Over the time sensor network readings become large datasets. A user reading the sensed data will not totally comprehend the readings without learning the path taken and understanding the dataset. As this is an accepted fact, the idea of including the provenance data while publishing sensor readings has been around for many years. First, the readings were annotated with data provenance such as r...

The provenance of a data product contains information about how the product was derived, and is crucial for enabling scientists to easily understand, reproduce, and verify scientific results. Currently, most provenance models are designed to capture the provenance related to a single run, and mostly executed by a single user. However, a scientific discovery is often the result of methodical exe...

Provenance management has become increasingly important to support scientific discovery reproducibility, result interpretation, and problem diagnosis in scientific workflow environments. This paper proposes an approach to provenance management that seamlessly integrates the interoperability, extensibility, and reasoning advantages of Semantic Web technologies with the storage and querying power...

Workflows are increasingly used in science to manage complex computations and data processing at large scale. Intelligent workflow systems provide assistance in setting up parameters and data, validating workflows created by users, and automating the generation of workflows from high-level user guidance. These systems use semantic workflows that extend workflow representations with semantic con...

SPADE is an open source software infrastructure for data provenance collection and management. The underlying data model used throughout the system is graph-based, consisting of vertices and directed edges that are modeled after the node and relationship types described in the Open Provenance Model. The system has been designed to decouple the collection, storage, and querying of provenance met...

Provenance describes how an object came to be in its present state. Thus, it describes the evolution of the object over time. Prior work on provenance has focussed on databases and the file system. The database or file system is enhanced or augmented in order to capture additional information about the historical evolution of document collections, and thus answer the provenance question. We add...

Case-based reasoning systems routinely record the results of prior problem-solving, but not the provenance of new cases: the way in which the new cases were derived. This paper proposes the value of tracking provenance information in CBR, especially when timely feedback may not be available. It illustrates the use of provenance information with studies of the application of provenance informati...

Provenance databases play an essential role in scientific experiments. The models considered to represent such data assume that there is a certainty in all the provenance relations. However, several experiments are not deterministic, which makes their results to be associated with uncertainties. Analyze provenance data in the presence of such uncertainties is not trivial. In this paper, we addr...

Work on the End-to-End Provenance System (EEPS) was begun in the later summer of 2009. The EEPS effort seeks to explore the three central questions in provenance systems; a) ”where and how do I design secure hostlevel provenance collecting instruments (called provenance monitors)?”, b) ”how do I extend completeness and accuracy guarantees to distributed systems and computations?”, and c) ”what ...

Recent work has begun exploring the characterization and utilization of provenance in systems based on the Service Oriented Architecture (such as Web Services and Grid based environments). One of the salient issues related to provenance use within any given system is its security. Provenance presents some unique security requirements of its own, which are additionally dependent on the architect...