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Metadata refers to the contextual information about a resource , such as a dataset. This metadata (e.g. a dataset), often described as “data about data”. This mMetadata 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.
Codebooks: A detailed document that provides information about the structure, content, and organization of a dataset. A codebook usually describes information such as variable names, and measurement methods and units.
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.
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