Concept Paper
Version 1
Preserved in Portico This version is not peer-reviewed
Agile Stock Assessment
Version 1
: Received: 21 October 2020 / Approved: 23 October 2020 / Online: 23 October 2020 (09:41:15 CEST)
How to cite: Hayashi, A.; Ichinokawa, M.; Kinoshita, J.; Manabe, A. Agile Stock Assessment. Preprints 2020, 2020100474. https://doi.org/10.20944/preprints202010.0474.v1 Hayashi, A.; Ichinokawa, M.; Kinoshita, J.; Manabe, A. Agile Stock Assessment. Preprints 2020, 2020100474. https://doi.org/10.20944/preprints202010.0474.v1
Abstract
Stock assessment determines the status of fishery stock to support manage- ment decision making. Considering the iterations between exploratory cal- culations and the need to compare outputs to elicit better model settings, we should focus on not only the accuracy of abundance estimation and the toler- ance of uncertainty but also the efficiency of the project workflow. Although in Japan, a stock assessment model was introduced written in the R language in 2012, the workflow did not sufficiently adjust, creating problems because the current workflow is contrary to the principles of effective value creation. To make our project sustainable, we propose adopting the agile methodol- ogy, an iterative development method used by software developers, for stock assessment. Therefore, we wrote an example report as a package document in the R language. Developed under a continuous integration environment, the report remains up to date, with every modification on component files. This method enabled our work to be efficient and transparent by allowing and documenting scenario branching, error corrections, and annual updates. We show that the iterative development cycle benefit us by allowing us to focus on the essential business problem of the assessment project.
Keywords
agile; waterfall, build; continuous integration; reproducible
Subject
Computer Science and Mathematics, Algebra and Number Theory
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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