The dramatic increase in the availability of data from various sources is creating many fundamental challenges in computing, storage, communication, and human computer interaction issues for data mining. Scientists, engineers, and businesses are faced with problems that involve understanding complex networked observations, massive simulation data sets, and ubiquitous sensory data streams. These heterogeneous data sources should be linked and analyzed for discovering the next frontiers of science, arts, and technology. We also need to look beyond the current cyber-infrastructure and explore how the next generation of networked data mining applications will support such large-scale, ubiquitous, multi-source, and data intensive domains.

This workshop on Next Generation Data Mining and Cyber Enabled Discovery for Innovation (NGDM-07) brings together data mining researchers, scientists and engineers from diverse backgrounds along with domain experts for various emerging problems that are relevant to Cyber Enabled Discovery for Innovation (CDI). NGDM-07 focuses on the areas of: data mining in sciences, engineering and digital humanities; data mining for security and surveillance with information privacy and security considerations; multimedia data mining; pervasive computing and ubiquitous data mining; and the web, semantics, and data mining.

The interdisciplinary nature of the workshop provides a forum for the participants to cooperatively analyze the state of the art in data mining and its role in CDI and formulate new data mining research directions, and outline development or infrastructure issues and activities that are fundamental in supporting CDI challenges. The workshop participants will also discuss fruitful collaborative and synergistic activities that will foster creation of CDI environments.

The workshop will generate a report detailing future directions of data mining research and will suggest promising modalities of research with an aim to foster innovation and technology transfer. The workshop website (www.cs.umbc.edu/~hillol/NGDM07/) also includes links to other relevant material.

Agency
National Science Foundation (NSF)
Institute
Division of Information and Intelligent Systems (IIS)
Type
Standard Grant (Standard)
Application #
0748951
Program Officer
Maria Zemankova
Project Start
Project End
Budget Start
2007-09-01
Budget End
2008-08-31
Support Year
Fiscal Year
2007
Total Cost
$49,500
Indirect Cost
Name
University of Maryland Baltimore County
Department
Type
DUNS #
City
Baltimore
State
MD
Country
United States
Zip Code
21250