European Integrated Infrastructure for Social Mining and Big Data Analytics

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SoBigData++ strives to deliver a distributed, Pan-European, multi-disciplinary research infrastructure for big social data analytics, coupled with the consolidation of a cross-disciplinary European research community, aimed at using social mining and big data to understand the complexity of our contemporary, globally-interconnected society. SoBigData++ is set to advance on such ambitious tasks thanks to SoBigData, the predecessor project that started this construction in 2015. Becoming an advanced community, SoBigData++ will strengthen its tools and services to empower researchers and innovators through a platform for the design and execution of large-scale social mining experiments. It will be open to users with diverse background, accessible on project cloud (aligned with EOSC) and also exploiting supercomputing facilities. Pushing the FAIR principles further, SoBigData++ will render social mining experiments more easily designed, adjusted and repeatable by domain experts that are not data scientists. SoBigData++ will move forward from a starting community of pioneers to a wide and diverse scientific movement, capable of empowering the next generation of responsible social data scientists, engaged in the grand societal challenges laid out in its exploratories: Societal Debates and Online Misinformation, Sustainable Cities for Citizens, Demography, Economics & Finance 2.0, Migration Studies, Sport Data Science, Social Impact of Artificial Intelligence and Explainable Machine Learning. SoBigData++ will advance from the awareness of ethical and legal challenges to concrete tools that operationalise ethics with value-sensitive design, incorporating values and norms for privacy protection, fairness, transparency and pluralism. SoBigData++ will deliver an accelerator of data-driven innovation that facilitates the collaboration with industry to develop joint pilot projects, and will consolidate an RI ready for the ESFRI Roadmap and sustained by a SoBigData Association.

Voukelatou, V., L. Pappalardo, L. Gabrielli, and F. Giannotti, "Estimating countries’ peace index through the lens of the world news as monitored by GDELT", 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), 2020.
Naretto, F., R. Pellungrini, F. Maria Nardini, and F. Giannotti, "Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks", ECML PKDD 2020 Workshops, Cham, Springer International Publishing, 2020//.

MALOTEC Seminar - Riccardo Guidotti: Evaluating Local Explanation Methods on Ground Truth 09/04/2021

Riccardo is an Assistant Professor at the Department of Computer Science, University of Pisa, and a member of the Knowledge Discovery and Data Mining Laboratory (KDDLab), a joint research group with the Information Science and Technology Institute

Image by Victorgrigas (Own work) CC BY-SA 3.0, via Wikimedia Commons
Web Site
Start Date
1 January 2020
End Date
31 December 2024
European Commission H2020
European Project
Department of Computer Science, University of Pisa (DI-UNIPI)
Istituto di Scienza e Tecnologie dell’Informazione, National Research Council of Italy (ISTI-CNR)