Long-term preservation of biomedical research data

A practical guide to bioimaging research data management in core facilities

Bioimage data are generated in diverse research fields throughout the life and biomedical sciences. Its potential for advancing scientific progress via modern, data-driven discovery approaches reaches beyond disciplinary borders. To fully exploit this potential, it is necessary to make bioimaging data, in general, multidimensional microscopy images and image series, FAIR, that is, findable, accessible, interoperable and reusable. These FAIR principles for research data management are now widely accepted in the scientific community and have been adopted by funding agencies, policymakers and publishers. To remain competitive and at the forefront of research, implementing the FAIR principles into daily routines is an essential but challenging task for researchers and research infrastructures. Imaging core facilities, well-established providers of access to imaging equipment and expertise, are in an excellent position to lead this transformation in bioimaging research data management. They are positioned at the intersection of research groups, IT infrastructure providers, the institution´s administration, and microscope vendors. In the frame of German BioImaging - Society for Microscopy and Image Analysis (GerBI-GMB), cross-institutional working groups and third-party funded projects were initiated in recent years to advance the bioimaging community's capability and capacity for FAIR bioimage data management. Here, we provide an imaging-core-facility-centric perspective outlining the experience and current strategies in Germany to facilitate the practical adoption of the FAIR principles closely aligned with the international bioimaging community. We highlight which tools and services are ready to be implemented and what the future directions for FAIR bioimage data have to offer.

Building a FAIR image data ecosystem for microscopy communities

Bioimaging has now entered the era of big data with faster-than-ever development of complex microscopy technologies leading to increasingly complex datasets. This enormous increase in data size and informational complexity within those datasets has brought with it several difficulties in terms of common and harmonized data handling, analysis, and management practices, which are currently hampering the full potential of image data being realized. Here, we outline a wide range of efforts and solutions currently being developed by the microscopy community to address these challenges on the path towards FAIR bioimaging data. We also highlight how different actors in the microscopy ecosystem are working together, creating synergies that develop new approaches, and how research infrastructures, such as Euro-BioImaging, are fostering these interactions to shape the field.

The Integration of a Canonical Workflow Framework with an Informatics System for Disease Area Research

A recurring pattern of access to existing databases, data analyses, formulation of new hypotheses, use of an experimental design, institutional review board approvals, data collection, curation, and storage within trusted digital repositories is observable during clinical research work. The workflows that support the repeated nature of these activities can be ascribed as a Canonical Workflow Framework for Research (CWFR). Disease area clinical research is protocol specific, and during data collection, the electronic case report forms can use Common Data Elements (CDEs) that have precisely defined questions and are associated with the specified value(s) as responses. The CDE-based CWFR is integrated with a biomedical research informatics computing system, which consists of a complete stack of technical layers including the Protocol and Form Research Management System. The unique data dictionaries associated with the CWFR for Traumatic Brain Injury and Parkinson's Disease resulted in the development of the Federal Interagency Traumatic Brain Injury and Parkinson's Disease Biomarker systems. Due to a canonical workflow, these two systems can use similar tools, applications, and service modules to create findable, accessible, interoperable, and reusable Digital Objects. The Digital Objects for Traumatic Brain Injury and Parkinson's disease contain all relevant information needed from the time data is collected, validated, and maintained within a Storage Repository for future access. All Traumatic Brain Injury and Parkinson's Disease studies can be shared as Research Objects that can be produced by aggregating related resources as information packages and is findable on the Internet by using unique identifiers. Overall, the integration of CWFR with an informatics system has resulted in the reuse of software applications for several National Institutes of Health-supported biomedical research programs.

Ensuring the Long-Term Preservation of and Access to the Italian Federated Electronic Health Record

The Italian Electronic Health Record (called the FSE) is based on a federated architectural model and involves various types of health data and documents deriving from public and private health stakeholders. Clinical documents are stored in repositories and indexed in a central regional index (registry) according to a defined metadata schema. The FSE repositories can be distributed in the regional network or centralized at the regional level, or regions can use subsidiarity services offered by the National Infrastructure for the regional FSEs Interoperability. In this scenario, this study addresses the open issue of the FSE documents’ long-term preservation and access over time, since the responsibility of their preservation is distributed among different stakeholders. As a consequence, the process traceability is necessary to ensure that a document indexed in an FSE is accessible over time, regardless of the document local discard policies applied for legal fulfilments. The results of this study show that the enhancement of metadata use could support the management and long-term preservation of the FSE documents. Addressing this issue is, finally, fundamental to guarantee the correct tracing and access to the clinical path of a patient and to ensure the efficiency of the entire care setting.

Development of an informatics system for accelerating biomedical research

The Biomedical Research Informatics Computing System (BRICS) was developed to support multiple disease-focused research programs. Seven service modules are integrated together to provide a collaborative and extensible web-based environment. The modules-Data Dictionary, Account Management, Query Tool, Protocol and Form Research Management System, Meta Study, Data Repository and Globally Unique Identifier -facilitate the management of research protocols, to submit, process, curate, access and store clinical, imaging, and derived genomics data within the associated data repositories. Multiple instances of BRICS are deployed to support various biomedical research communities focused on accelerating discoveries for rare diseases, Traumatic Brain Injury, Parkinson's Disease, inherited eye diseases and symptom science research. No Personally Identifiable Information is stored within the data repositories. Digital Object Identifiers are associated with the research studies. Reusability of biomedical data is enhanced by Common Data Elements (CDEs) which enable systematic collection, analysis and sharing of data. The use of CDEs with a service-oriented informatics architecture enabled the development of disease-specific repositories that support hypothesis-based biomedical research.