Cost and accuracy aware scientific workflow retrieval based on distance measure

Ma, Yinglong; Shi, Moyi; Wei, Jun

doi:10.1016/j.ins.2015.03.055

Cited by 5 publications

(2 citation statements)

References 53 publications

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“…The central aspect of this question is the definition of similarity in scientific workflows, to enable determining automatically that several workflows have the same kind of functionality. This topic of workflow similarity has been extensively studied in the last years and the concept of workflow similarity is now well understood [82,83,84,85]. However, while a few new efficient algorithms have been designed to search for workflows by similarity in large repositories [86] or to cluster similar workflows, none of them have been deployed in workflow sharing platforms.…”

Section: On Workflow Reuse and Reproducibilitymentioning

confidence: 99%

Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities

Cohen-Boulakia

Belhajjame

Collin

et al. 2017

Future Generation Computer Systems

134

100

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With the development of new experimental technologies, biologists are faced with an avalanche of data to be computationally analyzed for scientific advancements and discoveries to emerge. Faced with the complexity of analysis pipelines, the large number of computational tools, and the enormous amount of data to manage, there is compelling evidence that many if not most scientific discoveries will not stand the test of time: increasing the reproducibility of computed results is of paramount importance. The objective we set out in this paper is to place scientific workflows in the context of reproducibility. To do so, we define several kinds of reproducibility that can be reached when scientific workflows are used to perform experiments. We characterize and define the criteria that need to be catered for by reproducibility-friendly scientific workflow systems, and use such criteria to place several representative and widely used workflow systems and companion tools within such a framework. We also discuss the remaining challenges posed by reproducible scientific workflows in the life sciences. Our study was guided by three use cases from the life science domain involving in silico experiments. (Résumé d'auteur

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Section: On Workflow Reuse and Reproducibilitymentioning

confidence: 99%

Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities

Cohen-Boulakia

Belhajjame

Collin

et al. 2017

Future Generation Computer Systems

134

100

View full text Add to dashboard Cite

show abstract

“…As a promising candidate for further research areas, the authors of reference [5] took into account the active feedback of evaluation data in workflow process modelling, which encompassed the entire lifecycle of workflow and enabled active real-time controlling using workflow audit trail data from three perspectives, namely process, resource, and object. In order to assist users in selecting a sufficient workflow with appropriate quality of service (QoS) to meet their requirements, reference [6] proposed a novel approach to scientific workflow retrieval with cost constraints and defined a distance measure for comparing the similarities among cost constrained graph (CCGs), through which workflow retrieval and ranking could be conducted based on similarity computations. To allow companies to respond to changing markets by creating product variants derived from different combinations of existing or new modular components, reference [7] sought to define and measure workflow modularity.…”

Section: Related Workmentioning

confidence: 99%

Trustworthiness Measurement Algorithm for TWfMS Based on Software Behaviour Entropy

Han

2018

Entropy

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As the virtual mirror of complex real-time business processes of organisations' underlying information systems, the workflow management system (WfMS) has emerged in recent decades as a new self-autonomous paradigm in the open, dynamic, distributed computing environment. In order to construct a trustworthy workflow management system (TWfMS), the design of a software behaviour trustworthiness measurement algorithm is an urgent task for researchers. Accompanying the trustworthiness mechanism, the measurement algorithm, with uncertain software behaviour trustworthiness information of the WfMS, should be resolved as an infrastructure. Based on the framework presented in our research prior to this paper, we firstly introduce a formal model for the WfMS trustworthiness measurement, with the main property reasoning based on calculus operators. Secondly, this paper proposes a novel measurement algorithm from the software behaviour entropy of calculus operators through the principle of maximum entropy (POME) and the data mining method. Thirdly, the trustworthiness measurement algorithm for incomplete software behaviour tests and runtime information is discussed and compared by means of a detailed explanation. Finally, we provide conclusions and discuss certain future research areas of the TWfMS.

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Workflows for Bioinformatics Data Integration

COHEN‐BOULAKIA,

LEMOINE

2023

Biological Data Integration

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Cost and accuracy aware scientific workflow retrieval based on distance measure

Cited by 5 publications

References 53 publications

Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities

Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities

Trustworthiness Measurement Algorithm for TWfMS Based on Software Behaviour Entropy

Workflows for Bioinformatics Data Integration

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