Open data is data that can be freely used, re-used and redistributed by anyone – subject only, at most, to the requirement to attribute and share-alike (FOSTER).
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.
The term open data is connected with the term FAIR data that present an inevitable part of open science and describe basic principles of good data management and open access to research data.
The principles emphasise machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention). The ultimate goal of FAIR is to optimise the reuse of data.The FAIR principles were published in 2016 for the first time. They were accepted by the European Union and many other organisations, including universities and research institutions.
More information and resources in English:
Open Knowledge Foundation: https://okfn.org/opendata/
Open Data Handbook: https://opendatahandbook.org/guide/en/what-is-open-data/
UNESCO Recommendation on Open Science: https://en.unesco.org/science-sustainable-future/open-science/recommendation
GO FAIR: https://www.go-fair.org/