Data mining on NASA's Information Power Grid

Hinke, Thomas H.; Novotny, Janet A.

doi:10.1109/hpdc.2000.868663

Cited by 27 publications

(10 citation statements)

References 2 publications

(1 reference statement)

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“…Precedents in other disciplines include NASA's Information Power Grid (Johnston et al 1999;Hinke and Novotny 2000) and the National Science Foundation (NSF)'s National Virtual Observatory (NVO). The latter combines more than 100 TB of data from 50 ground-and space-based telescopes, with standards for services and data established by the astronomical community (Freeman 2003).…”

Section: Data Interoperability and Compu-tational Infrastructurementioning

confidence: 99%

Integrating and Interpreting Aerosol Observations and Models within the PARAGON Framework

Ackerman¹,

Braverman²,

Diner³

et al. 2004

Bull. Amer. Meteor. Soc.

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A comprehensive, global aerosol picture can be generated using modern high-performance computing, geospatial statistics, assimilation, and data mining approaches. The past decade has produced a remarkable increase in the amount of atmospheric data from observations and models, but these data are acquired or generated with nonuniform spatial and temporal sampling, scales, and coverage. The challenge for research into complex phenomena such as aerosol-climate interaction is to combine these disparate data into an integrated whole (Kahn and Braverman 1999;Huang et al. 2002). The ultimate goal is to establish a complete dataset that will effectively confront and constrain ever more realistic global three-dimensional models.A first step in attaining this objective is to produce a measurement-based description of global tropo- AFFILIATIONS: ACKERMAN-Pacific

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Section: Data Interoperability and Compu-tational Infrastructurementioning

confidence: 99%

Integrating and Interpreting Aerosol Observations and Models within the PARAGON Framework

Ackerman¹,

Braverman²,

Diner³

et al. 2004

Bull. Amer. Meteor. Soc.

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“…Finally, the ADaM [18] system is an agent-based DM framework developed at the University of Alabama in Huntsville, used to mine data in parallel hydrology from four sites.…”

Section: Related Workmentioning

confidence: 99%

KDDML‐G: a grid‐enabled knowledge discovery system

Romei

Sciolla

Turini

et al. 2007

Concurrency and Computation

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SUMMARYKDDML-G is a middleware language and system for knowledge discovery on the grid. The challenge that motivated the development of a grid-enabled version of the 'standalone' KDDML (Knowledge Discovery in Databases Markup Language) environment was on one side to exploit the parallelism offered by the grid environment, and on the other side to overcome the problem of data immovability, a quite frequent restriction on real-world data collections that has principally a privacy-preserving purpose. The last question is addressed by moving the code and 'mining' the data 'on the place', that is by adapting the computation to the availability and localization of the data.

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“…Many applications have been developed under this convention [12,13], so when these legacy applications are ported onto grids, there should be an initialization stage in which every data item is delivered to the calculators that require it. Minimizing the duration of this delivery process is important for reducing the total elapsed time of the job.…”

Section: Introductionmentioning

confidence: 99%