[dbsec] IEEE TSC special issue on "Processes meet Big Data"

  • From: Rafael Accorsi <rafael.accorsi@xxxxxxxxxxxxxxxxxxx>
  • To: wi@xxxxxxxxxxxxxxxxxxxxx, dbsec@xxxxxxxxxxxxx, safe-nl@xxxxxxxxxxxxxxxxxxxxx, aisworld@xxxxxxxxxxxxxxxx, IEEE.TFoPM@xxxxxxxxxxxxxxxxx
  • Date: Thu, 24 Jan 2013 11:03:47 +0100

Call for Papers
IEEE Transactions on Services Computing

Website: <http://bit.ly/TV0hlO>     CFP in PDF: <http://bit.ly/XyMGxz>

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

- Verifiably Secure Process-Aware Information Systems

- 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

Aug. 1, 2013: Submission deadline
Nov. 1, 2013: Notification of the first-round review
Jan. 10, 2014: Revised submission due
Mar. 1, 2014: Final notice of acceptance/reject

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.

Wil M.P. van der Aalst (TU Eindhoven, NL)
Rafael Accorsi (U of Freiburg, DE)
Ernesto Damiani (U of Milan, IT)

Dr. Rafael Accorsi

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