Keynotes

Mauro Dragoni

Title: Semantic AI for Healthcare - The HORUS.AI platform

Abstract: Automatically monitoring and supporting healthy lifestyle is a recent research trend, fostered by the availability of low-cost monitoring devices, and it can significantly contribute to the prevention of chronic diseases deriving from incorrect diet and lack of physical activity. In this talk I will present the HORUS.AI platform: an AI-based platform built upon the integration of semantic web technologies and persuasive techniques for motivating people to adopt healthy lifestyle or for supporting them to cope with the self-management of chronic diseases. The platform collects data from users’ devices, explicit users’ inputs, or from the external environment (e.g. facts of the world) and interacts with users by using a goal-based metaphor. Interactive dialogues are used for proposing set of challenges to users that, through a mobile application, are able to provide the required information and to receive contextual motivational messages helping them to achieve the proposed goals. HORUS.AI is constituted by two main layers: the Knowledge and the Dialog-Based Persuasive layers. The Knowledge Layer contains the knowledge bases modeling the specific domains for which users are monitored (e.g. diet), the rules provided by domain-experts, and the RDF-based reasoner that combines the modeled knowledge with the users’ generated data. The results produced by reasoning operations are coded into motivational strategies and messages by the Dialog-based Persuasive Layer. The Dialog-based Persuasive Layer creates and manages dialogues and generates motivational messages based on the information provided by the Knowledge Layer and learned from previous users’ behavior. This way, messages are tailored to specific users. These two layers are supported by an Input/Output Layer exploited for directly communicating with users (i.e. dedicated mobile application or social media channels) by providing summaries of the acquired data, the chat containing the interactions between the users and the system, and graphical items showing the users’ statuses with respect to their goals. HORUS.AI has been validated within the context of different territorial labs and projects and the observed results demonstrated the suitability of HORUS.AI in real-world scenarios.

Short Bio: Dr. Mauro Dragoni (https://pdi.fbk.eu/people/profile/dragoni) is a researcher scientist at Fondazione Bruno Kessler within the Process and Data Intelligence research unit (PDI). He received his Ph.D. in Computer Science from the University of Milan in 2010. His main research topics concerns the design of knowledge management and artificial intelligence strategies by focusing on the development of real-world prototypes, in particular for the healthcare domain, as outcome of his research activities. He has been involved in a number of international research projects, including Organic.Lingua (FP7), Medical CPS (EIT), PROMO (FESR), and Presto (FESR) and into the organization of workshops and other scientific events. He co-authored more than 100 scientific publications in international journals, conferences, and workshop.

George Konstantinidis

Title: Enabling Personal Consent in Data Management

Abstract: There is an evidently growing legal, cultural and technological need for tools and models that allow users to express their own intentions and consent over the usage of their personal data and information. Service providers and institutions that manage personal data rely on specifying monolithic “Terms and Conditions” written in natural language and enforced in an ad-hoc manner, by presenting users with top-down, coarse-grained, opt-in/out options. Flipping the perspective on the current paradigm we advocate the need for users rather than (only) providers to describe their personal contract of data usage, and do so in a formal, machine-processable language. Semantic Web technologies can have a central role in this approach by providing the formal tools and languages required. Expressing data sharing intentions, consent and data usage agreements in a technical way enables the development of algorithms that automatically respect a user’s policy. We show some initial results in this space which we believe will help organisations increase technological capabilities, abide by legal requirements, and avoid ad-hoc processes thus saving engineering resources.

Short Bio: Dr. George Konstantinidis is an Assistant Professor at the School of Electronics and Computer Science at the University of Southampton and a Turing Fellow at the Alan Turing Institute in London. His research interests include A.I. and data management, data integration, data privacy, the semantic web, and distributed systems. Before joining the University of Southampton he had been working for the University of Oxford and the University of Southern California developing algorithms and building systems that integrate thousands of information sources. He has co-authored over 25 scientific publications and has been involved in a number of research projects in USA (BIRN and SchizConnect on integrating bioinformatics and schizophrenia data, respectively), EU (TheyBuyForYou on integrating public procurement data) and the UK (PDQ and ED3 on query optimization and ontology-based data analytics, respectively).