Data fusion is the process of integrating multiple data and knowledge points about the same real-world object into a consistent, accurate, and useful representation. Fused data is more informative and synthetic than the original inputs.

Movia Source Handlers and Movia Artifact Processors are general-purpose interfaces between Movia and common data sources such as: documents, reports, email, relational databases, NoSQL databases, XML, etc. These data connectors consume low-level data, normalize the data to the cognitive models used in the current Movia application, and conflate the information to the most useful subset desired.

Movia can consume and fuse unstructured content (documents, reports, email, text, web pages), semi-structured data (CVS, XML, RDF, etc.) and structured databases (XMS, relational databases, NoSQL stores, etc.).

In all cases, data is:

  • converted to semantic facts, entities and relationships
  • related to the other information in the Graph
  • classified, and
  • associated with its provenance.

Information and knowledge is represented in Movia by a layered ontological model. The layering cleanly and clearly separates the higher order concepts such as time, space, quality, threats, opportunities from middle-tiers of external reference information (linked open web sources), from the logic, goals and objectives of your organization and the application of this specific.

Movia AGENT, from the lower level data representations of your Big Data resources.

Movia Layered Ontology Model

Movia provides a layered ontology model that insulates decision logic from low-level data-source churn