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Unit 2.8 Dataset metadata

Overview

Unit study time

  • 10 minutes

Intended Learning Outcome

By the end of the unit, you will be able to ...

  • Describe what dataset metadata provides and how it differs from study metadata

What is dataset metadata?

Dataset metadata describes the who, what, when, where, why, and how of a specific dataset. It provides information about the dataset's contents, structure, provenance, and access conditions.

For larger research projects, you may produce multiple datasets. These datasets may focus on different topics, be collected in different locations, or be created by different researchers. As such, having metadata for each dataset helps you manage vast amounts of data and saves you time in the future.

Many of the metadata elements used to describe a study can also be applied at the dataset level.

What metadata elements captured at the study level could also be captured at the dataset level?

Metadata elements commonly captured at both study and dataset level

Title The title of the dataset

Creator The creator of the dataset

Subject Keywords or topics

Description A description of the dataset and what it includes

Contributor People or organisations who contributed to the creation of the dataset. Show more lines

Date The date range of when the data for that dataset was collected

Type The nature of the dataset (e.g. survey data, interview data, administrative data).

Format The format that the dataset is stored in

Language The language used within the dataset

Relation Any other publications or resources that are related to that dataset

Coverage The geographical coverage of the dataset

Access rights The access rights for the dataset

We can also capture additional metadata elements that we didn't cover in the study metadata to give further information about a dataset.

What additional metadata elements should we collect for a dataset?

Additional metadata elements commonly captured at dataset level

Kind of data The type of information contained in the dataset, for example survey data, administrative data, observational data, interview transcripts, or experimental data.

Study The study that produced the dataset

Case quantity Case quantity refers to the number of records contained in the dataset (for tabular data, this is the number of rows)

Variables The number of variables contained in the dataset

Last Updated When the dataset was last updated

Test your knowledge

What is meant by “dataset metadata”?

  1. Information about individual variables only
  2. Information describing an entire dataset, including its structure, content, and context
  3. The values within the dataset
  4. The coding scheme for a single variable
Reveal answer

Information describing an entire dataset, including its structure, content, and context. Dataset metadata provides an overview of the dataset as a whole, including its structure, scope, and key characteristics.

Two datasets contain similar variables, but one dataset contains repeated observations over time, while the other is a single snapshot. Why does this matter?

  1. File formats may differ
  2. The datasets cannot be used together
  3. Variable names will change
  4. Dataset structure affects how the data can be analysed and compared
Reveal answer

Dataset structure affects how the data can be analysed and compared. Differences in dataset structure (e.g. longitudinal vs single collection) affect how data should be analysed and compared.

Why is dataset metadata important for reuse and sharing?

  1. It reduces storage requirements
  2. It ensures identical results
  3. It provides essential information for others to understand and work with the dataset
  4. It eliminates all errors
Reveal answer

It provides essential information for others to understand and work with the dataset. Dataset metadata helps others understand how the dataset is structured and how it can be used, supporting effective reuse.