SDCI Data: New Toolkit for Provenance Collection, Publishing, and Experience Reuse

Indiana University, Bloomington IN

Investigators

Abstract

OCI - SDCI Data: New Toolkit for Provenance Collection, Publishing, and Experience Reuse As research digital data collections created through computational science experiments proliferate, it becomes increasingly important to address the provenance issues of the data validity and quality: to record and manage information about where each data object originated, the processes applied to the data products, and by whom. The first outcome of this work is a provenance collection and experience reuse tool that makes minimal assumptions about the software environment and imposes minimal burden on the application writer. It stores and produces results in a form suitable for publication to a digital library. The provenance collection system is a standalone system that imposes a minimal burden on users to integrate it into their application framework and it exhibits good performance. A second outcome of the work is a recommender system for workflow completion that employs case-based reasoning to provenance collections in order to make suggestions to users about future workflow-driven investigations. The workflow completion tool builds on computer models of case-based reasoning to develop a support system that leverages the collective experience of the users of the provenance system to provide suggestions. As a key part of effectively evaluating aspects of the tool, this work builds a gigabyte benchmark database of real and synthetic provenance information. Real workflows are sought from the community, with synthetic extensions to the data set for completeness for purposes of testing. The software and database are available to the research community.