LAUSR

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.