...
Metadata refers to the contextual information about a resource, such as a dataset. This metadata can come in many different types and forms. Perhaps the 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:
...
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].
...