Imagine a digital library where every item doesn't just have a label, but a full biography that explains its history, who owns it, and the ethical rules for using it. It's like adding a smart, multi-layered digital passport to museum objects so anyone can use them legally and respectfully. This system uses AI to automatically organize these complex details across different languages.
Cultural institutions and creative companies struggle to manage the ethical and legal complexities of reusing digital heritage data. Current systems often lack the nuanced context and provenance needed for responsible commercial exploitation.
An open library of AI-driven software components for metadata enrichment and scalable infrastructures for collaborative data annotation.
If you are a digital content agency dealing with complex copyright and ethical usage of historical images — this project developed AI-driven software components that automate metadata enrichment. This ensures your assets are legally compliant and ethically sourced for commercial use.
If you are an immersive experience provider dealing with the need for accurate historical data for Digital Twins — this project developed multidimensional knowledge graphs. This allows you to build highly accurate, context-aware virtual environments based on verified heritage data.
If you are a CMS vendor dealing with outdated metadata standards for museums — this project developed an open library of Semantic Web components. These can be integrated into existing Collection Management Systems to provide advanced, multilingual data extraction.
Based on available project data, the project focuses on open source and open access software components, but specific commercial pricing is not listed.
Yes, the project specifically introduces scalable infrastructures designed to support large-scale crowdsourcing and citizen science campaigns.
The project embeds IPR and data provenance into the descriptions of digital objects and utilizes open source software components to ensure sustainable reuse.
The AI-driven software components are designed for seamless integration into existing Collection Management Systems.
The project runs from 2026-01-01 to 2029-06-30, indicating that final validated solutions will be available toward 2029.
The consortium is well-balanced for technology transfer, consisting of 17 partners across 8 countries. With 5 SMEs and 5 industrial partners (a 29% industry ratio), there is a strong commercial presence to ensure the software components meet market needs, while 9 university and research entities provide the necessary AI and Semantic Web expertise.
Contact ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA
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