As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Companies have been analyzing data from their own customer interactions on a smaller scale for many years. But only recently, they understood the potential treasure trove of non-traditional and less structured data (such as machine-generated data and social media data) that can be mined both for internal marketing purposes and for licensing to third parties.
From the business perspective, the protection of this data is needed to secure the significant economic investment that the “new data economy” can require. Otherwise, data holders may lack the incentives to share the data they own and control, because of the risk that non authorized users may “free ride” on their investment.
Granting property rights is often suggested as a solution to overcome the incentive problem. In the case of data, while relying on contract freedom may seem the favourite solution, between those extremes a spectrum of possible “halfway” approaches has been proposed. They range from “quasi-property” or “semi-commons”, with a liability-like regime, to access rights, requiring to license extractions and reuse of data on FRAND terms.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.