A Framework for Data Privacy
More than half of the population in many countries can be reliably identified with just three pieces of information: date of birth, gender and postcode. Face recognition, health records, conversations with Siri and Alexa… the amount of data that is continuously being generated is immense and we hardly ever know what it is used for and who is using it.
We do know that there are some companies whose mission is the efficient exploitation of this data. They live from it and for it. But there are many others whose mission is quite different; they use the data to create better products for the users: hospitals, universities and research centres, city councils, etc. How to harness the richness of this data to produce better services and, at the same time, maintain the privacy of the citizens who provide the data.
Privacy engineering
Privacy engineering has developed explosively in recent years. It is a discipline that seeks to avoid the problems that can be created for individuals as a result of processing their personal information and data.
Privacy engineering provides companies with models and tools to efficiently manage the exploitation of the data they collect while maintaining the privacy of the individuals who provide it. It provides, for example, a Risk Assessment model and a framework for exploiting data without incurring legal compliance issues or affecting customer trust.
ADA (Agile Data Analysis) is a project developed by prestigious European universities and co-funded by the European Commission. In ADA, data privacy is a priority and that is why it includes a Framework for Data Privacy through which existing data in repositories can continue to be exploited efficiently while maintaining the privacy of the users who provide it.
More information on the Framework for Data Privacy will be available at upcoming presentations in Madrid, Milan and Budapest. Dates and registration details can be found on the EIT Urban Mobility website: www.eiturbanmobility.eu
Fabián García Pastor
