by Scott Martin
Following our successful two-part workshop in Research Data Concepts for librarians at the University of Michigan Library, the Data Education Working Group wanted to follow up with a series of workshops exploring subject-specific data landscapes. This presented an interesting challenge: since individual liaison librarians are responsible for discrete subjects, how do you present a subject-specific workshop in such a way as to make it useful to librarians who serve other subjects?
Our Deep Dive into Data subgroup members (including myself) concluded that the best approach was to use these workshops to explore a ‘method’ for investigating disciplinary data landscapes, using individual subjects as exemplars. Using this approach, we would be able to lead workshop participants through various data resources available for a particular subject, illustrating the ways in which exploration of one part of the landscape can lead organically to other parts. Data policies for funding agencies or publications, for example, may suggest specific repositories as possible locations for data deposit, and those repositories may in turn suggest or require specific metadata formats.
In order to appeal to a broad variety of subjects, we initially decided to offer separate workshops using a STEM discipline (Ecology), a Social Science discipline (Psychology), and an Arts & Humanities discipline as exemplars. During the course of our planning, it became apparent that it would be difficult to find enough resources supporting any single discipline in the humanities to serve as an effective example of the methodology. We opted instead to pursue a project-based approach for Arts & Humanities data, showcasing a variety of data projects native to these disciplines, while proceeding as planned with our STEM and Social Science examples. As Biological Sciences Librarian, I crafted the outline of the Ecology session, which included the skeleton of the methodology we wished to present. Other members of the Deep Dive subgroup provided feedback, and I partnered with group members Katherine Akers, Natsuko Nicholls, Angie Oehrli, and Susan Turkel to refine the approach and develop supplementary materials, including a brief Repository Description Tool for taking a quick snapshot of the essential features of a repository, as well as a more formal Deep Dive Workflow document to articulate our methodology independent of the workshops.
Deep dive into Ecology data, and what’s next?
I presented the Ecology Deep Dive to a group of 15 colleagues on February 28, leading them through 90 minutes of interactive exploration of the data policies of leading Ecology journals (e.g., Ecology, Journal of Ecology), a few key ecological data repositories (e.g., Dryad, Knowledge Network for Biocomplexity (KNB), LTER Data Portal), and other facets of the Ecology data landscape. Initial feedback was very positive, and we look forward to our next Deep Dive, in which Katherine Akers and Susan Turkel will lead an excursion into the research data landscape of Psychology.
Curious about Ecology data?
Check out some of these articles that surfaced in the course of my own investigations:
Fegraus, Andelman, Jones, and Schildhauer (2005). Maximizing the value of ecological data with structured metadata: An introduction to Ecological Metadata Language (EML) and principles for metadata creation. Bulletin of the Ecological Society of America 86(3): 158-168.
Michener and Jones (2011). Ecoinformatics: Supporting ecology as a data-intensive science. Trends in Ecology & Evolution 27(2): 85-93. (See also other articles in this special issue on ecological and evolutionary informatics.)