Metadata is structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an information resource.
"Metadata facilitates and supports the discovery, identification, organisation and interoperability of research outputs. Having rich metadata will help maximise exposure, reuse and citation of your research findings." (Adapted from Source: Australian Research Data Commons)
Here is the metadata type table adapted from National Information Standards Organization United States.
| Metadata Type | Example Properties | Primary |
|---|---|---|
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Descriptive metadata Common fields which help users to discover online sources through searching and browsing |
Title Author Subject Genre Publication date |
Discovery Display Interoperability |
|
Technical metadata Fields which describe the information required to access the data |
File type File size Creation date/time Compression scheme |
Interoperability Digital object management Preservation |
|
Administrative Metadata for Preservation Fields that facilitate the management of resources |
Checksum Preservation event |
Interoperability Digital object management Preservation |
|
Administrative Metadata on Rights Fields which deal with intellectual property rights |
Copyright status License terms Rights holder |
Interoperability Digital object management |
|
Structural metadata Fields which describe how different components of a set of associated data relate to one another |
Sequence Place in hierarchy |
Navigation |
|
Markup languages Languages which integrate metadata and flags for other structural or semantic features within content |
Paragraph Heading List Name Date |
Navigation Interoperability |
The following is a video created by EDINA, University of Edinburgh, explaining what metadata is.
Metadata standards/schemas may vary from discipline to discipline. Dublin Core is one of the most commonly-used generic metadata standards.
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Simple Dublin Core involves 15 elements (optional & repeatable):
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Here are some useful resources for you to explore metadata schema in your research areas:
All research datasets should have an accompanying readme file that provides more information about the dataset, such as contact details of the research team, data collection methods, methodological information and data files and folder organisational structure etc. A README file is intended to help ensure that your research data can be correctly interpreted and re-used by others. It is intended to not only help other researchers, but also yourself, to ensure research reproducibility and maximise reuse of your data and accrue data citations.
Here are some best practices in creating comprehensive README files.
The table below is adapted from Cornell University's Guide to writing "readme" style metadata, and highlights possible contents that you could include in your README file. Fields indicated in bold are mandatory for inclusion in your readme file, and can be adapted for your own unique dataset and discipline.
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General information |
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| Data and file overview |
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| Sharing and access information |
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| Methodological information |
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| Data-specific information |
You may repeat this section as needed for each data file or dataset
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You can adapt to this template if appropriate. This template is adapted from Guide to Writing "readme" Style Metadata, Comprehensive Data Management Planning & Services, Cornell University.