Three fundamental dimensions of scientific workflow interoperability: Model of computation, language, and execution environment

Scientific experiments using workflows benefit from mechanisms to trace the generation of results. As workflows start to scale it is fundamental to have access to their underlying processes, parameters and data. Particularly in molecular dynamics (MD) simulations, a study of the interatomic interactions in proteins must use distributed high performance computing environments to produce timely results. Scientist's trust in experiments produced by gathering distributed partial results may be limited without provenance information. This paper presents a service architecture that captures and stores provenance data from distributed, autonomous, replicated and heterogeneous resources. Such provenance data can be used to trace the history of the distributed execution process. These services can be coupled to workflow management systems. The Kepler system was used as a basis to manage a grid workflow application. Experimental results regarding cluster and grid MD simulations were evaluated using the provenance services architecture.

Provenance Services for Distributed Workflows

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 execution of many scientific workflows with many datasets produced at different times by one or more users. Further, to promote and facilitate exchange of information between multiple workflow systems supporting provenance, the Open Provenance Model (OPM) has been proposed by the scientific workflow community. In this paper, we describe a new query model that captures implicit user collaborations. We show how this model maps to OPM and helps to answer collaborative queries, e.g., identifying combined workflows and contributions of users collaborating on a project based on the records of previous workflow executions. We also adopt and extend the high-level Query Language for Provenance (QLP) with additional constructs, and show how these extensions allow non-expert users to express collaborative provenance queries against this model easily and concisely. Furthermore, we adopt the Provenance Challenge 3 (PC3) workflows as a collaborative and interoperable usecase scenario, where different stages of the workflow are executed in three different workflow environments - Kepler, Taverna, and WSVLAM. Through this usecase, we demonstrate how we can establish and understand collaborative studies through interoperable workflow provenance.

/pdf/understanding-collaborative-studies-through-interoperable-53vvkfib1j.pdf

Understanding collaborative studies through interoperable workflow provenance

In e-Science, meaningful experiment processes and workflow engines emerge as important scientific resources. A complex experiment often involves services and processes developed in different scientific domains. Aggregating different workflows into one meta workflow avoids unnecessary rewriting of experiment processes and thus improves the reuse efficiency. Remote workflow engines explore the computing power of distributed environment. However, the diversity of workflow description and execution models makes the integration between engines difficult. An agent framework uses ontology based communication language and makes the integration to semantic information of resources seamless, it is thus suitable for coupling distributed engines. In this paper, we present our work in the context of Dutch Virtual Laboratory for e-Science (VL-e) project. A semantic registry for describing workflow engines is implemented, and mobile agents are used to manage distributed workflow coordination.

Distributed execution of aggregated multi domain workflows using an agent framework

Using ontologies for resource description in the CineGrid Exchange

VLE-WFBus: A Scientific Workflow Bus for Multi e-Science Domains

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VLE-WFBus: A Scientific Workflow Bus for Multi e-Science Domains