AI-DAPT brings forward a data-centric mentality in AI, that is effectively fused with a model-centric, science-guided approach, across the complete lifecycle of AI-Ops, by introducing end-to-end automation and AI-based systematic methods to support the design, the execution, the observability and the lifecycle management of robust, intelligent and scalable data-AI pipelines that continuously learn and adapt based on their context. AI-DAPT will design a novel AI-Ops / intelligent pipeline lifecycle framework cross-cutting the different business, legal/ethics, data, AI logic/models, and system requirements while always ensuring a human-in-the-loop (HITL) approach across five axis: “Data Design for AI”, “Data Nurturning for AI”, “Data Generation for AI”, “Model Delivery for AI”, “Data-Model Optimization for AI”. AI-DAPT will contribute to the current research and advance the state-of-the-art techniques and technologies across a number of research paths, including sophisticated Explainable AI (XAI)-driven data operations from purposing, harvesting/mining, exploration, documentation and valuation to interoperability, annotation, cleaning, augmentation and bias detection; collaborative feature engineering minimizing the data where appropriate; adaptive AI for model retraining purposes. Overall, AI-DAPT aims at reinstating the pure data-related work in its rightful place in AI and at reinforcing the generalizability, reliability, trustworthiness and fairness of Al solutions. In order to demonstrate the actual innovation and added value that can be derived through the AI-DAPT scientific advancements, the AI-DAPT results will be validated in two, interlinked axes: I. Through their actual application to address real-life problems in four (4) representative industries: Health, Robotics, Energy, and Manufacturing; II. Through their integration in different AI solutions, either open source or commercial, that are currently available in the market.

ACCOMPLISH aims at increasing the readiness of enterprises of any size to face an era of unprecedented regulatory scrutiny by simplifying, integrating and automating compliance in their data/AI operations, their data/AI assets, their solutions and eventually their overall organisations. ACCOMPLISH will deliver a novel AI-based compliance and certification framework cross-cutting the regulatory/legal, environmental, cybersecurity and business/industry-specific compliance perspectives to modernise, automate and trace the compliance and certification processes with the help of open-source, well-defined and extensible compliance policy models while always ensuring a human-in-the-loop (HITL) approach explaining the compliance requirements and results, as well as proactively alerting about any potential risks/violations. Through the ACCOMPLISH Compliance Digital Passport, the previously “static” compliance and certification assessments will be transformed into up-to-date compliance proof that effectively promotes transparency and accountability for any interested stakeholder. ACCOMPLISH shall also deliver inherently-compliant data economy enablers for Data/AI operations, as reliable mechanisms to design, execute, and trace/observe the data and AI/ML pipelines, as well as to monitor/control their outputs (in terms of datasets, ML/DL models, analytics results). In order to demonstrate the actual innovation and added value that can be derived through the ACCOMPLISH advancements, the ACCOMPLISH results will be validated: I. Through their actual application to address real-life problems in four representative industries that are characterised by a varying maturity level of data/AI operations and compliance: (a) Energy, (b) Automotive, (c) Robotics & Manufacturing, and (d) Aviation; II. Through their integration in different digital solutions, either open source or commercial, to showcase their application within the established data spaces and/or AI market landscape.