large data sets

[Francisco Cribari Neto <cribari@de.ufpe.br>]

SYMPOSIUM ON LARGE DATA SETS

November 6th, 2003
Amsterdam, The Netherlands
http://www.vvs-ssp.nl/symposium2003.html


Organization
________________________________
Section Statistical Software of The Netherlands Society for Statistics and 
Operations Research


Program Committee
________________________________
Dr. Ruud Koning, Universiteit of Groningen
Prof.dr. Arno Siebes, University of Utrecht
Dr. Siem Heisterkamp, National Institute of Public Health and the Environment 
(RIVM)
Prof.dr. Patrick Groenen, Erasmus University Rotterdam


Large Data Sets
________________________________
Fifteen years ago, handling of large datasets, let alone analysis in them was 
a nearly impossible task for researchers. The data were often stored on tape, 
and even the process of reading the dataset into the memory of a mainframe 
was slow. Memory was scarce, and so it was difficult to save intermediate 
results. Such datasets were analyzed using either tailor-made statistical 
software, or self-written programs using routines from numerical libraries 
like NAG or IMSL. Maximum-likelihood estimation of non-linear models was 
non-trivial if not impossible, and researchers often had to be satisfied with 
one-step improvements over some consistent estimator.

Things have changed for the better, from a technical point of view.  Huge 
datasets are routinely available to researchers in different fields, like 
finance, marketing, biomedical sciences, particle physics, astronomy, life 
sciences, and social sciences. Datasets used to be large in the sense of 
containing many observations on a small number of variables. But nowadays, 
e.g. in the life sciences we are confronted with datasets with a small number 
of observations and a huge number of variables. Data can be transported on 
media that can be read by most personal computers, and the computing power on 
the desk of a statistical researcher is absolutely impressive. Instead of 
focusing on the mechanics of the analysis of datasets, researchers can focus 
on the actual statistical analysis. Thus the question has turned into: Now 
that we have a lot of data, what could we do with it?

This conference addresses the analysis of very large datasets, both from the 
point of view of a statistician who works with such datasets as well as the 
point of view of practitioners from various fields. By presenting several 
applications and tools available to a modern day statistical researcher, we 
want to show that large datasets offer unique opportunities for researchers 
to answer questions that were difficult to tackle before. The program 
committee is delighted to be able to present a selection of the top 
researchers on this topic.


Registration
________________________________
Please register via email to admin@vvs-ssp.nl or online via:
http://www.vvs-ssp.nl/symposium2003registration.html


Program
________________________________
9:30  registration and coffee
10:00  opening
10:05  Yoav Benjamini
       Tel-Aviv University
       Multiplicity issues related to complex research questions
       in microarrays analysis
10:55  Philip Hans Franses
       Erasmus University, Rotterdam
       More, but also better?
11:40  Paul Eilers
       Leiden University Medical Centre
       Low Memory, High Speed Smoothing on Large
       Multidimensional Grids
12:30  Lunch
13:30  Andreas Buja
       University of Pennsylvania
       Hands-On Experiences with Mining Telecom Data
14:15  Jos Roerdink
       University of Groningen
       Visualization of large data sets with applications in
       life science
15:00  coffee/ tea break
15:15  Geert Wets
       Limburg University, Belgium
       Large data sets in traffic safety
16:30  Drinks



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The Netherlands

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-- 
Francisco Cribari-Neto               voice: +55-81-32747425
Departamento de Estatistica          fax:   +55-81-32718422
Universidade Federal de Pernambuco   e-mail: cribari@de.ufpe.br
Recife/PE, 50740-540, Brazil         http://www.de.ufpe.br/~cribari/

"Dear friend, theory is all grey and the golden tree of life is green."
                                                        --Goethe