility and adaptability of data processing and networks

4.F.1
Problem solving environments leveraging commercial products (e.g., Matlab, public domain environments) enabling use of common toolsets for data processing

1. Methodologies for measuring earth science search and retrieval response times
2. Methodologies for providing and measuring network QOS
3. System-wide real-time QOS mechanisms

1. Service visibility via discovery tools
2. Data service workflow formulation
3. Automated service invocation (e.g., data format transformation)
4. Express delivery / data push services via subscription

G

Improved organization and search of scientific data

4.G.1
Knowledge management (capture, representation, categorization and use of Earth Science knowledge)

1. Autogeneration of documentation
2. Improved support for navigation/discovery paradigm for data access

1. Exploit on-board processing and provide alerts

1. Natural language queries/analysis
2. Query representation to enable discovery, search, navigation, and exploration
3. Data organization for ease of user access for extraction & fusion
4. Management techniques for large, long-term data sets that support both random and sequential access

H

Improved extraction and fusion of scientific data

4.H.1
Improved tools and support for warehousing, data mining and knowledge discovery

1. "Hypothesis generation" for data mining algorithm development
2. Detect changes & produce content-based metadata / annotations

4.H.2
Improved tools and support for science data fusion

1. Data fusion from distributed and heterogeneous sources
2. Use of knowledge features, regions, models, objects and semantics

I

Improved analysis of scientific data

4.I.1
Optimize use of Web GIS spatial analysis techniques for earth science data

4.I.2
Enable automated analysis tools and techniques

4.I.3
Techniques to facilitate customized application-oriented data and information services

4.I.4
Optimize presentation of data and information

1. Bio-feedback outputs (sound, etc.) for multidimensional, complex, diverse objects and structures
2. Machine-assisted visualization for small features (anomaly detection and projection) in large data sets
3. Techniques employing latest understanding of human perception
4. Improve use of collaborative meeting and visualization tools

Goal
#

Requirements

Technology Needs

Potential Approaches

A

Improve mission performance through automation and autonomy

5.A.1
Goal-directed science data management (e.g., automatically task sensor web and corresponding ground components to reconfigure for on-demand event or model predictions)

B

Enable distributed heterogenous sensorwebs

5.B.1
Standard sensor representation for interoperability

1. Contingency planning
2. Formation flying coordination
3. Flight-route planning, etc.

J

Improve system interoperability and use of standards

5.J.1
Reusable & extensible software components, formats, & development processes including standards & testbeds, commercial standards & protocols

1. Identify and infuse NASA-specific requirements into commercial standards processes

5.J.2
Leverage component-based technologies and middleware

1. Web service bonding and chaining
2. Thin-client data management (i.e., leverage web search technologies for geospatial data)

K

Improve system management and operation

5.K.1
Interoperability among multiple planning and scheduling systems for diverse elements

5.K.2
Operator interface tools for constellation management

5.K.3
Standard interfaces between sensors and data consumers

L

Reduced life cycle cost of ground and space operations and processing

5.L.1
Establish reference architectures leveraging commercial and military technologies

5.L.2
Leverage systems engineering tools/environments to increase reuse of software, test plans, and case/scenarios for earth science

5.L.3
Tools to assist development of complex Earth Science processing

1. On-board processing
2. Parallel processing
3. Embedded processing
4. Distributed processing

5.L.4
Techniques to manage scalability issues related to performance and accuracy in processing, data fusion, storage and access

1. Standard data representation

5.L.5
Management tools for large evolving systems