Our research on dynamic Knowledge Graph technology forms the basis of our mission to solve complex industrial problems spanning across multiple sectors. The KG technology enables:

  • the ability to account for the dynamic nature of data and information
  • interoperability between heterogeneous data and software
  • building digital twins and interactions between them say, via smart contracts
  • live representation of the aspects of real world that can aid in scenario analysis and cross-domain decision support
  • knowledge management while taking into account the context of the data

Knowledge Graphs have come into prominence to solve the problem of data and information silos, while offering modularity and scalability. Our KGs leverage advanced agent-based operation and ontology representations, thus bringing automation and semantic context to machine-assisted solutions for the problems at hand. See our recent preprint that introduces a dynamic knowledge graph approach to digital twins, implemented using technologies from the Semantic Web.

Being built this way, Knowledge Graphs introduce a platform to seamlessly connect human, machines, and agents, making them able to infer new knowledge from large sets of available data. An interesting example of this is the concept of Cyber Physical Systems (CPS).


Cyber-Physical Systems

An emerging aspect of digitalisation deals with ensuring seamless machine-to-machine communication with little or no human intervention. This entails accounting for data semantics, standardisation and interoperability that are enabled via Ontology Engineering and AI. Once championed, such developments pave the way to harness the real benefits of connectivity through Internet of Things (IoT) and enable us to actively pursue use cases across multiple domains such as automotive, materials, energy mix, urban design/planning and environment that could not be perceived consistently before.

Alongside our internal efforts, this is being catalysed via involvement in collaborative research efforts, as well as engagement with initiatives such as the C4T programme of CARES at the University of Cambridge, and the “National Digital Twin” (NDT) programme at Centre for Digital Built Britain (CDBB).

One of the examples of our ongoing research is Marie, our chemistry KG with a natural language processing (NLP)-based chatbot for interaction. You can access the Marie chatbot here.

You can also contact us if you want to know more about the Knowledge Graph technology at CMCL, Cyber Physical Systems development or semantic interoperability.