Because the organisation and use of data via data centres and data sharing is becoming more and more important for research, it is essential that not only publications but also research data be openly accessible. And since every publication in the field of empirical sciences is based on data, the Berlin Declaration on Open Access (OA) applies just as much to data as it does to publications.

Research data can be integrated in publications, documented indirectly, for example via links in publications, or made available in the form of independent data sets. Data is mainly collected in academic and university research (small science). Because of the wide range of research conducted in this area, it offers the greatest potential for providing open access to and permitting the (re-) use of data.

Since research data is becoming more and more extensive and complex, it is rarely presented in the publications themselves, for example in tabular form. Recent cases of data manipulation and forgery highlight the importance of Open Access to the original data as a means of ensuring the verifiability and reproducibility of research results.

Big science is particularly data-intensive. For example, work in disciplines such as bioinformatics, (empirical) geoscience and environmental sciences is based primarily on data which is collected, analysed and interpreted collaboratively. Indeed, big science is mainly organised collaboratively and furnishes prime examples of the current structural transition to e-Science. Collaborators are linked as users and suppliers via data sharing, and the data is stored in data centres or databases which are often linked or grouped together in clusters.

Because of the added value it brings, Open Access to data is especially worthwhile and gives research completely new opportunities. GenBank and the Protein Structure Database are two exceptionally successful examples: "The success of the genome project is in no small part due to the fact that the world's entire library of published DNA sequences has been an open access public source for the past 20 years. If sequences could be obtained only in the way that traditionally published work can be obtained – there would be no genome project" (Patrick Brown 2004). Another example is the fact that, by using historical DNA, environmental and other data, it was possible to find cholera distribution patterns which would not otherwise have been detectable.

Legal Aspects

The report 'The legal status of raw data: a guide for research practice' is a guide to clarify the legal protection applying to research data, intended for researchers who need to know what they can do with other people’s data.  A brief guide is also provided to enable researchers to determine whether consent is required in order to reuse someone else’s research data.

Advantages of Open Access to data

In a nutshell, the main advantages of Open Access to data are:

• Research results based on data can be verified and critically examined.
• Unnecessary duplication of research work can be avoided.
• Data can be analysed comprehensively and made use of, for example in follow-up projects.
• The research process can be accelerated through data sharing.
• New findings can be achieved by merging data from different sources.
• The merging of data brings an informal added value and yields higher-quality data products, for example indices and data bases.
• Data sets which are collaboratively assembled and jointly used are more cost efficient.
• Open Access promotes re-use of data by the public and by industry.

 Read more Good Practices.