## Summary

This chapter highlights the importance of metadata and documentation in research data management. Metadata provides structured or unstructured information that describes, explains and contextualises your data, making it easier to find, understand, and reuse. Structured metadata follows a predefined format or schema, allowing for better organisation and easier retrieval, while unstructured metadata offers more flexible, free-form descriptions, capturing additional context and nuances.

Documentation plays an equally crucial role by ensuring that the processes behind data collection, analysis, and interpretation are clearly explained and reproducible. It includes detailed descriptions of research methods, assumptions, and any decisions made throughout the project. Good documentation enhances transparency, allows others to understand and reproduce your work, and helps ensures that your research remains accessible and valuable over time.

Together, metadata and documentation are vital for ensuring the integrity, accessibility, and long-term usability of your research data, facilitating collaboration and enabling future researchers to build upon your work.

Task 1:

Apply to Your Research
Think of a research project you are working on (or imagine a simple one, like a survey-based study).

1. Write down three pieces of structured metadata you would include for your dataset.

2. Write a short paragraph of unstructured metadata that provides additional context for the data.

3. List two key elements you would include in your project documentation to ensure reproducibility.

Task 2: (to be embedded)

Identify Metadata Types
Look at the following examples of information. For each, indicate whether it is an example of structured metadata, unstructured metadata, or documentation: