Session number: 5
Expected participants: Relevant to all, special relevance to those preparing data for publication
Type: Training or Presentation
Length: 1-1.5 hours
Web based exercises: Yes
What to bring: Slides, Flipchart, Paper & Pens
- Importance of quality data - The facilitator should take participants through the importance of producing high-quality Open Data including the implications for reuse and how quality data helps to generate greater value.
- Introducing the 5 Stars- The facilitator should take participants through each of the 5 stars of linked Open Data (Open licence, highly reusable format, open format, unique resource identifier and linked data) and explain how each of these stars builds toward higher technical quality and greater legal clarity for datasets.
- Introducing the Open Data Certificates - The facilitator should guide the participants through the Open Data Incubators Open Data Certificates and explain how the considerations of the legal, technical, social and practical aspects of a dataset help you design and deliver high-quality reusable data. The facilitator should highlight the certificates website and show participants how the self-certification process is completed.
- Discussing minimum quality - The participants should hold a group discussion of the minimum requirements for quality Open Data. The facilitator should highlight the 3-star level and pilot certificate as useful indicators of minimum quality standards for European Open Data.
- 5 stars of linked Open Data - Technical and legal quality assessment of Open Data.
- Open data Certificates - Technical, legal, practical and social certification of Open Data quality.
- Open data Consumer’s Checklist - Useful reference point on the expectations of Open Data reusers with regard to quality.
- Comparing the 5 star scheme with Open Data Certificates - Explanation of the difference between the two schemes.
- European Data Portal Examples of 1-5 star Open Data - 1 star dataset, 2 star dataset, 3 star dataset, 4 star dataset, 5 star dataset
Companion eLearning Modules:
When running this session, we recommend that participants complete the following eLearning module before attending:
Completion of the module will help your learners develop a shared understanding of the material before the course and allow you to focus in greater depth on those topics of most interest to the trainees.