Causality and the Semantics of Provenance

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been developed, motivated by informal notions such as influence, dependence, explanation and causality. However, there has been little study of whether these mechanisms formally satisfy appropriate policies or even how to formalize relevant motivating concepts such as causality. We contend that mathematical models of these concepts are needed to justify and compare provenance techniques. In this paper we review a theory of causality based on structural models that has been developed in artificial intelligence, and describe work in progress on using causality to give a semantics to provenance graphs.
Original languageEnglish
Title of host publicationDCM
Number of pages12
Publication statusPublished - 2010


Dive into the research topics of 'Causality and the Semantics of Provenance'. Together they form a unique fingerprint.

Cite this