Frequently Asked Questions

Personal health data cannot be publicly shared, however, high-level metadata describing the data collected can be shared, along with information on how to access the data. 

NFDI4Health has developed a generic information model to describe and preserve high-level metadata describing health-related studies. The resulting modular study metadata schema (MDS) covers clinical, epidemiological and public health studies, and includes data access and sharing options (learn more).

As an infrastructure for publishing such preservation metadata, NFDI4Health has developed the German Central Health Study Hub (learn more). 

Make sure to provide rich metadata not only about your study, but also about the study resources or documents used (e.g., study protocols, sample data entry forms, sample patient information and consent forms, codebooks, questionnaires, data dictionaries). 

In addition to the publication of study metadata, the German Central Health Study Hub allows researchers to individually publish additional study documents, link them to the study metadata, and provide information on access regulations (learn more) as well as information on the derived research data. 

For machine-readable questionnaires and data dictionaries in particular, the German Central Health Study Hub provides specific overviews, filters, and searches (learn more). 

The German Central Health Study Hub (Health Study Hub for short) is a platform to find and publish personal health research data. It allows scientists and data-holding organisations (data producers) to publish the metadata that characterises their research data, as well as documents and data related to their research, according to the FAIR principles. It also helps scientists or researchers (data consumers) to find information about past and ongoing studies in order to reuse existing research data for their projects. 

The Health Study Hub not only lists health-related studies with rich metadata, as some of existing registries do, but also allows researchers to individually publish additional study resources or documents (e.g., study protocols, sample data entry forms, sample patient information and consent forms, codebooks, data dictionaries). Furthermore, the portal allows the application of specific overviews, filters, and searches to machine-readable questionnaires and data dictionaries (learn more). 

To explore the potential for harmonisation across studies, the Health Study Hub allows you to search and compare variables from different study documents, such as questionnaires and data dictionaries (learn more).  

The content of questionnaires, data, and questionnaire items (annotated variables) are categorised according to the classification system developed by Maelstrom Research (learn more). The annotated variables can be browsed by list of areas of information (e.g. socio-economic characteristics or diseases) and the standardised scales/questionnaires used to collect them. 

Central Findability and Accessibility: By adding the information (metadata) of your study(s), study documents, and registries to our portal, they can be found centrally. This increases the visibility and accessibility of your research data and facilitates its reuse by humans and machines. 

Preserve your authorship: For the subsequent use, modification, and redistribution of your shared content, we propose a Creative Commons License that meets your requirements and regulates the possibilities of use (learn more).  

Promoting Reusability: When you register your resources in the Health Study Hub (e.g., studies, study documents), a Digital Object Identifier (DOI) will be automatically assigned. A DOI is a persistent identifier used to cite and link any objects — physical, digital or abstract — and guarantee their persistent findability. Thus, your resources can be cited, referenced, tracked and re-used for the long term. 

To be Findable: The first step is to publish comprehensive information about the context and accessibility of the research data (e.g., rich metadata of studies or study documents). Our entry mask is based on a metadata model with mandatory and recommended fields that allows you to describe your data with rich metadata. Furthermore, the metadata published in the Health Study Hub can receive a globally unique and persistent identifier, in this case, a DOI. 

To be Accessible: When published in the Health Study Hub, the metadata of your study and study documents are retrievable for humans and machines using a standardised communication protocol. This means that the metadata remains accessible, independently of the availability of data files. 

To be Interoperable: To enable data interoperability, the Health Study Hub’s metadata schema partially implements domain-overarching metadata standards such as DataCite and is aligned with other metadata schemas and terminologies for health research such as SNOMED CT, ICD, and clinical trial registries (DRKS, ClinicalTrials.gov, WHO ICTRP). Additionally, it is possible to reference and link to related resources (e.g., sub-studies, journal articles, questionnaires). 

To be Reusable: Our metadata model is designed to describe the data with a variety of accurate and relevant attributes for health research. By filling out the input mask in detail, you describe your study (meta)data in detail and provide information about the institutions or persons involved in the study. Furthermore, study documents that are registered and uploaded to the Health Study Hub are available for download and reuse, depending on the type of license assigned. 

In the Health Study Hub, you can publish three main types of resources: 

Study descriptions containing comprehensive information (metadata) about interventional or non-interventional studies from the clinical, epidemiological or public health sector. 

