Summary of the eosdis reference architecture
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Summary of the EOSDIS Reference Architecture. ESIP Federation Meeting ESDSWG SPG July 22, 2010. Outline. Background EOSDIS Architecture Framework Science Data System Functions Cross-cutting Functions Scenarios Satellite Data Field Campaign Airborne Issues. Flight Operations,

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Summary of the eosdis reference architecture

Summary of the EOSDIS Reference Architecture

ESIP Federation Meeting

ESDSWG SPG

July 22, 2010


Outline

Outline

  • Background

  • EOSDIS Architecture Framework

    • Science Data System Functions

    • Cross-cutting Functions

  • Scenarios

    • Satellite Data

    • Field Campaign

    • Airborne

  • Issues


Eosdis context

Flight Operations,

Data Capture,

Initial Processing,

Backup Archive

Data Transport

to Data Centers/

SIPSs

EOS

Spacecraft

EOSDIS Context

Science Data Processing,

Data Mgmt, Interoperable Data Archive, & Distribution

Data Acquisition

Distribution and Data

Access

Tracking & Data Relay Satellite (TDRS)

Research

Education

EOS Data and Operations System (EDOS)

Data Processing

White SandsComplex(WSC)

EOSDIS Data

Centers

Value-Added

Providers

Internet

(Search, order,

distribution)

Interagency

Data Centers

EOS Operations Center (EOC) Mission Control

DirectBroadcast(DB)

Earth

System Models

International

Partners

NASA Integrated Services Network (NISN) Mission Services

EOS PolarGround Stations

Instrument Teamsand Science

Investigator-ledProcessing System

(SIPS)

Decision Support

Systems

Direct Broadcast/

Direct Readout Stations

ESDIS

ESMO


Eosdis facilities

Data

Center

SIPSs

EOSDIS Facilities

Data centers, collocated with centers of science discipline expertise, archive and distribute standard data products produced by Science Investigator-led Processing Systems (SIPSs)

ASF DAAC

SAR Products

Sea Ice, Polar

Processes

SEDAC

Human Interactions

in Global Change

CDDIS

Crustal Dynamics

Solid Earth

NCAR, U of Col.

HIRDLS, MOPITT, SORCE

LP DAAC

Land Processes

& Features

GSFC

GLAS, MODIS, OMI, OBPG

GES DISC

Atmos Composition &

Dynamics, Global

Modeling, Hydrology,

Radiance

Key

NSIDC DAAC

Cryosphere, Polar

Processes

OBPG

Ocean Biology &

Biogeochemistry

JPL

MLS, TES

ORNL DAAC

Biogeochemical

Dynamics, EOS Land

Validation

LAADS/

MODAPS

Atmosphere

LaRC

CERES, SAGE III

San Diego

ACRIM

GHRC

Hydrological Cycle &

Severe Weather

PO.DAAC

Ocean Circulation

Air-Sea Interactions

ASDC

Radiation Budget,

Clouds, Aerosols,

Tropo Chemistry

GHRC

AMSR-E, LIS


Purpose

Purpose

  • Purpose of the EOSDIS Reference Architecture

    • Documents the way EOSDIS does business, in all of its variations

    • Enables discussion with other communities and agencies on earth science data system development

    • It provides a framework for the insertion of community developed systems into the core system

    • Informs new missions of the current processes

    • Serves as a starting point for a future-looking Earth Science Data System Architecture


Evolution of eosdis data system features

Discipline and mission specific data systems

Only community-specific standards

Only directory functions to point and link users to various data systems

Multi-site access and data inter-use cumbersome

Improved access to data with 90s technology

Cross-system search and order access via interoperability data model

Site-specific interfaces at DAACs/SIPs

Common distribution format (HDF); other formats also supported

Evolution of EOSDIS Data System Features

Technology,

Funding,

Lessons

Technology,

Funding,

Lessons

<1990

mid-1990s


Evolution of eosdis data system features1

Support for high data volumes, ambitious performance requirements, high availability/reliability

Integrated core infrastructure plus loosely coupled elements from community

Common data model

Automated metadata creation and ingest

No need for cross-site metadata translation

FGDC standards compliance

Expanded set of software tools and services

Flexible options for supporting or interoperating with external data sources

Coexistence of heterogeneous, distributed data providers/ information partners

Optimal set of core standards

Support for community-specific standards

Reusable software components

Exploitation of Service Oriented Architecture

On-line archives and cross-system service invocation

Ease of innovation and technology infusion

More services to meet community demands

Evolution of EOSDIS Data System Features

Technology,

Funding,

Lessons

Technology,

Funding,

Lessons

Technology,

Funding,

Lessons

Late 90s to present

Near-Future


Core and community capabilities characteristics

Core and Community Capabilities - Characteristics


Eosdis architecture framework

EOSDIS Architecture Framework


Satellite data scenario 1

Satellite Data Scenario #1


Summary of the eosdis reference architecture

NASAEDOS

JAXA-EOC

L1A Product Generation

Ground

Stations

NSIDC DAAC

Data Archive and Distribution

AMSR-E Data Flow

RBD & PDS

Level-0

NASAFDS

GBAD

Level-1

Level-1

PO.DAAC

Level-1

SIPS-RSS

TLSCF

Level-2 and Level-3

L2A algorithm

L2A Product Generation

Science

Software

I&T

L2 and L3

DAPs

Product Delivery

Record Server (PDRS)

SIPS-GHCC

L2B and L3 Algorithms

Algorithm

Teams

L2B and L3 Product Generation

(science, metadata, qa, ph, subsets, browse, DAPs)

Rain

Snow

Data

Ocean

Sea Ice

Land


Summary of the eosdis reference architecture

Descriptions of EOSDIS data holdings can be found at the archiving data center.

