– Ireland’s Centre For Applied AI

Projects

UPCAST Project

Project Status: Completed

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/

 

CeADAR is one of 16 partners in the UPCAST project and leads the Environmental Impact Optimiser Plugin, while also contributing to the Pricing Plugin.

The UPCAST consortium brings together 16 partners from 9 European countries to develop universal, trustworthy, transparent and user-friendly plugins for data sharing, monetisation and trading platforms. The project is designed to support actors in Common European Data Spaces by enabling automated data sharing and processing agreements, dynamic pricing, privacy and confidentiality safeguards, and compliance with legal and ethical requirements.

UPCAST supports the deployment of Common European Data Spaces by building on research in data management, privacy, monetisation, data exchange and automated negotiation. It also places a clear emphasis on environmental efficiency, lawful data exchange and responsible 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.