International Workshop on Spatio-temporal Data Mining in Life Sciences (SDM-LS 2007)

In Conjunction with

The 2007 International Conference on Intelligent Pervasive Computing (IPC-07)

October 11th - 13th, 2007, Jeju Island, Korea

CFP download (PDF)

Spatio-temporal data mining aims at discovering interesting, novel and useful relationships among very large set of objects which change their locations over time. Data mining tasks in this domain are more challenging than in traditional data sets because of the complex nature of the data, and the inapplicability of optimization techniques based on assumptions of statistical independence.

In this workshop, we shall explore the challenges and opportunities of spatio-temporal data mining on the data collected in life sciences in general. Here life sciences are loosely defined as the sciences of life and living objects including viruses, grasses, fungi, other plants, insects, birds, invasive species, humans, etc. Some motivating questions include: What can we do with data mining for the structure, evolution, distribution and habitat of living objects over time? What are unique data mining problems in life sciences? What are the significant patterns of changes in various properties of living objects? What are the primary causes of the changes? How do we efficiently explore living objects at a large scale?

To this end, we are soliciting high quality research papers from researchers and practitioners, which address directly or indirectly a range of issues in spatio-temporal data mining in life sciences including, but not limited to:

  • Algorithms of high performance, robustness and scalability.
  • Data structures for efficient data representation and processing.
  • Data cleaning of noise, outliers and missing/uncertain data.
  • Feature selection in life sciences data.
  • Duplicate detection and cleaning in heterogeneous data sources.
  • Spatiotemporal models of living objects.
  • Spatiotemporal models for the structure, evolution and habitat of living objects.
  • Visualization of spatial/temporal data mining results.
  • Applications of data mining with a large data set of living objects.
  • Spatiotemporal data mining on genealogy data.
  • Spatiotemporal data mining on herbarium data.
  • Spatiotemporal data mining on agricultural data.
  • Spatiotemporal data mining on land-cover change.
  • Novel and non-trivial applications.
  • Work in progress at a large scale.

Important Dates

Paper submission due: June 8, 2007
Acceptance notification: July 2, 2007
Camera Ready Due: July 10, 2007
Workshop Dates: October 11, 2007

Paper Submission

 Submit a full paper not exceed 6 pages (IEEE Computer Society Proceedings Manuscripts style: two columns, single-spaced), including figures and references, using 10 fonts, and number each page. You can confirm the IEEE Computer Society Proceedings Author Guidelines at the following web page: URL:

    SDM-LS 2007's submission web site : Click Here

 Accepted papers will be given guidelines in preparing and submitting the final manuscript(s) together with the notification of acceptance. The proceedings will be published by IEEE Computer Society Press with 6 pages for each paper. Authors of accepted papers, or at least one of them, are requested to register and present their work at the conference, otherwise their papers will be removed from the digital library after the conference.

Organizing Committee

Workshop Organizer:

SeungJin Lim, Utah State University, USA (

Program Committee (to be updated):

Walid Aref, Purdue, USA
Michael Chau, University of Hong Kong, China
Reynold Cheng, Hong Kong Polytechnic University, China
Hyoil Han, Drexel University, USA
Kathleen Stewart Hornsby, University of Maine, USA
Panos Kalnis, National University of Singapore, Singapore
Woong-Kee Loh, University of Minnesota
Mohamed F. Mokbel, University of Minnesota, USA
Cyrus Shahabi, USC, USA
Shashi Shekhar, University of Minnesota, USA
Anna Shillabeer, Flinders University, Australia
Yannis Theodoridis, University of Piraeus, Greece
Man Lung Yiu, Aalborg University, Denmark
Slawomir Zadrozny, Polish Academy of Sciences, Poland
Donghui Zhang, Northeastern University, USA