Beyond the dataset: integrating public voices in data science

The digitalisation of health data has helped drive initiatives like the Scottish Collaborative Optometry-Ophthalmology Network eResearch (SCONe), which links retinal images from community optometry practices with other routinely collected health data to enhance disease detection. As data-driven approaches expand throughout the healthcare system, patient and public involvement and engagement (PPIE) is increasingly recognised as essential for improving the quality, relevance, and acceptability of health research. However, despite growing endorsement, challenges remain, including inconsistent terminology, varying levels of involvement, limited implementation guidance, and a lack of evidence on its impact. These challenges are even more pronounced in data science, particularly within large-scale research, where PPIE is often underreported, leaving the field without a clear framework for meaningful implementation. This article offers a reflective account of the challenges and barriers encountered by SCONe in developing a PPIE strategy. By documenting this process, it provides insights into the complexities of implementing PPIE in large research consortia and offers practical guidance for future initiatives seeking to enhance the impact and relevance of public partnerships in large scale data science research.