Date: 11 April 2022 @ 10:00 - 12:00

Timezone: Bucharest

In general, metadata is the descriptive information about your data. However, what exactly is metadata and how much of it should be included with your data? Good metadata can make up for human fallibilities. People forget and misplace things, and leave research projects taking their knowledge of the research methodology and the data with them. Metadata ensures that we will be able to find the data, use it, preserve and reuse it in the future.

Finding Data. Metadata makes it much easier to find relevant data. Most searches are done using text (like a Google search), so formats like audio, images, and video are limited unless text metadata is available. Metadata also makes text documents easier to find because it explains exactly what the document is about.
Using Data. To use a dataset, researchers need to understand how the data is structured, definitions of terms used, how it was collected, and how it should be read.
Reusing Data. Researchers often want to reuse data collected for another project for their own project. The data still needs to be found and used, but often at a higher level of trust and understanding. Reusing data often requires careful preservation and documentation of the metadata.
This means that the metadata provides additional information that helps data consumers to better understand the meaning of the dataset, its structure and to clarify other issues, such as rights and license terms, the organization that generated the data, data quality, data access methods and the update schedule of datasets. Additionally, metadata also gives information about the data in general. What an actual metadata file includes, varies between disciplines and types of data you are working with. However, the documentation for your data should contain the minimum information required to be able to reuse (or understand) the data described.

In this lecture, we will be going over what metadata about your dataset should be included when you are sharing it. Additionally, we will also go over some examples on how to write a good README file.

Keywords: FAIR, metadata, README

Organizer: ELIXIR Estonia

Host institutions: University of Tartu, Institute of Computer Science

Eligibility:

  • First come first served

Target audience: Graduate students, Researchers

Capacity: 25

Event types:

  • Workshops and courses

External resources:

Activity log