Payumo Jane, Bello-Bravo Julia, Chennuru Vineeth, Mercene Solo Arman, Yim Chaeyeon, Duynslager Lee, Kanamarlapudi Bhanu, Posos-Parra Omar, Payumo Sky, Mota-Sanchez David
Research Evaluation and Data Analytics, MSU AgBioResearch, Michigan State University, East Lansing, MI 48824, USA.
Department of Agricultural Sciences Education and Communication, Purdue University, Lafayette, IN 47907, USA.
Insects. 2024 Sep 27;15(10):747. doi: 10.3390/insects15100747.
This paper presents a multi-method approach for evaluating the utility and impact of agricultural databases in the context of the rapidly expanding digital economy. Focusing on the Arthropod Pesticide Resistance Database, one of the most comprehensive global resources on arthropod pesticide resistance, we offer a framework for assessing the effectiveness of agricultural databases. Our approach provides practical guidance for developers, users, evaluators, and funders on how to measure the impact of these digital tools, using relevant metrics and data to validate their contributions. Additionally, we introduce an index-based method that evaluates impact across multiple dimensions, including data usage, accessibility, inclusivity, knowledge generation, innovation, research and policy development, and collaboration. The detailed methodology serves as both a reference and a model for evaluating the impact of other agricultural databases, ensuring they effectively support decision-making and foster innovation in the agricultural sector.
本文提出了一种多方法途径,用于在快速发展的数字经济背景下评估农业数据库的效用和影响。以节肢动物抗药性数据库为例,它是全球关于节肢动物抗药性最全面的资源之一,我们提供了一个评估农业数据库有效性的框架。我们的方法为开发者、用户、评估者和资助者提供了实用指导,告诉他们如何使用相关指标和数据来衡量这些数字工具的影响,以验证其贡献。此外,我们引入了一种基于指标的方法,该方法从多个维度评估影响,包括数据使用、可及性、包容性、知识生成、创新、研究与政策制定以及合作。详细的方法既作为评估其他农业数据库影响的参考,也作为模型,确保它们有效地支持农业部门的决策并促进创新。