Towards good practice In engaging users In evaluation of computer model Software: Introducing the critical appraisal approach (CAA)

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Caroline Rosello , Joseph H.A. Guillaume , Peter Taylor , Susan M. Cuddy , Carmel A. Pollino , Anthony J. Jakeman
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引用次数: 0

Abstract

Good practices in model software development are essential for boosting uptake. While user-centric approaches are much advocated, challenges remain in including users in development due to diverse definitions for ‘users’, their perceived credibility as an information source, and the influence of market-based innovation choices and the anticipation of (future) demands. While enhancing user feedback could help in addressing these challenges, there is a notable lack of guidance for best practices focused on users, as the emphasis has traditionally been on developers.
To tackle this gap, we propose a Critical Appraisal Approach (CAA) for model software evaluation, informed by the Basin Futures model software and detailed steps in its evaluation, thereby providing guidance to support associated best practices for such software. The paper shows the CAA can assist in 1) enhancing shared understanding between users and developers, 2) coordinating development and evaluation, and 3) aligning development with market dynamics.

Abstract Image

在计算机模型软件的评估中实现吸引用户的良好实践:引入关键评估方法(CAA)
模型软件开发中的良好实践对于提高采用率至关重要。虽然大力提倡以用户为中心的方法,但由于对“用户”的不同定义、他们作为信息来源的可信度、基于市场的创新选择的影响以及对(未来)需求的预期,在将用户纳入发展中仍然存在挑战。虽然增强用户反馈有助于应对这些挑战,但显然缺乏针对用户的最佳实践指南,因为传统上重点是开发人员。为了解决这一差距,我们提出了一种用于模型软件评估的关键评估方法(CAA),该方法基于盆地期货模型软件及其评估的详细步骤,从而为支持此类软件的相关最佳实践提供指导。本文表明,CAA可以帮助1)增强用户和开发人员之间的共同理解,2)协调开发和评估,3)使开发与市场动态保持一致。
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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