Spatial Discovery of Linked Research Datasets and Documents at a Spatially Enabled Research Library
- Author(s): Lafia, Sara
- Kuhn, Werner
- et al.
Published Web Locationhttps://doi.org/10.1080/15420353.2018.1478923
Current publishing practices in academia tend to result in datasets that are difficult to discover. This is because datasets are not well-integrated across academic domains and they are often not linked to the documents that reference them. For these reasons, discovering datasets across domains can be challenging; for example, discovering archaeological observations and biological specimens using the same search is not widely supported, even if both datasets share a similar spatial extent, like Mesoamerica. It is also challenging to retrieve relevant documents that reference datasets; for example, retrieving a series of field reports that reference archaeological observations is typically not supported. Our work develops an extensible method for: 1) geographically integrating collections across disciplinary repositories and 2) connecting datasets to related documents. We describe a collection of spatially-referenced researcher datasets, capturing their metadata elements and encoding them as linked open data. We then leverage existing library services to formalize links from datasets to documents. The system described in this work has been deployed, resulting in an experimental open data site for the UCSB campus. Results indicate that this system can be scaled-up with support from an institutional repository in the near future.