We develop a large number of software tools and hosting infrastructures to support the research developed at the Department. We will be detailing in this section the different tools available. You can take a look for the moment at the offer available within the UPF Knowledge Portal, the innovations created in the context of EU projects in the Innovation Radar and the software sections of some of our research groups:


 Artificial Intelligence

 Nonlinear Time Series Analysis

 Web Research 


 Music Technology

 Interactive  Technologies

 Barcelona MedTech

 Natural Language  Processing

 Nonlinear Time Series  Analysis


Wireless Networking

Educational Technologies




Back CS-Track − Expanding our knowledge on Citizen Science through analytics and analysis, new H2020 project with Davinia Hernández-Leo

CS-Track − Expanding our knowledge on Citizen Science through analytics and analysis, new H2020 project with Davinia Hernández-Leo




: H2020-SwafS-2019-1


Abstract: The Call focuses on Citizen Science (CS), understanding it in a comprehensive way and inviting projects to deepen and broaden our knowledge on CS activities and their impact. Indeed, overcoming present hurdles on the way to reach that knowledge will enable the potential benefits of CS – on individual citizens, organizations, and society at large – to be realized more effectively and frequently. This is the aim of our proposed project, CS- Track, which will seek this increased knowledge by “observing” a large and diverse set of CS activities, gathering data from the web, interviews of involved players, etc., and from a more direct inspection of running activities. Vast amounts of data will thus be studied, relying for this on (1) web- based analytics, i.e. the use of computational analyses to study CS activities based on their manifestations and traces on the web and social media, and (2) deepening and combining these analyses with approaches known from social studies through multi-perspective analysis and triangulation. Our data analytics and analysis will target both “own” aspects and developments of the CS activities (organizational/operational characteristics, scientific outcomes, good practices, individual/group learning, other success or failure indicators, etc.), and societal aspects, related to the impact of those activities on society, such as gender, age, geographical and socio-economic differences; science as a discipline and its role in society, changing attitudes to science, women in science, etc. This will enable us to understand complex processes, disseminate good practices and formulate knowledge-based policy recommendations intended to optimize CS to make it a major, positive factor for EU’s society and economy. The project will last 36 months, involving 9 partners from 7 countries.

Contact for additional details: Patricia Santos



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