VisTrails

Callahan, Steven P.; Freire, Juliana; Santos, Emanuele; Scheidegger, Carlos; Silva, Cláudio T.; Vo, Huy T.

doi:10.1145/1142473.1142574

Cited by 341 publications

(36 citation statements)

References 7 publications

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“…Galaxy combines these descriptions with execution traces to publish them online as workflow execution (histories). Vistrails [4] system is specialised for visualisation workflows. Vistrails embodies a comprehensive library of visualisation tools, which operate over a common information model.…”

Section: Factorial Design In Workflow Systemsmentioning

confidence: 99%

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Static analysis of Taverna workflows to predict provenance patterns

Alper

Belhajjame

Goble

2017

Future Generation Computer Systems

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Workflows have found adoption in scientific domains particularly due to their automation and provenance features. Using workflows scientists can repeat analyses with different input parameters to later use provenance to access and compare results based on respective parameters. An assumption that is often made is that by designing an analysis as a workflow, we get parameterto-result traceability for free with workflow provenance. This assumption holds for cases of coarse-grained traceability, where an entire workflow is subjected to repetition and all workflow parameters contribute to all results. On the other hand for cases requiring finer grained traceability, where a workflow is configured with collections of parameters and analyses within a workflow are repeated with combinations of parameters from collections, this assumption is not guaranteed to hold. In this paper we identify two dimensions that affect fine-grained traceability as: 1) the level of granularity supported by a workflow system in modelling parameters/data in workflows and in provenance, which we name as the level of support for Factorial Design, and 2) the practice of scientists in successfully encoding Factorial Design into workflows. Taverna is a workflow system that provides extensive features for factorial design, meanwhile it provides an uncontrolled approach to workflow design; meaning scientists may create workflows, which, when run, could break traceability in provenance. Using a real-world Taverna workflow we show how broken traceability manifests in provenance and how it can render provenance practically useless for accessing workflow outputs derived from particular input parameters. In order to prevent broken traceability from occurring, we describe a rule-based static analysis technique, which operates over workflow descriptions and anticipates patterns in provenance. Our rules exploit the well-defined execution behaviour in the Taverna system. In order to understand Factorial Design support in workflow systems in general, we provide a comparative survey. We conclude that other workflow systems also provide constructs for Factorial Design, and, similar to Taverna, they too are prone to broken traceability.

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Section: Factorial Design In Workflow Systemsmentioning

confidence: 99%

“…For example, in Kepler [3] an array structure is a single one blob in provenance, and in Vistrails [4] activities can be repeated, but it appears as if the repetitions consume one piece of data, while in fact they consume individual elements of an array.…”

Section: Introductionmentioning

confidence: 99%

Static analysis of Taverna workflows to predict provenance patterns

Alper

Belhajjame

Goble

2017

Future Generation Computer Systems

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“…VisTrails [5] uses an SQL database for storage of retrospective provenance and an XML serialization for storing prospective provenance. It also records provenance about the evolution of workflows as they are edited.…”

Section: Related Workmentioning

confidence: 99%

“…Many scientific workflow tools, such as Taverna [3], Kepler [4] and VisTrails [5], are monolithic "integrated development environments". Instead of locking a user into a single tool, we seek to facilitate their mobility between tools, to allow them to use the best tools for the job.…”

Section: Introductionmentioning

confidence: 99%

Intermediate Notation for Provenance and Workflow Reproducibility

Michaelides

Parker

Charlton

et al. 2016

Lecture Notes in Computer Science

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Abstract. We present a technique to capture retrospective provenance across a number of tools in a statistical software suite. Our goal is to facilitate portability of processes between the tools to enhance usability and to support reproducibility. We describe an intermediate notation to aid runtime capture of provenance and demonstrate conversion to an executable and editable workflow. The notation is amenable to conversion to PROV via a template expansion mechanism. We discuss the impact on our system of recording this intermediate notation in terms of runtime performance and also the benefits it brings.

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“…The VisTrails system [27,46] is the first one to support provenance tracking of workflow evolution. In VisTrails, workflow evolution provenance is represented as a rooted tree, in which each node corresponds to a version of a workflow, and each edge corresponds to an update action that was applied to the parent workflow to create the child workflow.…”

Section: Storing and Querying Scientific Workflow Provenancementioning

confidence: 99%

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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VisTrails

Cited by 341 publications

References 7 publications

Static analysis of Taverna workflows to predict provenance patterns

Static analysis of Taverna workflows to predict provenance patterns

Intermediate Notation for Provenance and Workflow Reproducibility

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

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