Toward data lakes as central building blocks for data management and analysis.

Data lakes are a fundamental building block for many industrial data analysis solutions and becoming increasingly popular in research. Often associated with big data use cases, data lakes are, for example, used as central data management systems of research institutions or as the core entity of machine learning pipelines. The basic underlying idea of retaining data in its native format within a data lake facilitates a large range of use cases and improves data reusability, especially when compared to the schema-on-write approach applied in data warehouses, where data is transformed prior to the actual storage to fit a predefined schema. Storing such massive amounts of raw data, however, has its very own challenges, spanning from the general data modeling, and indexing for concise querying to the integration of suitable and scalable compute capabilities. In this contribution, influential papers of the last decade have been selected to provide a comprehensive overview of developments and obtained results. The papers are analyzed with regard to the applicability of their input to data lakes that serve as central data management systems of research institutions. To achieve this, contributions to data lake architectures, metadata models, data provenance, workflow support, and FAIR principles are investigated. Last, but not least, these capabilities are mapped onto the requirements of two common research personae to identify open challenges. With that, potential research topics are determined, which have to be tackled toward the applicability of data lakes as central building blocks for research data management.

[Secondary Use of Electronic Medical Record Data from Primary Health Care is Feasible: Report from RADAR Project]. / Sekundäre Nutzung von hausärztlichen Routinedaten ist machbar ­ Bericht vom RADAR Projekt.

Objectives It is difficult to obtain longitudinal 'real world' data from ambulatory medical care in Germany in a systematic way. Our vision is a large German research data repository featuring representative, anonymized patient and outpatient health care data, longitudinal, continuously updated and across different providers, offering a perspective of linking secondary care data or additional data obtained from research cohorts, for example patient reported data or biodata, and will be accessible for other researchers. Here we report specific methods and results from the RADAR project.Methods Survey of legislation, design of technical processes and organisational solutions, with a feasibility study to evaluate technical and content functionality, acceptability and performance fitness for health services research questions.Results In 2016, a multi-disciplinary scientific team initiated the development of a privacy protection and IT security concept for data exported from the electronic medical records (EMR) of physicians' practices in line with the European General Data Protection Regulation. Technical and organisational requirements for lawful research infrastructure were developed and executed for use in a specific case, namely ̒oral anticoagulation'. In 7 Lower Saxonian general practices, 100 patients were selected by their physician and their data - reduced to 40 essential data fields - extracted from EMR via a mandatory software interface after informed consent. Still in the practice, the data were split into identifying or medical data. These were encrypted and transferred either to a trusted third party (TTP) or to a data repository, respectively. 75 patients who met our inclusion criteria (minimum of one year of oral anticoagulation treatment) received a quality-of-life questionnaire via the TTP. Of the 66 returns, 63 responses were then linked to the EMR data in the repository.Conclusion Results from RADAR project proved the technical and organisational feasibility of lawful, pseudonymised data acquisition and the linkage of questionnaires to EMR data. The protecting concepts privacy by design and data minimization (Art. 25 GDPR with Recital 78) were implemented. Without informed consent, secondary use of routine data from ambulatory care which are sufficiently anonymized but still meaningful is all but impossible under current German law.

Designing and piloting a generic research architecture and workflows to unlock German primary care data for secondary use.

BACKGROUND: Medical data from family doctors are of great importance to health care researchers but seem to be locked in German practices and, thus, are underused in research. The RADAR project (Routine Anonymized Data for Advanced Health Services Research) aims at designing, implementing and piloting a generic research architecture, technical software solutions as well as procedures and workflows to unlock data from family doctor's practices. A long-term medical data repository for research taking legal requirements into account is established. Thereby, RADAR helps closing the gap between the European countries and to contribute data from primary care in Germany. METHODS: The RADAR project comprises three phases: (1) analysis phase, (2) design phase, and (3) pilot. First, interdisciplinary workshops were held to list prerequisites and requirements. Second, an architecture diagram with building blocks and functions, and an ordered list of process steps (workflow) for data capture and storage were designed. Third, technical components and workflows were piloted. The pilot was extended by a data integration workflow using patient-reported outcomes (paper-based questionnaires). RESULTS: The analysis phase resulted in listing 17 essential prerequisites and guiding requirements for data management compliant with the General Data Protection Regulation (GDPR). Based on this list existing approaches to fulfil the RADAR tasks were evaluated-for example, re-using BDT interface for data exchange and Trusted Third Party-approach for consent management and record linkage. Consented data sets of 100 patients were successfully exported, separated into person-identifying and medical data, pseudonymised and saved. Record linkage and data integration workflows for patient-reported outcomes in the RADAR research database were successfully piloted for 63 responders. CONCLUSION: The RADAR project successfully developed a generic architecture together with a technical framework of tools, interfaces, and workflows for a complete infrastructure for practicable and secure processing of patient data from family doctors. All technical components and workflows can be reused for further research projects. Additionally, a Trusted Third Party-approach can be used as core element to implement data privacy protection in such heterogeneous family doctor's settings. Optimisations identified comprise a fully-electronic consent recording using tablet computers, which is part of the project's extension phase.