LinDaFIX - Linked Data for Fighting Inequality in Complex Societies


This project is aimed at proposing a set of tools that facilitates the integration, enrichment, and analysis of the data provided by the Social Rights Department of the Ajuntament de Barcelona. Our basic approach builds on semantic technologies, automated reasoning and machine learning to cross information and discover relationships that probabilistically indicate which are the individuals at risk of social exclusion and poverty.


The main development tasks correspond to our main concrete objectives: (1) a semantic model that reflects the concepts manipulated by the social services domain, including inequality indicators and the mapping between the model and the concrete data, (2) a semantic exploration and query tool, and (3) models for probabilistic prediction of vulnerability and identification of citizens at risk.

The image of the project has all rights reserved to its author Antony Theobald.

Duration of the project 
June, 2018 to December, 2019
Funded by 
Areas of expertise involved in the project 
Project Manager 

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