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AMModels: An R package for storing models, data, and metadata to facilitate adaptive management
Agencies are increasingly called upon to implement their natural resource management programs within an adaptive management (AM) framework. This article provides the background and motivation for the R package, AMModels. AMModels was developed under R version 3.2.2. The overall goal of AMModels is s...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5830045/ https://www.ncbi.nlm.nih.gov/pubmed/29489825 http://dx.doi.org/10.1371/journal.pone.0188966 |
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author | Donovan, Therese M. Katz, Jonathan E. |
author_facet | Donovan, Therese M. Katz, Jonathan E. |
author_sort | Donovan, Therese M. |
collection | PubMed |
description | Agencies are increasingly called upon to implement their natural resource management programs within an adaptive management (AM) framework. This article provides the background and motivation for the R package, AMModels. AMModels was developed under R version 3.2.2. The overall goal of AMModels is simple: To codify knowledge in the form of models and to store it, along with models generated from numerous analyses and datasets that may come our way, so that it can be used or recalled in the future. AMModels facilitates this process by storing all models and datasets in a single object that can be saved to an .RData file and routinely augmented to track changes in knowledge through time. Through this process, AMModels allows the capture, development, sharing, and use of knowledge that may help organizations achieve their mission. While AMModels was designed to facilitate adaptive management, its utility is far more general. Many R packages exist for creating and summarizing models, but to our knowledge, AMModels is the only package dedicated not to the mechanics of analysis but to organizing analysis inputs, analysis outputs, and preserving descriptive metadata. We anticipate that this package will assist users hoping to preserve the key elements of an analysis so they may be more confidently revisited at a later date. |
format | Online Article Text |
id | pubmed-5830045 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58300452018-03-19 AMModels: An R package for storing models, data, and metadata to facilitate adaptive management Donovan, Therese M. Katz, Jonathan E. PLoS One Research Article Agencies are increasingly called upon to implement their natural resource management programs within an adaptive management (AM) framework. This article provides the background and motivation for the R package, AMModels. AMModels was developed under R version 3.2.2. The overall goal of AMModels is simple: To codify knowledge in the form of models and to store it, along with models generated from numerous analyses and datasets that may come our way, so that it can be used or recalled in the future. AMModels facilitates this process by storing all models and datasets in a single object that can be saved to an .RData file and routinely augmented to track changes in knowledge through time. Through this process, AMModels allows the capture, development, sharing, and use of knowledge that may help organizations achieve their mission. While AMModels was designed to facilitate adaptive management, its utility is far more general. Many R packages exist for creating and summarizing models, but to our knowledge, AMModels is the only package dedicated not to the mechanics of analysis but to organizing analysis inputs, analysis outputs, and preserving descriptive metadata. We anticipate that this package will assist users hoping to preserve the key elements of an analysis so they may be more confidently revisited at a later date. Public Library of Science 2018-02-28 /pmc/articles/PMC5830045/ /pubmed/29489825 http://dx.doi.org/10.1371/journal.pone.0188966 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Donovan, Therese M. Katz, Jonathan E. AMModels: An R package for storing models, data, and metadata to facilitate adaptive management |
title | AMModels: An R package for storing models, data, and metadata to facilitate adaptive management |
title_full | AMModels: An R package for storing models, data, and metadata to facilitate adaptive management |
title_fullStr | AMModels: An R package for storing models, data, and metadata to facilitate adaptive management |
title_full_unstemmed | AMModels: An R package for storing models, data, and metadata to facilitate adaptive management |
title_short | AMModels: An R package for storing models, data, and metadata to facilitate adaptive management |
title_sort | ammodels: an r package for storing models, data, and metadata to facilitate adaptive management |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5830045/ https://www.ncbi.nlm.nih.gov/pubmed/29489825 http://dx.doi.org/10.1371/journal.pone.0188966 |
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