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Vol: 61(75) No: 1 / March 2016      

Provenance Based Runtime Manipulation and Dynamic Execution Framework for Scientific Workflows
Eszter Kail
Obuda University, John von Neumann Faculty of Informatics, Bécsi str. 96/b., H-1034, Budapest, Hungary, phone: (+36) 555-5555, e-mail: kail.eszter@nik.uni-obuda.hu
Anna Bánáti
Obuda University, John von Neumann Faculty of Informatics , Bécsi str. 96/b., H-1034, Budapest, Hungary, e-mail: banati.anna@nik.uni-obuda.hu
Péter Kacsuk
MTA SZTAKI, LPDS, Kende str. 13-17, H-1111, Budapest, Hungary, e-mail: miklos.kozlovszky@sztaki.mta.hu
Miklós Kozlovszky
University of Westminster, 115 New Cavendish Street, London W1W 6UW, United Kingdom, e-mail: peter.kacsuk@sztaki.mta.hu


Keywords: scientific workflow, dynamic execution, interaction, user steering, provenance.

Abstract
Scientific workflows (swf) are commonly used to model and execute large-scale scientific experiments. From the scientist\'s perspective the workflow execution is like black boxes. The scientist submits the workflow and at the end, the result or a notification about failed completion is returned. Concerning long running experiments or when workflows are in experimental phase it may not be acceptable. Scientist need some feedback about the actual status of the execution, about failures and about intermediary results in order to save energy and time and to make adequat deceisions about the continuation. Thus scientists need to monitor the experiment during its execution in order to fine-tune their experiments or to analyze provenance data and dynamically interfere with the execution of the scientific experiment. To the best of our knowledge most of the existing solutions for dynamic execution aim to help in better optimisation but do not solve the problem of real user steering. To support the scientist with special user interaction tool we introduced the concept of intervention points (iPoints) where the user takes over the control for a while and has the possibility to interfere, namely to change some parameters or data, to stop, to restart the workflow or even to deviate from the original workflow model during enactment. We plan to implement our solution in IWIR language which was targeted to provide interoperability between four existing well-known Scientific Workflow Management Systems (SWfMS) within the framework of the SHIWA project.

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