In an era where digital progress runs fast, it is imperative to find ways to innovate infrastructures through technology in order to help them improving the quality of their services. This thesis focuses on finding ways to extract information from data supplied by "Biblioteche Civiche Torinesi" (BCT) to implement a recommender system capable of suggesting a book tailored to the reader. This is done in order to offer services that can improve the reading experience. For the thesis, I followed three main phases. The first was the data characterization one: my main objective was to define, quantify and preprocess BCT data in order to make it apt to being used as input for a recommender system.