GECCO Industrial Challenge 2017 Dataset: A water quality dataset for the 'Monitoring of drinking-water quality' competition at the Genetic and Evolutionary Computation Conference 2017, Berlin, Germany.

Dataset  of the 'Industrial Challenge: Monitoring of drinking-water quality' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 15th-19th 2017, Berlin, Germany

The task of the competition was to develop an anomaly detection algorithm for a water- and environmental data set.

Included in zenodo: 

- dataset of water quality data

- additional material and descriptions provided for the competition

The competition was organized by:

M. Friese, J. Stork, A. Fischbach, M. Rebolledo, T. Bartz-Beielstein (TH Köln)

The dataset was provided and prepared by:

Thüringer Fernwasserversorgung,

IMProvT research project (S. Moritz)

Industrial Challenge: Monitoring of drinking-water quality

Description:

Water covers 71% of the Earth's surface and is vital to all known forms of life. The provision of safe and clean drinking water to protect public health is a natural aim. Performing regular monitoring of the water-quality is essential to achieve this aim.

Goal of the GECCO 2017 Industrial Challenge is to analyze drinking-water data and to develop a highly efficient algorithm that most accurately recognizes diverse kinds of changes in the quality of our drinking-water.

Submission deadline:

June 30, 2017

Official webpage:

http://www.spotseven.de/gecco-challenge/gecco-challenge-2017/