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WHITE LABEL CONSULTANCY

WHITE LABEL CONSULTANCY APS
Country: Denmark

WHITE LABEL CONSULTANCY

3 Projects, page 1 of 1
  • Funder: European Commission Project Code: 101094905
    Overall Budget: 3,000,000 EURFunder Contribution: 3,000,000 EUR

    AI4Gov is a joint effort of policy makers, public institutions / organizations, legal, Social Science and Humanities and Big Data/AI experts to unveil the potentials of Artificial Intelligence (AI) and Big Data technologies for developing evidence-based innovations, policies, and policy recommendations to harness the public sphere, political power, and economic power for democratic purposes. The project will also uphold fundamental rights and values standards of individuals when using AI and Big Data technologies. Hence, the project aims to contribute to the promising research landscape that seeks to address ethical, trust, discrimination, and bias issues by providing an in-depth analysis and solutions addressing the challenges that various stakeholders in modern democracies are faced with when attempts are made to mitigate the negative implications of Big Data and AI. In this direction, the project will introduce solutions and frameworks towards a two-fold sense, to facilitate policymakers on the development of automated, educated and evidence-based decisions and to increase the trust of citizens in the democratic processes and institutions. Moreover, the project will leverage the capabilities of state-of-the-art tools for providing un-bias, discrimination-free, fair, and trusted AI. These tools will be validated in terms of their ability to provide technical and/or organisational measures, causal models for bias and discrimination, and standardized methodologies for achieving fairness in AI.

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  • Funder: European Commission Project Code: 101070279
    Overall Budget: 8,808,060 EURFunder Contribution: 8,808,060 EUR

    Mobility in the urban and maritime domains hugely impacts the global economy, generating data at high rates from an increasing number of moving objects. Management of the complete lifecycle of such data implies that trustworthy and privacy-preserving infrastructures need to be put in place, so that reliable and secure data operations can be provided. Meanwhile, the mobility data exploitation has still a wide potential due to the emerging applications and the environmental footprint caused by mobility (e.g., carbon emissions, energy consumption). Motivated by these pressing needs, MobiSpaces delivers an end-to-end mobility-aware and mobility-optimized data governance platform with key differentiating factor that the outcomes of mobility analytics will be utilized to optimize the complete data path, in terms of efficient, reliable, secure, fair and trustworthy data processing. MobiSpaces promises the extraction of actionable insights from ubiquitous mobile sensor data and IoT devices in a decentralized way, offering intelligent transportation services, enforcing privacy constraints at the expected point of action. XAI techniques will be applied at the level of data management and machine learning, supporting the creation of comprehensive and interpretable prediction models, while all the research outcomes will be validated through five use cases: 1) intelligent public transportation services in urban environments, 2) intelligent infrastructure traffic sensing for smart cities, 3) vessel tracking for non-cooperative vessels, 4) decentralized processing on-board of vessels, and 5) enhanced nautical maps via crowdsourced bathymetry vessels data. These actions will be continuously adapted and monitored for their environmental sustainability, whereas MobiSpaces will create a widely accepted standard of data processing and analytics, alongside a data-rich ecosystem providing trustworthy and actionable data that is vital for enabling the growth of the EU digital economy.

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  • Funder: European Commission Project Code: 101080718
    Overall Budget: 9,998,710 EURFunder Contribution: 9,998,710 EUR

    During the last decades, overweight & obesity rates have reached epidemic proportions across EU. Prevalence in childhood is particularly alarming, resulting in psychological impacts & increased risks for NCDs. However, although obesity-related research has provided interesting results, several issues arise due to the lack of meta-reviews & the nature of data collected. To address this, Bio-Streams aims on supporting the optimal use (and re-use) of health data (e.g. biological, demographic, epigenetic, etc.) to generate metadata/knowledge and provide new evidences, methodologies & tools for: a) creating and deploying the Bio-Streams Biobank that will act as a scientific platform for research in obesity and better diagnostic and therapeutic approaches;b) understanding the transition from metabolically healthy to unhealthy, preventing under age obesity; c) designing better strategies to educate & empower young citizens for weight self-management; d) coordinating authorities & policy makers to develop cross-sectoral solutions for health promotion & under age obesity prevention. Specifically, Bio-Streams delivers a dedicated under age obesity biobank providing real-world health data (including biospecimens, anthropometrics, behavioural and cost data) from retrospective and prospective sources, while taking into account efficient data harmonisation and standardisation principles, transforming data valorisation towards under age obesity prevention and future research. Moreover, the Bio-Streams framework for data handling, provides robust and transparent methodologies for operational procedures (data infrastructures), analysis and reporting (via meta-reviews and AI-based Apps/components, evaluated via 12 multi-site pilots (7 clinical and 5 schools)), citizen awareness and lifestyle alteration, delivering obesity prevention guidelines, knowledge generation while fostering considerable opportunities for regional and national health authorities/policymakers.

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