| dc.description.abstract | The fight against the coronavirus needs (big) data to orient decision making and healthcare policies. For various reasons, researchers, private organisations, and non-research public bodies process large amounts of (non-personal) data which can tackle the pandemic in various ways. Two data processing settings can be singled out. The first one encompasses processing of scientific data (e.g. data input vital to find a vaccine), but also statistical data and other research inputs. Actors harvesting them are, in the first place, researchers in the fields of natural and social sciences (‘scientific & research data’, ‘SRD’). On the other hand, private enterprises and non-research public bodies (e.g. national authorities) hoard data as a result or as a by-product of their activities. These datasets prove likewise crucial to address issues of public interest such as the Covid-19 pandemic (‘privately & publicly collected data’, ‘PPCD’). The success of data-driven policies, however, mostly depends on how data is managed. During the Covid-19 crisis, two main tendencies have emerged in this respect. On the one hand, there exist a data management system resting on (access) barriers which restrict data access. Conversely, an alternative data management system is founded on open data access approaches valuing data availability amongst a wide number of actors. This contribution aims to describe and assess the two data management systems concerning SRD and PPCD, presenting the main tendencies which have arisen during the Covid-19 pandemic. Accordingly, it concludes with some policy arguments on the role of IP and other areas of law as to fostering data access for public interest purposes. | |