Many institutions use metrics to evaluate their research productivity; however, it is challenging to effectively summarize and evaluate research across academic disciplines. We use topic modeling to develop maps of science at multiple levels of detail. The maps were used in an institutional review and evaluated by leading researchers at an earth science institute. We demonstrate that mapping research topics supports the review process by offering insights into interdisciplinary research collaborations and areas of expertise at the institute.
Institutional reviews typically rely on scientometrics, like the h-index and impact factors of their participants, to assess research productivity. Productivity is not the only review criterion however, and scientometrics can be difficult to generate and compare in multidisciplinary settings. “Distant reading” methods from the Digital Humanities can complement the current quantitative evaluation paradigm; these methods support qualitative narratives, comprehension, and discovery of knowledge by arranging vast bodies of text into graphs, maps, and trees. To test this idea, we apply distant reading methods to a multidisciplinary body of research authored by 240 researchers from the Earth Research Institute (ERI) at UC Santa Barbara over the past decade. We model cross-disciplinary topics of research publications and projects emerging at multiple levels of detail. From these, we design maps that reveal the latent thematic structure of multidisciplinary research. ERI’s researchers use and evaluate these maps of research topics in the context of an institutional review to “read” ERI’s body of research at a distance, i.e. at multiple levels of detail. We find that our approach strengthens the institutional review process by exposing thematic expertise, relationships between researchers, topical distributions and clusters of work, and the evolution of these aspects over time.
Academic libraries have always supported research across disciplines by integrating access to diverse contents and resources. They now have the opportunity to reinvent their role in facilitating interdisciplinary work by offering researchers new ways of sharing, curating, discovering, and linking research data. Spatial data and metadata support this process because location often integrates disciplinary perspectives, enabling researchers to make their own research data more discoverable, to discover data of other researchers, and to integrate data from multiple sources. The Center for Spatial Studies at the University of California, Santa Barbara (UCSB) and the UCSB Library are undertaking joint research to better enable the discovery of research data and publications. The research addresses the question of how to spatially enable data discovery in a setting that allows for mapping and analysis in a GIS while connecting the data to publications about them. It suggests a framework for an integrated data discovery mechanism and shows how publications may be linked to associated data sets exposed either directly or through metadata on Esri's Open Data platform. The results demonstrate a simple form of linking data to publications through spatially referenced metadata and persistent identifiers. This linking adds value to research products and increases their discoverability across disciplinary boundaries.3
Georeferencing is the process of aligning a text description of a geographic location with a spatial location based on a geographic coordinate system. Training aids are commonly created around the georeferencing process to disseminate community standards and ideas, guide accurate georeferencing, inform users about new tools, and help users evaluate existing geospatial data. The Georeferencing for Research Use (GRU) workshop was implemented as a training aid that focused on the creation and research use of geospatial coordinates, and included both data researchers and data providers, to facilitate communication between the groups. The workshop included 23 participants with a wide background of expertise ranging from students (undergraduate and graduate), professors, researchers and educators, scientific data managers, natural history collections personnel, and spatial analyst specialists. The conversations and survey results from this workshop demonstrate that it is important to provide opportunities for biocollections data providers to interact directly with the researchers using the data they produce and vice versa.
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