Using Semantic Web Technologies for Representing E-science Provenance

Zhao, Jun; Wroe, Chris; Goble, Carole; Stevens, Robert; Quan, Dennis; Greenwood, Mark

doi:10.1007/978-3-540-30475-3_8

Cited by 106 publications

(71 citation statements)

References 7 publications

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“…This semantic provenance overlays approach is really complementary to the problem discussed in this section, and early experiment done on Taverna show promising results [17].…”

Section: Workflow Results Analysismentioning

confidence: 83%

Building Scientific Workflow with Taverna and BPEL: A Comparative Study in caGrid

Tan

Missier

Madduri

et al. 2009

Service-Oriented Computing – ICSOC 2007

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Abstract. With the emergence of "service oriented science," the need arises to orchestrate various services to facilitate scientific investigation --that is, to create "science workflows." In this paper we summarize our findings in providing a workflow solution for the caGrid service-based grid infrastructure. We choose BPEL and Taverna as candidate solutions, and compare their usability in the full lifecycle of a scientific workflow, including service discovery, service composition, workflow execution, and workflow result analysis. We determine that BPEL offers a comprehensive set of primitives for modeling processes of all flavors, while Taverna provides a more compact set of primitives and a functional programming model that eases data flow modeling. We hope that our analysis not only helps researchers choose a tool that meets their needs, but also provides some insight on how a workflow language and tool can fulfill the requirement of scientists.

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“…This semantic provenance overlays approach is really complementary to the problem discussed in this section, and early experiment done on Taverna show promising results [17].…”

Section: Workflow Results Analysismentioning

confidence: 83%

Building Scientific Workflow with Taverna and BPEL: A Comparative Study in caGrid

Tan

Missier

Madduri

et al. 2009

Service-Oriented Computing – ICSOC 2007

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“…The myGrid/Taverna system [121,122] uses Semantic Web technologies for representing provenance metadata at four levels: process, data, organization, and knowledge. Two levels of ontologies are used.…”

Section: Storing and Querying Scientific Workflow Provenancementioning

confidence: 99%

“…For example, Taverna [121,122] is known to use Sesame [23] and Jena [118,119] as a provenance storage backend. In this work, we present relational RDF store RDFPROV that is specifically optimized for provenance querying and management based on known provenance metadata characteristics (provenance immutability, incremental data loading, common query patterns, etc.).…”

Section: Our Research In the Context Of Related Workmentioning

confidence: 99%

“…The scope of our performance comparison and case study in the previous sections was limited to open-source RDF stores, such as Jena and Sesame, since they are free to use and distribute with non-commercial scientific workflow management systems, such as Taverna [121,122] and VIEW [68,69]. However, we are also interested in exploring if RDFPROV is up-to-date with state of the art The inference mechanisms were turned off in the systems and the same dataset (see Table 3) and test queries (see Table 5) were used in the experiments.…”

Section: Comparison Of Rdfprov With Commercial Rdf Storesmentioning

confidence: 99%

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RDFProv: A relational RDF store for querying and managing scientific workflow provenance

Chebotko¹,

Lu²,

Fei³

et al. 2010

Data & Knowledge Engineering

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Provenance metadata has become increasingly important to support scientific discovery reproducibility, result interpretation, and problem diagnosis in scientific workflow environments. The provenance management problem concerns the efficiency and effectiveness of the modeling, recording, representation, integration, storage, and querying of provenance metadata. Our approach to provenance management seamlessly integrates the interoperability, extensibility, and inference advantages of Semantic Web technologies with the storage and querying power of an RDBMS to meet the emerging requirements of scientific workflow provenance management. In this paper, we elaborate on the design of a relational RDF store, called RDFPROV, which is optimized for scientific workflow provenance querying and management. Specifically, we propose: i) two schema mapping algorithms to map an OWL provenance ontology to a relational database schema that is optimized for common provenance queries; ii) three efficient data mapping algorithms to map provenance RDF metadata to relational data according to the generated relational database schema, and iii) a schema-independent SPARQL-to-SQL translation algorithm that is optimized on-the-fly by using the type information of an instance available from the input provenance ontology and the statistics of the sizes of the tables in the database. Experimental results are presented to show that our algorithms are efficient and scalable. The comparison with two popular relational RDF stores, Jena and Sesame, and two commercial native RDF stores, AllegroGraph and BigOWLIM, showed that our optimizations result in improved performance and scalability for provenance metadata management. Finally, our case study for provenance management in a real-life biological simulation workflow showed the production quality and capability of the RDFPROV system. Although presented in the context of scientific workflow provenance management, many of our proposed techniques apply to general RDF data management as well.

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“…They want to know the why-provenance [1] that is, which sources and/or which tools have been used to calculate the data they obtain. Traceability is particularly important for verifying results, drawing conclusions and testing biological hypotheses [19].…”

Section: Transparent Queries and Traceabilitymentioning

confidence: 99%

A User-Centric Framework for Accessing Biological Sources and Tools

Cohen-Boulakia

Davidson

Froidevaux

2005

Lecture Notes in Computer Science

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Biologists face two problems in interpreting their experiments: the integration of their data with information from multiple heterogeneous sources and data analysis with bioinformatics tools. It is difficult for scientists to choose between the numerous sources and tools without assistance. Following a thorough analysis of scientists' needs during the querying process, we found that biologists express preferences concerning the sources to be queried and the tools to be used. Interviews also showed that the querying process itself -the strategy followed -differs between scientists. In response to these findings, we have introduced a user-centric framework allowing to specify various querying processes. Then we have developed the BioGuide system which helps the scientists to choose suitable sources and tools, find complementary information in sources, and deal with divergent data. It is generic in that it can be adapted by each user to provide answers respecting his/her preferences, and obtained following his/her strategies. Abstract. Biologists face two problems in interpreting their experiments: the integration of their data with information from multiple heterogeneous sources and data analysis with bioinformatics tools. It is difficult for scientists to choose between the numerous sources and tools without assistance. Following a thorough analysis of scientists' needs during the querying process, we found that biologists express preferences concerning the sources to be queried and the tools to be used. Interviews also showed that the querying process itself -the strategy followed -differs between scientists. In response to these findings, we have introduced a user-centric framework allowing to specify various querying processes. Then we have developed the BioGuide system which helps the scientists to choose suitable sources and tools, find complementary information in sources, and deal with divergent data. It is generic in that it can be adapted by each user to provide answers respecting his/her preferences, and obtained following his/her strategies.

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Using Semantic Web Technologies for Representing E-science Provenance

Cited by 106 publications

References 7 publications

Building Scientific Workflow with Taverna and BPEL: A Comparative Study in caGrid

Building Scientific Workflow with Taverna and BPEL: A Comparative Study in caGrid

RDFProv: A relational RDF store for querying and managing scientific workflow provenance

A User-Centric Framework for Accessing Biological Sources and Tools

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