FAIR principles make data technically accessible but do not guarantee cognitively accessible experiences, especially in data-rich repositories. Cognitive accessibility is often overlooked, yet interfaces with high cognitive load affect all users, not just those with diagnosed disabilities. Neurodivergent researchers, likely overrepresented in academia, face additional challenges due to differences in working memory, executive function, and processing speed, making repository UX a critical equity issue.

This presentation addresses three common cognitive pain points: scanning large volumes of metadata to find relevant information; switching between broad and highly specific searches while maintaining context; and navigating repository structures that do not reflect the varied priorities of different user groups.

Drawing on cognitive load theory and W3C COGA guidelines, the presentation demonstrates practical UX patterns that reduce extraneous cognitive load: grouping related metadata into clear, scannable sections; eliminating redundant information; and providing persistent mechanisms to carry context across search and discovery modes. Attendees will learn how to identify cognitive anti-patterns in their own repositories and apply these design solutions making FAIR-compliant metadata more usable, inclusive, and equitable for a wide range of researchers.

MEx (Metadata Exchange) is a digital platform that maps metadata on research activities and research data at the Robert Koch Institute (RKI) in a transparent way, aiming to facilitate the reuse of this data. MEx is one of many measures being taken to implement the German government's open data strategy. The core data is managed in the MEx management platform, and this is maintained, kept up-to-date, and evolves as the requirements of the research environment change. The objective of the repository project is to ensure that as that data evolves and is added to, that a stable view can be provided to researchers which maintains the version history of changes, and to enable researchers to discover and view research important to them. This presentation will introduce MEx as a project and data model/vocabulary, and talk about the motivation for publishing the dataset in a repository. The platform chosen for this is InvenioRDM, and we will talk about the reasons for that, and then look at the technical changes that were required to support the model.