Imagine trying to organize a giant puzzle where the pieces are buried in different layers of earth across several countries. Instead of taking messy notes and fixing them later, this tool lets researchers record everything digitally and accurately right on the spot, even without internet. It turns these scattered notes into a smart, connected map that makes finding and linking information instant.
Field researchers spend excessive time manually cleaning and curating data after fieldwork. Current digital tools often fail in remote areas due to lack of power and connectivity.
A knowledge graph infrastructure, AI-powered bibliography tools, 3D documentation capabilities, and offline/online connectivity protocols.
If you are a digital archiving firm dealing with fragmented site records — this project developed knowledge graph infrastructure that organizes stratigraphic and spatial data. This reduces the time from discovery to publication by automating data structuring.
If you are a consultancy dealing with unexpected archaeological finds during construction — this project developed 3D field documentation and offline-ready tools. This allows for rapid, accurate recording of site layers to avoid project delays.
If you are a software provider dealing with unstructured field data — this project developed AI-powered tools for creating annotated bibliographies. This enables the creation of FAIR-compliant datasets for specialized research sectors.
Based on available project data, all tools will be open-source, meaning there is no purchase price for the software itself.
The project uses a 'works-everywhere' solution designed for diverse conditions and is being validated across 7 different international case studies, suggesting high scalability for field operations.
The project emphasizes open science and open-source tools, while maintaining data control and ownership within EU-based institutions to support strategic autonomy.
It utilizes variable connectivity protocols that allow for seamless offline and online work, ensuring data is not lost in remote areas.
The project period runs from 2025-10-01 to 2029-03-31, indicating that full tool validation will occur over these four years.
The consortium is heavily research-oriented, featuring 10 research organizations and 6 universities. However, it includes 3 industry partners (including 2 SMEs), providing a 14% industry ratio that ensures the tools are developed with practical, real-world application in mind across 13 different countries.
Contact the Consiglio Nazionale delle Ricerche (CNR) in Italy
Contact us to track the development of these open-source AI tools for field data.
