Objectives: Public sharing of de-identified biomedical data promotes collaboration between researchers and accelerates the development of disease prevention and treatment strategies. However, open-access data sharing presents challenges to researchers who need to protect the privacy of study participants, ensure that data are used appropriately, and acknowledge the inputs of all involved researchers. This article presents an approach to data sharing which addresses the above challenges by using a publicly available dashboard with de-identified, aggregated participant data from a large HIV surveillance cohort.
Materials and methods: Data in this study originated from the Rakai Community Cohort Study (RCCS), which was integrated into a centralized data mart as part of a larger data management strategy for the Rakai Health Sciences Program in Uganda. These data were used to build a publicly available, protected health information (PHI)-secured visualization dashboard for general research use.
Results: Using two unique case studies, we demonstrate the capability of the dashboard to generate the following hypotheses: firstly, that HIV prevention strategies ART and circumcision have differing levels of impact depending on the marital status of investigated communities; secondly, that ART is very successful in comparison to circumcision as an interventional strategy in certain communities.
Discussion: The democratization of large-scale anonymized epidemiological data using public-facing dashboards has multiple benefits, including facilitated exploration of research data and increased reproducibility of research findings.
Conclusion: By allowing the public to explore data in depth and form new hypotheses, public-facing dashboard platforms have significant potential to generate new relationships and collaborations and further scientific discovery and reproducibility.
Keywords: Rakai Community Cohort Study (RCCS); Rakai Health Sciences Program (RHSP); dashboard; de-identification; human immunodeficiency virus (HIV).
Published by Oxford University Press on behalf of the American Medical Informatics Association 2024.