Do you remember the connecting-the-dots puzzles from your childhood? Dinosaur or daisy — gradually transpiring from the jumble of dots and numbers as you’re counting upwards, connecting the lines. At gluoNNet, we are working on a software solution for connecting-the-dots puzzles of some sorts, still trying to make sense of a (much bigger) jumble.
Our solution is called ‘Headron’, gluoNNet’s analytical engine. The Headron Analytical Engine will less likely reward its user with a silhouette of an animal or object, but it can help them to see the bigger picture, nevertheless. Its visualisations have the potential to reveal surprising relationships in the data. The data-visualisation method depicts the data (nodes) and sets them into respective relations (connecting lines), based on metadata. The innovative aspect of Headron’s relational approach is its user friendliness. With its simple and intuitive ways of interaction the programme empowers users of all skill levels to make the most of their data.The fully functional beta version of the engine will be launched in early 2022.
The Headron Engine will eventually be integrated into ‘Sunflower’, a first-of-its-kind digital regulation system for the aviation industry gluoNNet co-develops. This innovative system aims to allow better management of aviation-related issues that require regulatory oversight, such as quickly verifying information, speeding up approval procedures, and stopping actions that are illegal or deceptive. Once the Headron Engine has been successfully integrated and sufficiently tested, the gluoNNet developers will work on a more general application.
The Headron visualisation can be applied to various purposes. Financial authorities could track the money flow among publicly registered companies in their purview. In another scenario from the public sector, authorities could benefit from the visualisation method in applying it to legal enforcement, highlighting correlations between committed crimes, eventually helping solve them. Furthermore, the Headron project can support humanitarian endeavours. For instance, it could help analyse and visualise the sanitation situation in third and second world countries, flagging up areas that need more attention from the government or humanitarian agencies.
“The application purposes are vast and manifold. The engine’s design allows running different sets of data from different domains and helps to find connections among those different domains. A universal instrument for data analysis that can be easily implemented into existing systems,” says Richárd Forster, the lead developer of the project.
Of course, the Headron Engine can also analyse scientific data. The underlying structure of the Headron visualisation is inspired by particle-track reconstruction algorithms developed by scientists and engineers at the European Laboratory for Particle Physics (CERN).