|
|
|
@inproceedings{DBLP:conf/ssdbm/StiberJS97,
author = {Michael Stiber and
Gwen A. Jacobs and
Deborah Swanberg},
editor = {Yannis E. Ioannidis and
David M. Hansen},
title = {LOGOS: A Computational Framework for Neuroinformatics Research},
booktitle = {Ninth International Conference on Scientific and Statistical
Database Management, Proceedings, August 11-13, 1997, Olympia,
Washington, USA},
publisher = {IEEE Computer Society},
year = {1997},
isbn = {0-8186-7952-2},
pages = {212-222},
ee = {db/conf/ssdbm/StiberJS97.html},
crossref = {DBLP:conf/ssdbm/97},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Neuroinformatics presents a great challenge to the computer science community. Quantities of data currently range up to multiple-petabyte levels. The data itself are diverse, including scalar, vector (from 1 to 4 dimensions), volumetric (up to 4 dimensional spatio-temporal), topological, and symbolic, structured knowledge. Spatial scales range from Angstroms to meters, while temporal scales go from microseconds to decades. Base data vary greatly from individual to individual, and results computed can change with improvements in algorithms, data collection techniques, or underlying methods.
We describe a system for managing, sharing, processing, and visualizing such data. Envisioned as a ``researcher's associate'', it will facilitate collaboration, interface between researchers and data, and perform bookkeeping associated with the complete scientific information life cycle, from collection, analysis, and publication to review of previous results and the start of a new cycle.
Copyright © 1997 by The Institute of Electrical and Electronic Engineers, Inc. (IEEE). Abstract used with permission.