Imagine if the internet's search bar wasn't owned by a few giant companies that track everything you do. This effort creates a community-driven way to find information and connect devices without giving up your privacy. It's like building a public library for the digital age where the rules are transparent and everyone can contribute.
Companies rely on opaque, third-party search platforms that compromise data privacy and create technological dependency. This makes it difficult to search internal IoT data or sensitive industry records without risking data leaks.
A portfolio of 51 open-source projects including privacy-aware search engines, misinformation detectors, and domain-specific search tools for health and food.
If you are a health data cooperative dealing with sensitive patient records and strict privacy laws — this project developed domain-specific search services in health that allow secure data discovery without relying on non-transparent global platforms.
If you are a smart factory operator dealing with thousands of connected sensors in an Industry 4.0 setting — this project developed new ways to search and represent heterogeneous IoT data sources to make sense of complex machine environments.
If you are a food supply chain auditor dealing with fragmented traceability data — this project developed domain-specific search services in food that help find and interpret trustworthy information across distributed data lakes.
Based on available project data, all funded projects are open source, meaning the core code is available without proprietary licensing fees.
The project funded 51 different projects, with over 75 percent delivering deployable code, suggesting a high capacity for practical implementation across various scales.
All funded projects are open source, ensuring that the resulting technologies are transparent and accessible for further development.
The project focuses on privacy-aware search engines and ethical AI to reduce dependency on opaque business models that often violate privacy and trust.
Based on available project data, the tools are designed to handle heterogeneous sources including IoT, semantic data, and multimedia, making them adaptable to different digital infrastructures.
The consortium is lean, consisting of 6 partners across 4 countries. While led by Aarhus Universitet, it has a strong entrepreneurial lean with 4 SMEs and a 17% industry ratio, focusing more on ecosystem activation and mentoring than traditional corporate R&D.
Contact Aarhus Universitet regarding the NGI Search open-source portfolio.
Explore the 51 open-source search implementations to find a fit for your data infrastructure.
