1. The IPY Data and Information Service—How do we get there? IPY Data Workshop Cambridge, England 3 March 2006 World Data Center for Glaciology, Boulder Facilitating the international exchange of snow and ice data Mark A. Parsons IPY Data Policy and Management Sub-committee IPY Data and Information Service Electronic Geophysical Year

2. IPY1 IPY2 IGY (IPY3) IPY 4

3. IPYDIS; Mark A. Parsons, 3 March 20063 What will IPY4 bring? The Challenge! Will researchers be able to find all the data relevant to their research and see relationships between data sets. Access Will they be able to merge and integrate different data sets across experiments and disciplines? Interoperability Will they be able to subset, visualize, and transform the data? Usability Will they be able to retrieve and understand IPY4 data in 2050? Preservation IPY4

4. IPYDIS; Mark A. Parsons, 3 March 20064 Organization of IPY Data Management IPY Joint Committee Data Policy & Management Subcommittee scientists data managers funding agencies Programme Office Data & Information Service eGY Projects Data Centers, Virtual Observatories, etc. Users

5. IPYDIS; Mark A. Parsons, 3 March 20065

6. 6 Alternate Views of the DIS DIS?

7. IPYDIS; Mark A. Parsons, 3 March 20067 Systems and Innovation The Standish Group’s “CHAOS report”. An assessment of over 40,000 IT application projects Succeeded “Challenged” Failed “We're entering a new world in which data may be more important than software.” - Tim O'Reilly

8. IPYDIS; Mark A. Parsons, 3 March 20068 The People Part Service counts. “A striking proportion of project difficulties stem from people in both customer and supplier organisations failing to implement known best practice.” — 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

9. IPYDIS; Mark A. Parsons, 3 March 20069 The People Part: Science and Data Management Many have stated the need to involve scientists in data management, but… It is also important to involve data managers in conducting science. Field Experiments: 20% increase in data quality (Parsons, et al. 2004) 70% of experiment cost is data assembly (Bernhardsen 1992, Longley, et al. 2001) Observing systems

10. IPYDIS; Mark A. Parsons, 3 March 200610 Preservation and Access—Two Peas in a Pod Scientific Data Stewardship: “preservation and responsive supply of reliable and comprehensive data, products, and information for use in building new knowledge to…” —US Global Climate Research Program, 1998 “the long-term preservation of the scientific integrity, monitoring and improving the quality, and the extraction of further knowledge from the data” — H. Diamond et al., NOAA/NESDIS, 2003

11. IPYDIS; Mark A. Parsons, 3 March 200611 Access. What is it? Preservation requirements are well defined in the Open Archive Information System (OAIS) Reference Model, but No similar model for access requirements Not even a common definition of “access” and what restricts it Unique access requirements for social science data and non-digital collections (physical samples, photographs, audio, etc.) “Facts are terrible things if left sprawling and unattended…” - Norman Cousins

12. IPYDIS; Mark A. Parsons, 3 March 200612 Standards—Essential but Cumbersome Some Possibilities: ISO19115 metadata standard OAIS Reference Model OGC data transfer standards Other OGC Standards “Web Services” (WSDL, SOAP) Other XML-based standards (GML, OAI-PMH, RSS,…) Etc, etc, No New Standards! “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

13. IPYDIS; Mark A. Parsons, 3 March 200613 011000101001001111010111 000111101100101010001110 011100101010011101010100 111000110101101000010000 10010100100101011001001 00010101001001001010101 01001010100101001010100 000111110010110101010110 100010111101011010110101 010011000101001001111010 111000111101100101010001 110011100101010011101010 100111000110101101000010 00010010100100101011001 00100010101001001001010 10101001010100101001010 100000111110010110101010 110100010111101011 Issues with the Data Itself Formats: Archives and users may have different needs Consider four themes (Raymond, 2004) Transparency Interoperability Extensibility Storage or transaction economy “We often get blinded by the forms in which content is produced, rather than the job that the content does.” - Tim O’Reilly

14. IPYDIS; Mark A. Parsons, 3 March 200614 Other Questions and Issues How interoperable can we be? What does “portal” mean to you? How do maximize use of existing data systems and structures? CODATA? WDCs? How does IPY data fit into current operational systems? What about GEOSS—can IPY be a prototype? Which technological trends can help us? (ontologies, virtual observatories, portals, etc.) How do we incorporate historical data? Need a solid business model esp. for the long-term

15. IPYDIS; Mark A. Parsons, 3 March 200615 Breakout Groups Methods for Data discovery—portals Paul Berkman, room 370 Ensuring data submission and publicatio-- carrots and sticks Jim Moore, room 303b Semantics, ontologies, and language Heather Lane, main room

16. IPYDIS; Mark A. Parsons, 3 March 200616 Charge to Breakout Groups 1.Determine rapporteur 2.Explicitly define problem(s) 3.Identify options to solve problem 4.Recommend steps to solve problem 5.Present to whole group for feedback 6.Revise 7.Write up results to be part of a larger workshop report. Include outstanding issues, next steps, etc. Workshop report will be presented to broader IPY research community for feedback and buy in.

17. IPYDIS; Mark A. Parsons, 3 March 200617 Data Systems Today © N. Carr 2006

18. IPYDIS; Mark A. Parsons, 3 March 200618 What they need to become © N. Carr 2006