– Ireland’s Centre For AI

Projects

UPCAST Project

Project Status: Live Project

EU Programme: HORIZON.2.4 – Digital, Industry and Space

Start Date: 01/01/2023

Finish Date: 31/12/2025

Project Website: https://www.upcast-project.eu/

 

This project consortium is made of 16 partners from 9 countries from across the European continent.

The high-level objective of UPCAST is to design and deploy a set of universal plugins for data sharing, monetisation and trading platforms that enable actors in common European data spaces to collaboratively negotiate, improve and enforce data sharing contracts automatically, providing dynamic fair pricing mechanisms while implementing energy-efficient data exchange, ensuring privacy, confidentiality and legislation compliance and adhering to ethical and responsibility guidelines.

UPCAST supports the deployment of Common European data spaces by consolidating and acting upon mature research in data management, privacy, monetisation, exchange, and automated negotiation. It considers environmental efficiency and ensures compliance with EU and national initiatives, AI regulations, and ethical procedures, promoting sustainable and lawful data practices.

CeADAR are working on the following plugins:

Environmental Impact Optimiser Plugin

Responsible partner: CeADAR Ireland

This plugin aims to reduce carbon emissions by optimising data processing workflows. It estimates energy costs for data storage and processing, identifies and explains the factors affecting energy consumption using explainable AI techniques (XAI), and helps comply with EU regulation. It also provides real-time monitoring of energy usage during data processing

Pricing Plugin

Responsible partner(s): LSTech & CeADAR Ireland

This plugin aids data providers in setting fair prices for their data products and helps data consumers estimate costs for data acquisition. It can also be used to assess the pricing of customised data products, making it a valuable tool for informed decision-making in data trading platforms. Using explainable AI techniques (XAI), the plugin also provides transparency by identifying the key factors influencing the price.