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AMModels: An R package for storing models, data, and metadata to facilitate adaptive management

Overview of attention for article published in PLOS ONE, February 2018
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2 tweeters

Citations

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Title
AMModels: An R package for storing models, data, and metadata to facilitate adaptive management
Published in
PLOS ONE, February 2018
DOI 10.1371/journal.pone.0188966
Pubmed ID
Authors

Therese M. Donovan, Jonathan E. Katz

Abstract

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.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 24%
Student > Ph. D. Student 3 14%
Other 3 14%
Student > Bachelor 3 14%
Student > Doctoral Student 1 5%
Other 0 0%
Unknown 6 29%
Readers by discipline Count As %
Environmental Science 4 19%
Agricultural and Biological Sciences 4 19%
Computer Science 1 5%
Psychology 1 5%
Social Sciences 1 5%
Other 2 10%
Unknown 8 38%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 July 2018.
All research outputs
#13,717,431
of 20,582,425 outputs
Outputs from PLOS ONE
#114,785
of 177,649 outputs
Outputs of similar age
#182,343
of 292,930 outputs
Outputs of similar age from PLOS ONE
#1,965
of 2,701 outputs
Altmetric has tracked 20,582,425 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 177,649 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 292,930 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2,701 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.