Current state of data stewardship tools in life science.

In today's data-centric landscape, effective data stewardship is critical for facilitating scientific research and innovation. This article provides an overview of essential tools and frameworks for modern data stewardship practices. Over 300 tools were analyzed in this study, assessing their utility, relevance to data stewardship, and applicability within the life sciences domain.

Setting up an institutional OMERO environment for bioimage data: Perspectives from both facility staff and users.

Modern bioimaging core facilities at research institutions are essential for managing and maintaining high-end instruments, providing training and support for researchers in experimental design, image acquisition and data analysis. An important task for these facilities is the professional management of complex multidimensional bioimaging data, which are often produced in large quantity and very different file formats. This article details the process that led to successfully implementing the OME Remote Objects system (OMERO) for bioimage-specific research data management (RDM) at the Core Facility Cellular Imaging (CFCI) at the Technische Universität Dresden (TU Dresden). Ensuring compliance with the FAIR (findable, accessible, interoperable, reusable) principles, we outline here the challenges that we faced in adapting data handling and storage to a new RDM system. These challenges included the introduction of a standardised group-specific naming convention, metadata curation with tagging and Key-Value pairs, and integration of existing image processing workflows. By sharing our experiences, this article aims to provide insights and recommendations for both individual researchers and educational institutions intending to implement OMERO as a management system for bioimaging data. We showcase how tailored decisions and structured approaches lead to successful outcomes in RDM practices.

Unlocking Real-World Health Data from Non-University Locations Through Effective Provision of Tools and Knowledge.

INTRODUCTION: The Medical Informatics Initiative (MII) in Germany has pioneered platforms such as the National Portal for Medical Research Data (FDPG) to enhance the accessibility of data from clinical routine care for research across both university and non-university healthcare settings. This study explores the efficacy of the Medical Informatics Hub in Saxony (MiHUBx) services by integrating Klinikum Chemnitz gGmbH (KC) with the FDPG, leveraging the Fast Healthcare Interoperability Resources Core Data Set of the MII to standardize and harmonize data from disparate source systems. METHODS: The employed procedures include deploying installation packages to convert data into FHIR format and utilizing the Research Data Repository for structured data storage and exchange within the clinical infrastructure of KC. RESULT: Our results demonstrate successful integration, the development of a comprehensive deployment diagram, additionally, it was demonstrated that the non-university site can report clinical data to the FDPG. DISCUSSION: The discussion reflects on the practical application of this integration, highlighting its potential scalability to even smaller healthcare facilities and to pave the way to access to more medical data for research. This exemplary demonstration of the interplay of different tools provides valuable insights into technical and operational challenges, setting a precedent for future expansions and contributing to the democratization of medical data access.

The German Central Health Study Hub - A Service to Find and Publish Clinical, Public Health and Epidemiolocal Studies and Associated Documents.

INTRODUCTION: The German Central Health Study Hub is a service that was initially developed at short notice during the COVID-19 pandemic. Since then, it has been expanded in scope, content, active users and functionality. The service is aimed at two main audiences: data provider and data consumers. The former want to share research data from clinical, public health and epidemiological studies and related documents according to the FAIR criteria for research data, and the latter want to find and ultimately reuse relevant research data in the above areas. METHODS: The service connects both groups via graphical and programmatic interfaces. A sophisticated information model is employed to describe and publish various research data objects while obeying data protection and fulfilling FAIR requirements. The service is being developed in a demand-driven manner with extensive user interaction. RESULTS: A free-to-use service, built on open-source software (Dataverse, MICA, Keycloak), accessible via a web-browser. In close collaboration with users several features (ranging from collection to group items to combined data capture via API and UI) were created. The adoption of the service increases continuously and results in over 1,970 research data objects in June 2024. CONCLUSION: The service fills a marked gap and connects both user groups, yet it still needs to be improved in various dimensions (features, content, usage). The impact on the community needs to be further assessed. Despite recent legislative changes (GDNG, EHDS), the system improves the findability of sensitive data, provides a blueprint for similar systems and shows how to create a useful and user-friendly service together with users.

MeDaX: A Knowledge Graph on FHIR.

In Germany, the standard format for exchange of clinical care data for research is HL7 FHIR. Graph databases (GDBs), well suited for integrating complex and heterogeneous data from diverse sources, are currently gaining traction in the medical field. They provide a versatile framework for data analysis which is generally challenging for raw FHIR-formatted data. For generation of a knowledge graph (KG) for clinical research data, we tested different extract-transform-load (ETL) approaches to convert FHIR into graph format. We designed a generalised ETL process and implemented a prototypic pipeline for automated KG creation and ontological structuring. The MeDaX-KG prototype is built from synthetic patient data and currently serves internal testing purposes. The presented approach is easy to customise to expand to other data types and formats.

Data Policy Finder: an easily integratable tool connecting data librarians with researchers to navigate publication requirements.

The Data Policy Finder is a searchable database containing librarian-curated information, links, direct quotes from relevant policy sections, and notes to help the researcher search, verify, and plan for their publication data requirements. The Memorial Sloan Kettering Cancer Center Library launched this new resource to help researchers navigate the ever-growing, and widely varying body of publisher policies regarding data, code, and other supplemental materials. The project team designed this resource to encourage growth and collaboration with other librarians and information professionals facing similar challenges supporting their research communities. This resource creates another access point for researchers to connect with data management services and, as an open-source tool, it can be integrated into the workflows and support services of other libraries.

The DMPTool NIH DMSP Templates Project.

The DMPTool NIH Data Management and Sharing Plan (DMSP) Templates Project was launched in response to the 2023 NIH Data Management and Sharing (DMS) Policy. This new policy introduced a more structured framework for DMS Plans, featuring six key elements, a departure from the 2003 NIH DMS policy. The project aimed to simplify the process for data librarians, research administrators, and researchers by providing a template with curated guidance, eliminating the need to navigate various policies and guidelines. The template breaks out each Plan section and subsection and provides related guidance and examples at the point of need. This effort has resulted in two NIH DMSP Templates. The first is a generic template (NIH-Default) for all ICs, complying with NOT-OD-21-013 and NOT-OD-22-198. More recently, an NIMH-specific template (NIH-NIMH) was added based on NOT-MH-23-100. As of October 2023, over 5,000 DMS Plans have been written using the main NIH-Default template and the NIH-NIMH alternative template.