 Finally, data-intensive practices also have implications for the institutional organization of science, as exemplified by the push for open access on one hand and commercial interests in big data on the other (Calvert &amp; Frow 2015; Kastenhofer 2013a,b; Leonelli 2013, 2014; Royal Society 2012; Vermeulen 2011). Data are often produced and compiled without specific aims in mind and are used and reused for multiple purposes, and scholars have stressed the need to reconsider the relation between data and evidence, and between basic and applied science. Moreover, as contexts for ownership of data change, also reward-systems in terms of authorship and credits may need to be reconsidered (Ankeny &amp; Leonelli 2015).