Panda: A System for Provenance and Data

Panda (for Provenance and Data) is a new project whose goal is to develop a general-purpose system that unifies concepts from existing provenance systems and overcomes some limitations in them. Panda is designed for "data-oriented workflows," fully integrating data-based and process-based provenance. Panda's provenance model will support a full range from fine-grained to coarse-grained provenance. Panda will provide a set of built-in operators for exploiting provenance after it has been captured, and an ad-hoc query language over provenance together with data. The processing nodes in Panda's workflows can vary from well-understood relational transformations, to "semi-opaque" transformations with a few known properties, to fully-opaque "black boxes." A theme in Panda is to take advantage of transformation knowledge when present, but to degrade gracefully when less information is available. Panda yields interesting optimization problems, including...

• Type: Journal
• Year: 2010
• Where: DEBU
• Authors: Robert Ikeda, Jennifer Widom
• Keywords: DEBU 2010, Distributed And Parallel Computing, Panda, Process-based Provenance, Provenance