(Revised from a March 2015 post at Thea’s Adventures in Librarianship blog)
I’m passionate about data and data services. I’m passionate about transparency and facilitating science. And I’m passionate about building off the DMPTool at my institution — meaning, building the Libraries’ ability to provide data services, even if I have to keep scalability and feasibility in mind.
I’m reading through Henderson and Knott’s Starting a Research Data Management Program Based in a University Library (2015), and I thought I’d share my notes and takeaways here.
First off, I talk a lot about libraries being homes for information, and we’re great organizers and disseminators of information. This is why we’re a great home for data, but it’s good to have concrete examples like GenBank:
“One of the first national, collaborative data initiatives was collecting and compiling DNA data into GenBank. Initially, the data was compiled in printed volumes before being made available digitally on CD-ROMs and through a web-based infrastructure. This was one way libraries initially became involved in the provision of data for research at some institutions.”
> Tips from Henderson and Knott
- Build off of other successful data services — definitely investigate the early adopters and their successes and challenges
- Look at documented data management needs of faculty from previous articles, like the ones below. (Can we extrapolate that grad students are similar?)
- Use the Purdue Data Curation Profiles to expand your understanding of different disciplines and their data management needs
- Use SWOTs to outline resources and services available, and gaps present at your institution
- Be prepared to deal with some territoriality, and find ways to “meet service gaps, not undermine or replace existing services.”
- Finally, use an environmental scan to see what’s currently going on in your institution around data.
I’d love to pursue an environmental scan — though it seems intimidating for some reason (but! comfort zone! challenge that!), so it’s good to see it reiterated here.
RDM Services to Consider Offering
Some of the services to check for and consider might include the following (again from Henderson & Knott). They won’t be right for every institution, but you can discuss which gaps are best met by current library staffing and resources:
|data collection||data processing||analysis of data|
|saving data for the long term||data curation||sharing data|
|finding data to reuse||depositing data in a repository||using GIS services|
|presenting data||designing research||collecting metrics to show the impact of shared data|
|writing data management plans||teaching best practices for data collection & use|
Finally, a last bit of sage advice: “When starting data services, it is helpful to have a practical focus.”
This is something I struggle with! I get excited about my ideas and then find I have too many on the table. Kind of like how my books multiply. But these resources remind us: we can’t do it all at once, and small steps are a good starting point.
Henderson, M. E., & Knott, T. L. (2015). Starting a Research Data Management Program Based in a University Library. Medical Reference Services Quarterly, 34(1), 47-59. http://scholarscompass.vcu.edu/libraries_pubs/25/
- Westra, B. (2010). Data Services for the Sciences: A Needs Assessment. Ariadne. (64). http://www.ariadne.ac.uk/issue64/westra/
- Johnson, L. M., Butler, J. T., & Johnston, L. R. (2012). Developing e-science and research services and support at the University of Minnesota health sciences libraries. Journal of library administration, 52(8), 754-769. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3621913/
- Parsons, T. (2013). Creating a Research Data Management Service. International Journal of Digital Curation, 8(2), 146-156. http://ijdc.net/index.php/ijdc/article/view/279