Scientific discovery within data streams

Andrew J. Cowell, Sue Havre, Richard May, Antonio Sanfilippo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We have presented our vision for a next generation analytical environment for scientific discovery within data-streams. By utilizing components from our research portfolio in Information Analytics, Rich Interaction Environments and Knowledge Engineering, we envision a system that can handle massive data streams of differing data types, present the most important elements of these streams visually and allow for advanced interactions within a group context.

Original languageEnglish
Title of host publicationAmbient Intelligence for Scientific Discovery
Subtitle of host publicationFoundations, Theories, and Systems
EditorsYang Cai
Pages66-80
Number of pages15
Publication statusPublished - 1 Dec 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3345 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Cowell, A. J., Havre, S., May, R., & Sanfilippo, A. (2005). Scientific discovery within data streams. In Y. Cai (Ed.), Ambient Intelligence for Scientific Discovery: Foundations, Theories, and Systems (pp. 66-80). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3345 LNAI).