Building a Query Engine for a Corpus of Open Data

Public Administrations openly publish many data sets concerning citizens and territories in order to increase the amount of information made available for people, firms and public administrators. As an effect, Open Data corpora has become so huge that it is impossible to deal with them by hand; as a consequence, it is necessary to use tools that include innovative techniques able to query them. In this paper, we present a technique to select open data sets containing specific pieces of information, and retrieve them in a corpus published by a portal of open data. In particular, users can formulate structured queries blindly submitted to our search engine prototype (i.e., being unaware of the actual structure of data sets). Our approach reinterpret and mixes several known information retrieval approaches, giving at the same time a database view of the problem. We implemented this technique within a prototype, that we tested on a corpus containing more that over 2000 data sets. We noted that our technique provides focused results w.r.t. the baseline experiments performed with Apache Solr.