Project Objectives

In order for BigO to build a system that collects Big Data on children’s behaviour and helps planning health policies against obesity, a specific set of detailed scientific, technological, validation and business objectives have been set:


Scientific Objectives

Aetiology:  The first objective of BigO is to extract causal relations between local environment and personal behavioural patterns that can lead to obesity behavioural risk factors.

Prediction: The second objective is to model how changes of the local environment can modify personal behavioural patterns and eventually obesity behavioural risk factors.

Prediction: the third objective is to produce quantified models that map changes of obesity-related behavioural risk factors (what and how children eat, how they move, how they sleep) to the prevalence of obesity.

Privacy Preservation: to define a parsimonious behavioural model and data structure that will be free of redundant individual information and will minimize the use of sensitive information.


Technological Objectives

BigO will build an extensive network of information sources: (i) sensors like smartphones and bracelets, (ii) mobile applications collecting subjective and objective data, (iii) server based applications interfacing to publicly available data, like maps, statistics, metadata, etc.

BigO will determine a set of policies for big-data governance, privacy and anonymisation and develop the technical means to enforce them.

BigO will provide 3 core decision support functionalities (i) the Policy Advisor that offers aetiology and data evaluation services, (ii) the Policy Planner that offers simulation and prediction services and (iii) the Clinical Advisor that offers evaluation and decision support for the individual at the point of care.


Validation Objectives

Validation of BigO will be conducted at three different levels: (a) Evaluation of the system components (b) Evaluation of the integrated system in realistic usage environments including data acquisition and (c) Evaluation of the decision support platform. The entire validation procedure will exploit data from more than 9000 active contributors. 

Business Objectives

BigO will define an effective, pragmatic and viable business plan and exploitation scheme in line with two targeted uses: (i) as a framework for supporting public health authorities and (ii) as a tool that offers evidence to the health professionals at the point of care.

BigO is built around the “citizen-scientist” model, which relies on individuals sharing their behaviour data. As part of the business plan, BigO will propose policies integrating also economic benefits as incentives (e.g. discounts by health insurance) for active data contributors.