Background: A critical aspect of the NIH Translational Research roadmap, which seeks to accelerate the delivery of “bench-side” discoveries to patient’s “bedside,” is the management of the provenance metadata that keeps track of the origin and history of data resources as they traverse the path from the bench to the bedside and back. A comprehensive provenance framework is essential for researc...

As more data (especially scientific data) is digitized and put on the Web, the importance of tracking and sharing its provenance metadata grows. Besides capturing the annotation properties of data, provenance research also emphasizes interlinking relevant data. Therefore, it is desirable to make provenance metadata easy to access, share, reuse, integrate and reason with. To address these requir...

We consider the problem of defining, generating, and tracing provenance in dataoriented workflows, in which input data sets are processed by a graph of transformations to produce output results. We first give a new general definition of provenance for general transformations, introducing the notions of correctness, precision, and minimality. We then determine when properties such as correctness...

The growing recognition of the importance of provenance for data intensive and multidisciplinary domains is leading to careful collection of provenance. One consequence of this is the proliferation of provenance repositories hosted for individual organization or communities, with limited ability to reconstruct and query for and on provenance across them. Community standards like the Open Proven...

Provenance, from the French word “provenir”, describes the lineage or history of a data entity. Provenance is critical information in scientific applications to verify experiment process, validate data quality and associate trust values with scientific results. Current industrial scale eScience projects require an end-to-end provenance management infrastructure. This infrastructure needs to be ...

In spite of a growing interest in provenance-aware systems, mechanisms for automated provenance collection have failed to win acceptance in mainstream operating systems. This is due in part to a lack of consensus within disparate provenance development communities on a single general solution – provenance collection mechanisms have been proposed at a variety of operational layers wthin host sys...

Digital provenance describes the ancestry or history of a digital object. Most existing provenance systems, however, operate at only one level of abstraction: the system call layer, a workflow specification, or the high-level constructs of a particular application. The provenance collectable in each of these layers is different, and all of it can be important. Single-layer systems fail to accou...

The Swift parallel scripting language allows for the specification, execution and analysis of large-scale computations in parallel and distributed environments. It incorporates a data model for recording and querying provenance information. In this article we describe these capabilities and evaluate interoperability with other systems through the use of the Open Provenance Model. We describe Sw...

The provenance of a file represents the origin and history of the file data. A Distributed Provenance Aware Storage System (DPASS) tracks the provenance of files in a distributed file system. The provenance information can be used to identify potential dependencies between files in a filesystem. Some applications of provenance tracking include (i) tracking the transformations applied to process...

Provenance is well understood in the context of art or digital libaries, where it respectively refers to the documented history of an art object, or the documentation of processes in a digital object’s life cycle [3]. Interest for provenance in the “e-science community” [9] is also growing, since provenance is perceived as a crucial component of workflow systems [2] that can help scientists ens...