Looking at the data courses offered by universities, the consortium identified critical limitations:


Courses are fragmentary in time and space. The duration of a data science course ranges from one week to a semester or a 1-2-year master degree. They are organized as face to face lesson, or through web platforms.


The syllabus of these courses are very different. Even though, the data literacy profile is often connected to competences in data visualisation, statistics, machine learning, each course gives different weights to these macro topics. As a result, there is not a homogeneous competence profile for data literacy

Not qualified

It does not exist a qualification system recognized at European level related to data literacy and data science profession.


The needs of job market have not been adequately analysed. It’s clear that there is still not a mature debate on this topic between academia and businesses
The overall objectives of the projects derive from the challenges and needs identified during the need analysis, and are the following:


Defining a common understanding of what a data literate person is supposed to know and is able to do, not only as worker but also as an active citizen


Designing and developing innovative didactic frameworks related to data literacy that reflect the views and needs of academia and job market.


Fostering a culture of data literacy among European citizens


Making graduate students acquire the data skills they need to success in the job market and to actively take part in the civil society