GraphIK has three main scientific directions:
decidability, complexity and algorithms for problems in languages corresponding to first-order logic fragments;
the addition of expressive and non-classical features (to
the first-order logic languages studied in the first direction)
with a good expressivity/efficiency trade-off;
the integration of theoretical tools to real knowledge-based systems.
From an applicative viewpoint, two themes are currently privileged:
knowledge representation for agronomy, the final objective being a knowledge-based system to aid decision-making for the quality control in food processing.
data integration and quality improvement, specifically for document metadata.