Collection of provenance information is an important aspect of any scientific workflow system. Workflow provenance generally captures lot of information about individual modules in the workflow including input parameters, input and output data products, intermediate data products, module invocation times etc. Therefore, a complete provenance graph contains enough information for someone to have...

Provenance is an increasing concern due to the revolution in sharing and processing scientific data on the Web and in other computer systems. It is proposed that many computer systems will need to become provenance-aware in order to provide satisfactory accountability, reproducibility, and trust for scientific or other high-value data. To date, there is not a consensus concerning appropriate fo...

The advent of cloud computing provides a cheap and convenient mechanism for scientists to share data. The utility of such data is obviously enhanced when the provenance of the data is also available. The cloud, while convenient for storing data, is not designed for storing and querying provenance. In this paper, we present desirable properties for distributed provenance storage systems and pres...

Many applications facilitate a data processing chain, i.e. a workflow, to process data. Results of intermediate processing steps may not be persistent since reproducing these results are not costly and these are hardly re-usable. However, in stream data processing where data arrives continuously, documenting fine-grained provenance explicitly for a processing chain to reproduce results is not a...

Using provenance to explain why a query returns a result or why a result is missing has been studied extensively. However, the two types of questions have been approached independently of each other. We present an efficient technique for answering both types of questions for Datalog queries based on a game-theoretic model of provenance called provenance games. Our approach compiles provenance r...

MARCH/APRIL 2011 1540-7993/11/$26.00 © 2011 IEEE COPUBLISHED BY THE IEEE COMPUTER AND RELIABILITY SOCIETIES 83 Patrick McDaniel Pennsylvania State University cesses and inputs that created or transformed the data. Where provenance enumerates the entities that contributed to the data. Consider a patient x-ray image document used in a healthcare system. The provenance record for that document wou...

In many application areas like e-science and data-warehousing detailed information about the origin of data is required. This kind of information is often referred to as data provenance or data lineage. The provenance of a data item includes information about the processes and source data items that lead to its creation and current representation. The diversity of data representation models and...

Regardless of how useful provenance is for capturing knowledge related to scientific research, the way provenance is managed, e.g. the infrastructure that stores the provenance, can greatly affect its reusability. For example, for some scientists, research is performed mainly on a single workstation and scientific results, data and data-related provenance, are stored on the same system. Consequ...

Provenance, i.e., the origin or source of something, is becoming an important concern, since it offers the means to verify data products, to infer their quality, to analyse the processes that led to them, and to decide whether they can be trusted. For instance, provenance enables the reproducibility of scientific results; provenance is necessary to track attribution and credit in curated databa...

PROV has been adopted by a number of workflow systems for encoding the traces of workflow executions. Exploiting these provenance traces is hampered by two main impediments. Firstly, workflow systems extend PROV differently to cater for system-specific constructs. The difference between the adopted PROV extensions yields heterogeneity in the generated provenance traces. This heterogeneity dimin...