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Unit 2.5 Metadata standards

Unit overview

Unit study time

  • 25 minutes

Intended learning outcomes

By the end of the unit, you'll be able to...

  • Define metadata standards and schemas
  • Describe the role metadata standards and schemas in metadata creation and management
  • Identify relevant metadata standards and schemas

Standardising metadata

Even within a research area, there may be different ways of saying the same thing. In the last unit 2.5, we looked at how controlled vocabularies can help standardise the terms used in our metadata, so it becomes interoperable and machine readable.

While controlled vocabularies standardise the content of metadata elements (i.e. the allowed inputs), metadata schemas and standards offer a broader framework around how to structure and define metadata elements. They help us to further create accurate, consistent, standardised and interoperable metadata.

What is the benefit of using standards?

A case study on standardisation: USB-C chargers

In 2022, the European Union introduced Directive 2022/2380, requiring most portable electronic devices to adopt USB-C as a universal charging port. This regulation was driven by two key goals: reducing electronic waste and improving convenience[1].

Before this mandate, different brands used different proprietary connectors, for example Apple had a specific Lightning cable for their iPhones. This lack of standardisation created inefficiencies and tonnes e-waste annually. Consumers save money by reusing chargers instead of buying new ones and Manufacturers gain clarity on design requirements, while interoperability improves across the tech ecosystem.

Standardisation simplifies workflows, increases efficiency, prevents duplication, and promotes sustainability. As people work from the same specification, it enables clear communication and collaboration.

A similar example can be seen in UK plugs and sockets. They follow the standard ISO 4400:1994 set out by the International Organization for Standardization. By doing this, we know all three-pin sockets in the UK will meet the technical needs to work.

Just like these examples of standardisation, metadata standards in research ensure consistency, interoperability and reuse. Without them, metadata, and consequently the data it's describing, becomes siloed and difficult to integrate.

Although the terms 'metadata schemas' and 'metadata standards' are often used interchangeably, they are different. But how?

Metadata standards

Metadata standards are a ready-made framework that set out the content and structure of your metadata. They provide a consistent way to structure your metadata, for example they predefine metadata elements, valid inputs and can specify which controlled vocabularies to use[2].

CODATA defines a metadata standards as...

High level, shared representation of the metadata elements related to a dataset, collection, or other digital object. May also provide an XML schema describing the format in which the elements should be stored. Typically, a standard XML format is defined using XML Schema or document type definition (DTD). [3]

Who creates metadata standards?

Metadata standards are created and maintained by a particular knowledge or data community. Within this community, there is usually some form of governance around the standard so they can be actively reviewed and updated, ensuring it is relevant to the needs of the people using it.

While there are a few cross-discipline standards, most are discipline specific.

  • Dublin Core is a standard to describe digital resources in order to help discovery.
    • Dublin Core is commonly expressed directly as a schema which are based on the Dublin Core standard
  • PBCore is a standard for describing sound and moving images.
  • schema.org is a standard used to describe webpages and other online resources.
  • DataCite is a standard for describing research and academic outputs.
    • Like Dublin Core, DataCite is commonly expressed directly as a schema that is updated and based on the DataCite standard.
    • Some countries have a national standard for publishing metadata so that it is interoperable across the country's repositories. For example, Czech Republich have the Czech Core Metadata Model for Research Data (CCMM)[https://www.ccmm.cz/en/core-model-ccmm/].

There are also metadata standards which serve specific disciplines and research areas.

  • Data Documentation Initiative (DDI) is a standard for describing social science data which includes a metadata specification, controlled vocabularies, and tools for working with DDI metadata.
  • SDMX to standardise metadata for statistical data.
  • NeXus is a standard for neutron, x-ray, and muon experiment data.

Metadata schemas

Metadata schemas are the blueprint people follow to create metadata. They are similar to standards in that they outline what metadata elements to use, their valid inputs and specify controlled vocabularies where necessary. However, whereas standards are a guiding framework that people can draw from to inform their metadata creation, schemas are the practical documentation used to create metadata. As such, they might include further information about how the structure should be implemented for example, what metadata elements are required and which are optional.

How do metadata schemas relate to metadata standards?

A schema can be created independent of a standard. This is where the schema defines all the elements, structure and valid inputs from scratch and does not draw from a standard to inform its content. A schema can also be based on a metadata standard, using the structure and definitions outlined in the standard to create its content. In this way, a schema is the technical implementation of a standard for a specific use, and multiple schemas can be created from a single standard. In some cases, where a metadata standard has a narrow scope, a standard may be expressed as a schema directly as it only has a one or two technical implementations. For example, the metadata standard Dublin Core is expressed directly as a schema whereas DDI, which is a larger standard, has multiple schemas created from it.

Creating metadata schemas

A schema can be created by an individual, an organisation or a data community...

  • An individual may create their own metadata schema for a particular project
  • An individual may use a publicly available schema for their own project
  • An organisation may create a schema for internal use so metadata for similar resources will be captured in the same way
  • An organisation or knowledge community may create a schema that is publicly available so anyone documenting a similar resource can use it
  • A public data repository or catalogue may create a schema and require anyone wishing to deposit their data to use that schema

For example, Gesis has created their own metadata schema to document resources being upload to the Gesis Data Archive (DAS)[4]. As Gesis is focused on social science research, it has based the schema on the standard Data Documentation Initiative Alliance (DDI Alliance) which is the leading standard for metadata across social, economic, and health sciences. This means it uses metadata elements and controlled vocabularies defined by DDI within a structure that is specific to the archive's needs.

Benefits of metadata standards and schemas

Facilitate data sharing and collaboration

Through standardising metadata structure and terminology, metadata standards enable the exchange of metadata between people and organisations (interoperability).

