The world, our lives are increasingly influenced by Information and Communication Technologies, the main driver of current technological progress, shaped around information and data. Our society, health, wellness, economy, and government are strongly based on data and information, thus asking for proper methodologies, technologies, and solutions to deal with related challenges.

The ICT landscape was subjected to  several revolutions in the last few decades (e.g., cloud, edge, IoT, 5G), boosting an exponential increase in the amount of data to collect, analyze and manage, targeting GeopBytes (2^100 - 10^30 Bytes) by 2025. Cloud, IoT, and 5G are now effective solutions triggering digital transformation and economies, thus moving interests towards data science, including its technologies and applications. The cloud computing paradigm, indeed, is now mature and IoT systems are finally becoming production-ready, as well as Edge computing, complementing the cloud by migrating the computation at the edge of the network, closer to end devices. The advent of 5G networks is then boosting yet another ICT revolution,  enabling a new wave of smart services based on increased throughput, decreased latency, and massive sensor support, with plenty of applications such as smart cities and communities, Industry 4.0, Intelligent transportation systems, edutainment, intelligent and cognitive systems, to name but a few.

We are moving towards a world and society whose systems and services are built on large digital ecosystems, characterized by the need to safely manage huge amounts of heterogeneous data and information. In this new connected world and society, sensors and smart devices are part of everyday life, from smart grids and smart transportation systems to smart healthcare and smart homes, and contribute to increasing the centrality of data in modern systems and services. 

The digital economy thus established, mainly and strongly based on data, is a solid reality with examples as Google, Facebook-Meta, and many others, now identified as surveillance capitalism under the mantra  “data is the new oil” coined by the British mathematician Clive Humby in 2006. This concept, renewed in 2017 in an article appeared in the Economist claiming that “the world’s most valuable resource is no longer oil, but data”,  describing the data-driven ecosystem in which we live and interoperate, where huge amounts of data are collected, shared, and analyzed by multiple actors working within and across organizational boundaries. These trends are increasing and according to Statista the entire world produced and consumed a total of 79 zettabytes, which is predicted to grow to over 180 zettabytes by 2025.

Data science as the foundation of a data-driven society plays the role of developing all technologies and applications necessary to support the construction of systems based on data in multidisciplinary and increasingly complex fields. Data science technologies and applications are at the core of modern (distributed) systems and supply chains, becoming the cornerstone for the development of a novel ICT-based society in a multitude of application domains, from energy to finance and legal, from smart city to transportation and automotive, from climate change to health, to name but a few. The ability to properly and timely access, manage and analyze data can result in huge benefits for all actors including industry, public administration, research institutions, and finally the whole society. The digital transformation we are witnessing is then pushing towards a data-driven ecosystem that poses strong requirements on data management and data analysis, as well as on data protection and system trustworthiness. 

In this scenario, the CINI Lab on Data Science is built around four main pillars:

  1. Data governance, trustworthiness, and sovereignty
  2. Data analysis and processing
  3. Data architectures and infrastructures
  4. Open science and open data

that are refined in research areas. Activities in the lab will contribute to the European Strategy for Data (, promoting a single market for data, which is built on Common European dataspaces as "an environment where data can be stored, processed and shared in a trusted, secure and mutually beneficial way, to create a thriving data economy" (European Commission, 2020).

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