Study documents which provide information about studies or research-related content such as design, conduct or instruments. Study documents could be made available for download when providing a data file. You can find an overview of the study documents that can be published here. 

Registries providing information about registries or databases systematically collecting data about particular diseases or conditions. 

Please note that participant/patient individual data collected in studies are not considered a resource type and will not be published in the Health Study Hub. However, information on the availability of the collected data must be provided as part of a study description. 

You need to fill in the entry mask with the information (metadata) about your health-related study/substudy or data collection event. Although you can publish your research data in the Health Study Hub by submitting only the information in the mandatory fields, we encourage you to provide as much information as possible to improve the discoverability of your resources. 

The metadata will be entered into 5 different sections of the Health Study Hub. Each section has mandatory and recommended fields. The sections are: 

• General information: E.g., title, description, language(s), acronyms  
• Contributors: Information on person(s) and/or organization(s) responsible for the study 
• Study characteristics: E.g., study type, study design and population, focus of the study, outcome measures 
• Administrative information: Information on the current status of the study (e.g., ethics committee approval) and data sharing plans 
• Related resources: To show and link related studies, study documents (e.g., questionnaires), and publications (e.g., journal articles) 

The mandatory fields in each section are: 

General information:  

• Title/name

• Language of the title/name  

• Description 

• Language of the description
  

Contributors:  

• Personal/organisational (at least one contributor must be entered) 

• Type of contributor (e.g. contact)  

• Name of contributor

Study design:  

• Primary design 

• Study type 

• ICD groups of diseases 

• Primary study subject 

• Study country(ies)

Administrative information:  

• Overall study status 

• Data sharing plans 
  

Although you can publish your research data in the Health Study Hub by submitting only the information in the mandatory fields, we encourage you to provide as much information as possible to improve the discoverability of your resources. 

Fill in the information (metadata) about the study documents. The metadata will be entered into 3 different sections of the Health Study Hub. Each section has mandatory and recommended fields. We encourage you to provide as much information as possible to improve the discoverability of your resources. The sections are:  

• General information: E.g., title, description, language(s), acronyms  

• Contributors: Information on person(s) and/or organization(s) responsible for the study documents 

• Related resources: To show and link related studies, study documents (e.g., questionnaires), and publications (e.g., journal articles) 
  

For study documents, you can share only the metadata describing the resource or additionally upload the data file. The latter option is preferred. If you choose it, your study documents will be available for download. Therefore, please: 

1. Define and label your document with an (open) license to clarify copyright issues. For more information, please click here.

2. Prepare study documents in reusable formats. For more information, please click here.

3. Indicate if the study document has already been assigned a DOI. Otherwise, a DOI will be automatically assigned upon publication to ensure persistent findability. For more information, please click here.

4. Questionnaires and data dictionaries in the OPAL-Format will be entered in the Instrument Portal of the Health Study Hub. For more information, please click here. 

When choosing the type of resource, you can select among the following types of study documents:

• Dataset 

• Secondary data source 

• Biobank 

• Study protocol (study plan, study proposal) 

• Data dictionary 

• Informed consent form (template) 

• Patient/participant information sheet 

• Manual of operations/ Standard operating procedures (SOPs) 

• Statistical analysis plan 

• Data management plan 

• Case report form (CRF) 

• Codebook 

• Questionnaire 

• Interview scheme and themes 

• Observation guide 

• Discussion guide 

• Participant tasks 

• Other data collection instrument 

• Other study document 

• Other 

Provided file formats should be open (non-proprietary), machine-readable and machine-actionable to make study documents findable and interoperable. Formats like .xml, .txt, .csv, .json, PDF(A) or .rdf are preferred. 

We also accept non-machine-readable formats like common PDF and proprietary formats like .xlsx or .docx. However, this will reduce the findability, interoperability and reusability of your study documents. 

Yes, each published resource in the Health Study Hub will be automatically minted with a Digital Object Identifier (DOI). A DOI is a persistent identifier used to cite and link any objects - physical, digital or abstract - and guarantees their persistent findability. 

Each published resource in the Health Study Hub will be automatically minted with a Digital Object Identifier (DOI). Therefore, the person submitting a resource must be authorised to mint a DOI, which means that the agreement of all parties holding intellectual property rights is provided, and all authors or creators of the resource are specified.  

Study documents that have already been published elsewhere under a DOI will not receive a new DOI. The DOI already assigned must be entered in the section “related resources”. 

