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About Us

MAKE THE DIFFERENCE
WITH THE DATA

Empowering People Through Responsible Data and AI

WHAT WE BELIEVE IN

The DataScientia Menifesto

01

Data, as they are available on the Internet, is the fuel that is boosting the rise of a new, smarter society that we want to be open, inclusive and enabling a higher quality of life.

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Data should be available and reusable at affordable costs by everybody, regardless of gender, religion, nationality, level of wealth or any other contingent factor.

03

Data should properly represent the diversity of the world, as it results from the local culture and traditions, needs and purpose. Data should be expressed in the local languages and should record those facts that are contextually relevant, with the format and values that are most appropriate.

04

Languages and knowledge should absorb the diversity of data into progressively more unified representations of the world.

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Languages, knowledge and data should be developed thanks to the voluntary efforts of the interested parties, each operating in full autonomy.

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DataScientia is a non-profit organization aiming to support the emergence of a unitary understanding of the world as represented by data.

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DataScientia’s first aim is a technological infrastructure enabling person-centric and data-centric AI-enabled research and social innovation.

08

DataScientia’s second aim is the organizational infrastructure, enabling the development and adoption of best practices.

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DataScientia’s third aim is the legal infrastructure, which deals, among other things, with issues related to licensing, privacy and ethics.

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DataScientia’s fourth aim is the social infrastructure, that is, a community centered around the understanding of data, their development and their exploitation, both social and economic.

Fausto Giunchiglia - Coordinator DataScientia

DataScientia Structure

DataScientia is a non-profit organization whose goal is to build a more inclusive society with a higher quality of life, enabling social innovation supported by data-centric AI. DataScientia works in strict collaboration with its partner Universities. Universities support DataScientia in its lifelong educational programs, in the development and support of the local communities as well as in its research and innovation activities. DataScientia is a global organization with many local nodes which interact closely with the local universities and communities, and with one global node coordinating the activities of the local nodes. The global node provides the supporting infrastructure, as needed. It acts under the strategic guidelines defined by the governance. The local nodes participate in the governance of DataScientia.

How do we sustain ourselves?

DataScientia sustains itself based on the revenues generated by the technological and social innovation it enables, mainly focused on its own end-to-end data management process. All DataScientia economic revenues must follow a process consistent with its internal ethical standards. Revenues must come from activities that generate meaningful social innovation.

DataScientia has two primary sources of income.

01

The first is providing services enabled by the data and technologies developed by DataScientia. Each type of data enables different data-specific services.

02

The second is the support of the start-up and growth of highly innovative companies which take advantage of their own technology.

DataScientia supports the collection, sharing and usage of person-centric data as a common good, in the interest of people and society at large. 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 that allows us to interpret and compose the data we collect.

Person-centric data will be used towards the generation and dissemination of knowledge concerning individuals, society, and the world, as perceived and articulated by people. We want to analyze and comprehend the variances in interpretation. The aim is to uncover the deeper unity that underlies diversity, allowing us to delve beneath surface differences.

We all create and use our own mental models of the world. Perception creates it, language allows us to share its description with other people, thus causing its objectivation, and knowledge is what we learn about it by observing what repeats itself through change, as described by language.

Our 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, the Internet has exponentially increased the possibility of exposure to new people, speaking different languages, and holding different knowledge, cultures and traditions. On the 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 how to bridge the gap between opportunities and difficulties is critical to sustainable AI innovation. We need to find a way to go beyond the current, only technology-driven, person, society and diversity-unaware approach to data-driven AI innovation.
Person-centric data will be used towards the generation and dissemination of knowledge concerning individuals, society, and the world, as perceived and articulated by people. We want to analyze and comprehend the variances in interpretation. The aim is to uncover the deeper unity that underlies diversity, allowing us to delve beneath surface differences.

We want to analyze and comprehend the variances in interpretation. The aim is to uncover the deeper unity that underlies diversity, allowing us to delve beneath surface differences. We want to enable a process where anybody can increase their awareness and active participation in the development of AI technological innovation. Technological innovation should be driven by social innovation, and citizens should proactively participate in the definition of the social innovation agenda.
Person-centric data will be used towards the generation and dissemination of knowledge concerning individuals, society, and the world, as perceived and articulated by people. We want to analyze and comprehend the variances in interpretation. The aim is to uncover the deeper unity that underlies diversity, allowing us to delve beneath surface differences.

The Four Pillars

01

Citizen Science

Help users share and discover ideas, contributions, and needs around AI and data.

The DataScientia Community Platform

Personal member pages View public profiles and explore community expertise. Discover or start projects Create and manage your personal professional identity. Moderated discussion groups Set up institutional pages for organizational visibility.

DataScientia News

Sign up to DataScientia newsletter to keep updated with the latest developments, insights, and announcements.

Events & Meetups

Participate in talks, workshops, and community-driven events.

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Information

Share curiosity, needs, and ideas.

We provide tools for people to express and share what they know, want to know, and what matters to their communities.

02

Education

Build skills through courses, workshops, tutorials, and guided learning resources.

Learning Opportunities

Courses & workshops Join structured learning activities on data, AI, and research methods. Micro-modules Access short learning units designed for flexible participation. Certificates & badges Gain recognition for completed learning and community contributions.

Seminars & Tutorials

Take part in expert-led sessions that introduce practical tools, concepts, and emerging research directions.

Learning

Grow skills through shared knowledge.

Education activities help members understand, use, and contribute to diversity-aware data and AI resources.

03

Research

Support interdisciplinary research through shared data resources, methods, and collaboration spaces.

Research Collaboration

Shared resources Access curated datasets and language resources for research use. Project participation Join ongoing research activities led by institutions and partners. Research visibility Showcase contributions, outputs, and expertise through community profiles.

Responsible Data Use

Data access is governed through clear agreements, consistent schemas, and research-oriented distribution processes.

Research

Collaborate through trusted resources.

Researchers can discover, access, and contribute to community-supported data and knowledge resources.

04

Innovation

Enable partners and community members to contribute to innovation activities connected to data, AI, and open infrastructure.

Innovation Activities

Data challenges Host or participate in competitions, datathons, and practical challenges. Open infrastructure Support access to reusable platforms, tools, and open-source resources. Partner-led projects Partners may host, lead, or support innovation-related activities.

Recognition & Impact

Community members gain visibility through profiles, while partner work is cited, credited, and communicated through DataScientia channels.

Innovation

Turn ideas into shared activities.

Innovation connects partners, researchers, and communities through challenges, services, tools, and collaborative projects.

Ethics and privacy

At DataScientia, our utmost priority is safeguarding our users’ privacy. Consequently, we have established the following policy to
inform you about our handling of your personal information. This policy outlines the types of information we collect from you, how we use it, and the circumstances under which we may share it with third parties.


Please be aware that this policy exclusively pertains to DataScientia and does not apply to any other companies, organizations, or websites that we may link to. It’s important to note that these external entities may have significantly different privacy provisions from ours.


Therefore, we strongly recommend reviewing the privacy policy of any other website you visit, whether you access it through our site(s) or independently. This will help you understand their policies and how they collect, use, and share your personal information.

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