CRiTERIA

'Comprehensive data-driven Risk and Threat Assessment Methods for the Early and Reliable Identification, Validation and Analysis of migration-related risks'.

The EU's external borders are busy places. Border officials are required to address numerous issues - from document fraud and public health threats to people smuggling, unregulated migration and terrorism. In this context, the EU-funded CRiTERIA project designed a risk assessment methodology that stems from existing analysis technologies and tools that are tailored to the new comprehensive threat indicators of its methodology. The focus is on the role of narratives, events and attitudes and the vulnerability of borders and humans.

In the CRiTERIA project we seek to strengthen and expand existing risk analysis methods, by introducing novel approaches, such as identifying risk factors from qualitative evidence (e.g. narrative analysis), building composite indicators (e.g. using sentiment indicators to predict behaviour), incorporating risk interaction and risk cascading assessments and consolidating the human security and human rights dimensions of border security.

Building upon existing text, media, data and network analysis technology, in CRiTERIA, wel develop and evaluate advanced analysis technologies and tools that are tailored to the new comprehensive risk and vulnerability indicators of the CRiTERIA methodology. Special focus is given to the role of narratives, events, attitudes, perception of situations for migration-related decisions as well as for the evolution of migration-related situations, the vulnerability of borders and humans and the development of threats.

However, the complexity of the analysis tasks requires further technology support beyond collecting evidences for risks and vulnerabilities. It has to be ensured that evidences and indicators can be understood and validated for reliably and efficiently basing decisions and actions upon them. For this purpose, the CRiTERIA project also develops technology for explaining automatically extracted findings following the ideas of explainable AI as well as technology for automated validation of risk and vulnerability related findings.

Duration of the project

2021 - 2024

Awarded grant

4,890,177 euros (of which 446,875 euros for the UG), obtained from Horizon 2020

Contact persons at our Faculty

Prof. G.P. (Jeanne) Mifsud Bonnici
Mr. M. (Melania) Tudorica

Websites with additional information