Automatic metadata annotation through reconstructing provenance

Annotating datasets with metadata is an important part of organizing and curating data. However, it is a time consuming process and often not done in a rigorous fashion. In this paper, we propose a new approach to annotating datasets through the use of reconstructed provenance. A detailed survey of the related work in this area is given. Additionally, we provide an overview of our approach for both reconstructing provenance and using that provenance to automatically annotate datasets with metadata. This approach leverages existing work in AI planning and change detection algorithms.