State-of-art analysis of OA strategies to scientific data

This study report examines strategies that aim to foster open access to scientific data—such as the types of incentives given at the researcher and institutional levels and the level of compliance by researchers and funded organisations—and also examines how, and whether, these policies are monitored and enforced. The infrastructures developed to store and share OA scientific data are also examined. The analysis is supported by findings from the literature on the global progression of OA scientific data since 2000—including its growth as a segment of scholarly publishing—as well as some broader themes and debates that have emerged from the movement. 

The concept of OA to scientific data was first implemented more than 50 years ago in order to share data collected as part of the 1957-1958 International Geophysical Year by the International Council of Science (ICSU) (Committee on Scientific Accomplishments of Earth Observations from Space, National Research Council, 2008). Since then, its growth has followed a complex pattern in terms of its spread across disciplines, countries, and types of organisations. Today, a few mature databases have grown to become inevitable references, while an unknown number of databases are still in their infancy. 

Importantly, however, compared to OA repositories of theses and scientific articles, institutional repositories that support the archiving of scientific datasets remain marginal.  Open data is evolving rapidly in an environment in which citizens, institutions, governments, non-profits, and private corporations loosely cooperate to develop infrastructure, standards, prototypes, and business models. Hack-a-thons and social media are testing grounds for novel approaches. Repository overlay journals are experimenting with new forms of scholarly communication involving raw data.

Many scientists spend painstaking hours collecting data that can then be used to derive a competitive advantage vis-à-vis colleagues who do not have access to these data. Many of the most successful researchers are in fact running small businesses, and asking them to give up the data on which these businesses are built can pose a very tangible barrier to greater data openness.

There are sizeable barriers to the widespread implementation of open access to data. These include a closed government culture; privacy legislation, absence of strong Right to Information laws, or weak or absent data protection laws; limited quality of data, limited user-friendliness of data; unequal access to data; lack of standardisation of policy; security threats; existing charging models; lack of awareness, education, and public interest; and uncertain economic impacts (Davies, 2013; Fioretti, 2014; Huijboom & Van den Broek, 2011).