1. Data Life Cycle GeoData 2011 Workshop March 2, 2011, Broomfield, CO Peter Fox (RPI) foxp@rpi.edu, pfox@cs.rpi.edufoxp@rpi.edupfox@cs.rpi.edu Tetherless World Constellation http://tw.rpi.eduhttp://tw.rpi.edu

2. Motivation, temptation A world of challenges – as if Tim did not motivate you enough Data and people at the heart of it Researchers and their data are valuable (as ever) But not enough attention, focus 2Tetherless World Constellation

3. 3 Working premise Scientists – actually ANYONE - should be able to access and use a global, distributed knowledge base of scientific data that: appears to be integrated appears to be locally available But… data and information is obtained by multiple means (instruments, models, analysis) using various (often opaque) protocols, in differing vocabularies, using (sometimes unstated) assumptions, with inconsistent (or non-existent) meta-data. It may be inconsistent, incomplete, evolving, and distributed AND created in a form that facilitates generation, not use (except by accident) And … significant levels of semantic heterogeneity, large- scale data, complex data types, legacy systems, inflexible and unsustainable implementation technology… Uh-oh

4. Definitions Data - are encodings that represent the qualitative or quantitative attributes of a variable or set of variables. Data (plural of "datum", which is seldom used) - are typically the results of measurements and can be the basis of graphs, images, or observations of a set of variables but are now models, etc. Data - are often viewed as the lowest level of abstraction from which information and knowledge are derived*** 4

5. Definitions ctd. Information –Representations (of facts? data?) in a form that lends itself to human use Knowledge –Check out Wikipedia…. meaning Metadata – data about data Metainformation – information about information Data documentation – integrated collection of information and metadata intended to support all aspects of data (find, access, use…) 5

6. Examples Rock sample: –Data – weight, composition, shape, size –Information – images of the rock as collected –Knowledge – evidence of geologic activity –Metadata – location and time of collection –Documentation – published lab report … Weather –Data – wind speed and direction, temperature,.. –Information – weather map with contours and features –Knowledge – high pressure system, stable weather –Metadata – type of radar, sensor, use of model 6

7. Cox/2005 AGU Spring Fields vs. objects classic geology “Feature” viewpoint classic geophysics “Coverage” viewpoint simple data structures collated/gridded ready for analysis netCDF, HDF-EOS complex data database insertion complete feature interpretations XML documents

8. Definitions ctd. Data life-cycle elements (simple 3-level) –Acquisition: Process of recording or generating a concrete artefact from the concept (see transduction) –Curation: The activity of managing the use of data from its point of creation to ensure it is available for discovery and re-use in the future (http://www.dcc.ac.uk/FAQs/data- curator)http://www.dcc.ac.uk/FAQs/data- curator –Preservation: Process of retaining usability of data in some source form for intended and unintended use –Stewardship: Process of maintaining integrity across acquisition, curation and preservation 8

9. Definitions ctd. Stewardship -> Management: Process of arranging for discovery, access and use of data, information and all related elements. Also oversees or effects control of processes for acquisition, curation, preservation and stewardship. Involves fiscal and intellectual responsibility. Not explicitly the focus of this workshop.. 9

10. 10.. Data has Lots of Audiences From “Why EPO?”, a NASA internal report on science education, 2005 More Strategic Less Strategic Science too!

11. Too many diagrams

12. 20080602 Fox VSTO et al.12 Curation stages People!

13. On to Life Cycle… Life Cycle, lifecycle, life-cycle … By now I hope you know I know it’s about a mix of factors Research data and researchers

14. Digital Curation Center model http://www.dcc.ac.uk/resources/curation-lifecycle-model

15. MIT DDA Alliance model http://libraries.mit.edu/guides/subjects/data-management/cycle.html

16. It does not go on forever…

17. Business or software model?

18. 18 Physical quantity versus measured as quantity Value and units? Reference frame? Reference units? Value and units? Courtesy Krishna Sinha (VT)

19. 21 September 2015© GEO Secretariat Local in-situ Networks and Systems Air pollution measurement station Emden, Germany Local and national air pollution networks Venice, Italy, and Indonesia

20. © GEO Secretariatslide 20 Global in situ Networks and Systems Global Seismic Network Signal from the Indian Ocean Earthquake - 26 December 2004 Global Argo Float Array Measuring ocean temperature and salinity

21. © GEO Secretariat ENVISAT RA-2 observing the Gulf Stream current velocity Satellite Observation Systems

22. © GEO Secretariat Can we really fulfil futures with diagrams?

23. Modeling the Climate as a System Transformative Science, Data Infrastructures and the IPCC Experience Lawrence Buja National Center for Atmospheric Research Boulder, Colorado CAM T341- Jim Hack

24. Briefing on Results : USGS Science Strategy to Support U.S. Fish & Wildlife Service Polar Bear Listing Decision: a 6 month effort U.S. Department of the Interior U.S. Geological Survey

25. E.g. Solar Irradiance

27. One composite, one assumption

28. Another composite, different assumption

29. 29 Temptation To run screaming from the room? –Wait – there are cookies (and a reception)! To really focus on what you are DOING (less that WANT to do) and NOT DOING, but need to – near term (next week) Talk about it… argue it… listen to others To focus on value – the real and immediate value to you and the people you work with and institution/ communities you work for/ with!

30. Questions? foxp@rpi.edu