Salimi, YasaminYasaminSalimiDomingo Fernández, DanielDanielDomingo FernándezBobis-Álvarez, CarlosCarlosBobis-ÁlvarezHofmann-Apitius, MartinMartinHofmann-ApitiusBirkenbihl, ColinColinBirkenbihl2022-06-022022-06-022022-05-21https://publica.fraunhofer.de/handle/publica/41812010.1186/s13195-022-01009-4Background: Currently, Alzheimer’s disease (AD) cohort datasets are difficult to find and lack across-cohort interoperability, and the actual content of publicly available datasets often only becomes clear to third-party researchers once data access has been granted. These aspects severely hinder the advancement of AD research through emerging data-driven approaches such as machine learning and artificial intelligence and bias current data-driven findings towards the few commonly used, well-explored AD cohorts. To achieve robust and generalizable results, validation across multiple datasets is crucial. Methods: We accessed and systematically investigated the content of 20 major AD cohort datasets at the data level. Both, a medical professional and a data specialist, manually curated and semantically harmonized the acquired datasets. Finally, we developed a platform that displays vital information about the available datasets. Results: Here, 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. It allows researchers to quickly identify AD cohorts that meet user-specified requirements for discovery and validation studies regarding available variables, sample sizes, and longitudinal follow-up. Additionally, we publish the underlying variable mapping catalog that harmonizes 1196 unique variables across the 20 cohorts and paves the way for interoperable AD datasets. Conclusions: In conclusion, ADataViewer facilitates fast, robust data-driven research by transparently displaying cohort dataset content and supporting researchers in selecting datasets that are suited for their envisioned study. The platform is available at https://adata.scai.fraunhofer.de/.enAlzheimer’s diseaseDementiaData harmonizationSemantic mappingMRIVariable catalogInteroperabilityData curationCohort studyDDC::000 Informatik, Informationswissenschaft, allgemeine Werke::000 Informatik, Wissen, Systeme::000 Informatik, Informationswissenschaft, allgemeine WerkeDDC::600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und GesundheitDDC::600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::616 Krankheitenjournal article