Institute for Methods Innovation, Trinity Technology & Enterprise Campus, Unit 23, Dublin, Ireland.
Department of Sociology, University of Warwick, Coventry, United Kingdom.
PLoS One. 2022 Mar 10;17(3):e0264914. doi: 10.1371/journal.pone.0264914. eCollection 2022.
This study investigates how research data contributes to non-academic impacts using a secondary analysis of high-scoring impact case studies from the UK's Research Excellence Framework (REF). A content analysis was conducted to identify patterns, linking research data and impact. The most prevalent type of research data-driven impact related to "practice" (45%), which included changing how professionals operate, changing organizational culture and improving workplace productivity or outcomes. The second most common category was "government impacts", including reducing government service costs and enhancing government effectiveness or efficiency. Impacts from research data were developed most frequently through "improved institutional processes or methods" (40%) and developing impact via pre-analyzed or curated information in reports (32%), followed by "analytic software or methods" (26%). The analysis found that research data on their own rarely generate impacts. Instead they require analysis, curation, product development or other forms of significant intervention to leverage broader non-academic impacts.
本研究使用英国卓越研究框架(REF)中高分影响案例研究的二次分析,调查研究数据如何产生非学术影响。通过内容分析,确定了将研究数据与影响联系起来的模式。与“实践”(45%)相关的最常见的一类数据驱动型影响包括改变专业人员的运作方式、改变组织文化和提高工作场所的生产力或成果。第二类常见的类别是“政府影响”,包括降低政府服务成本和提高政府的效果或效率。通过“改进机构流程或方法”(40%)和通过报告中的预分析或策划信息来发展影响(32%),最频繁地产生研究数据的影响,其次是“分析软件或方法”(26%)。分析发现,研究数据本身很少产生影响。相反,需要进行分析、策划、产品开发或其他形式的重大干预,才能利用更广泛的非学术影响。