Explaining why a certain answer is in the result ofa query or why it is missing from the result is important for manyapplications including auditing, debugging data, and answeringhypothetical questions about data. Both types of questions, i.e.,why provenance and why-not (missing answer) provenance havebeen studied extensively. Provenance games, a game-theoreticapproach t...

Provenance databases are an important asset in data analytics of large-scale scientific data. The data derivation path allows for identifying parameters, files and domain data values of interest. In scientific workflows, provenance data is automatically captured by workflow systems. However, the power of provenance data analyses depends on the expressiveness of domain-specific data along the pr...

As has been frequently observed in the literature, there is a strong connection between a derived data item’s provenance and its authoritativeness, utility, relevance, or probability. A standard way of obtaining a score for a derived tuple is by first assigning scores to the “base” tuples from which it is derived — then using the semantics of the query and the score measure to derive a value fo...

Many applications which require provenance are now moving to cloud infrastructures. However, it is not widely realised that clouds have their own need for provenance due to their dynamic nature and the burden this places on their administrators. We analyse the structure of cloud computing to identify the unique challenges facing provenance collection and the scenarios in which additional proven...

A unique characteristics of provenance data is that it forms a directed acyclic graph (DAG) in accordance with the underlying causality dependencies between entities (acting users, action processes and data objects) involved in transactions. Data provenance raises at least two distinct security-related issues. One is how to control access to provenance data which we call Provenance Access contr...

We introduce HadoopProv, a modified version of Hadoop that implements provenance capture and analysis in MapReduce jobs. It is designed to minimise provenance capture overheads by (i) treating provenance tracking in Map and Reduce phases separately, and (ii) deferring construction of the provenance graph to the query stage. Provenance graphs are later joined on matching intermediate keys of the...

Running scientific workflows in distributed environments is motivating the definition of provenance gathering approaches that are loosely coupled to the workflow systems. We have proposed a provenance gathering strategy that is independent from workflow system technology. This strategy has evolved into a provenance management system named ProvManager. The main principle is that each workflow ac...

This paper considers the issue of cycles in provenance metadata. Cyclic provenance poses a problem as they hide the distinction between ancestors and decendants. Yet this distinction is at the heart of provenance. Our contributions are: development of terminology, defining the parameters of our ideal solution and present and evaluate four approaches to cyclic provenance. Before diving into a se...

In this demonstration, we exhibit a new type of provenance system, one that is not tied to any particular domain, closed-world system or use. The PLUS provenance system was inspired by government requirements to enable provenance capture, storage and use across multi-organizational systems. PLUS is general enough to interact across open-world distributed systems, often without administrative ac...

Provenance is a critical aspect in evaluating scientific output, yet, it is still often overlooked or not comprehensively produced by practitioners. This incomplete and partial nature of provenance has been recognized in the literature, which has led to the development of new methods for reconstructing missing provenance. Unfortunately, there is currently no agreed upon evaluation framework for...