STATUS: IN DEVELOPMENT
Short description
Metadata refers to the contextual information about a resource, such as a dataset. This metadata can come in many different types and forms. Perhaps tThe type of metadata you might be most familiar with is the generic metadata often collected from in repositories (e.g., such as Zenodo (see the example of how zenodo describes the resources on its repository). This generic metadata includes details about on what the resource is about (e.g., data from patient health records), who created it (e.g., a research team at Radboudumc) and when it was collected (e.g., 2023). Typically, it also discloses information about the possible uses of the resource (e.g., applicable licensing) and access restrictions (e.g., available for public use/restricted access). There are other types of metadata, below a non-exhaustive list:
Provenance metadata: This refers to how the resource came to be, what protocols were followed, and what tools were used. The purpose of this metadata is to ensure that you, your colleagues or others can reproduce the initial research.
Content metadata: Depending on the type of resource, this refers to a detailed description of your resource that goes beyond the generic information explained above. For instance, in the context of a dataset containing data collected from a questionnaire, content metadata could include the questions asked and the allowed range of values.
In this step, the focus will be on assessing the availability of your metadata. This involves identifying and collecting all types of metadata being gathered about your resource. Check their quality and ensure they are as accurate and complete as possible. Depending on your objectives <point towards FAIR objectives>, this step is a good starting point. Whether you aim to simply gain a clear view of what metadata currently describes your resource, expand your current metadata, ensure compliance with requirements to publish it in a metadata catalogue <Point to Register resource level metadata> or follow a semantic model to describe your metadata; this step is common across multiple purposes.
In this step, the focus will be on assessing the availability of your metadata. This step is a good starting point and a common first step for multiple objectives <point towards FAIR objectives>, whether you aim to:
gain a clear view of what metadata currently describes your resource
expand your current metadata
ensure compliance with requirements to publish it in a metadata catalogue <Point to Register resource level metadata>
follow a semantic model to describe your metadata
This step involves identifying and collecting all types of metadata gathered for your resource, checking their quality and ensuring they are as accurate and complete as possible.
Metadata is data about data. It comes in many types, such as descriptive metadata, provenance metadata, etc [cb_metadata]. Metadata helps people to locate the data and allows it to be reused and cited [GoFAIR]. Furthermore, metadata can be machine-actionable, allowing for automation of data handling and validation [RDMKit_MachineActionable]. Findability, accessibility and reusability of data can be improved by providing metadata with details about license, copyright, etc., as well as description of use conditions and access of data [Generic].
Maybe more how to:
Check whether metadata regarding regarding findability, accessibility, and reusability is already available and whether this metadata is already being collected using standardized vocabularies [Generic, FAIRopoly]. What metadata should be gathered may depend on the stakeholder community [Generic].
[FAIRopoly] Identify what metadata is already being collected by your registry (e.g., provenance, creation date, file type and size, timestamp). The result of this step will support defining the metadata model of your registry. Also, check if your metadata is already being collected using standardized vocabularies.
Why is this step important
Generally:
To be able to register resource level metadata you need to make sure you have/collect it.
with respect to HRI:
Health-RI is in the process of defining a metadata scheme for onboarding in the Health-RI metadata portal. To allow for onboarding of a dataset, the minimal metadata set must be provided. It is therefore essential that you assess whether this minimal set is collected/available or whether additional metadata needs to be collected.
How to
[FAIRopoly] → Doesn’t really sound like “assess” though?
Usually, terms from upper ontologies can be used to describe metadata. For example, use dcat:Dataset from Data Catalog Vocabulary (DCAT) [DCAT] to describe the type of any rare disease dataset and dct:creator from DCMI Metadata Terms (DCT) to indicate the relationship between a dataset and its creator.
The How to section should:
be split into easy to follow steps;
Step 1
Step 2
etc.
help the reader to complete the step;
aspire to be readable for everyone, but, depending on the topic, may require specialised knowledge;
be a general, widely applicable approach;
if possible / applicable, add (links to) the solution necessary for onboarding in the Health-RI National Catalogue;
aim to be practical and simple, while keeping in mind: if I would come to this page looking for a solution to this problem, would this How-to actually help me solve this problem;
contain references to solutions such as those provided by FAIR Cookbook, RMDkit, Turing way and FAIR Sharing;
contain custom recipes/best-practices written by/together with experts from the field if necessary.
Expertise requirements for this step
This section could describe the expertise required. Perhaps the Build Your Team step could then be an aggregation of all the “Expertise requirements for this step” steps that someone needs to fulfill his/her FAIRification goals.
Practical examples from the community
This section should show the step applied in a real project. Links to demonstrator projects.
Training
Add links to training resources relevant for this step. Since the training aspect is still under development, currently many steps have “Relevant training will be added in the future if available.”
Suggestions
Visit our How to contribute page for information on how to get in touch if you have any suggestions about this page.