Lesson
Guidelines for ensuring quality in open data and metadata
Being able to assess the usability of open data is a crucial skill in the data collection phase. In this lesson, you'll learn how to evaluate the quality of open data, understand the standards and markers of high-quality open data, and discover guidelines on data and metadata quality. You'll be introduced to a tool that helps you check the quality of your metadata, and through interactive videos and readings, you'll learn how to create high-quality DCAT-AP datasets. By the end of this lesson, you'll have the skills to judge the usability of open data, ensure the quality of your own data, understand the role and application of controlled vocabularies, and apply tools to assess the quality of your datasets.
About this lesson
- Level:
- Intermediate
- Course:
- Improving open data and metadata quality
- Theme:
- QualityBusiness
- Format:
- Reading, Videos, E-learning, Tools
Lesson materials
These are the slides used for the training session on "Data and Metadata Quality".
This report contains a set of guidelines for delivering high-quality data. It supports data providers in preparing the data, developing a data strategy and ensuring data quality.
The Open Data Goldbook is a practical guidebook for data managers and data holders about open data in general, how to build an open data strategy, technical preparation and implementation, putting in place an open data lifecycle, and ensuring and monitoring success.
What makes quality open data?E-Learning
This is the eLearning related to the lesson 'What makes quality open data?'. This eLearning is offered in English, French, German, Italian, Spanish and Swedish.
The Metadata Quality Assurance is intended to help data providers and data portals check their metadata against various indicators. The methodology page contains information on which metrics we use for indicator measurements.