© 2007, IDEALS This work is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License. To view a copy of this license, visit

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Presentation transcript:

© 2007, IDEALS This work is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License. To view a copy of this license, visit Illinois Digital Environment for Access to Learning and Scholarship Small Science: First Impressions of Curation Needs Sarah L. Shreeves IDEALS Coordinator University of Illinois at Urbana- Champaign DLF Fall Forum 2007

Outline Background First impressions Challenges Where we’re going

Caveats: Raw perceptions from the field Not claiming any generalizations Not claiming any special expertise Talking about ‘small’ science

Small science? Reference Collections – established infrastructure, staffing, standards; funding for at least for medium to long term; key component in research across multiple fields and in education Example: Protein DatabankProtein Databank Resource Collections – sit on a continuum, but generally grant funded, serve single scientific community establish community level standards; intermediate in size Example: Cell Centered DatabaseCell Centered Database Research collections –product of one or more projects; manage data for a single project; standards may or may not conform and may be proprietary; budget is small; do not necessarily intend to preserve data Example: Datasets produced out of a single lab Long lived digital data collections – National Science Board –

Data Curation is…. Data Curation Activities: enable data discovery and retrieval maintain data quality and add value provide for re-use over time Data Curation Tasks: appraisal and selection authentication representation archiving preservation the active and on-going management of data through its lifecycle of interest and usefulness to scholarship, science, and education. Adapted from a slide by Melissa Cragin, GSLIS, UIUC

The Context… Meeting with faculty and departments around campus to discuss IDEALS ( in our early adopter phase ( ) Asked by faculty about data early on in this process Began to investigate what it would mean to include data

Our first data set in IDEALS….

Animal Biologist: Background: Retired faculty member afraid department would delete datasets made available through web site; Data represented his career Size, type, and format: 150 small csv or excel files; pdfs of maps; web pages with protocol information Access and Rights: Open though first rights on usage of the data given to another scientist (at different institution) Other information included: Protocols; unpublished manuscripts; list of published papers Special considerations: Faculty member had no technical expertise so we did the deposit work for him Questions: Is this something we would have traditionally taken into our archives?

Crystallographer Background: Crystallography is a service for chemists; raw data images but processed into a ascii derived file and then into a cif file (standard – crystallographic information file - Size, type, and format: hundreds of cif files (up to a MB each); raw and derived files larger; total about 30 GB right now Access and Rights: Rights complicated as crystallography work a a service for chemists; Timed release of data to coincide with publication; sometimes can release sooner (PMR refers to the golden moment) Other information included: Link back to the derived files; process cif file into a cml file Special considerations: Looking at Spectra project for model Questions: How important is the raw and derived data?

LIDAR (Light Detection and Ranging) Group Background: LIDAR group collected atmospheric data at the South Pole; Data can be used as a benchmark for future studies Size, type, and format: about 10.dat files about 60 kb in size; images derived from data; publication list Access and Rights: No problems with rights to data; want to make this openly accessible (benchmark); wants to make sure publications are archived as well (negotiation in progress) Other information not included: Need to gather and provide protocols Special considerations: There is a discipline based repository for this data but not interested in depositing because of high barriers and feels the University should have it

Biological Anthropologist Background: Runs evolutionary biomechanics laboratory; “reconstruct aspects of the locomotor behaviors used by fossil primates and human ancestors”; studies gait; Size, type, and format: Image files (dicom* format) and.dat files of motion sets; currently about a TB worth Access and Rights: Restrict access until publications are finished; rights to image files complicated because bones from a small natural history museum Other information included: Can provide protocol information but will need to gather; links to papers Questions: Managing restricted access material; complicated rights issues *Digital imaging and communications in medicine

Crop Science Background: 100 years worth of data on long-term selection experiment for oil and protein in corn; faculty member retiring and passing on data to colleague; Size, type, and format: 8 sas files (12 kb each); list of all publications derived from data (over 135); protocols Access and Rights: Willing to make open and available provided colleague has first publication rights Special considerations: Also has given the University Archives the analog data; believes is important for the University of preserve this material Questions: How do we link between these files and the publications?

Information Scientist Background: Database of discussion between grant funding agency and grant recipients; performing qualitative data analysis on this set; Size, type, and format: ? Access and Rights: Restrict access to particular community of researchers with agreement of grant funding agency Questions: Privacy; access restrictions; raw primary data not created by researcher

Challenges… Variety and heterogeneity of data, disciplines, needs Appraisal and selection – need to work closely with domain specialists Crystallography example Archiving / preservation vs providing access / manipulation / data mining Limited infrastructure to work with all data

Libraries have a role to play Libraries could be particularly well suited to work with ‘small’ science Subject specialists can work closely with scientists - negotiation and consultation for individual scientists/labs Part of a suite of scholarly communication services Need training and better understanding of roles of library in data curation processes IMLS NLG to Purdue (lead) and UIUC to study how librarians can interact with scientists to make their research output available, identifying practices and tools to support this work MIT Libraries also developing a matrix for discussions with scientists about data issues Library schools are developing data curation programs

Contact information Sarah L. Shreeves