-------- Original-Nachricht -------- Betreff: [AISWorld] IEEE TSC special issue on "Processes meet Big Data" Datum: Mon, 09 Dec 2013 11:16:25 +0100 Von: Rafael Accorsi rafael.accorsi@iig.uni-freiburg.de Organisation: University of Freiburg, Germany An: aisworld@lists.aisnet.org Kopie (CC): Rafael Accorsi rafael.accorsi@iig.uni-freiburg.de
====================================================================== Call for Papers IEEE Transactions on Services Computing SPECIAL ISSUE "PROCESSES MEET BIG DATA"
Website: http://bit.ly/TV0hlO CFP in PDF: http://bit.ly/XyMGxz ======================================================================
*AIMS AND SCOPE* The aim of process mining is to discover, monitor and improve business processes by extracting knowledge from event logs readily available in today's information systems. When large-scale processes are executed, e.g., on (cloud-based) service-oriented environments, process logs increasingly exhibit all typical properties of “big data”: wide physical distribution, diversity of formats, non-standard data models, heterogeneous semantics. Computing metrics over such "big logs" also requires to handle security and privacy concerns of many participants, and even to deal with non-uniform trustworthiness of log entries. New techniques are therefore required for designing, validating and deploying process metrics in this scenario, as well as for effectively dash-boarding the processes' performance indicators.
This special issue of IEEE Transaction on Service-Oriented Computing is intended to create an international forum for presenting innovative developments of process monitoring and analysis over service-oriented architectures, aimed at handling “big logs” and use them effectively for discovery, dash-boarding and mining. The ultimate objective is to identify the promising research avenues, report the main results and promote the visibility and relevance of this new area.
The special issue is related to two Dagstuhl Seminars happening in 2013: - Unleashing Operational Process Mining http://www.dagstuhl.de/en/program/calendar/semhp/?semnr=13481
- Verifiably Secure Process-Aware Information Systems http://www.dagstuhl.de/en/programm/kalender/semhp/?semnr=13341
*TOPICS COVERED* - Software engineering methods for scalable data analysis - Engineering software to handle "big logs" - Process monitoring on SOA and clouds - Validation and benchmarking of process monitoring - Efficiently mining rare patterns in "big logs" - Scalable techniques for distributed process monitoring - Monitoring and analysis of cloud-based processes - Architectures and data models for synthesizing and handling "big logs" - Privacy-aware computation of process metrics - Securing log data - Log obfuscation and access control - Practical systems and tools for big log analysis and log dashboards - Applications combining process management and big data, e.g. audit
*IMPORTANT DATES* January 30, 2014: Submission deadline March 30, 2014: Notification of the first-round review April. 30, 2014: Revised submission due June 15, 2014: Final notice of acceptance/reject
*SUBMISSION GUIDELINES* Manuscripts should be prepared according to the instruction of the "Information for Authors" section of the journal. Submissions should be done through the IEEE TSC journal website: http://mc.manuscriptcentral.com/tsc-ieee/. Submitted manuscripts will be thoroughly reviewed using the standard procedure that is followed for regular IEEE TSC submissions.
*GUEST EDITORS* Wil M.P. van der Aalst (TU Eindhoven, NL) Rafael Accorsi (U of Freiburg, DE) Ernesto Damiani (U of Milan, IT)