See AMSR-E at the National Snow and Ice Data Center (NSIDC).

Select the Order Data option.

http://nsidc.org/data/amsre/


Summary of the eosdis reference architecture

Users have a variety of ways to access EOSDIS data.

For example select the WIST option.

http://nsidc.org/data/amsre/order_data.html


Warehouse inventory search tool wist

Warehouse Inventory Search Tool (WIST)

  • The EOS ClearingHouse (ECHO) is a metadata catalog of NASA’s EOS data and a registry for related data services (e.g. reformatting, pattern recognition). ECHO’s catalog contains more than 2800 data sets held at 12 EOSDIS data centers.

  • WIST, the Warehouse Inventory Search Tool, is the primary web-based client for discovering and ordering cross-discipline data from all of ECHO’s metadata holdings. WIST allows users, including those without specific knowledge of the data, to search science data holdings, retrieve high-level descriptions of data sets and detailed descriptions of the data inventory, view browse images, and submit orders via ECHO to the appropriate data providers.

  • The WIST search-and-order tool has the following features: 

    • Search capability—Allows a user to explore the list of data sets or granules returned by a search by viewing their temporal coverage, spatial coverage, attributes (metadata), related documents (guide search), and browse images.

    • Order function—Allows the user to select data for ordering, choose packaging information, enter ordering information (such as shipping address), place an order, and view order status.

      Reference:

      http://wist.echo.nasa.gov/~wist/api/imswelcome/


Other scenarios

Other Scenarios

  • Field Campaign (In situ) scenario

  • Ground and Ocean-based scenario

  • Airborne scenarios

  • Ancillary scenarios

  • Satellite scenarios

    • US

    • International


Examples of eosdis data center implementations

Examples of EOSDIS Data Center Implementations


Eosdis reference architecture

EOSDIS Reference Architecture

  • Plan both a document & website

  • EOSDIS Reference Architecture Draft

    • Under discussion and drafting components

      • DAACs

      • Committee of NASA data system planners

    • Scenarios Developed

      • Satellite Data

      • Field Campaign

      • Airborne

  • Basic Website in place

  • However, the reference architecture only documents EOSDIS functions in a very broad approach

    • Does not take the place of official NPR documentation

    • Each new Mission requires direct communication and distinct documentation


Example science interfaces documentation

Example Science Interfaces & Documentation

ESDIS Project

IPA

Flight Project

ICD

W/A

Science Team

ESDIS Project

DMR

ADURD

ATBD

ICD

ICD

IRD

ICD

OA

EDOS

Data Centers

SIPSs

ICD

ICD

Users

ICD

ICD

ICD

ICD

ECHO

A subset of interfaces are shown for mission operations

Networks

ESDIS Metrics System

ESMO Project

MRT Mission Readiness Test Plan

http://esdis.eosdis.nasa.gov/dsdocs


Interoperability on many levels

Interoperability on Many Levels

  • Process Methodology

    • Configuration control

    • Business processes

    • Policy processes

  • Software Reuse – S4PA, subsetting

  • Standards

    • Metadata model

    • Data formats

    • Interface controls

  • EOSDIS ClearingHouse

  • EOSDIS Metrics components


Eosdis business model

EOSDIS Business Model

  • Budget preparation and tracking of actual expenses is performed across the Project.

  • Components of EOSDIS submit yearly budgets and work plans

  • Budgets and actuals are tracked monthly against phasing plans and schedules

  • Metrics are collected for both technical and fiscal management

  • Coordination across the architecture allows for cost savings


Specific areas of cost tracking

Specific Areas of cost tracking


Conclusion

Conclusion

  • The EOSDIS Reference Architecture is still under draft by many staff members

    • Thanks to all of you!!!

  • Any questions? Comments?

  • Feel free to contact me:

    • Jeanne Behnke

    • [email protected]


Summary of the eosdis reference architecture

AMSR-E – Advanced Microwave Scanning Radiometer - Earth Observing System

JAXA – National Space Development Agency (Japan)

TLSCF – Team Leader Science Computing Facility (AMSR-E)

RSS – Remote Sensing Systems (company)

GHCC – Global Hydrology and Climate Center (MSFC, Huntsville, Ala)

DAAC – Distributed Active Archive Center

PO.DAAC – Physical Oceanography DAAC

NSIDC – National Snow and Ice Data Center (NSIDC)

DAP – Delivery Algorithm Package

GBAD – Ground based attitude determination

FDS – Flight Dynamics System

RBD – Rate buffered data

PDS – Production data set


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