Open and dynamic online services, such as those created in the context of Cloud Computing, Big Data and the Internet of Things provide benefits, such as easy exchange of information, faster processing of data and 24/7 access. However, potential users of online services are still reluctant to outsource sensitive data to these services, mainly due to lack of control over management of their data and privacy issues. For example, cloud users may have concerns about what Cloud Service Providers intend to do with their data. In fact, users may have little or no information as to when and how their data is used.
Similar scenarios can be identified in the case of Public Administration (PA), since PAs collect, transmit, share and collate huge amounts of personal data. In the case of Public Administration, the issue of privacy plays a much more important role as citizens do not have, in many cases, the option of refusing to provide their data (as is the case with commercial services) but are obliged in many cases by law to do so. For example, citizens who have to submit their self-assessment tax returns must provide their tax office with their private information (e.g. personal details). Any solution that reassures citizens that their data are being used correctly will increase their trust in online PA services.
The VisiOn project developed a visual privacy platform to help public entities deliver safe and privacy-enhanced e-government services that meet the highest privacy standards and nowadays necessities, and offer citizens greater and personalised control over their data.
The VisiOn project extended, developed and provided a hybrid valuation methodology of personal data, based on audience and affinity indicators. This method will help users to increase their awareness about how their data are used as well as their ability to assess and control the level of risk for their privacy. Users will gain useful insights on the value and potential monetisation of their digital personal data and will manage the use of their personal data in a transparent way. All involved entities, citizens and public administrators, will benefit from loyalty and trust that is built for their transactions. This methodology will vastly improve users decision-making when it comes to the specification of Privacy Level Agreements (PLAs).
This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 653642
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