CfP Workshop on Data Mining in Agriculture DMA 2013

Call for Paper
          Intern. Workshop Data Mining in Agriculture DMA 2013
                 July 19, 2013, New York/ USA

                        Workshop Chair
                Georg Ru�, tecData AG, Uzwil, Switzerland

                       Program Committee
      Alexander Brenning, University of Waterloo, Waterloo, Canada
      Warwick Graco, Australian Taxation Office, Canberra, Australia
            Ernesto W. De Luca, TU Berlin, Germany Gonzalo Pajares Martinsanz, University Complutense of Madrid, Spain
          Antonio Mucherino, CERFACS, Toulouse, France Allan Tucker, Brunel University, London, UK

Data mining, the art and science of intelligent analysis of (usually large) data sets for meaningful
(and previously unknown) insights, is nowadays actively applied in a wide range of disciplines related
to agriculture. Due to the emerging importance of data mining techniques and methodologies in the area
of agriculture, this workshop aims to bring together practitioners and researchers in this field. It
creates a community of people who are actively using data mining tools and techniques and apply them
to agriculture data.

                         Scope of the Workshop
Carrying out effective and sustainable agriculture has become an important issue in recent years.
Agricultural production has to keep up with an ever-increasing population. A key to this is the usage
of modern technologies such as GPS (for precision agriculture) and data mining techniques to take advantage
of the soil's heterogeneity. The large amounts of data that are nowadays virtually harvested along with the
crops have to be analysed and should be used to their full extent - this is clearly a data mining task.
Data mining allows to extract the most important information from such vast data and to uncover previously
unknown patterns that may be relevant to current agricultural problems, thereby helping farmers and managing
organisations to transform data into business decisions.

The goals of this workshop are to provide a forum for identifying important contributions and opportunities
for research on data mining as it applies to agriculture to promote the systematic study of how to apply data
mining to agriculture data to develop practical applications.

Topics of interest include (but are not limited to):
* Data Mining on Sensor and Spatial Data from Agricultural Applications
* Analysis of Remote Sensor Data
* Feature Selection on Agricultural Data
* Evaluation of Data Mining Experiments
* Spatial Autocorrelation in Agricultural Data

Target Group
* Computer scientists working on agriculture problems
* Machine learners, data miners and statisticians with an interest in agriculture
* Agricultural researchers with a background in data mining
* Agriculture professionals with data mining applications and showcases
* Middleware developers covering data mining aspects in data (pre)processing
* Farmers with an interest in data mining and related aspects
..and similar professional and research people

Submission Requirements
Workshop papers will be published in the workshop proceedings by ibai-publishing.
PostScript (compressed and uncoded) or PDF paper submissions should be formatted according to Springer LNCS format,
with a maximum of ten pages. Author's instructions along with LaTeX and Word macro files are available on the web at
Springer (

Please submit the electronic version of your camera-ready paper through the CMS-system. If you have any problems with
the system please do not hesitate to contact

Important Dates
Submission Deadline: March 20th, 2013
Notification Date: April 30th, 2013
Camera-Ready Deadline: May 12th, 2013
Workshop date: July 19th, 2013

New York Do, 24.Jan.2013

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