Lauren Maxwell
Lauren Maxwell is an epidemiologist and mixed methods researcher focused on enabling the FAIR and equitable reuse of data and samples for pandemic preparedness. She leads the FAIR and Equitable Data and Sample Reuse Research Group at Universitätsklinikum Heidelberg and serves as a Senior Researcher with the Ecraid Foundation, where she addresses data interoperability and governance challenges within a European network of clinical trials. She leads data work packages for several EU-funded pandemic preparedness consortia, including ECRAID-Base, CoMeCT, CONTAGIO, and the BE READY European Partnership for Pandemic Preparedness, developing the metadata, governance frameworks, and policy intelligence needed to support federated, pandemic-ready data ecosystems. She co-chairs the CODATA-RDA Health Data Commons Working Group and is a co-author of the CODATA Cross-Domain Interoperability Framework (CDIF).
Session
Effective disaster detection and response depends on integrating heterogeneous signals across meteorological, geospatial, epidemiological, infrastructure, and community domains, yet these systems remain siloed, lacking a persistent, machine-actionable way to navigate the relationships among them. This workshop explores how persistent identifiers (PIDs) and a connected PID graph can serve as the connective tissue for a complex adaptive disaster management system. Drawing on the CADEM framework's emphasis on non-linear, multi-actor, feedback-driven response, and on Fakhruddin's work on FAIR data policy for disaster risk, we ask: what would it take to make cross-domain disaster data not just FAIR, but actionable at speed? Applying CODATA's Cross-Domain Interoperability Framework (CDIF), participants will work collaboratively to map PID requirements across disaster management phases, identify the governance and technical barriers to a functional DRR PID graph, and propose a practical implementation roadmap aligned with the Sendai Framework.