"Polluted Leftovers: Repository Metrics from the Perspective of a Most Downloaded Item" (Wheeler, Arlitsch)
Over- and under-reporting of item downloads within institutional repositories (IR) are known issues which largely derive from inconsistent measurement of bot activity. The challenges of identifying and filtering the activity of "bad" versus "good" bots can fall outside the interest and scope of duties for repository managers, while the abundance of metrics applications and configurations among common IR platforms can contribute to rather than alleviate existing complexities. In this project briefing, librarians from Montana State University and the University of New Mexico (UNM) present a mapping of DSpace Solr log to Google Analytics data together with the outcomes of the resulting analysis. By telling the discovery and access "stories" of the most downloaded items from UNM's IR, LoboVault, presenters will characterize human and bot behaviors which illustrate the reporting challenges facing repository managers and the contrasts between metrics services.
"Making Data Count: Promoting Open Data Through Usage and Impact Tracking" (Abrams)
Research data are fundamental to the success of the academic enterprise. However, the primary vehicle for scholarly credit and accountability remains the journal article, and the academic community still gauges the impact of scholarship primarily through article citation and usage statistics. How can we expand this to include research data? The challenge in doing so is that the complex, aggregative, and often dynamic nature and use of datasets is quite different from that of publications. Any solution will require the development of new modes for tracking impact through data-level metrics (DLM). The widespread availability of such measures would constitute an important incentive for promoting open data principles and encouraging adoption of research data management best practices. Our project, Making Data Count (MDC), aims to do just that: to build the necessary social and technical infrastructure to support data as first class research outputs. The MDC team (including the California Digital Library, COUNTER, DataCite, and DataONE) are working together to publish a new COUNTER recommendation on data usage statistics; launch a DataCite-hosted MDC service for aggregated DLM based on the open-source Lagotto platform; and to build tools for data repository and discovery services to easily integrate with the new MDC service. This effort will provide a clear path for data outputs to be given better recognition and fuller integration into the scholarly ecosystem and workflows.
https://dlm.datacite.org/
