SciK-Health: an open-data dashboard for the multidimensional evaluation of Italian academic health science centers

Academic Health Science Centers (AHSCs) integrate research, education, and clinical care within complex organizational settings, making performance assess- ment inherently multidimensional. Traditional evaluation approaches based on single-source bibliometric data provide only a partial representation of this com- plexity, failing to capture the full translational spectrum from basic research to clinical application and societal impact. This paper presents SciK-Health, an integrated knowledge management platform designed to transform heterogeneous research data into actionable insights for multiple stakeholders. The platform addresses three key challenges: fragmentation across data sources, institutional heterogeneity requiring standardized metrics, and differentiated user needs. Methodologically, it implements a transparent three-stage workflow integrating OpenAlex (publications), Dimensions (clinical trials, patents, grants, datasets), and Altmetric (social impact), using Research Organization Registry identifiers and DOI-based cross-linking. The system oper- ationalizes over 140 standardized indicators across five dimensions: bibliometric impact, social engagement, industrial innovation, clinical research activity, and competitive funding success. Applied to 49 Italian public AHSCs, SciK-Health adopts a user-centered design serving distinct audiences: citizens accessing institutional expertise, clinical man- agers supporting strategic monitoring, and policy makers conducting portfolio- level analyses. Empirical results highlight substantial institutional heterogeneity and show that single-source bibliometric approaches provide a systematically incomplete assessment of performance. Relative to existing platforms (SciVal, InCites, CWTS Leiden Open Edition), SciK-Health contributes a fully open-data infrastructure, multi-output integra- tion, and a citizen-oriented LLM-assisted search interface. While the method- ological framework is transferable, cross-national application requires substantial adaptation of data sources, institutional taxonomies, and indicator systems.