Research data can be extremely diverse: from spreadsheets, audio-visual materials, databases, to 3D-models and result lists from large experiments. Sizes may vary from a couple of small files related to a specific publication (‘long tail of research data’) to vast collections of experimental results (‘big data’), that can only be processed using specialized programmes. 

The need for adequate documentation and description is obvious, as reproducibility is the key factor when it comes to scientific research. Specialized repositories, such as Zenodo, have been established to collect and preserve datasets of all kinds, and possibly linking them to publications and projects related to the creation of the set. Collecting, describing, licensing and preserving data proves to be a big challenge, and experience with Research Data Management quickly becoming a sought-after asset for researchers and supporting staff.

Open Knowledge Foundation has defined Open Data in ‘The Open Definition’, as "machine-readable, available in bulk, and provided in an open format (i.e., a format with a freely available published specification which places no restrictions, monetary or otherwise, upon its use) or, at the very least, can be processed with at least one free/libre/open-source software tool."

See also: OpenAIRE Open Research Data Pilot Factsheet.