Process minding: Closing the big data gap

Avigdor Gal, Arik Senderovich

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The discipline of process mining was inaugurated in the BPM community. It flourished in a world of small(er) data, with roots in the communities of software engineering and databases and applications mainly in organizational and management settings. The introduction of big data, with its volume, velocity, variety, and veracity, and the big strides in data science research and practice pose new challenges to this research field. The paper positions process mining along modern data life cycle, highlighting the challenges and suggesting directions in which data science disciplines (e.g., machine learning) may interact with a renewed process mining agenda.

Original languageEnglish
Title of host publicationBusiness Process Management - 18th International Conference, BPM 2020, Proceedings
EditorsDirk Fahland, Chiara Ghidini, Jörg Becker, Marlon Dumas
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages14
ISBN (Print)9783030586652
StatePublished - 2020
Event18th International Conference on Business Process Management, BPM 2020 - Seville, Spain
Duration: 13 Sep 202018 Sep 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12168 LNCS


Conference18th International Conference on Business Process Management, BPM 2020

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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