The Identity of the Public Library and Reading Practices: Overview of the Reading(&)Machine Project and Its Context

Introduction

This contribution presents and discusses the contexts, objectives, methods and expected results of the Reading(&)Machine project (hereinafter R(&)M) developed by the Polytechnic of Turin SmartData@ PoliTO and VR@PoliTO centers and by the University of Turin Department of Historical Studies. R(&)M adopts two integrated perspectives. The first concerns the design and implementation, with the help of Artificial Intelligence technologies, of a recommendation system able to capture, enhance and enrich the reading experience. The second describes its contextualization within the physical space of the Turin public libraries involved in this phase of the project. The specific components of R(&)M are:

• 1.

  a recommendation system based on library data, as well as data extracted from the aNobii social reading platform and generalist social networks. Data will be processed anonymously and checked for bias;

• 2.

  an immersive, enhanced and augmented interface for receiving recommendations based on algorithms that is accessible in various ways (web, app for mobile devices, hybrid environments created in the library space);

• 3.

  a hybrid environment, physical and digital, through which algorithm recommendations and the interface become part of the library space.

The project's first goal is to create a working prototype, so as to test and evaluate the impact of an innovative environment (on a conceptual and technological level) for capturing and enhancing the reading experience within the reading space of contemporary public libraries.

The following describes the project's main characteristics, linking them to the scientific literature that identifies and describes the contexts. These contexts are numerous and varied. Some fall within the domain of Library & Information Science, whereas others call for interdisciplinary collaboration with other fields, in particular that of data science. It is therefore important to adopt an interpretative and methodological perspective centered on reading, distinguishing among the different types of reading performed in the library space (see map of library reading practices in Fig. 4). Identifying the types of reading helps understand the diversity of reading styles and practices rooted within the library space. Reading metadata in an online catalogue, for example, is different from reading the text or paratext of a book, and reading part of a website is very different from browsing through the books displayed on a shelf. The schematic map of types of reading helps understand in which phase of the reading experience the recommendation system provides suggestions.

These elements of theoretical and methodological awareness, resulting from the critical analysis of contexts, must be considered carefully to avoid a merely technocratic approach to the technological aspects of the project. Reading practices in public libraries must be considered essential in promoting quality of life, lifelong learning, information literacy, and, in short, people's wellbeing. For these reasons it is important to pay close attention to the multiple dimensions of context, and in particular to the integration of new tools, the impact of artificial agents, and the practices and techniques rooted in the functions of human intelligence, which form an inextricably linked, rapidly evolving unitary dimension.

The following pages will examine: a) the scientific and bibliographic contexts of the R(&)M project; b) a few significant case studies; c) the general characteristics of the project; d) the main functions of the recommendation systems; e) the library space model, which reflects the identity of the public library and within which the project is to be implemented; f) development prospects; g) a few brief final considerations.