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Curating data for integrated science

Curating data for integrated science. Chris Rusbridge NERC Data Management Workshop February 2009. Contents. Curation Integrated science Poetry & Philosophy of D H Rumsfeld Designated Community & Knowledge Base Curation and integration Data and Texts. Curation. Wikipedia

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Curating data for integrated science

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  1. Curating data for integrated science Chris Rusbridge NERC Data Management Workshop February 2009

  2. Contents • Curation • Integrated science • Poetry & Philosophy of D H Rumsfeld • Designated Community & Knowledge Base • Curation and integration • Data and Texts

  3. Curation • Wikipedia • Curator: a content specialist responsible for an institution's collections and, together with a publications specialist, their associated collections catalogs. • Digital Curation: the curation, preservation, maintenance, collection and archiving of digital assets • Sheer curation: an approach to digital curation where curation activities are quietly integrated into the normal work flow of those creating and managing data and other digital assets. • DCC: Digital curation is maintaining and adding value to a trusted body of digital information for current and future use.

  4. Integrated Science? • Mostly educational: easy-to-swallow science • Some strange things • One nice essay • Lots of environmental science

  5. University of Integrated Science, California • Degree Programs: • Vertical reality • Tachyon Holistic Wellness • Tantra (including Sexual Alchemy for Singles 101) • Vegan and Live Food Nutrition Masters Program • …and that’s it!

  6. Edward O Wilson (1998) • “Science: organized systematic enterprise that gathers knowledge about the world and condenses the knowledge into testable laws and principles. Defining traits are • 1st, confirmation of discoveries & support of hypotheses through repetition by independent investigators, preferably with different tests & analyses; • 2nd, mensuration, the quantitative description of the phenomena on universally accepted scales; • 3rd, economy, by which the largest amount of information is abstracted into a simple and precise form, which can be unpacked to re-create detail; • 4th, heuristics, the opening of avenues to new discovery and interpretation. • And 5th, and finally, is consilience, the interlocking of causal explanations across disciplines.” • Consilience: “the concurrence of multiple inductions drawn from different data sets” Wilson, E. O. (1998, 27 March 1998). Integrated Science and The Coming Century of The Environment. Science Magazine, 279, 2048-2049.

  7. Wilson concluding • “Arguably the foremost of global problems grounded in the idiosyncrasies of human nature is overpopulation and the destruction of the environment. The crisis is not long-term but here and now; it is upon us. Like it or not, we are entering the century of the environment, when science and polities will give the highest priority to settling humanity down before we wreck the planet.”

  8. NCAR: January 2009 • The Integrated Science Program will promote scientific frontiers that are dependent on an integrated approach, across NCAR laboratories and across disciplines. ISP will focus on thematic areas where the mission and expertise at NCAR, and in the university atmospheric and related sciences community, can be advanced by contributions from the social and environmental sciences beyond those that typically occur within single programs or departments. These areas include, but are not limited to, Earth system-society interactions, building societal resilience to weather and climate hazards, hydrologic sciences, and biogeochemistry.

  9. Fisheries & Oceans Canada • Integrated Science Data Management (ISDM) Providing Access to Ocean Data • “ISDM's mandate is to manage and archive ocean data collected by DFO, or acquired through national and international programmes conducted in ocean areas adjacent to Canada, and to disseminate data, data products, and services to the marine community in accordance with the policies of the Department.”

  10. Integrated Science • We need a definition that works better; something like: “The application of multiple scientific disciplines to one or more core scientific challenges” • Examples of integrated sciences? • Archaeology • Environmental sciences

  11. Integrated Science implications • Scientists will be using unfamiliar data, therefore • Data curators and managers must make their data available for unfamiliar users! • And now for something unfamiliar?

  12. Poetry & Philosophy of D H Rumsfeld Hart Seely, April 2, 2003, SLATE http://www.slate.com/id/2081042/

  13. A Confession ‘Once in a while, I'm standing here, doing something. And I think, "What in the world am I doing here?" It's a big surprise.’ —May 16, 2001, interview with the New York Times

  14. Clarity ‘I think what you'll find, I think what you'll find is, Whatever it is we do substantively, There will be near-perfect clarity As to what it is. ‘And it will be known, And it will be known to the Congress, And it will be known to you, Probably before we decide it, But it will be known.’ —Feb. 28, 2003, Department of Defense briefing

  15. The Unknown ‘As we know, There are known knowns. There are things we know we know. We also know There are known unknowns. That is to say We know there are some things We do not know. But there are also unknown unknowns, The ones we don't know We don't know.’ —Feb. 12, 2002, Department of Defense news briefing

  16. The 4th Rumsfeld? • 3 epistemological classes (???) • Known knowns • Known unknowns • Unknown unknowns • 4th class? • Uknown knowns? • Critical issue for integrated sciences

  17. Some OAIS Concepts? • Knowledge Base: allows a consumer to understand something • Designated Community: the set of consumers for whom the archive curates something • Representation Information: helps you interpret a data object yielding an information object • The amount and nature of RepInfo required is dependent on the Knowledge Base of the Designated Community • If you curate for project colleagues in the short term, little if any RepInfo required • If you curate for those unfamiliar with the data, more RepInfo is needed • (All broadly interpreted!) CCSDS (2002). Reference Model for an Open Archival Information System (OAIS). Retrieved. from http://public.ccsds.org/publications/archive/650x0b1.pdf.

  18. Time • KB is f1(DC, t) • DC is f2(t) • RepInfo needed is f3(f1(DC, t), f2(t)) • (but none of these concepts can be precisely defined!) • If DC is small and t is short (months to year or so), then both may be ignored, and RepInfo be assumed part of the KB • If DC is extensive (eg cross-discipline) and t is long (5 years to 25 plus), then RepInfo must be articulated • If t is very long, most bets are off (post-hoc reconstruction likely to be needed)

  19. What might RepInfo include • Structure information: file format definitions, etc • Semantic information: data dictionaries, code books etc • Robust methods (working code?) • Not to mention many kinds of metadata, provenance, documentation of hidden assumptions, etc • Cross-domain schemas one approach to articulating RepInfo? • (Never perfect, of course)

  20. What about Rumsfeld 4? • Biggest concern with unfamiliar user is clashing concepts, eg different baselines, units, geographies, granularity • Especially where terms are ambiguous or differently interpreted • The KBs of two DCs conflict, potentially silently • Happens all the time, of course • The unspoken: tacit knowledge, unknown knowns!

  21. Timing • Curation starts before creation • Before project proposal! • Data acquisition should not happen at the end • Continuous acquisition much better? • Enforcement… or credit for data?

  22. Other curation issues of concern • Sustainability (work on your survival) • Succession (what happens to your data if you don’t) • Data audit (know what you’ve got) • Data risk assessment (assess your chances of loss) • Repository external audit??? • Provenance & computational lineage • Archiving database changes • Community proxy roles: help your communities develop data standards & data practices • DCC has tools & support for some of these…

  23. … and what is the role of RDF?

  24. RDF • Anchors data to (well?) defined ontology or schema • Reduces 4th Rumsfeld risk? • Allows processing by increasing class of tools • More suited to comparatively isolated “facts” or claims than substantial data arrays?

  25. … and Research Outputs? • Need more semantically aware texts to support cross-community understanding • Coded up (cf microformats, RDFa) • People • Citations & references • Science features (eg chemicals, reactions) • Graphs, spectra, tables linking to • Supplementary data • PDF is pretty bad at this

  26. Thanks… and now for the experts!

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