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A Five-Star Guide for Achieving Replicability and Reproducibility When Working with GIS Software and Algorithms
Annals of the American Association of Geographers ( IF 3.982 ) Pub Date : 2020-10-13
John P. Wilson, Kevin Butler, Song Gao, Yingje Hu, Wenwen Li, Dawn J. Wright

The availability and use of geographic information technologies and data for describing the patterns and processes operating on or near the Earth’s surface have grown substantially during the past fifty years. The number of geographic information systems software packages and algorithms has also grown quickly during this period, fueled by rapid advances in computing and the explosive growth in the availability of digital data describing specific phenomena. Geographic information scientists therefore increasingly find themselves choosing between multiple software suites and algorithms to execute specific analysis, modeling, and visualization tasks in environmental applications today. This is a major challenge because it is often difficult to assess the efficacy of the candidate software platforms and algorithms when used in specific applications and study areas, which often generate different results. The subtleties and issues that characterize the field of geomorphometry are used here to document the need for (1) theoretically based software and algorithms; (2) new methods for the collection of provenance information about the data and code along with application context knowledge; and (3) new protocols for distributing this information and knowledge along with the data and code. This article discusses the progress and enduring challenges connected with these outcomes.



中文翻译:

使用GIS软件和算法时实现可重复性和可重复性的五星级指南

在过去的五十年中,用于描述在地球表面上或附近运行的模式和过程的地理信息技术和数据的可用性和使用已大大增加。在此期间,地理信息系统软件包和算法的数量也迅速增长,这得益于计算的飞速发展和描述特定现象的数字数据的可用性的爆炸性增长。因此,地理信息科学家越来越多地发现自己在多个软件套件和算法之间进行选择,以执行当今环境应用程序中的特定分析,建模和可视化任务。这是一个重大挑战,因为当在特定应用程序和研究领域中使用候选软件平台和算法时,通常很难评估其效果,而后者往往会产生不同的结果。这里使用表征地形学领域的微妙和问题来记录对以下方面的需求:(1)基于理论的软件和算法;(2)收集有关数据和代码的来源信息以及应用程序上下文知识的新方法;(3)用于分发此信息和知识以及数据和代码的新协议。本文讨论了与这些结果相关的进展和持久挑战。这里使用表征地形学领域的微妙和问题来记录对以下方面的需求:(1)基于理论的软件和算法;(2)收集有关数据和代码的来源信息以及应用程序上下文知识的新方法;(3)用于分发此信息和知识以及数据和代码的新协议。本文讨论了与这些结果相关的进展和持久挑战。这里使用表征地形学领域的细微之处和问题来记录对以下方面的需求:(1)基于理论的软件和算法;(2)收集有关数据和代码的来源信息以及应用程序上下文知识的新方法;(3)用于分发此信息和知识以及数据和代码的新协议。本文讨论了与这些结果相关的进展和持久挑战。

更新日期:2020-10-13
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