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International projects source: SICRIS

DATAPACT: COMPLIANCE BY DESIGN OF DATA/AI OPERATIONS AND PIPELINES

Keywords
Data, AI pipelines, compliance, toolbox
Organisations (1)
0106  Jožef Stefan Institute
Abstract
DataPACT develops novel tools and methodologies that enable efficient, compliant, ethical, and sustainable data/AI operations and pipelines. DataPACT delivers a transformative approach where compliance, ethics, and environmental sustainability are not afterthoughts but foundational elements of data/AI operations and pipelines. DataPACT contributes to the design, implementation, and management of data/AI operations and pipelines by embedding compliance, privacy, and environmental sustainability at their core design. It delivers compliance by design for data/AI operations and pipelines by developing innovative technical tools (DataPACT Compliance Toolbox) and tool-supported methodologies (DataPACT Compliance Framework) for compliance assessment and realization of data/AI pipelines designed, deployed and executed through a set of pipeline management tools and techniques (DataPACT Compliance-aware Data/AI Pipeline Toolbox). DataPACT validates its core results through a strong selection of seven complementary use cases offered by SMEs, large companies, and public sector organizations in relevant areas, including media and entertainment, healthcare, smart cities, law enforcement and security, customer relationship management, manufacturing, and public data. DataPACT helps them ensure straightforward and cost-effective compliance with existing and emerging regulations and guidelines, shorter time-to-market for compliant data solutions, fair and unbiased data-driven systems, respect for privacy and other fundamental rights, and lower and transparent environmental impact for intensive data/AI pipeline operations. DataPACT gathers a balanced consortium of 18 partners from 16 countries, consisting of two large companies, two public sector organizations, four SMEs, two research centers, and seven universities, covering relevant aspects related to legal, ethical, social, environmental, and technical compliance of data/AI operations and pipelines.
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