No Discipline is an Island. No Discipline is an Island: Where Computing and Other Disciplines Meet. Lillian (Boots) Cassel Villanova University. An Introduction - My journey. Questions from the bingo game: Have never lived in a big city
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No Discipline is an Island: Where Computing and Other Disciplines Meet
Lillian (Boots) Cassel
* Jim Gray summary
The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud computing technologies.
KiloHow much information is there?
Soon most everything will be recorded and indexed
Data summarization, trend detection anomaly detection are key technologies
Most bytes will never be seen by humans.
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These require algorithms, data and knowledge representation, and knowledge of the domain
See Mike Lesk: How much information is there: http://www.lesk.com/mlesk/ksg97/ksg.html
See Lyman & Varian:
How much information
24 Yecto, 21 zepto, 18 atto, 15 femto, 12 pico, 9 nano, 6 micro, 3 milli
Slide source Jim Gray – Microsoft Research (modified)
Over 30 thousand gigabytes (30TB) of images will be generated every night during the decade-long LSST sky survey.
LSST and Google share many of the same goals: organizing massive quantities of data and making it useful.
This data-driven modeling and discovery linkage has entered a new paradigm. The acquisition of scientific data in all disciplines is now accelerating and causing a nearly insurmountable data avalanche. It is no longer possible for humans to look at any representative fraction of the data. Instead, we may be looking over the shoulders of assisted learning machines at innovative visualizations of metadata. Discoveries will be made via searches for correlations. The role of the experimental scientist increasingly is as inventor of ambitious new searches and new algorithms. Novel theories of nature are tested through searching for the predicted statistical relationships across big data bases. With this accelerated advance in data generation capability, we will require novel, increasingly automated, and increasingly more effective scientific knowledge discovery systems.
http://www.informationweek.com/news/197800880 -- Information Week - March 7, 2007
Communications of the ACM
Vol. 54 No. 10, Pages 66-71
Current NSF project to explore the issues of motivation and the challenges, and what can be done about them.