Meetings

Location:  DIMACS Center, CoRE Building,
Rutgers University, Piscataway, NJ

Organizers:
Adam Buchsbaum, AT&T Labs - Research, alb@research.att.com
Rajeev Motwani, Stanford University, rajeev@cd.standford.edu
Jennifer Rexford, AT&T Labs, jrex@research.att.com

Presented under the auspices of the Special Focus on
Data Analysis and Mining.

The DIMACS Working Group on Streaming Data Analysis will begin with a
public workshop on the topic, to be held on November 5, 2001, at
DIMACS. At the workshop, participants in the working group will
present current work on analyzing data streams.

Data stream analysis presents many practical and theoretical challenges.
Many critical applications require immediate (seconds) decision making
based on current information: e.g., intrusion detection and fault
monitoring. Data must be analyzed as it arrives, not off-line
after being stored in a central database. Processing and integrating the
massive amounts of data generated by a number of continuously
operating, heterogeneous sources poses is not straightforward. At some
point, data sets become so large as to preclude most computations
that require more than one scan of the data, as they stream by. Analysis of
data streams also engenders new problems in data visualization. How is
time-critical information best displayed? Can automatic response
systems be created to deal with common cases? Etc.

Speakers at the workshop will discuss current work in all aspects of data
stream analysis: theoretical issues, including modeling; practical
issues, including work on existing systems; and bridges and
bottlenecks, both current and potential, between theory and
practice. The goal of the workshop and the ensuing working group is to
foster interdisciplinary collaborations among researchers studying
data streams from many disparate perspectives and application areas.

Preregistration Deadline: October 29, 2001.

Information on participation, registration, accommodations, and travel can
be found at:

http://dimacs.rutgers.edu/Workshops/Streaming/