Graphql Adopted to Help Application Developer Access Knowledge Graphs
Ontotext Platform 3.0 features GraphQL interfaces to make it easier for application developers to access knowledge graphs without tedious development of back-end APIs or complex SPARQL. The underlying Semantic Object service implements an efficient GraphQL to SPARQL translation optimized for GraphDB, as well as a generic configurable security model.
In the last two decades, Ontotext has had the chance to work for enterprises with very advanced knowledge management capabilities – from BBC and FT to S&P and AstraZeneca.
“We helped them push the frontiers and identify even more meaning across diverse databases and massive amounts of unstructured information. We learned what the challenges are, and what tools are needed to reduce complexity and technology risk and make the development of such solutions more efficient. Ontotext Platform 3.0 is the next major release streamlining the development of solutions around enterprise knowledge graphs, integrating internal knowledge with external reference data.” – Atanas Kiryakov, CEO, Ontotext
Ontotext Platform 3.0 features significant technology improvements to enable simpler and faster graph navigation. The new GraphQL user-centric API exposes an additional interface to start consuming complex information much faster at a lower cost. Business analysts (BAs) and subject matter experts (SMEs) are in charge to define Semantic Objects as specific views, abstracting developers from the complexity and peculiarities of the knowledge graph. Based on these definitions, the Semantic Object service implements an efficient GraphQL to SPARQL translation optimized for GraphDB – Ontotext’s semantic graph database engine. This service implements a generic configurable security model, enabling access control without back-end development.
“The Ontotext Platform and knowledge graphs help you organize all your enterprise metadata, reference and master data. You can efficiently maintain it up-to-date with the existing silos or third party data providers, as well as lower the implementation costs by delivering ready-to-use patterns. The Platform and its GraphQL API query language help you start implementing the application directly on top of the ontology model.” – Vassil Momtchev, CTO, Ontotext
The Platform is cloud-agnostic and supports an easy extension with custom services packaged as Docker containers. It includes operational dashboards for service monitoring, efficient metric collection services, alerting, as well as all other functionalities necessary for delivering high-availability business-critical production services.