A5076069599- Scientific Computing and Data Management
- Research Data Management Practices
- Data Quality and Management
- Ethics in Clinical Research
- Meta-analysis and systematic reviews
- Privacy-Preserving Technologies in Data
- Autoimmune and Inflammatory Disorders
- scientometrics and bibliometrics research
- Inflammatory Bowel Disease
- Biomedical Text Mining and Ontologies
- Artificial Intelligence in Healthcare and Education
- Radiomics and Machine Learning in Medical Imaging
- Distributed and Parallel Computing Systems
- Big Data Technologies and Applications
- Colorectal Cancer Treatments and Studies
Heidelberg University
2021-2024
University Hospital Heidelberg
2021-2024
Medizinische Fakultät Mannheim
2024
Wismar University of Applied Sciences
2023
University of Rostock
2023
Universitätsmedizin Greifswald
2023
University Medical Centre Mannheim
2021-2023
Heidelberg University
2023
MSH Medical School Hamburg – University of Applied Sciences and Medical University
2023
University of Regensburg
1995
Reproducible research and open science practices have the potential to accelerate scientific progress by allowing others reuse outputs, promoting rigorous that is more likely yield trustworthy results. However, these are uncommon in many fields, so there a clear need for training helps encourages researchers integrate reproducible into their daily work. Here, we outline eleven strategies making norm at institutions. The strategies, which emerged from virtual brainstorming event organized...
Data provenance has raised much attention across disciplines lately, as it been shown that enrichment of data with information leads to better credibility, renders more FAIR fostering reuse. Also, the biomedical domain recognised potential capture. However, several obstacles prevent efficient, automated, and machine-interpretable information, such heterogeneity, complexity, sensitivity. Here, we explain how in Germany clinical are transferred from hospital systems into a integration centre...
Background The record of the origin and history data, known as provenance, holds importance. Provenance information leads to higher interpretability scientific results enables reliable collaboration data sharing. However, lack comprehensive evidence on provenance approaches hinders uptake good practice in clinical research. Objective This scoping review aims identify criteria for tracking biomedical domain. We reviewed state-of-the-art frameworks, associated artifacts, methodologies...
In the context of Medical Informatics Initiative, medical data integration centers (DICs) have implemented complex flows to transfer routine health care into research repositories for secondary use. Data management practices are importance throughout these processes, and special attention should be given provenance aspects. Insufficient knowledge can lead validity risks reduce confidence quality processed data. The need implement maintainable is undisputed, but there a great lack clarity on...
Across disciplines, researchers increasingly recognize that open science and reproducible research practices may accelerate scientific progress by allowing others to reuse outputs promoting rigorous is more likely yield trustworthy results. While initiatives, training programs, funder policies encourage adopt practices, these are uncommon in many fields. Researchers need integrate into their daily work. We organized a virtual brainstorming event, collaboration with the German Reproducibility...
Secondary investigations into digital health records, including electronic patient data from German medical integration centers (DICs), pave the way for enhanced future care. However, only limited information is captured regarding integrity, traceability, and quality of (sensitive) elements. This lack detail diminishes trust in validity collected data. From a technical standpoint, adhering to widely accepted FAIR (Findability, Accessibility, Interoperability, Reusability) principles...
Abstract Background In the context of Medical Informatics Initiative funded by German government, medical data integration centers have implemented complex flows to load routine health care into research repositories for secondary use. Data management practices are importance throughout these processes, and special attention should be given provenance aspects. Additionally, insufficient knowledge about processes can lead validity risks weaken quality extracted data. The need collect during...
The need to harness large amounts of data, possibly within a short period time, became apparent during the Covid-19 pandemic outbreak. In 2022, Corona Data Exchange Platform (CODEX), which had been developed German Network University Medicine (NUM), was extended by number common components, including section on FAIR science. principles enable research networks evaluate how well they comply with current standards in open and reproducible To be more transparent, but also guide scientists...
<sec> <title>BACKGROUND</title> In the context of Medical Informatics Initiative, medical data integration centers (DICs) have implemented complex flows to transfer routine health care into research repositories for secondary use. Data management practices are importance throughout these processes, and special attention should be given provenance aspects. Insufficient knowledge can lead validity risks reduce confidence quality processed data. The need implement maintainable is undisputed,...
Zusammenfassung Gesundheitsdaten haben in der heutigen datenorientierten Welt einen hohen Stellenwert. Durch automatisierte Verarbeitung können z. B. Prozesse im Gesundheitswesen optimiert und klinische Entscheidungen unterstützt werden. Dabei sind Aussagekraft, Qualität Vertrauenswürdigkeit Daten wichtig. Nur so kann garantiert werden, dass die sinnvoll nachgenutzt werden können. Konkrete Anforderungen an Beschreibung Kodierung von den FAIR-Prinzipien beschrieben. Verschiedene nationale...
<sec> <title>BACKGROUND</title> Secondary investigations into digital health records, including electronic patient data from German medical integration centers (DICs), pave the way for enhanced future care. However, only limited information is captured regarding integrity, traceability, and quality of (sensitive) elements. This lack detail diminishes trust in validity collected data. From a technical standpoint, adhering to widely accepted FAIR (Findability, Accessibility, Interoperability,...
<sec> <title>BACKGROUND</title> The record of the origin and history data, known as provenance, holds importance. Provenance information leads to higher interpretability scientific results enables reliable collaboration data sharing. However, lack comprehensive evidence on provenance approaches hinders uptake good practice in clinical research. </sec> <title>OBJECTIVE</title> This scoping review aims identify criteria for tracking biomedical domain. We reviewed state-of-the-art frameworks,...