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Short description
As already mentioned across many of these chapters, metadata Metadata refers to the contextual information about a resource, such as a dataset. This metadata may can come in many formats, the types. The most familiar type of metadata is generic metadata provides overall information about a resource, which may include details about what the data resource is about (e.g., data from patient health records, imaging data), who created it (e.g., a research team at Radboudumc) and when it was collected (e.g., collected in 2023) and also disclose information about how can the data be used . 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). But there are other types of information that can be useful to include in the metadata:
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Content metadata: Refers to what elements are included in the dataset and the possible values (e.g., Imagine questionnaire data is collected it may be relevant to specify in the metadata which questions are being asked and the possible answer choices).
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Other types metadata that provide useful information are:
Provenance metadata: This refers to how the resource came to be, what protocols were followed, and what data collection tools were used. The purpose of this metadata is to ensure that you, your colleagues or others can reproduce the initial research.
Content metadata: When speaking about data, this refers to a description of the elements included in your dataset and their possible 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.
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
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