Scientific discovery within data streams

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

doi:10.1007/978-3-540-32263-4_4

Scientific discovery within data streams

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

^*Corresponding author for this work

Pacific Northwest National Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 language	English
Title of host publication	Ambient Intelligence for Scientific Discovery
Subtitle of host publication	Foundations, Theories, and Systems
Publisher	Springer Verlag
Pages	66-80
Number of pages	15
ISBN (Print)	3540244662, 9783540244660
DOIs	https://doi.org/10.1007/978-3-540-32263-4_4
Publication status	Published - 2005
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3345 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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10.1007/978-3-540-32263-4_4

Cite this

Cowell, A. J., Havre, S., May, R., & Sanfilippo, A. (2005). Scientific discovery within data streams. In 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). Springer Verlag. https://doi.org/10.1007/978-3-540-32263-4_4

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title = "Scientific discovery within data streams",

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.",

author = "Cowell, {Andrew J.} and Sue Havre and Richard May and Antonio Sanfilippo",

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doi = "10.1007/978-3-540-32263-4_4",

language = "English",

isbn = "3540244662",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Ambient Intelligence for Scientific Discovery",

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Cowell, AJ, Havre, S, May, R & Sanfilippo, A 2005, Scientific discovery within data streams. in Ambient Intelligence for Scientific Discovery: Foundations, Theories, and Systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3345 LNAI, Springer Verlag, pp. 66-80. https://doi.org/10.1007/978-3-540-32263-4_4

Scientific discovery within data streams. / Cowell, Andrew J.; Havre, Sue; May, Richard et al.
Ambient Intelligence for Scientific Discovery: Foundations, Theories, and Systems. Springer Verlag, 2005. p. 66-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3345 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Havre, Sue

AU - May, Richard

AU - Sanfilippo, Antonio

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AB - 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.

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DO - 10.1007/978-3-540-32263-4_4

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AN - SCOPUS:36849014906

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SN - 9783540244660

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Cowell AJ, Havre S, May R, Sanfilippo A. Scientific discovery within data streams. In Ambient Intelligence for Scientific Discovery: Foundations, Theories, and Systems. Springer Verlag. 2005. p. 66-80. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-32263-4_4

Scientific discovery within data streams

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