Big data in the health sector
The definition of big data implies that a massive volume of data available can be rapidly processed, analysed and used as a valuable resource, which can be summarized as the "4 V's": volume, variety, velocity and value.

In the health industry, the use of data analytics can enable the identification of a potential connection between a drug and a disease. Also, it may provide evidence that a medicament is suited for a particular individual, facilitating the treatment of illnesses. For instance, apps such as K-Health apply artificial intelligence and data analytics to give users access to accurate information about their symptoms. It works by comparing the user's self-reported symptoms and similarities to other patients’, providing data research based on gender and age.

Challenges for big data in healthcare
Despite some advantages of big data being outstanding, there are still uncertainties about its use in the healthcare sector. The first issue is: who owns all the data gathered from individuals? Considering that patients and users contribute to data by sharing their symptoms and other personal data, is it fair that companies retain this information and, above all, profit from it?

If we examine this problem from the medical industry's point of view, it is arguable that all the data available has no meaning (or even value) if it is not analysed efficiently, and this is only possible by the use of data analytics. However, from a consumer's perspective, it is defendable that society needs new models of data ownership and protection that reflect the current role of information.

Consequently, this leads to a second point: should data be retained only by a few companies, or should it be accessible to anyone? While public access could enhance innovation in the medical field, it is also believed that sharing the data incautiously could lead to privacy rights violations. Therefore, the dilemma "open access vs. monopoly" is a tricky one to solve, as striking a balance between privacy and security is still problematic.

To some extent, the EU has acknowledged that data use may clash with the fundamental right of privacy. For this reason, the General Data Protection Regulation (GDPR) 2016/679 came into effect in May 2018. However, emerging issues of data ownership and financial compensation for users are still being discussed.

Finally, the third problem is: if medical inventions rely on data from users' health, should patients be entitled to profit from this? And if so, what would be the legal ground of this profit? By applying the principle of distributive justice, perhaps each one of us sharing the data might have the right to profit, and companies should compensate individuals accordingly. Also, if we suppose privacy as a new kind of property as did Lawrence Lessig in his same-titled book, it might be time to consider the establishment of a specific property title, which reflects the current nature and economic use of data.

Economic perspective on big data
While these are all difficult questions to answer promptly, it might be useful if we analyse them from an economic point of view. Essentially, as data is considered a non-rival good, it is not subject to scarcity, which means that, differently from physical resources, data can be utilised more than once. In fact, some argue that the more data is used, the more advantageous for society.

From a utilitarian perspective, it is crucial to utilise the current resources in a manner that will bring optimal outcomes, by finding a balance between freedom and incentive to innovation. Accordingly, the stimulus to collect data may be linked to the possibility that companies may gain some financial reward for the information obtained, which, on the other hand, may conflict with data rights, whose ownership belongs to individuals and not the collectors. From this, a sensitive question arises, the solution to which requires a multidisciplinary analysis of law and economics.

Further, it should be borne in mind that the absence of data scarcity coupled with its easy and broad access can lead to positive externalities that discourage the use of protective collectors, precisely in the search for an economic outcome more favourable to society from a general perspective.

As people contribute to data regardless of any financial incentive, there is maybe no need to give incentives to the production of data. Consequently, granting exclusive rights could impair the balance between access to data and incentive to production. In order to solve this issue, it is essential to develop new approaches in relation to the perception of users' data as a valuable commodity. Perhaps it is time to consider a new form of right to compensate individuals, keeping in mind the balance between economic incentives and innovation.