Article

Data farming: discovering surprise

Authors:

Gary E. Horne,

Ted E. MeyerAuthors Info & Claims

WSC '04: Proceedings of the 36th conference on Winter simulation

Pages 807 - 813

Published: 05 December 2004 Publication History

Get Access

Abstract

The development of models and analysis of modeling results usually requires that models be run many times. Very few modelers are satisfied with the computing resources available to do sensitivity studies, validation and verification, measurement of effectiveness analysis, and related necessary activities. Fortunately, high performance computing, in the form of distributed computing capabilities and commodity node systems, is becoming more pervasive and cost effective. In this paper the authors describe the concept and methods of Data Farming, the study and development of methods, interfaces, and tools that make high performance computing readily available to modelers and allows analysts to explore the vast amount of data that results from exercising models.

References

[1]

Brandstein, A. and Horne, G. 1998. Data Farming: A Meta-Technique for Research in the 21^st Century. Maneuver Warfare Science 1998, Marine Corps Combat Development Command Publication, Quantico, Virginia.

Google Scholar

[2]

Buja, A., McDonald, J. A., Michalak, J., and Stuetzle, W. 1991. Interactive Data Visualization Using Focusing and Linking. Proceedings of the 2nd conference on Visualization '91, San Diego, California, SESSION: Multivariate visualization, Pages: 156 -- 163. IEEE Computer Society Press. Los Alamitos, California.

Digital Library

Google Scholar

[3]

Horne, G. 2001. Beyond Point Estimates: Operational Synthesis and Data Farming. Maneuver Warfare Science 2001. United States Marine Corps Project Albert. Quantico, Virginia.

Google Scholar

[4]

Lucas, T., Sanchez, S., Brown, L., and Vinyard, W. 2002. Better Designs for High-Dimensional Explorations of Distillations. Maneuver Warfare Science 2002. United States Marine Corps Project Albert. Quantico, Virginia.

Google Scholar

[5]

Meyer, T. and Johnson, S. 2001. Visualization for Data Farming: A Survey of Methods. Maneuver Warfare Science 2001. United States Marine Corps Project Albert. Quantico, Virginia.

Google Scholar

[6]

Upton, Stephen. 2004. Users Guide: OldMcData, the Data Farmer, Version 1.0. United States Marine Corps Project Albert. Quantico, Virginia.

Google Scholar

Cited By

View all

Le HHu X(2020)Extended model space specification for mobile agent-based systems to support automated discovery of simulation modelsProceedings of the Winter Simulation Conference10.5555/3466184.3466439(2233-2244)Online publication date: 14-Dec-2020
https://dl.acm.org/doi/10.5555/3466184.3466439
Hofmann MMeyer-Nieberg SUhlig TJohansson BJain S(2018)Inferential statistics and simulation generated samplesProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320583(479-490)Online publication date: 9-Dec-2018
https://dl.acm.org/doi/10.5555/3320516.3320583
Hofmann MHuschka TChick S(2016)Null hypothesis significance testing in simulationProceedings of the 2016 Winter Simulation Conference10.5555/3042094.3042172(522-533)Online publication date: 11-Dec-2016
https://dl.acm.org/doi/10.5555/3042094.3042172
Show More Cited By

Recommendations

Data farming: discovering surprise
WSC '05: Proceedings of the 37th conference on Winter simulation

Data Farming is a methodology and capability that makes use of high performance computing to run models many times. This capability gives modelers and their clients the enhanced ability to discover trends and outlier in results, do sensitivity studies, ...
Data modeling for Precision Dairy Farming within the competitive field of operational and analytical tasks

The interdisciplinary concept of Precision Dairy Farming sets very high standards for data management. Special consideration during its implementation must therefore be given to support both operational and analytical data uses (e.g., OLAP). The ...
Shrimp farming on the grid
MG '08: Proceedings of the 15th ACM Mardi Gras conference: From lightweight mash-ups to lambda grids: Understanding the spectrum of distributed computing requirements, applications, tools, infrastructures, interoperability, and the incremental adoption of key capabilities

The concept of task farming provides a mechanism to mange the execution of multiple instances of a serial application on distributed computing resources. These type of jobs fall into the category of "embarrassingly parallel" applications, for which it ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

WSC '04: Proceedings of the 36th conference on Winter simulation

December 2004

2052 pages

ISBN:0780387864

Publisher

Winter Simulation Conference

Publication History

Published: 05 December 2004

Check for updates

Qualifiers

Article

Acceptance Rates

WSC '04 Paper Acceptance Rate 144 of 171 submissions, 84%;

Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

21
Total Citations
View Citations
316
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)0

Reflects downloads up to 22 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Le HHu X(2020)Extended model space specification for mobile agent-based systems to support automated discovery of simulation modelsProceedings of the Winter Simulation Conference10.5555/3466184.3466439(2233-2244)Online publication date: 14-Dec-2020
https://dl.acm.org/doi/10.5555/3466184.3466439
Hofmann MMeyer-Nieberg SUhlig TJohansson BJain S(2018)Inferential statistics and simulation generated samplesProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320583(479-490)Online publication date: 9-Dec-2018
https://dl.acm.org/doi/10.5555/3320516.3320583
Hofmann MHuschka TChick S(2016)Null hypothesis significance testing in simulationProceedings of the 2016 Winter Simulation Conference10.5555/3042094.3042172(522-533)Online publication date: 11-Dec-2016
https://dl.acm.org/doi/10.5555/3042094.3042172
Huber DKallfass D(2015)Applying data farming for military operation planning in nato MSG-124 using the interoperation of two simulations of different resolutionProceedings of the 2015 Winter Simulation Conference10.5555/2888619.2888910(2535-2546)Online publication date: 6-Dec-2015
https://dl.acm.org/doi/10.5555/2888619.2888910
Tolk ADe Rango FRisco Martín JCetinkaya D(2015)The next generation of modeling & simulationProceedings of the Conference on Summer Computer Simulation10.5555/2874916.2874964(1-8)Online publication date: 26-Jul-2015
https://dl.acm.org/doi/10.5555/2874916.2874964
Horne GSeichter SBuckley SMiller J(2014)Data farming in support of nato operationsProceedings of the 2014 Winter Simulation Conference10.5555/2693848.2694143(2355-2363)Online publication date: 7-Dec-2014
https://dl.acm.org/doi/10.5555/2693848.2694143
Kallfass DSchlaak TRose OUhrmacher A(2012)NATO MSG-088 case study results to demonstrate the benefit of using data farming for military decision supportProceedings of the Winter Simulation Conference10.5555/2429759.2430057(1-12)Online publication date: 9-Dec-2012
https://dl.acm.org/doi/10.5555/2429759.2430057
Sanchez SWan H(2011)Better than a petaflopProceedings of the Winter Simulation Conference10.5555/2431518.2431689(1441-1455)Online publication date: 11-Dec-2011
https://dl.acm.org/doi/10.5555/2431518.2431689
Sanchez SWan HDunkin AIngalls R(2009)Better than a petaflopWinter Simulation Conference10.5555/1995456.1995470(60-74)Online publication date: 13-Dec-2009
https://dl.acm.org/doi/10.5555/1995456.1995470
Chua CSim CChoo CTay VJefferson TFowler JIngalls R(2008)Automated red teamingProceedings of the 40th Conference on Winter Simulation10.5555/1516744.1516999(1456-1462)Online publication date: 7-Dec-2008
https://dl.acm.org/doi/10.5555/1516744.1516999
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Recommendations