Cowl: pushing OWL 2 over the Edge

The ever-complex information environments and rapidly expanding data volumes of the modern digital infrastructure demand efficient knowledge organization and retrieval techniques. The Semantic Web initiative has defined principles and technologies, such as the Resource Description Framework (RDF) and the Web Ontology Language (OWL), to create structured and semantically rich Knowledge Graphs. Current OWL toolkits, however, are largely unsuitable for resource-constrained platforms, hindering development of truly ubiquitous knowledge-enabled frameworks and applications. This paper introduces Cowl, an OWL manipulation software designed for a wide spectrum of devices, ranging from workstations to embedded systems with stringent resource limitations. Its architecture, optimizations, and novel processing techniques are detailed, emphasizing computation efficiency and minimal memory use, and providing actionable design principles for future toolkit developers. Comparative experiments reveal state-of-the-art performance and memory efficiency, and its versatility is demonstrated through a comprehensive evaluation on a popular microcontroller platform. Finally, a case study illustrates its usefulness in a knowledge-enabled smart city context.