A formal model of provenance in distributed systems

We present a formalism for provenance in distributed systems based on the π-calculus. Its main feature is that all data products are annotated with metadata representing their provenance. The calculus is given a provenance tracking semantics, which ensures that data provenance is updated as the computation proceeds. The calculus also enjoys a pattern-restricted input primitive which allows processes to decide what data to receive and what branch of computation to proceed with based on the provenance information of data. We give examples to illustrate the use of the calculus and discuss some of the semantic properties of our provenance notion. We conclude by reviewing related work and discussing directions for future research.peer-reviewe

Causality and the semantics of provenance

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 a causal semantics for provenance graphs.Comment: Workshop submissio

The lifecycle of provenance metadata and its associated challenges and opportunities

This chapter outlines some of the challenges and opportunities associated with adopting provenance principles and standards in a variety of disciplines, including data publication and reuse, and information sciences

Using a Model-driven Approach in Building a Provenance Framework for Tracking Policy-making Processes in Smart Cities

The significance of provenance in various settings has emphasised its potential in the policy-making process for analytics in Smart Cities. At present, there exists no framework that can capture the provenance in a policy-making setting. This research therefore aims at defining a novel framework, namely, the Policy Cycle Provenance (PCP) Framework, to capture the provenance of the policy-making process. However, it is not straightforward to design the provenance framework due to a number of associated policy design challenges. The design challenges revealed the need for an adaptive system for tracking policies therefore a model-driven approach has been considered in designing the PCP framework. Also, suitability of a networking approach is proposed for designing workflows for tracking the policy-making process.Comment: 15 pages, 5 figures, 2 tables, Proc of the 21st International Database Engineering & Applications Symposium (IDEAS 2017

Archaeology, science-based archaeology and the Mediterranean Bronze Age metals trade

Archaeologists often seem either sceptical of science-based archaeology or baffled by its results. The underpinnings of science-based archaeology may conflict with social or behavioural factors unsuited to quantification and grouping procedures. Thus, the interaction between archaeologists and their science-based colleagues has been less profitable than it might have been. The main point I consider in this study, and exemplify by considering metals provenance studies in the Bronze Age Mediterranean, is the relevance and application of the stated aims of science-based archaeology to the contemporary discipline of archaeology. Whereas most practitioners today recognize that science-based archaeology has the potential to contribute positively to the resolution of problems stemming from our field's inadequate and incomplete data resource, I contend that science and scientific analyses alone cannot adjudicate between cultural possibilities. Rather they provide analytical data which are likely to be open-ended, subject to multiple social interpretations, and in need of evaluation by collaborating archaeologists using social theory