Overslaan en naar de inhoud gaan

Open Data formats

Deze inhoud is alleen in het Engels beschikbaar
Session Outline: This session explores the various techniques to publish a dataset and the advantages and disadvantages of each. We will specifically focus on publishing in a CSV format and introduce tools to help manage CSV projects.

Session number: 9

Expected participants: Relevant to all, special relevance to those publishing data

Type: Training

Length: 1.5 hours

Exercises: Yes

Web based exercises: Yes

What to bring: Slides, Flipchart, Paper & Pens


Session Flow:

  1. Defining Open Data formats - The participants should define what an Open Data format is. The facilitator should collect their definitions and lead a group discussion. The facilitator should highlight the difference between a data structure like tabular (which refers to the way the data points are presented) and a data format like .csv (which refers to the file extension and the encoding of the data).
  2. Common Open Data structures - The facilitator should guide participants in a discussion of the difference between tabular, hierarchical and network data structures and examine some examples of datasets which correspond to these three structures.
  3. Exploring specific data types - The facilitator should examine specific examples of data types such as legislative, statistical and geographic data which require special treatment. Facilitator should select the data types most relevant to the audience and discuss in greater detail the landscape of the data type(s) including leading a conversation on participant experiences.
  4. Common Open Data formats - The facilitator should examine common data formats such as CSV, JSON, GeoJSON, KML, XML and RDF Turtle. The formats studied should be adapted to the audience. Participants should use a group discussion to highlight the benefits and challenges of the different formats. Finally the facilitator should lead an exercise where participants suggest the best format and structure for several hypothetical dataset examples.




Companion eLearning Modules:

When running this session, we recommend that participants complete the following eLearning module before attending:

Choosing the right format for Open Data

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.