Acting as Advocate? Seven steps for libraries in the data decade
1. UKOLN is supported by: Acting as Advocate? Seven steps for libraries in the data decade Dr Liz Lyon, Director, UKOLN, University of Bath, UK Associate Director, UK Digital Curation Centre IATUL Conference, Purdue University, June 2010 . This work is licensed under a Creative Commons Licence Attribution-ShareAlike 2.0
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3. data s c a l e Human Genome printed http://www.flickr.com/photos/johnjobby/2252981353/sizes/l/ Human Genome printed http://www.flickr.com/photos/johnjobby/2252981353/sizes/l/
4. “ Data sets are becoming the new instruments of science”
10. Reference Linking Research Outputs User registration data; Instrument allocation data etc. Comments, annotations, ratings etc. Risk assessment data; other sample data Analyse Derived Data Research Concept and/or Experiment Design Acquire Sample Peer-review Proposal Conduct Experiment Generate, Create, & Collect Raw Data Process Raw Data into Derived Data Interpret & Analyse Results Data Archive, Preservation & Curation IPR, Embargo & Access Control Validate, Reuse & Repurpose Data Publish Research Results Data Derived Data Processed Data Raw, Correction & Calibration Data Papers, articles, presentations, reports An Idealised Scientific Research Data Lifecycle Model Documentation, Metadata & Storage (Reference, Provenance, Context, Calibration etc.) Start Project Write Proposal (include DMP) Scholarly Knowledge Write Usage Reports Publication Database Research Activity Research Admin Activity Archive Activity Information Flow KEY Prepare Supplementary Data Prepare Manuscript Peer Review Research Discover & Access Appraisal & Quality Control Programs (generate customised software) Publication Activity
14. Benefits Taxonomy: Summary Keeping Research Data Safe2 Report: April 2010 Dimension 1 Direct Indirect (costs avoided) Dimension 2 Near-term Long-term Dimension 3 Private Public
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16. Ethics, Privacy, Culture “ You have zero privacy anyway. Get over it” Scott McNealy, CEO Sun Microsystems, 1999
22. “ While many researchers are positive about sharing data in principle, they are almost universally reluctant in practice. ..... using these data to publish results before anyone else is the primary way of gaining prestige in nearly all disciplines.” INCREMENTAL Project
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24. Participatory medicine : share data & empower the patient... Sage Congress San Francisco April 2010
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27. Professional Scientists Enthusiastic amateurs Training Citizen scientist Standards and ethics Local : natural history, environ. Peer-review Global : astronomy Organisational support Self-supporting
The I2S2 project aims to understand and identify the requirements for a data-driven research infrastructure in the Structural Sciences. The work is focused on the exemplar domain of Chemistry, but with a view towards inter-disciplinary application. This Idealised Scientific Research Data Lifecycle Model produced by the I2S2 project seeks to extend and adapt from a “researcher perspective”, the Keeping Research Data Safe (KRDS) Activity Model. It adapts KRDS from an archive-centric to a researcher-centric view by: Defining and emphasising more of the activities in the research (KRDS “Pre-Archive” ) phase where research data is created; Adding a “Publication” set of activities; Concatenating the KRDS “Archive” phase activities in the centre of the model for simplification and presentational purposes; Adding some specific local research administration activities. In addition for the purposes of the project, it adds some selective detail of information flows and information objects between the activities. Note this is an idealised model and several activities such as peer review or conduct experiment may have multiple instances or repetitions. It also represents a project view as of June 2010 and may be subject to further changes.
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