ADataViewer: Exploring Semantically Harmonized Alzheimer's Disease Cohort Datasets

INTRODUCTION: Currently, AD cohort datasets are difficult to find, lack across-cohort interoperability, and the content of the shared datasets often only becomes clear to third-party researchers once data access has been granted. METHODS: We accessed and systematically investigated the content of 20 major AD cohort datasets on data-level. A medical professional and a data specialist manually curated and semantically harmonized the acquired datasets. We developed a platform that facilitates data exploration. RESULTS: We present ADataViewer, an interactive platform that facilitates the exploration of 20 cohort datasets with respect to longitudinal follow-up, demographics, ethnoracial diversity, measured modalities, and statistical properties of individual variables. Additionally, we publish a variable mapping catalog harmonizing 1,196 variables across the 20 cohorts. The platform is available under https://adata.scai.fraunhofer.de/. DISCUSSION: ADataViewer supports robust data-driven research by transparently displaying cohort dataset content and suggesting datasets suited for discovery and validation studies based on selected variables of interest.