Portal of Medical Data Models

• Applicant: Professor Dr. Martin Dugas
• Subject Area: Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics ; Epidemiology and Medical Biometry/Statistics
• Term: from 2015 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 256379806

Efficient information systems are a key success factor for medical research. Currently, most of these systems apply heterogeneous and proprietary data models, which impede scientifc work. There is a demand for information infrastructures to enable exchange and standardization of medical data models on a national and international level - a challenging task given the complexity of patient data: approximately 100.000 concepts are required to describe the clinical properties of patients.The overall objective of this proposal is to develop a sustainable platform for high-quality medical data models as an information infrastructure for medical research and routine healthcare. The main goal is to further develop the existing prototype portal of medical data models (www.medical-data-models.org) into an international repository of medical data models for the scientific community. The University Library of Münster contributes to this project expertise for sustainable, high-quality information infrastructures regarding technical, contents and organisational aspects.The current prototype system consists of 12.500+ data models (according to the applicant’s knowledge the largest system of its kind world-wide, there is no similar system available in the DFG portal and MERIL database). Quality of those models shall be improved by expert curation within this project. Contents shall be increased to 20.000+ data models to cover relevant models from European hospitals with a research focus. Existing international collaborations in the field of oncology will be leveraged to generate high-quality contents.A set of new informatics tools will be developed and maintained to generate and process medical data models. A set of export functions shall be developed to make those models usable for a wide scientific user group. Semantic annotation based upon international standards, professional curation, user feedback, flexible search functions and format converters are important services of this system. Open access and linked open data principles will by applied for this information infrastructure.Expected benefits for the scientific community are improved and accelerated design of medical data models by sharing best practice, more standardized data models with semantic annotation and better information exchange between information systems, in particular Electronic Data Capture (EDC) systems in clinical research and Electronic Health Records (EHR) in routine patient care. The current prototype system was presented successfully in several national and international conferences and there is evidence for a strong demand by the scientific community.

• DFG Programme: Research data and software (Scientific Library Services and Information Systems)
• Participating Institution: Universität Münster; Universitäts- und Landesbibliothek