Over the past couple of years I’ve written several posts that each focus on trying to answer a simple question relating to data and/or open data.
I’ve collected them together into a list here for easier reference. I’ll update the list as I write more related posts:
- What is a dataset?
- What is a dataset? Part 2: A Working Definition
- What does your dataset contain?
- How do we attribute data?
- What is an open API?
- What is derived data?
- What is a data portal?
- How can we manage risks when publishing open data?
- Who is the intended audience for open data?
- How can open data publishers monitor usage?
- Why are bulk downloads of open data important?
- How do different communities create unique identifiers?
- When are open (geospatial) identifiers useful?
- What kind of data is it useful to include in a register?
- How can we describe different types of dataset?
- How do data publishing choices shape data ecosystems?
- How can publishing more data increase the value of existing data?
- How can publishing more data decrease the value of existing data?
- How can you help support the use of a dataset?
- How can we dataset recipes help us create more value from data?
- Why is change discovery important for open data?
- What is collaborative maintenance of data?
- What are the building blocks of data infrastructure? Part 1 and Part 2
- What is data asymmetry?
I find that asking and then trying to answer these questions are a good way to develop understanding. Often there are a number of underlying questions or issues that can be more easily surfaced.
Lost Boy 