Query
Data is fundamental to critical business decisions. However, when trying to leverage their data, organisations can be hindered due to incosistent terminology, scattered data silos and poor integration.
Knowledge graphs are powerful in addressing these challenges head on. CMCL deploy semantic knowledge graphs to unify definitions, bridge silos and foster collaboration across departments, organisations and sectors.
Knowledge graphs have proven to be powerful tools in many industries, and are rapidly growing in uptake. They are fundamental to our work with The World Avatar™. They offer a comprehensive way to represent the complex relationships that make up our world, and as such they underpin much of the ecosystem.
“If you want to model the full diversity of the real world, you need something like a graph to really do that”
– Ora Lassila, Semantic Web Pioneer
CMCL have developed deep expertise applying knowledge graphs to a range of challenges in a wide variety of sectors, unlocking intra- and inter-sector queries.
Knowledge graphs are Consistent Unifying Flexible
Knowledge graph advantages
Flexibility
CMCL can export critical data in a range of formats, from json to csv. In addition, due to our experience in ontologies, our solutions are easily extensible via the adoption of new schemas and taxonomies.
Inference
CMCL’s solutions support inference. As a simple example, a knowledge graph could store the fact that CMCL is based in Cambridge, and separately that Cambridge is in the UK. It can then infer that CMCL is based in the UK.
Scalability
When scaling across applications with many complex interactions, traditional databases would increasingly require an impractical number of queries. CMCL’s solutions scale to capture new actors and concepts efficiently and effectively.
Despite these advantages, we appreciate that changing from legacy workflows and operations is not trivial due to vendor lock-in and resource requirements. For that reason, we deploy our solutions on top of existing relational/graph databases and pipelines, minimising disruption to organisations and allowing business-as-usual operation.
Beyond knowledge graphs
Knowledge graphs have rapidly gained popularity in both enterprise applications and research fields. They are highly useful for integrating diverse information sources and building common understanding. Dynamic knowledge graphs, with rapidly changing data, build upon this capability. However, there is a serious need for robust methods to deal with complex interdependencies and information provenance.
To solve these issues, CMCL have helped to develop the Derived Information Framework.
The Derived Information Framework (DIF), developed as part of The World Avatar™ is a framework which CMCL uses to extend the capabilities of knowledge graphs. We leverage it to go beyond traditional knowledge graphs, seamlessly managing complex information interdependencies and provenance.
The framework handles these issues, combining knowledge graphs with software agents. It records provenance, tracking when and how pieces of information are obtained from others, instilling confidence in the validity of data and ensuring values are up-to-date. It allows for autonomous workflows which propagate changes/updates to data through the knowledge graph. Ripples through the triples!
Features
Live
Data is kept up to date, avoiding issues with mismatched caching in complex dynamic knowledge graphs.
Autonomous
Software agents autonomously cascade and integrate data, co-ordinated via an overarching architecture.
Tracked
Records of data provenance are automatically generated and marked up by agents via an ontology.
The Derived Information Framework has the power to solve complex challenges where information is rapidly changing and provenance is key. It is already currently delivering results within the banking, smart cities and chemicals industries and we are continuously discovering novel applications.
More information is available via The World Avatar™ website. Alternatively, get in touch with us directly.