Automating Annotation Of Media With Linked Data Workflows

Computational feature extraction provides one means of gathering structured analytic metadata for large media collections. We demonstrate a suite of tools we have developed that automate the process of feature extraction from audio in the Internet Archive. The system constructs an RDF description of the analysis workflow and results which is then reconciled and combined with Linked Data about the recorded performance. This Linked Data and provenance information provides the bridging information necessary to employ analytic output in the generation of structured metadata for the underlying media files, with all data published within the same description framework.