Artem Chebotko

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Scientific workflows have recently emerged as a new paradigm for scientists to formalize and structure complex and distributed scientific processes to enable and accelerate many scientific discoveries. In contrast to business workflows, which are typically control flow oriented, scientific workflows tend to be dataflow oriented, introducing a new set of(More)
Storing and querying XML documents using a RDBMS is a challenging problem since one needs to resolve the conflict between the hierarchical, ordered nature of the XML data model and the flat, unordered nature of the relational data model. This conflict can be resolved by the following XML-to-Relational mappings: schema mapping, data mapping and query(More)
Article history: Received 12 October 2008 Received in revised form 8 March 2010 Accepted 11 March 2010 Available online 23 March 2010 Provenance metadata has become increasingly important to support scientific discovery reproducibility, result interpretation, and problem diagnosis in scientific workflow environments. The provenance management problem(More)
Scientific workflows have recently emerged as a new paradigm for scientists to formalize and structure complex and distributed scientific processes to enable and accelerate many scientific discoveries. In contrast to business workflows, which are typically control flow oriented, scientific workflows tend to be dataflow oriented, introducing a new set of(More)
In this demo, we present current status of our VIsual sciEntific Workflow management system called VIEW, highlighting the following two features: (i) the use of Semantic Web technology to represent, store, and query provenance metadata, leading to an interoperable and extensible provenance system, and (ii) the support of visualization of various provenance(More)
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(More)
Provenance, the metadata that pertains to the derivation history of a data product, has become increasingly important in scientific workflow environments. In many cases, both data products and their provenance can be sensitive and effective access control mechanisms are essential to protect their confidentiality. In this paper, we propose i) a formalization(More)
Various computing and data resources on the Web are being enhanced with machine-interpretable semantic descriptions to facilitate better search, discovery and integration. This interconnected metadata constitutes the Semantic Web, whose volume can potentially grow the scale of the Web. Efficient management of Semantic Web data, expressed using the W3C's(More)
In scientific workflow environments, scientific discovery reproducibility, result interpretation, and problem diagnosis primarily depend on provenance, which records the history of an in-silico experiment. Resource Description Framework is frequently used to represent provenance based on vocabularies such as the Open Provenance Model. For complex scientific(More)