Meta-data
Contents
Meta-data¶
Content 💡👩🏽🏫¶
In the following you’ll find the objectives and materials for each of the topics we’ll discuss during this session.
Objectives 📍¶
what are metadata and why are they important
what makes good metadata
what do we get for all our troubles of making good metadata
how can you make good metadata
Questions you should be able to answer based on this lecture 🖥️✍🏽📖¶
What is the purpose of data dictionaries
To provide human readable explanations and definitions for variables and values in your data, such as text based phenotypic data tables. This can include units for numeric data or definitions for (abbreviated) levels of categorical data.
Why are data dictionaries not enough
Because terms and definitions can be ambiguous. For unambigous definitions of variables and values, we need to use terms from taxonomies or controlled vocabularies. Developing a new controlled vocabulary is a complex process that requires input from experts in the community to achieve broad agreement on the terms.
Why should metadata be machine readable
So we can provide services that can integrate large amounts of structured meta data across datasets automatically such as dataset search, cohort definition, and provenance tracking.