DistillFlow: removing redundancy in scientific workflows - Laboratoire d'informatique de l'école polytechnique Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

DistillFlow: removing redundancy in scientific workflows

Résumé

Scientific workflows management systems are increasingly used by scientists to specify complex data processing pipelines. Workflows are represented using a graph structure, where nodes represent tasks and links represent the dataflow. However, the complexity of workflow structures is increasing over time, reducing the rate of scientific workflows reuse. Here, we introduce DistillFlow, a tool based on effective methods for workflow design, with a focus on the Taverna model. DistillFlow is able to detect "anti-patterns" in the structure of workflows (idiomatic forms that lead to over-complicated design) and replace them with different patterns to reduce the workflow's overall structural complexity. Rewriting workflows in this way is beneficial both in terms of user experience and workflow maintenance.
Fichier principal
Vignette du fichier
distillflowdemo.pdf (1.39 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01091033 , version 1 (04-12-2014)

Identifiants

Citer

Jiuqiang Chen, Sarah Cohen-Boulakia, Christine Froidevaux, Carole Goble, Paolo Missier, et al.. DistillFlow: removing redundancy in scientific workflows. SSDBM '14 Proceedings of the 26th International Conference on Scientific and Statistical Database Management, Jun 2014, Aalborg, Denmark. ⟨10.1145/2618243.2618287⟩. ⟨hal-01091033⟩
339 Consultations
155 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More