A Short Account of Techniques for Assisting Users in Mastering Big Data

One of the most challenging problems faced by the database community is to assist inexperienced or casual users, who need the support of a sophisticated system that guides them in making sense of the data. This problem becomes especially relevant in the case of Big Data, where the amount of data may quickly overwhelm users and discourage them from leveraging the richness of the data patrimony. In the last years, often in collaboration with other members of the Italian database community, we have developed several different techniques whose aim is both to reduce the size of the problem and to focus on the information that is most relevant to the user. To this end, most of these techniques fruitfully extract and exploit data semantics, for example by succinctly characterizing data via intensional properties such as integrity constraints or by tailoring the answer to the user context or preferences. Other techniques support the users in information exploration, for instance by extracting data not readily accessible (such as the Hidden Web) or by presenting them with appropriate summaries and suggesting possible exploration paths.