Talks and Poster Presentations (with Proceedings-Entry):
A. Murguzur, J. Schleicher, H. Truong, S. Trujillo, S. Dustdar:
"DRain: An Engine for Quality-of-Result Driven Process-Based Data Analytics (Short Paper)";
Talk: 12th International Conference on Business Process Management (BPM 2014),
Eindhoven, The Netherlands;
- 2014-09-11; in: "Business Process Management, 12th International Conference, BPM 2014, Proceedings",
S. Sadiq, P. Soffer, H. Völzer (ed.);
The analysis of massive amounts of diverse data provided by large cities, combined with the requirements from multiple domain experts and users, is becoming a challenging trend. Although current
process-based solutions rise in data awareness, there is less coverage
of approaches dealing with the Quality-of-Result (QoR) to assist data
analytics in distributed data-intensive environments. In this paper, we present the fundamental building blocks of a framework for enabling
process selection and configuration through user-defined QoR at runtime. These building blocks form the basis to support modeling, execution and configuration of data-aware process variants in order to perform analytics. They can be integrated with different underlying APIs, promoting abstraction, QoR-driven data interaction and configuration. Finally, we carry out a preliminary evaluation on the URBEM scenario, concluding that our framework spends little time on QoR-driven selection and configuration of data-aware processes.
Data-aware Processes, Runtime Configuration, Data Analytics, Smart Cities
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Created from the Publication Database of the Vienna University of Technology.