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Inter-American Workshop on Environmental Data Access Panel discussion on scientific and technical issues Merilyn Gentry, LBA-ECO Data Coordinator NASA.

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Presentation on theme: "Inter-American Workshop on Environmental Data Access Panel discussion on scientific and technical issues Merilyn Gentry, LBA-ECO Data Coordinator NASA."— Presentation transcript:

1 Inter-American Workshop on Environmental Data Access Panel discussion on scientific and technical issues Merilyn Gentry, LBA-ECO Data Coordinator NASA / LBA-ECO Project Office & University of Tennessee 04-March-2004

2 NASA Field Experiments Over the last 2 decades, NASA has been funding field experiments for ground-truthing satellite observations –FIFE – Grasslands/prairie of midwestern U.S. - Kansas –BOREAS – Boreal forests of Canada –Safari 2000 – South Africa –LBA-ECO – LBA project led by Brazil Data from these experiments are archived at ORNL DAAC

3 Data Policy Considerations NASA Data Policy –Data should be made available to the public as quickly as reasonably possible, allowing for adequate quality assured Brazilian Law –Data collected in Brazil must remain in Brazil LBA Data Policy –All data resulting from the LBA study will be archived in Brazil –All LBA data will be made available to the public

4 LBA DATA RAW PRELIMINARY YEAR 1 PRELIMINARY YEARS 1..2.. >> FINAL MATURITY DOCUMENTATION UPDATE METADATA FTP TO INPE/CPTEC PROCESS Register Metadata Complete Available to Public Before Leaving Brazil

5 Goal: Long-term archive & distribution The “scientific and technical requirements for long-term preservation and accessibility of environmental data” was a key factor in the system design ORNL DAAC is part of a network of NASA data archive and distribution centers forming the Earth Observing System (EOS) DIS As a member of this network, ORNL DAAC must conform to certain EOSDIS protocols (interoperability) ORNL DAAC has evolved its own data archive standards and recommendations as well, “20-year rule”: accessible, retrievable, usable

6 Build a prototype -- KISS NASA funded ORNL to develop a system: –Efficient, simple, highly automated –Computer platform independent –Use Web browser interfaces / software –Same system works as data matures from raw, preliminary, to final data –PI maintains full control of data visibility –Painless user “learning curve” –Yet with flexible, comprehensive searching

7 The System Today 2 browser-based interfaces –LME – The LBA Metadata Editor –Beija-flor – Metadata Search & Data Retrieval System Uses traditional search engine technology, e.g. Yahoo, Altavista However, searches from only sources identified as LBA DIS metadata Metadata Data

8 Technical interoperability of LBA DIS Hardware & Software Metadata –Uses XML (ASCII) code and standard metatag conventions –Uses FGDC metadata standards + LBA-specific fields –Imports from/exports to a DIF Data –Data formats are not dictated by LBA DIS, though proprietary formats are discouraged –Data files can reside at LBA DIS nodes, other data centers, PI web sites

9 Metadata_File.xml ASCII text and contains standard metatags that are accessible to many search engines Also contains URLs to allow users to link to related data, documentation, and ancillary files, regardless of format Metadata_File.xml ASCII text and contains standard metatags that are accessible to many search engines Also contains URLs to allow users to link to related data, documentation, and ancillary files, regardless of format LBA Metadata File – the key to technical interoperability Data1.txt Data2.xls File.jpg Doc.txt Search engine

10 Semantic interoperability of environmental data across disciplines and languages English is the language standard Every LBA-ECO team has a U.S. PI and a Brazilian Co-Investigator Minimize space science jargon Beija-flor offers multiple search approaches: –Fielded searches – pick lists provided for values in the metadata –Character string searches accommodate more open-ended queries (and possibly less-expert users) –Map-based / spatial searches and temporal range searches –Combination searches –Browsing

11 Facilitating interdisciplinary and international access to environmental data resources Both countries have committed long-term support for the archive and distribution of the LBA data collection: –LBA DIS in Brazil –ORNL DAAC in the U.S. Global Change Master Directory will include a “DIF” for every LBA data set archived in the U.S. Links to non-LBA Amazonian-related data are available via Beija-flor The LBA metadata will be available for indexing by non- LBA search engines and metadata databases

12 Human factors affecting data availability Scientists want to hold on to their data as long as they can Data collected is often part of students’ thesis Few incentives for scientists to publish their data Documentation requirements are often prohibitive

13 Transfer Raw Preliminary Year 1 Data Products, Data Set Descriptions, Papers, Posters LBA Metadata Editor (LME) Preliminary Years 2+ > Data Archive at CPTEC PI Produces Data 1 1 PI Registers/Updates Metadata 2 2 3 3 PI Transfers Data To CPTEC Beija-Flor Search Engine for LBA Data Metadata are compiled in Receive 4 4 The LBA community and the public can access via Beija-Flor Search Final QA’d with Documentation Brazilian Counterpart

14 What is Needed for Archiving LBA-ECO Data Sets at the ORNL DAAC? Reference: Best Practices for Archiving Data 1.Metadata –LBA project parameters (i.e., Beija-flor metadata) must comply with latest GCMD / EOSDIS standards 2.Data files –Suggested format: tabular data in ASCII, Gridded data in ASCII Grid, Image data in binary or non-proprietary format –Self-describing to identify key entries such as parameter names and units of measure www.daac.ornl.gov/DAAC/PI/info.html

15 What is Needed for Archiving LBA-ECO Data Sets at the ORNL DAAC (continued) 3. Data Set Documentation Documentation should include what a user would need to know about the data 20+ years from now; i.e., the 20-year rule –Data collection goals and description –Description of sample collection sites –Description of measurement methods (e.g., calibration, calculations, software) –Known errors and problems –Description of data file organization –Description of data reporting conventions (e.g., parameter names, units, codes, flags, example data records) –Key information from B-f (e.g., investigator (s), abstract, spatial and temporal attributes, data set citation, references, etc.)


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