BPMN task instance streaming for efficient micro-task crowdsourcing processes

Stefano Tranquillini, Florian Daniel, Pavel Kucherbaev, Fabio Casati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The Business Process Model and Notation (BPMN) is a standard for modeling and executing business processes with human or machine tasks. The semantics of tasks is usually discrete: a task has exactly one start event and one end event; for multi-instance tasks, all instances must complete before an end event is emitted. We propose a new task type and streaming connector for crowdsourcing able to run hundreds or thousands of micro-task instances in parallel. The two constructs provide for task streaming semantics that is new to BPMN, enable the modeling and efficient enactment of complex crowdsourcing scenarios, and are applicable also beyond the special case of crowdsourcing. We implement the necessary design and runtime support on top of Crowd- Flower, demonstrate the viability of the approach via a case study, and report on a set of runtime performance experiments.

Original languageEnglish
Title of host publicationBusiness Process Management - 13th International Conference, BPM 2015, Proceedings
PublisherSpringer Verlag
Pages333-349
Number of pages17
Volume9253
ISBN (Print)9783319230627
DOIs
Publication statusPublished - 2015
Event13th International Conference on Business Process Management, BPM 2015 - Innsbruck, Austria
Duration: 31 Aug 20153 Sep 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9253
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Business Process Management, BPM 2015
CountryAustria
CityInnsbruck
Period31.8.153.9.15

Fingerprint

Business Model
Streaming
Business Process
Notation
Process Model
Semantics
Industry
Connector
Modeling
Viability
Scenarios
Necessary
Demonstrate
Experiment
Experiments

Keywords

  • BPMN
  • Crowdsourcing processes
  • Task instance streaming

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Tranquillini, S., Daniel, F., Kucherbaev, P., & Casati, F. (2015). BPMN task instance streaming for efficient micro-task crowdsourcing processes. In Business Process Management - 13th International Conference, BPM 2015, Proceedings (Vol. 9253, pp. 333-349). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9253). Springer Verlag. https://doi.org/10.1007/978-3-319-23063-4_23

BPMN task instance streaming for efficient micro-task crowdsourcing processes. / Tranquillini, Stefano; Daniel, Florian; Kucherbaev, Pavel; Casati, Fabio.

Business Process Management - 13th International Conference, BPM 2015, Proceedings. Vol. 9253 Springer Verlag, 2015. p. 333-349 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9253).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Tranquillini, S, Daniel, F, Kucherbaev, P & Casati, F 2015, BPMN task instance streaming for efficient micro-task crowdsourcing processes. in Business Process Management - 13th International Conference, BPM 2015, Proceedings. vol. 9253, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9253, Springer Verlag, pp. 333-349, 13th International Conference on Business Process Management, BPM 2015, Innsbruck, Austria, 31.8.15. https://doi.org/10.1007/978-3-319-23063-4_23
Tranquillini S, Daniel F, Kucherbaev P, Casati F. BPMN task instance streaming for efficient micro-task crowdsourcing processes. In Business Process Management - 13th International Conference, BPM 2015, Proceedings. Vol. 9253. Springer Verlag. 2015. p. 333-349. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-23063-4_23
Tranquillini, Stefano ; Daniel, Florian ; Kucherbaev, Pavel ; Casati, Fabio. / BPMN task instance streaming for efficient micro-task crowdsourcing processes. Business Process Management - 13th International Conference, BPM 2015, Proceedings. Vol. 9253 Springer Verlag, 2015. pp. 333-349 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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