Metadata, e.g., the descriptions of studies or study documents, are not subject to copyright and, therefore, do not need to be licensed and can be freely used after publication. 

Different licenses are possible for a study document. Open licenses like some of the Creative Commons (CC) licenses are desirable, but licenses that restrict the reuse of your data are also possible. For further details, please look at our flyer Publish study documents and survey instruments quickly and easily.

For the terms and conditions of the selected license to take effect, your work must be properly marked. This is often achieved by adding a statement that your material is licensed under a chosen license and attaching the link to the webpage where the standard text of the license agreement can be found.  

As study documents are available for download and, therefore, can be used offline, a simple indication of the license on an individual webpage of the resource in the Health Study Hub is not sufficient: The license statement and the link to the license text should be inserted directly in the files.  

For example, if you decide to license your study document under the CC BY 4.0 license, the following text should be included: 

“This work is licensed under the Creative Commons Attribution 4.0 International Public License (CC BY 4.0). To view a copy of the license, visit https://creativecommons.org/licenses/by/4.0/legalcode.” 

Or you could insert the applicable license buttons with the same statement and URL link. 

The Creative Commons help page provides further important information on marking works with a CC license. 

NFDI4Health can label your study documents with CC-Licenses for you. You only need to choose your preferred CC-License when filling out our registration form. If you choose a CC BY License, you also must confirm the mandatory questions. 

There are two ways to register your data: 

1. Create a user account and fill in the registration form with the information (metadata) about your health-related study or study document. You can also contact us via studyregistration@ndfi4health.de, and we will assist you with the registration of your research data.
2. You can use an API to automatically submit metadata and study documents to our portal. For more information on our API, see the documentation under https://csh.nfdi4health.de/doc/api 

Collaborative work in the Health Study Hub is already possible. Contributors can also edit your created resources, but only entries that have not been published or received a DOI could be deleted. All contributors must be registered in the Health Study Hub. 

If you are interested in adding contributors to your entry/resource, please send us the username that the person used to register in the Health Study Hub together with the Resource-ID (the number at the end of the URL is the ID) to studyregistration@ndfi4health.de. 

Currently, it is possible to upload only one file per study document entry. 

Once you have registered your data, an NFDI4Health data steward will check the completeness of the uploaded research metadata to ensure it follows the FAIR principles. You may receive feedback via email with possible suggestions for additions or improvements to your metadata. During the review process, the status of your resource will be “PENDING”, and you won’t be able to edit the entry until it is accepted (published) or declined (improvements may be needed). 

Your entry will be published once everything is approved. 

Our data stewards will review your uploads as quickly as possible. However, the time taken for approval also depends on the volume of data received by the Health Study Hub and whether any changes are required. 

You can always modify the metadata of published data, e.g., update the study description or study status or add new related resources such as recently published journal articles. After uploading your changes, a NFDI4Health data steward will check the accuracy and completeness of the modified metadata. Once everything is approved, your data will be published under a new version, and a new DOI will be assigned. Old versions of your resource will remain accessible. 

Only entries that have not been published or received a DOI can be deleted.  

A collection in the Health Study Hub allows to group resources around particular topics (e.g. COVID-19), projects (e.g. coverCHILD study platform), or institutions (e.g. BIPS).  

You can request the creation of a collection for your project via studyregistration@ndfi4health.de. We require a collection title, description, and a logo. 

There is no consensus on the definition of research data. It varies depending on disciplines and research funders. According to the German Research Foundation, research data might consist of measurement data, laboratory values, audiovisual information, texts, survey data, objects from collections, or samples that were created, developed or evaluated during scientific work. Methodical forms of testing such as questionnaires, software and simulations could also be categorized as research data (1). 

In general, research data refer to data originated in the scientific work process and serve as the basis of every research activity (2). 

