Assigning Persistent Identifiers to Datasets and Other Scientific Resources: An Early Assessment of Success
The presentation will also discuss work to develop and evaluate tools for automating the tracing of research resource identification and referencing in the research literature via persistent citable identifiers. Manual processes can be very effective at tracing references to scientific resources within the scientific literature, but are fraught with problems since they are time consuming, require multiple tools (e.g. Google Scholar, literature databases), and do not scale. The human capital required to do this work is far too scarce to be practical beyond small-scale case studies. Automated processes are thus of considerable importance in enabling these traceability efforts to scale as the numbers of identifiers being created for unique scientific resources continues to grow rapidly.