The ACM DEBS 2017 Grand Challenge is the seventh in a series of challenges which seek to provide a common ground and evaluation criteria for a competition aimed at both research and industrial event-based systems. The focus of the 2017 Grand Challenge is on the analysis of the RDF streaming data generated by digital and analogue sensors embedded within manufacturing equipment. The analysis aims at the detection of anomalies in the behavior of such manufacturing equipment. This paper describes the specifics of the data streams and continuous queries that define the DEBS 2017 Grand Challenge. It also describes the benchmarking platform that supports testing of corresponding solutions.
%0 Conference Paper
%1 Gulisano:2017:DGC:3093742.3096342
%A Gulisano, Vincenzo
%A Jerzak, Zbigniew
%A Katerinenko, Roman
%A Strohbach, Martin
%A Ziekow, Holger
%B Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems
%C New York, NY, USA
%D 2017
%I ACM
%K projecthobbit
%P 271--273
%R 10.1145/3093742.3096342
%T The DEBS 2017 Grand Challenge
%U http://doi.acm.org/10.1145/3093742.3096342
%X The ACM DEBS 2017 Grand Challenge is the seventh in a series of challenges which seek to provide a common ground and evaluation criteria for a competition aimed at both research and industrial event-based systems. The focus of the 2017 Grand Challenge is on the analysis of the RDF streaming data generated by digital and analogue sensors embedded within manufacturing equipment. The analysis aims at the detection of anomalies in the behavior of such manufacturing equipment. This paper describes the specifics of the data streams and continuous queries that define the DEBS 2017 Grand Challenge. It also describes the benchmarking platform that supports testing of corresponding solutions.
%@ 978-1-4503-5065-5
@inproceedings{Gulisano:2017:DGC:3093742.3096342,
abstract = {The ACM DEBS 2017 Grand Challenge is the seventh in a series of challenges which seek to provide a common ground and evaluation criteria for a competition aimed at both research and industrial event-based systems. The focus of the 2017 Grand Challenge is on the analysis of the RDF streaming data generated by digital and analogue sensors embedded within manufacturing equipment. The analysis aims at the detection of anomalies in the behavior of such manufacturing equipment. This paper describes the specifics of the data streams and continuous queries that define the DEBS 2017 Grand Challenge. It also describes the benchmarking platform that supports testing of corresponding solutions.},
acmid = {3096342},
added-at = {2017-08-28T09:00:28.000+0200},
address = {New York, NY, USA},
author = {Gulisano, Vincenzo and Jerzak, Zbigniew and Katerinenko, Roman and Strohbach, Martin and Ziekow, Holger},
biburl = {https://www.bibsonomy.org/bibtex/2e0feef918b77efcb39f15c4934ad9fe7/georgis_chris},
booktitle = {Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems},
doi = {10.1145/3093742.3096342},
interhash = {fdc39b7c0cc3d222f564fd5a630e81bf},
intrahash = {e0feef918b77efcb39f15c4934ad9fe7},
isbn = {978-1-4503-5065-5},
keywords = {projecthobbit},
location = {Barcelona, Spain},
numpages = {3},
pages = {271--273},
publisher = {ACM},
series = {DEBS '17},
timestamp = {2017-08-28T15:50:49.000+0200},
title = {The DEBS 2017 Grand Challenge},
url = {http://doi.acm.org/10.1145/3093742.3096342},
year = 2017
}