*************************************************************** * Special Issue on Workflows for Data-Driven Research * Journal Future Generation Computer Systems * http://www.journals.elsevier.com/future-generation-computer-systems/call-for... **************************************************************** Data-intensive Workflows (a.k.a. scientific workflows) are routinely used in the majority of data-driven research disciplines today, often exploiting rich and diverse data resources and parallel and distributed computing platforms. This special issue focuses on the many facets of data-intensive and data-dependent workflows, from their use as a notation for describing, refining and sharing data-driven methods to the underpinning management systems that enact those methods. As such, it will welcome insights and clarity about any relevant topics including notations, strategies and tools for creating high quality data-intensive methods, and all aspects of mapping such methods onto platforms and organizing their execution, during their development and during their production use. The special issue therefore covers a broad range of topics in the scientific workflow lifecycle that include: the representation of data-intensive workflows and their enactment; workflow design and composition interfaces; workflow mapping techniques that may optimize the execution of the workflow; workflow enactment engines that need to deal with failures in the application and execution environment; and a number of computer science problems related to scientific workflows such as semantic technologies, compiler methods, fault detection and tolerance. The special issue welcomes research as well as position papers. Areas include, but are not limited to: - Workflow applications and their requirements - Abstract models and notations for data-intensive workflows - Methods for designing, refining and quality assuring workflows - Workflow composition, tools and languages - Workflow interoperability - Workflow debugging methods and tools - Workflow provenance collection, representation and use - Interactive workflows engaging domain specialists’ judgment - Workflow user environments, including portals - Methods and tools for mapping workflows to target platforms - Diverse platforms: e.g. HPC, HTC, Cloud and specialized data-intensive clusters, and smart devices - Exascale computing with workflows - Data streaming systems - Data-driven workflow processing - Workflow execution in distributed environments - Adaptive workflows - Dynamic data-dependent workflow systems - Big Data analytics workflows - Workflow fault-tolerance and recovery techniques - Workflow monitoring - Workflow optimizations - Performance analysis of workflows - Workflows for live data streams or dynamic networks e.g. sensor nets, Internet of Things (IoT) or mobile devices - Current and future challenges for data-driven workflow research *Submission Guidelines* Original, high quality contributions that are not yet published or that are not currently under review by other journals or peer-reviewed conferences are sought. Exceptions that may be accepted are invited high-quality papers from the last 10 years of the workshop WORKS and which are very significantly updated and extended. These must have at least 40% difference from the original conference papers. Papers will be peer reviewed by independent reviewers and selected based on originality, scientific quality and relevance to this Special Issue. The journal editors will make final decisions on the acceptance of the papers. Authors should prepare their manuscript according to the Guide for Authors available from the online submission page of the Future Generation Computer Systems at http://ees.elsevier.com/fgcs. Authors should select “SI: WORKS” when they reach the “Article Type” step in the submission process. *Important Dates* Paper submission due: 30 April, 2016 First-round acceptance notification: 30 June 2016 Revision submission: 15 September 2016 Notification of final decision: 15 January 2017 Submission of final paper: 28 February 2017 Expected publication: May 2017 *Guest Editors* Ian Taylor, University of Cardiff, UK and University of Notre Dame, USA Johan Montagnat, CNRS, France Malcolm Atkinson, University of Edinburgh, UK Sandra Gesing, University of Notre Dame, USA ------------------------------------------------------------------------------------------------------------ Sandra Gesing Research Assistant Professor, Department of Computer Science and Engineering Computational Scientist, Center for Research Computing University of Notre Dame http://www3.nd.edu/~sgesing ------------------------------------------------------------------------------------------------------------