Imagine trying to find a needle in a haystack, but the haystack is made of messy, locked files from different government offices. This project builds a digital bridge that connects these files and uses smart software to spot red flags and cheating. It turns chaotic paperwork into a clear map that helps leaders make honest, evidence-based decisions.
Public administrations struggle with fragmented, non-digitized data, making it nearly impossible to detect corruption and fraud during emergency spending. This lack of data harmony prevents evidence-based decision-making.
A set of secure APIs, data connectors, and ML operations tools. It also includes 10+ harmonized datasets and a Minimum Viable Product (MVP) for fraud detection.
If you are a software provider dealing with fragmented government archives — this project developed secure connectors and APIs that integrate with 6+ Common European Data Spaces to automate fraud detection.
If you are a consultancy dealing with lack of evidence in corruption cases — this project developed a way to fuse and harmonise 10+ high-quality datasets that make evidence-based decision-making possible.
If you are an analytics firm dealing with poor quality public data — this project developed methods for generating synthetic data and anonymization techniques to improve real-world data quality for ML operations.
Based on available project data, the EU contribution is EUR 8,999,550, but specific commercial pricing for the resulting tools is not listed.
Yes, the project specifically focuses on developing scalable technologies for big data management and Machine Learning operations to handle complex public data sources.
Based on available project data, licensing terms are not specified, though the project aligns with the European Data Act and European Strategy for Data.
The project builds interoperable and secure connectors and APIs designed to enrich 6+ Common European Data Spaces.
The project runs from 2024-01-01 to 2026-12-31, with a Minimum Viable Product (MVP) defined for delivery at month 12.
The consortium is heavily weighted toward practical application, with 12 industry partners (39% ratio) and 7 SMEs, balancing the academic input from 3 universities and 7 research centers. The inclusion of 9 'other' entities, including 3 NGOs and 7 public end-users across 11 countries, ensures the tools are tested against real-world public administration needs.
Contact ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXKS (REC) in Greece
Contact us to explore licensing opportunities for the CEDAR fraud-detection APIs.
