The 5th IFIP International Symposium on Data-Driven Process Discovery and Analysis

The IFIP International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA 2014) offers a unique opportunity to present new approaches and research results to researchers and practitioners working in business process data modeling, representation and privacy-aware analysis.

The symposium will bring together leading researchers, engineers and scientists from around the world. Full papers must not exceed 15 pages. Short papers are limited to at most 4 pages. All papers must be original contributions, not previously published or under review for publication elsewhere. All contributions must be written in English and must follow the LNCS Springer Verlag format. Templates can be downloaded from:

Accepted papers will be published in a pre-proceeding volume of CEUR workshop series. The authors of the accepted papers will be invited to submit extended articles to a post-symposium proceedings volume hich will be published in the LNBIP series (Lecture Notes in Business Information Processing,, scheduled for eraly 2015 (extended papers length will be between 7000 and 9000 words). Around 10-15 papers will be selected for publication after a second round of review.

Topics of interest for submission include, but are not limited to:

  • Business Process modeling languages, notations and methods
  • Lightweight Process Model
  • Data-aware and data-centric approaches
  • Process Mining with Big Data
  • Variability and configuration of process models
  • Process simulation and static analyses
  • Process data query languages
  • Process data mining
  • Privacy-aware process data mining
  • Process metadata and semantic reasoning
  • Process patterns and standards
  • Foundations of business process models
  • Resource management in business process execution
  • Process tracing and monitoring
  • Process change management and evolution
  • Business process lifecycle
  • Case studies and experience reports
  • Social process discovery
  • Crowdsourced process definition and discovery