1. Reconstituting the Ocean: a tale from U.S. JGOFS Cyndy Chandler (MCG, WHOI) U.S. JGOFS Data Management Office and Ocean Carbon and Biogeochemistry Coordination and Data Management Office 10 August 2005 MBARI-MMI Marine Metadata Workshop Boulder, CO

2. 10 August 2005 U.S. JGOFS DMO 2 of 17 Question: What do users want from metadata anyway? This presentation will focus mostly on usage metadata.

3. 10 August 2005 U.S. JGOFS DMO 3 of 17 Introduction Introduction What is U.S. JGOFS?What is U.S. JGOFS? Ocean reconstitution explained Ocean reconstitution explained merged productsmerged products metadatametadata Topics in today’s presentation:

4. 10 August 2005 U.S. JGOFS DMO 4 of 17 What is U.S. JGOFS? part of multinational JGOFS part of multinational JGOFS U.S. Global Change Research Program (US GCRP), Scientific Committee on Oceanic Research (SCOR), and International Geosphere-Biosphere Programme (IGBP) U.S. Global Change Research Program (US GCRP), Scientific Committee on Oceanic Research (SCOR), and International Geosphere-Biosphere Programme (IGBP) long term (U.S. 1989-2005) long term (U.S. 1989-2005) multidisciplinary (bio, chem, PO, geology) multidisciplinary (bio, chem, PO, geology) process studies (U.S. 1989-1998), time-series, global surveys, synthesis and modeling, data management process studies (U.S. 1989-1998), time-series, global surveys, synthesis and modeling, data management investigate ocean carbon flux investigate ocean carbon flux U.S. Joint Global Ocean Flux Study

5. 10 August 2005 U.S. JGOFS DMO 5 of 17 Lessons Learned...  metadata is of critical importance   accurate, complete, available with data   monitor emerging standards   define minimum metadata requirements   standards-compliant solutions where possible   complete metadata record enables reuse of data metadata assembly is time consuming, but is the key to enabling secondary (reuse) of data

6. 10 August 2005 U.S. JGOFS DMO 6 of 17 metadata documentation providing answers to the who, what, where, when, why and how questions

7. 10 August 2005 U.S. JGOFS DMO 7 of 17 Lessons Learned...   quality assurance is an ongoing process   intense QA process during initial acquisition and ingestion into data system   problems discovered as data are utilized by others ◊ ◊ insufficient or inaccurate metadata   process of data product synthesis becomes a valuable diagnostic tool for improving data quality

8. 10 August 2005 U.S. JGOFS DMO 8 of 17 Data Synthesis merged data products merged data products combine all data from the same sampling device for a defined geospatial area and time range “attempt to put the ocean back together” combine all data from the same sampling device for a defined geospatial area and time range “attempt to put the ocean back together”

9. 10 August 2005 U.S. JGOFS DMO 9 of 17 U.S. JGOFS Process Study Areas

10. 10 August 2005 U.S. JGOFS DMO 10 of 17 CTD photos let the frenzy begin!

11. 10 August 2005 U.S. JGOFS DMO 11 of 17 Arabian Sea Niskin Bottle Data 73 data entities from 6 cruises in 1995 data contributed by 46 different PIs 73 data entities from 6 cruises in 1995 data contributed by 46 different PIs

12. 10 August 2005 U.S. JGOFS DMO 12 of 17 Results of Data Synthesis merged products for bottle and CTD data merged products for bottle and CTD data bottle data products include many parameters: bottle data products include many parameters: Arabian Sea > 110 North Atlantic > 80 Equatorial Pacific > 110 Southern Ocean > 170

13. 10 August 2005 U.S. JGOFS DMO 13 of 17 The Merging Process establish rules establish rules which data entities to combine?which data entities to combine? common sampling device common sampling device what determines the columns and rows?what determines the columns and rows? could not have merged this many different data entities without sufficient metadata could not have merged this many different data entities without sufficient metadata

14. 10 August 2005 U.S. JGOFS DMO 14 of 17 Columns and Rows each column contains data from a different parameter (variable) each column contains data from a different parameter (variable) parameter names are uniquely defined by long name (definition of term), units (encoding) and methodology rows are uniquely defined by X,Y,Z and T rows are uniquely defined by X,Y,Z and T usually this could be done by matching time, longitude, latitude, depth, station, cast and bottle number

15. 10 August 2005 U.S. JGOFS DMO 15 of 17 Property Depth LAS v6 Property- Depth Arabian Sea Nitrate from merged product generated by DMO from in situ Niskin bottle data

16. 10 August 2005 U.S. JGOFS DMO 16 of 17 The Challenge the originating PI doesn’t need an explicit, written record of metadata during the initial analysis of their data the originating PI doesn’t need an explicit, written record of metadata during the initial analysis of their data the metadata supplied with a data contribution is often insufficient to support secondary use of data the metadata supplied with a data contribution is often insufficient to support secondary use of data

17. 10 August 2005 U.S. JGOFS DMO 17 of 17 Summary What do users want from metadata anyway? users require sufficient information to: determine data of interest determine data of interest determine quality of data source determine quality of data source answer basic meta questions: who, what, where, when, how (and sometimes why) answer basic meta questions: who, what, where, when, how (and sometimes why)

18. 10 August 200509 August 2005 U.S. JGOFS DMO 18 of 17 U.S. JGOFS web site http://usjgofs.whoi.edu