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IPY, eGY and Data Management Mark A. Parsons co-chair IPY Data Policy and Management Subcommittee

IPY, eGY and Data Management Mark A. Parsons co-chair IPY Data Policy and Management Subcommittee. World Data Center for Glaciology, Boulder. Facilitating the international exchange of snow and ice data. American Geophysical Union Baltimore, Maryland, USA 24 May 2006.

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IPY, eGY and Data Management Mark A. Parsons co-chair IPY Data Policy and Management Subcommittee

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  1. IPY, eGY and Data ManagementMark A. Parsonsco-chair IPY Data Policy and Management Subcommittee World Data Center for Glaciology, Boulder Facilitating the international exchange of snow and ice data American Geophysical Union Baltimore, Maryland, USA 24 May 2006

  2. Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  3. Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  4. 0 11 11 01 00 00 11 01 10 11 1 Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  5. Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  6. What is a Utility? • Simple • Predictable • Reliable • Extensible • Accessible, i.e. usable • Durable It is infrastructure Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  7. “The core functions of IT—data storage, processing, and transport— … are becoming costs of doing business that must be paid for by all but provide distinction to none” – Nicholas G. Carr, “IT Doesn’t Matter” 2003 “We need to start thinking about software in a way more like how we think about building bridges, dams, and sewers” – Dan Bricklen, “Software that lasts 200 Years” 2004 IT is Infrastructure Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  8. Timeline of a Utility Users or Units eGY / IPY? Unit Cost Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  9. What does this mean? It can guide our thinking about: • Interface design • Interoperability • Transfer mechanisms • Communication protocols • Usability • Software design • Cost models • Data preservation • Distributed vs. centralized data management Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  10. The Challenge! • Will you be able to find all the data relevant to your research and see relationships between data sets. Access • Will you be able to merge and integrate different data sets across experiments and disciplines and assimilate them into your model? Interoperability • Will you be able to subset, visualize, and transform the data? Usability • Will your students be able to retrieve and understand IPY4 data in 2050? Preservation Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  11. Some common themes • Outreach to the scientific community • Data discovery and access • Interoperability • Explore new technologies and techniques—ontologies, virtual observatories • Long term preservation Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  12. Vision: a cultural shift in science You are not finished until you have done the research, published the results, and published the data, receiving formal credit for everything. “Preserve or Perish” Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  13. 18 May 2006

  14. Interoperability “What few things must be the same so everything else can be different.”- Eliot Christian • A few good standards: • ISO19115 metadata • Open Geospatial Consortium • Explore advanced semantic approaches Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  15. The People Part “A striking proportion of project difficulties stem from people in both customer and supplier organisations failing to implement known best practice.” Service counts. — Oxford University/Computer Weekly survey of public and private sector IT projects (emphasis added) However, people are much more able to adapt to change, uncertainty, and messy systems Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  16. Design for Durability “Fold knowledge into data, so program logic can be stupid and robust.” TransparencyInteroperabilityExtensibilityStorage economy Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  17. Documentation (metadata) goes on forever Describe uncertainty Challenge your assumptions to speak to you audience Documentation “We must not … start from any and every accepted opinion, but only from those we have defined — those accepted by our judges or by those whose authority they recognize.” —Aristotle c. 350 BC Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

  18. A scholar’s positive contribution is measured by the sum of the original data that he contributes. Hypotheses come and go but data remain. – Santiago Ramón y Cajal (Nobel Prize winner,1906) in Advice to a Young Investigator (1897) Parsons; IPY, eGY and Data Management; AGU,2 4 May 2006

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