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The SURROUND Ontology Platform

Solutions for addressing complex knowledge problems

SURROUND’s solutions combine semantic data enrichment and machine learning (ML), applying open standards.

Our vision is to solve the world’s most complex problems ethically, to achieve real-world outcomes for people and society. 

Our mission is to achieve this through sense-making by linking knowledge across policy, planning, and information holdings to improve organisational performance.

Other foundations that support SURROUND’s technology offerings are

Comparable eXplainable Reasoning (CXR) provides the ability to use different types of reasoning styles which can be cross-compared to optimise the results produced. CXR uses contextual metadata and data from either SOP or across the data fabric to provide knowledge insights. In addition, CXR enables the reshaping of metadata and data within SOP. Ensembles of algorithms are employed to analyse and parse information in these components. These components can also be employed to parse and transform semantic information from SOP to meet a particular information consumption requirement.

Discrete Global Grid System (DGGS) Converter (DGGSC) the DGGS provides a canonical view of geospatial data as a set of region points. The DGGSC transforms latitude and longitude into two-dimensional region points. It also converts latitude, longitude, and elevation into three-dimensional region points. The DGGSC can also perform these transformations in the opposite direction. When combined with the dimension of time in the SOP, the result enables the ability to reason over the rate of change over space and time. This capability is very useful in predicting future scenarios such as the impacts of natural disasters, and concepts such as long-term unemployed people or community health.

The SURROUND Ontology Platform enables and underpins numerous capabilities and software robots, integrated and working together or stand-alone

The SURROUND Ontology Platform (SOP) is a proven industrial-strength platform that enables all knowledge sources to be connected and queried both textually and/or visually. 

The SOP leverages the key concept of linking knowledge assets across a data fabric. This enables the user to ask complex questions and receive answers, while having the ability to trace the derivation of the answer. It presents these knowledge assets via connected knowledge graphs, thereby creating linked knowledge graphs that can be used as one  integrated knowledge repository. 

Leveraging the SOP, our product suite can

  • Provide knowledge insights to generate scenarios, predict outcomes, and explain recommended decisions 
  • Provide answers to complex questions (posed using natural language queries)
  • Enable users to receive answers to questions using faceted searches across information (the connected data fabric)
  • Classify and visualise knowledge and information even when the data fabric changes, using pre-set and dynamic rules 
  • Create multiple relationships between data assets to analyse and visualise testable scenarios relative to specific situations, using techniques such as trade-off analysis and impact analysis (Markov backward-chaining)
  • Automate processes around data lineage, data management, metadata and data governance, exception handling/reporting, and publishing data assets as semantic assets (thereby enabling these assets to be reused by human- and machine-driven processes)
  • Connect to multiple datasets (both internal and external) using a high-performance, industrial-strength API gateway, dedicated connectors, generalised connectors (e.g. JDBC), endpoints, and scripted integration