Examples of research data in biomedicine (3): 

• Data from basic research (e.g. sequencing or -omics data) 
• Electronic Medical Records (EMRs) and Electronic Health Records (EHRs) 
• Patient/disease registries (e.g. ENCePP Resources Database) 
• Health surveys (e.g. National Cohort Study (NAKO)) 
• Clinical and health data (e.g. European Health Information Portal) 
• Clinical trials registries and databases (e.g. German Clinical Trials Register (DRKS)) 
• Catalogue for population health data 
• Thesauri, ontologies and classifications and codes of diseases or substances (e.g. International Statistical Classification of Diseases and Related Health Problems (ICD)) 

Sources: 

(1) Deutsche Forschungsgemeinschaft. DFG Guidelines on the Handling of Research Data [Internet]. 2015 [cited 2023 Dec 15]. Available from: https://www.dfg.de/download/pdf/foerderung/grundlagen_dfg_foerderung/forschungsdaten/guidelines_research_data.pdf 

(2) PUBLISSO. Research Data Management [Internet]. [cited 2023 Dec 15]. Available from: https://www.publisso.de/en/research-data-management 

(3) Fürst J, Lindstädt B, Perrar I, Shutsko A, Vandendorpe J. NFDI4Health Online Training Workshop on Research Data Management in (Bio-)Medicine [Internet]. [cited 2023 Dec 15]. Available from: https://doi.org/10.4126/FRL01-006452640 

Research Data Management (RDM) refers to the series of measures that need to be taken during a research project in order to obtain high-quality data, make the data available and usable over the long-term, and make research findings reproducible beyond the research project (4). 

RDM-Steps: 

• Planning 
• Data collection 
• Data processing (incl. data documentation) 
• Data quality control 
• Data publishing & safeguarding access to data 
• Data preservation (ensuring the long-term interpretability of data) 
• Data reuse & search 

Sources: 

(4) Vandendorpe J, Lindstädt B, Shutsko A, Markus K. Online Training Workshop on Research Data Management in (Bio-)Medicine [Internet]. 2023 [cited 2023 Dec 15]. Available from: https://doi.org/10.4126/FRL01-006452660 

Metadata is in its simplest definition “data about data”. It provides information about the attributes and characteristics of digital resources in a formal and machine-readable structure. (5)(6) 

Descriptive metadata primarily describes the content and context of a resource (e.g. title, abstract, author, publishing institution) for purposes such as discovery and identification. (5)(6) 

Technical metadata informs about the creation, conversion, and formatting of digital objects (e.g. file name, file size, file format). (5) 

Structural metadata indicates how the components of a digital information resource are organised and related so that the resource can be reconstructed and made available for use. (5) 

Administrative metadata provides information to help manage a resource, such as the origin of digital objects (e.g. creation, acquisition), the measures taken to preserve them (e.g. software, logs, methods, author), persistent identifiers (e.g. DOIs), contractual arrangements for archiving, and information on rights. (5)(6) 

Sources: 

(5) PUBLISSO. Metadata in digital preservation [Internet]. [cited 2023 Dec 15]. Available from: https://www.publisso.de/en/digital-preservation/dp-metadata 

(6) National Information Standards Organization (NISO). Understanding Metadata [Internet]. 2001 [cited 2023 Dec 15]. Available from: https://web.archive.org/web/20141107022958/http:/www.niso.org/publications/press/UnderstandingMetadata.pdf 

Metadata schemas define metadata elements and the rules for using these elements to best describe a resource according to the user community needs. (7) 

Metadata standards often start as schemas (8). They group metadata elements into sets designed for a specific purpose, including for example rules on what content must be included, what syntax must be used, or controlled vocabularies to apply (9). The standardization of metadata schemas helps to ensure consistency in metadata application and facilitates the interoperability of resources as well as their discoverability, and reusability (10). 

Sources:  

(7) Atla LibGuides. Digitizing Collections: Metadata Schema [Internet]. 2022 [cited 2023 Dec 15]. Available from: https://atla.libguides.com/digitizing-collections/metadata-schema  

(8) UNC University Libraries. Metadata for Data Management: A Tutorial: Standards/Schema [Internet]. 2023 [cited 2023 Dec 15]. Available from: https://guides.lib.unc.edu/metadata/standards  

(9) How to FAIR. Metadata [Internet]. [cited 2023 Dec 15]. Available from: https://howtofair.dk/how-to-fair/metadata/  

(10) Breytenbach A, Smith I, Groenewald M.E. Metadata put into practice: applications for preservation and retrieval purposes, using the Qualified Dublin Core metadata schema [Internet]. 2007 [cited 2023 Dec 15]. Available from: http://hdl.handle.net/2263/2823  

More information about RDM fundamental concepts can be found in our slide deck “NFDI4Health Online Training Workshop on Research Data Management in (Bio-)Medicine”.