DataRepExp: a R shiny Application that makes Data FAIRfor Data Repositories

The Data Repository Explorer, DataRepExp, is an open-source R Shiny application developed to improve the findability, accessibility, interoperability, and reusability (FAIR) (Wilkinson et al., 2016) of research data held in a data repository.The application displays standardised metadata across multiple studies including data availability by categories (such as demographics, medical history, imaging data and genomic data) to allow high-level comparison.It enables users to explore and run preliminary analysis from participants that match certain criteria.In addition, it provides features to export reports and aggregated results for data access application purposes.The application was initially developed for a discipline-specific data-sharing platform, the Dementias Platform Australia (DPAU) (CHeBA (Centre for Healthy Brain Ageing), UNSW, 2024a). Statement of NeedData repositories have become increasingly important in recent years as more emphasis has been placed on open science practices and data sharing.By making data publicly available through repositories, researchers can ensure data persistence and support data preservation, as well as facilitate the reuse of their data, thereby increasing the potential for new scientific discoveries.However, challenges exist for data findability, accessibility, interoperability, and reusability (FAIR).Even though most data repositories have adopted various metadata schemas to describe the dataset (Contaxis et al., 2022), it is increasingly a challenge for researchers to find relevant data that meet research interests or needs (Gregory, 2018).For multi-study research, applying to access different datasets usually comes with diverse and complicated data-sharing requirements and workflows, extensive administrative workloads and waiting periods.Upon approval, substantial efforts of data harmonization are usually required due to inconsistent data structures and labelling conventions, and harmonised datasets are hardly reused.We found that many data repositories do not provide comprehensive metadata, nor centralised tables for comparison.With repositories that provide data visualisation, Power BI and Tableau are commonly used but costs are incurred.R-shiny could provide more flexibility and functions at a fraction of the cost.Designed to enable easier access to research data held in data repositories, DPAU seeks to