FAIRwDDI project outline the benefit of metadata standards and using Document Data Initiative (DDI) in social science research. Below they provide an example of how standards help avoid confusion and inconsistency in creating metadata.[5]

A standard provides a common language so there is a shared understanding.

Example: The term “Creator” is used to describe the person, corporate body, or agency responsible for making the resource in several metadata standards. The “Publisher” is used to describe the person or organization responsible for making the resource available in different metadata standards. Without standards, people may use these terms interchangeably.

Makes metadata creation more efficient

Metadata standards save you time when creating metadata as the structure and controlled inputs are already specified. That means you don't have to create a documentation system yourself.

Facilitate integration into data catalogues and repositories

Data repositories and data catalogues will often specify what metadata standard and/or schema to use so they can integrate a vast range of resources coherently. These sites are dependent on standardisation to enable the search and filter functions (as we explore in unit 2.3. This improves the discoverability of research and encourages the reuse of data, making data FAIR.

Enable automation in data processing and analysis

By providing a clear and consistent structure, metadata standards help make your metadata more actionable by machines, opening up the potential for further functionalities such as automating data processing and analysis workflows.

Supports cross study comparison and data reuse**

For example, have a look at these cross-study comparisons below. Each study uses the same metadata standard, DDI. This means the studies can be integrated into the same data catalogues, the UK Data Service and CLOSER Discovery. This then allows researchers to discover data on these sites and easily compare different areas of the study so they can draw new findings.

  • The rise of the obesity epidemic[6]: this piece of research uses data drawn from new findings through comparing data across five studies...

    • MRC National Survey of Health and Development (1946 British birth cohort)
    • National Child Development Study (1958 British birth cohort)
    • 1970 British Cohort Study
    • Avon Longitudinal Study of Parents and Children
    • Millennium Cohort Study

  • Childhood environment and adult mental well-being[7]: this piece of research uses data drawn from new findings through comparing data across three studies...

    • MRC National Survey of Health and Development
    • 1958 National Child Development Study
    • 1970 British Cohort Study

Finding a metadata standard for your research

How can you find the right standard for your research?

You can use the following sites to search for a relevant metadata standard...

  • Metadata standards catalogue which compiles metadata standards across researchdisciplines and allow you to search for the standard most relevant to your research.
  • FAIRSharing allows you to search for standards, schemas and controlled vocabularies across disciplines.
  • WC3 lists all their standards that describe web resources. You can search their standards here.
  • DCC Metadata standards guideline which contains a list of metadata standards for different disciplines.

Data repositories and catalogues ...

Data respositories and catalogues often specify what metadata standard to use. If you're planning to deposit your data, check what standards the might require.

Recommended standards in your disciplines ...

In some disciplines, there are leading metadata standards for example, DDI in social science research. Check with leading research organisations or colleagues whether there is a recommended standard to use.

What to consider when choosing a metadata standard ...

  • Uptake of the metadata standard in your field
  • Ability of the metadata standard to meet your needs and aims e.g. does it capture include all / most of the metadata elements you need?
  • How regularly a metadata standard is reviewed and updated by a community

Why is it important to take time in finding the best metadata standard for your research?

There is no one 'best' standard to use. What standard you pick will depend on the resource you want to document, how you want to share it and the scope of your work.

The more widely a metadata standard is used, the more powerful it becomes. Having one main standard for a field helps simplify workflows, improve interoperability, and reduce confusion. When more people use the same standard, more data can work together, making research easier to share and compare. If you don’t choose the best standard for your research, your data may be harder to find and less useful for cross-study analysis.

If the main metadata standard in your field doesn’t fully meet your needs, it’s still best to build on its structure and adapt it where necessary, rather than creating a completely new standard. This helps keep workflows simpler and more consistent.

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🔍 Practice activity: Finding a metadata standard

You're a social science researcher who is about to conduct research into the availability of adult education services in the UK and people's perception of it. You want to use a metadata standard to describe your data in order to ensure the metadata is interoperable with other studies.

Try and find a relevant metadata standard using the tools we suggested above.

Metadata standard for this context

First, we identity the scope and focus of the research. Here, our research discipline is social science and our focus is adult education.

Next, we can use the metadata standards cataloguesubject page. If we click to Education, we can find one main metadata standard AMB (General metadata profile for educational resources) which offers a structure for describing learning and teaching resources. As this has limited applicability to the research project outlined above, we can next look at the Social Sciences topic instead. Here, we can see three items listed CESSDA CMM, CESSDA Data Catalogue DDI Profiles and DDI. As the first two are schemas based on DDI, we can choose DDI as the relevant standard as it describes data from the social, behavioral, and economic sciences.

If you explore the catalogue page for DDI, you can view the latest documentation for the standard, the relationship the standard has to other standards and schemas, and tools you can use to create metadata in this standard.

➡ Now try finding a relevant metadata standard and/or schema for your area of research.

Test your knowledge

True or false...

  • A metadata standard can be based on a schema.
  • A metadata standard never changes once it has been created.
  • All metadata standards use the same set of elements.

Which of the following is an example of a metadata standard?

  1. CSV
  2. Dublin Core
  3. HTML
  4. Excel
  5. UK Data Service

How can you find a relevant metadata standard for your research?

Answers

True or false...

  • A metadata standard can be based on a schema. TRUE
  • A metadata standard never changes once it has been created. FALSE
  • All metadata standards use the same set of elements. FALSE

Which of the following is an example of a metadata standard?

  1. CSV
  2. Dublin Core
  3. HTML
  4. Excel
  5. UK Data Service

How can you find a relevant metadata standard for your research?

You can find a relevant metadata standard by identifying your research domain and searching trusted sources like FAIRsharing.org or the Digital Curation Centre. Also, check published studies, funder requirements, or ask your research community for recommendations.

References