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Introduction to Metadata Course

Welcome to the Introduction to Metadata training course.

Metadata is an essential part of the research process, shaping how data can support knowledge creation, reuse, and impact over time. Yet for many people, working with metadata can feel confusing, overly technical, or difficult to engage with. We are often expected to work with metadata when the underlying concepts and terminology are unfamiliar, and it can feel like something you are simply “supposed to know” rather than something you have had the opportunity to properly learn.

Despite its importance, metadata is rarely taught in a formal or structured way. Instead, it is often learned informally, inconsistently, and under pressure, through on the job experience and local conventions or undocumented knowledge. This lack of shared foundations can make it difficult to know where to start, interpret guidance or standards, feel confident, and make consistent decisions.

This course provides a structured introduction to metadata, helping to establish a shared understanding and common language across projects and organisations. By grounding metadata practice in a theoretical foundation, it supports more consistent and intentional decision making about data and metadata.

Improving metadata competency will enable you to:

  • Get more value from research infrastructures and data services
  • Start a new role more productively and confidently, reducing reliance on informal, “on the job” learning
  • Improve metadata creation, research data management, and system development

What will I learn from this course?

By the time you've completed the course you will be able to...

  • Describe what research data is and how it is generated
  • Describe the principles of research data management (RDM) and FAIR, and explain their importance in research
  • Define what metadata is and its relationship to research data
  • Explain the role of metadata in aiding discovery, understanding and reuse of data
  • Explain how metadata supports the implementation of the FAIR principles
  • Describe how metadata is used throughout the research lifecycle
  • Describe the role of data repositories and metadata catalogues in enabling data discovery and access
  • Use metadata to support research activities such as assessing data and its relevance to your work
  • Evaluate the quality of metadata and identify the features that make metadata high quality
  • Define controlled vocabularies and describe their role in improving metadata quality
  • Explain the role of metadata standards and schemas in metadata creation and management
  • Apply basic principles to create study‑level metadata for your research

This course mainly focuses on what metadata is and how we use metadata in research. In the next course, Foundation (which will be available shortly), we will look at creating metadata.

Who's this course for?

This course is for anyone who will be engaging with research data as part of their work, for example using, analysing or collecting research data.

This course may be particularly relevant for ...

  • Masters and PhD students
  • Researchers
  • Data stewards and data managers
  • People working for funding bodies of academic research
  • People working in policy areas that use data and academic research in their work

What level of information do I need to know before starting the course?

You don't have to have any previous knowledge or training in metadata in order to do the Introduction course. As we'll explore in the course, we use metadata in many areas of our lives already often without even realising it. Even if this is the first time encountering the term, you have most likely engaged with it already.

You may already know about metadata and have done some training. This course aims to solidify knowledge around key concepts of metadata.

How do I take the course?

The Introduction course is split into 10 units. These are...

If this is your first time engaging with metadata, we recommend working through the units sequentially so you can build on your understanding.

If you already have a strong understanding of metadata, you may only want to dip in and out of units to refresh your knowledge or address any gaps in your learning.

How long will the course take?

The training course is estimated to take about 5 hours to complete. This is estimated based on:

  • An average reading speed of 300 words per minute
  • Additional learning time for comprehension of technical concepts (between 20-70% added time)
  • Time for exercises, examples, and quizzes

These are estimated times. Your own time may vary depending on experience, background knowledge, and whether you complete all activities.

Terminology

As the way we understand and use metadata is evolving, it's important to note that some terms may be used differently by people or disciplines. The way some concepts are defined in this course may be different to how you currently understand them. So that you have a clear understanding of the course content, we'll define key terms and concepts as we go along.

To maintain a level of consistency in our definitions, where possible we will refer to the Research Data Management (RDM) Terminology Bank developed by CODATA[1]. We may also provide further definitions from other sources to give a more rounded description of a concept.

The RDM Terminology Bank is a community reviewed, cross-discipline vocabulary that defines key concepts in research data management (RDM). As it is regularly updated, it reflects the latest understanding of RDM and aims to offer a single source of truth for terms that can be used in different ways. You can access the RDM Terminology Bank here and we recommend having this open while you go through the course so you can look up any terms that may be new to you, or you want to clarify[2].

Starting the course

If you're starting the course from the beginning, head to unit 1.1 where we'll unpack what research data is and what its key characteristics are.

Get started

Resources

You can find additional resources for all the units on the resources page.

References