The Open Definition gives full details on the requirements for ‘open’ data and content. Open data are the building blocks of open knowledge. Open knowledge is what open data becomes when it’s useful, usable and used.
The key features of openness are:
- Availability and access: the data must be available as a whole and at no more than a reasonable reproduction cost, preferably by downloading over the internet. The data must also be available in a convenient and modifiable form.
- Reuse and redistribution: the data must be provided under terms that permit reuse and redistribution including the intermixing with other datasets. The data must be machine-readable.
- Universal participation: everyone must be able to use, reuse and redistribute — there should be no discrimination against fields of endeavour or against persons or groups. For example, ‘non-commercial’ restrictions that would prevent ‘commercial’ use, or restrictions of use for certain purposes (e.g. only in education), are not allowed.
What kinds of open data?
There are many kinds of open data that have potential uses and applications:
- Culture: Data about cultural works and artefacts — for example titles and authors — and generally collected and held by galleries, libraries, archives and museums.
- Science: Data that is produced as part of scientific research from astronomy to zoology.
- Finance: Data such as government accounts (expenditure and revenue) and information on financial markets (stocks, shares, bonds etc).
- Statistics: Data produced by statistical offices such as the census and key socioeconomic indicators.
- Weather: The many types of information used to understand and predict the weather and climate.
- Environment: Information related to the natural environment such presence and level of pollutants, the quality and rivers and seas.
The Open Data Handbook
For a more complete look at open data including a detailed guide on how to open it up and a glossary of key terms, read it online.