Foundations of Metadata Course
Welcome to the Foundations of Metadata training course. The course aims to build understanding of the core concepts and frameworks that support the creation of metadata.
What will I learn from this course?
This 'Foundations of Metadata' course builds on the core principles introduced in the 'Introduction to Metadata' training course. While the Introduction covered what metadata is, how it is used, and the benefits it provides to you, your collaborators, and the wider research community, in this course, we introduce additional foundational metadata principles that are key for managing both metadata and data effectively. You will then learn how to make informed decisions about what metadata to create and how to create it, before moving on to practical guidance on producing metadata for your own research.
The 'Introduction to Metadata' course focused on what metadata is and how we use it in research, while the 'Foundations of Metadata' focuses on what metadata to create, why it is needed, and how to create it.
By the time you've completed the course you will be able to...
- Explain why metadata is important for research quality, understanding, comparison, and reuse
- Identify the key metadata used to describe studies, datasets, variables, questions, concepts, populations, and data collection methods
- Explain how metadata elements relate to one another and support interpretation of data
- Explain how metadata creation varies between projects and make informed decisions about what metadata to create
- Recognise the role of metadata standards, controlled vocabularies, and good practice in creating high-quality metadata
- Describe factors that influence the choice of metadata tools for different projects
- Create clear, structured metadata that supports discovery, understanding, and reuse of research data
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
No advanced technical experience is required.
What level of information do I need to know before starting the course?
You do not need specialist knowledge to begin this course. However, you should understand the basics of metadata, its role, and the essentials of research data and FAIR principles which are all covered in the 'Introduction to Metadata' training course. This 'Foundations of Metadata' course then builds from those concepts toward more practical skills in deciding what metadata to create and how to create it effectively.
If you are unfamiliar with any of the topic areas covered in the 'Introduction to Metadata' training (i.e. basics of metadata, its role, the essentials of research data, FAIR principles and how to use metadata), or would like a refresher then please go to the Introduction to Metadata training course, and browse the units.
How do I take the course?
The 'Foundations of Metadata' course is split into separate units. These are listed on the left menu.
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.
Creating metadata activities
We will look at creating metadata predominantly for quantitative, tabular data, and use examples focused on metadata for data collection instruments such as questionnaires and surveys.
While metadata can be created for any research project and data type, we will be focusing on metadata for tabular data (data found in tables). If you have a tabular dataset you would like to create metadata for, have it open while completing this course. If you do not regularly work with tabular data, the metadata elements and concepts this course covers are still relevant across disciplines and data types.
In this course, we will mainly focus on creating metadata for small scale research projects, with the purpose of personal use or sharing with project collaborators.
The metadata elements we explore will also be relevant to those working on large scale projects whose (meta)data will be widely shared, however, for these projects, you will have to take into account further contextual considerations such as discipline specific metadata standards, controlled vocabularies and data repository/catalogue requirements.
How long will the course take?
The training course is estimated to take about 6 hours 30 minutes 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 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 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 may want to access CODATA Research Data Management Terminology Bank and have 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.
Starting the course
If you're starting the course from the beginning, head to Unit 1.1 where we'll recap what metadata is and why different types of research projects require different approaches. If you need a refresher of metadata first, head to the Introduction to Metadata training course.
Feedback on the course
We are running a short survey to get more general feedback, if you are able to find 10 minutes to complete it once you've completed the course.
- [1] CODATA (2025) CODATA Research Data Management Terminology