What is a Citizen Science Community?
A Citizen Science Community consists of people who voluntarily help conduct scientific research. Citizen scientists may be involved in various aspects of the research process, e.g., design experiments, collect data, analyze results, and solve problems.
What is DataScientia?
DataScientia is a Citizen Science community of people who are interested in contributing to, learning about, and influencing the future Data-driven Artificial Intelligence (AI) technological evolution, for themselves and for society.
Within DataScientia, the participants collecting data, the objects described by data, the scientists learning from data, and also the innovators exploiting them, are the citizens themselves. DataScientia aims at enabling a process where citizens collect data and learn about themselves and the part of the world where they live, according to their diverse cultures and perspectives.
DataScientia is an Open Data Community where, analogously to what happens for programmers in Open-Source Communities, citizens share the data they collect, according to their own interests, and thus enjoy the added value generated by the collaboration with others.
What do we do?
DataScientia supports the collection of person-centric data and makes them available to people, for their own needs and goals, as a common good. By person-centric data we mean suitably anonymized personal data, data about the culture, milieu and events around us, as well as the language(s) we speak and the knowledge which allows to interpret and compose the data we collect.
The main goal is to use person-centric data to generate and share knowledge about people, society, and the world, as seen and described by people. The ultimate goal is to analyze and understand how the interpretation of the world, e.g., places and events, as well as language, culture, competences, skills, opinions and goals, differs across space and time, while - more importantly - manifesting a deeper unity, that is, what we all share and enables our going below the surface of diversity.
Why do we do what we do?
We all create and use our own mental model the world. Perception creates it, language allows us to share its description with the other people, thus causing its objectivation, knowledge is what we come to learn about it by observing what repeats itself through change, as described by language.
Our own mental models are different from those of everybody else. The negotiation or conflict between frames of mind is part of the communication process and is inherent to any encounter among cultures and people. However, Internet has exponentially increased the possibility to get exposed to new people, speaking different languages, and holding different knowledge, cultures and traditions. On one hand, this increased exposure to diversity provides us with an unprecedented wealth of opportunities for learning and innovating, while, on the other hand, revealing our limited capability to harness such richness.
Learning about this process and about how to bridge this gap between opportunities and difficulties is key towards sustainable data-driven AI based technological innovation.
What do we hope to achieve?
We want to enable a process where anybody can increase their level of awareness and active participation in the current data-driven AI technological innovation. Technological innovation should be driven by social innovation, and citizens should proactively participate to the definition of the social innovation agenda.
Everybody should be enabled to be in control of their own data and make sure that these data are used to their own benefit and for purposes they agree with.