WfCommons: A framework for enabling scientific workflow research and development

Coleman, Tainã; Casanova, Henri; Pottier, Loïc; Kaushik, Manav; Deelman, Ewa; Silva, Rafael Ferreira da

doi:10.1016/j.future.2021.09.043

Cited by 27 publications

(3 citation statements)

References 26 publications

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“…Workflow fragment recommendation is an important research problem in the field of service computing (Coleman et al, 2022). It can shorten development cycles and reduce the cost by recommending suitable services and workflow fragments for users (Almarimi et al, 2019) from an open, large-scale library of Web services (Modi and Garg, 2019).…”

Section: Social-aware Workflow Fragment Discoverymentioning

confidence: 99%

“…With the wide-adoption of web service technology, recurring data and computational resources are increasingly encapsulated as web services or mashup APIs and assembled as scientific workflows (Fischer et al, 2021;Coleman et al, 2022). Online repositories, such as myExperiment 1 , are publicly accessible for publishing and sharing of scientific workflows constructed by scientists from various disciplines (Gkortzis et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Bioinformatic workflow fragment discovery leveraging the social-aware knowledge graph

et al. 2022

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Constructing a novel bioinformatic workflow by reusing and repurposing fragments crossing workflows is regarded as an error-avoiding and effort-saving strategy. Traditional techniques have been proposed to discover scientific workflow fragments leveraging their profiles and historical usages of their activities (or services). However, social relations of workflows, including relations between services and their developers have not been explored extensively. In fact, current techniques describe invoking relations between services, mostly, and they can hardly reveal implicit relations between services. To address this challenge, we propose a social-aware scientific workflow knowledge graph (S2KG) to capture common types of entities and various types of relations by analyzing relevant information about bioinformatic workflows and their developers recorded in repositories. Using attributes of entities such as credit and creation time, the union impact of several positive and negative links in S2KG is identified, to evaluate the feasibility of workflow fragment construction. To facilitate the discovery of single services, a service invoking network is extracted form S2KG, and service communities are constructed accordingly. A bioinformatic workflow fragment discovery mechanism based on Yen’s method is developed to discover appropriate fragments with respect to certain user’s requirements. Extensive experiments are conducted, where bioinformatic workflows publicly accessible at the myExperiment repository are adopted. Evaluation results show that our technique performs better than the state-of-the-art techniques in terms of the precision, recall, and F1.

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Section: Social-aware Workflow Fragment Discoverymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bioinformatic workflow fragment discovery leveraging the social-aware knowledge graph

et al. 2022

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“…14 With continuous use of workflows in scientific projects and by user communities, workflows are becoming more complex and require more sophisticated workflow management capabilities. 15 Automated workflow composition (AWC) was demonstrated to be a feasible approach to design novel and similar workflows. Automated Pipeline Explorer (APE) is a commandline tool for AWC.…”

Section: Introductionmentioning

confidence: 99%

An Automated Workflow Composition System for Liquid Chromatography–Mass Spectrometry Metabolomics Data Processing

Du,

Dastmalchi,

Diller

et al. 2023

J. Am. Soc. Mass Spectrom.

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Liquid chromatography−mass spectrometry (LC− MS) metabolomics studies produce high-dimensional data that must be processed by a complex network of informatics tools to generate analysis-ready data sets. As the first computational step in metabolomics, data processing is increasingly becoming a challenge for researchers to develop customized computational workflows that are applicable for LC−MS metabolomics analysis. Ontology-based automated workflow composition (AWC) systems provide a feasible approach for developing computational workflows that consume high-dimensional molecular data. We used the Automated Pipeline Explorer (APE) to create an AWC for LC− MS metabolomics data processing across three use cases. Our results show that APE predicted 145 data processing workflows across all the three use cases. We identified six traditional workflows and six novel workflows. Through manual review, we found that onethird of novel workflows were executable whereby the data processing function could be completed without obtaining an error. When selecting the top six workflows from each use case, the computational viable rate of our predicted workflows reached 45%. Collectively, our study demonstrates the feasibility of developing an AWC system for LC−MS metabolomics data processing.

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Robust Makespan Optimization via Genetic Algorithms on the Scientific Workflow Scheduling Problem

Barredo

Puente

2022

Bio-Inspired Systems and Applications: From Robotics to Ambient Intelligence

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WfCommons: A framework for enabling scientific workflow research and development

Cited by 27 publications

References 26 publications

Bioinformatic workflow fragment discovery leveraging the social-aware knowledge graph

Bioinformatic workflow fragment discovery leveraging the social-aware knowledge graph

An Automated Workflow Composition System for Liquid Chromatography–Mass Spectrometry Metabolomics Data Processing

Robust Makespan Optimization via Genetic Algorithms on the Scientific Workflow Scheduling Problem

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