A survey of methods for data inclusion in system dynamics models: Methods, tools and applications
Numerical data is experiencing a renaissance because 1) traditional data such as census and economic surveys are more readily accessible 2) new sensors are measuring things that have never been measured before, and 3) previously 'unstructured' data - such as raw text, audio, images, and vi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en_US |
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© The System Dynamics Society
2022
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| Online Access: | https://proceedings.systemdynamics.org/2014/proceed/proceed.pdf https://hdl.handle.net/1721.1/141748 |
| _version_ | 1826196600789139456 |
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| author | Houghton, James Siegel, Michael Wirsch, Anton Moulton, Allen Madnick, Stuart E. Goldsmith, Daniel |
| author_facet | Houghton, James Siegel, Michael Wirsch, Anton Moulton, Allen Madnick, Stuart E. Goldsmith, Daniel |
| author_sort | Houghton, James |
| collection | MIT |
| description | Numerical data is experiencing a renaissance because 1) traditional data such as census and economic surveys are more readily accessible 2) new sensors are measuring things that have never been measured before, and 3) previously 'unstructured' data - such as raw text, audio, images, and videos - is becoming more amenable to quantification. Because of this explosion and the popular buzz surrounding ‘Big Data’, clients expect to see strong incorporation of data methods into dynamic models, and it is imperative that System Dynamics Modelers are fully versed in the techniques for doing so. The SD literature contains surveys that explain methods for including data in system dynamics modeling, but techniques have continued to develop. This paper attempts to bring these surveys up to date, and serve as a menu of modern techniques. |
| first_indexed | 2024-09-23T10:30:31Z |
| format | Article |
| id | mit-1721.1/141748 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:30:31Z |
| publishDate | 2022 |
| publisher | © The System Dynamics Society |
| record_format | dspace |
| spelling | mit-1721.1/1417482022-04-08T03:29:40Z A survey of methods for data inclusion in system dynamics models: Methods, tools and applications Houghton, James Siegel, Michael Wirsch, Anton Moulton, Allen Madnick, Stuart E. Goldsmith, Daniel Numerical data is experiencing a renaissance because 1) traditional data such as census and economic surveys are more readily accessible 2) new sensors are measuring things that have never been measured before, and 3) previously 'unstructured' data - such as raw text, audio, images, and videos - is becoming more amenable to quantification. Because of this explosion and the popular buzz surrounding ‘Big Data’, clients expect to see strong incorporation of data methods into dynamic models, and it is imperative that System Dynamics Modelers are fully versed in the techniques for doing so. The SD literature contains surveys that explain methods for including data in system dynamics modeling, but techniques have continued to develop. This paper attempts to bring these surveys up to date, and serve as a menu of modern techniques. This material is based on work supported by the U.S. Office of Naval Research, Grant No. N00014-09-1-0597. Any opinions, findings, conclusions or recommendations therein are those of the author(s) and do not necessarily reflect the views of the Office of Naval Research. 2022-04-07T16:08:21Z 2022-04-07T16:08:21Z 2014-07-20 Article https://proceedings.systemdynamics.org/2014/proceed/proceed.pdf https://hdl.handle.net/1721.1/141748 Houghton, J., Siegel, M., Wirsch, A., Moulton, A., Madnick, S., & Goldsmith, D. (2014). A survey of methods for data inclusion in system dynamics models: Methods, tools and applications. In Pål Davidsen, & Etiënne A. J. A. Rouwette (Eds.), Proceedings of the 32nd International Conference of the System Dynamics Society. System Dynamics Society. en_US Attribution-NonCommercial-NoDerivs 3.0 United States http://creativecommons.org/licenses/by-nc-nd/3.0/us/ application/pdf © The System Dynamics Society |
| spellingShingle | Houghton, James Siegel, Michael Wirsch, Anton Moulton, Allen Madnick, Stuart E. Goldsmith, Daniel A survey of methods for data inclusion in system dynamics models: Methods, tools and applications |
| title | A survey of methods for data inclusion in system dynamics models: Methods, tools and applications |
| title_full | A survey of methods for data inclusion in system dynamics models: Methods, tools and applications |
| title_fullStr | A survey of methods for data inclusion in system dynamics models: Methods, tools and applications |
| title_full_unstemmed | A survey of methods for data inclusion in system dynamics models: Methods, tools and applications |
| title_short | A survey of methods for data inclusion in system dynamics models: Methods, tools and applications |
| title_sort | survey of methods for data inclusion in system dynamics models methods tools and applications |
| url | https://proceedings.systemdynamics.org/2014/proceed/proceed.pdf https://hdl.handle.net/1721.1/141748 |
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