Emergent Analytics

The core of the problems with managing information comes down to two fundamental properties that technologies today lack: extensibility and interoperability. When new types of data need to be collected, new systems must be built because the old ones are not extensible. This is only a minor problem for collecting data but, when it comes time to use that data, the difficulty of gaining interoperability between different systems poses a serious challenge. In many cases, the scale of the issue makes this challenge insurmountable. There is a need for a fundamental change in information technology that will promote distributed and unpredictable data.

Knowledgebases

Semantic technology offers a new mechanism for storing and accessing data called a knowledgebase. A knowledgebase, in its simplest form, is an RDF graph which uniquely identifies things with Uniform Resource Identifiers (URIs). The graph represents entities and relationships between entities (facts). It can be distributed or centrally located. A graph-based approach frees data from being locked into a rigid schema. Everything exists as a URI (a node in a graph) with properties attached that define what the thing is. Any person or application anywhere can make an assertion about something simply by referencing its URI.

Ontologies

Data in a knowledgebase is organized using an ontology, a formal (machine-readable) model that defines the precise meaning of the concepts and relationships that are relevant to a domain. When the precise meanings of the concepts are captured, reuse of data, integration of disparate data sets, and extension of the ontology become significantly simpler. A person or machine is able understand exactly what the different terms used to describe the data mean. Another added benefit of using ontologies is that they can be reasoned over by machines enabling new facts and relationships to be inferred from asserted ones based on rules defined within the ontology or outside the ontology.

Collaboration

Our product, Knoodl.com, is used to collaboratively construct, manage, and use ontologies and knowledgebases in a secure, scalable environment. Collaboration is important when developing ontologies because it enables organizations to reach a consensus on the meaning of things. A large community can also take advantage of the network effect in building and evolving a knowledgebase the same way that Wikipedia does. Individual people and applications may add only small amounts of data but, when these actions are performed on a large scale, as in an enterprise, new information begins to emerge. This is Emergent Analytics.

Transitioning your data from being stored in siloed systems to being part of a knowledgebase is a process that Revelytix has gained much experience implementing. The ROI is an integrated, extensible view of all your information enabling you to analyze it in a far more flexible, powerful way than you can today.