Centralpoint MphC (Mult-Polyheirarchical Classification)

Properly classifying data involves a multi-tiered ontology. This hierarchy comprises various levels, each defining the data's nature and context. Simultaneously, data is classified based on intended audiences or departments, tailoring content relevance. Adding another layer, data classification is influenced by security roles, ensuring access control.

Imagine this as a three-dimensional matrix of classification: the first axis delineates the data's core ontology, dissecting it into intricate facets. The second axis bifurcates data for diverse audiences or departments, aligning content with their specific needs. Lastly, the third axis encompasses data classification based on security roles, safeguarding sensitive information from unauthorized access.

In practice, this means each record is meticulously tagged with metadata, departmental relevance, and security clearance. This layered approach orchestrates a finely tuned orchestration of data, culminating in a harmonious symphony of contextualized, relevant, and secured information delivery.

Another way to describe this MphC (or Multi Polyhiearchical Classification) would be "Multi-Dimensional Hierarchical Classification" or "Nested Hierarchical Classification" which refers to a classification structure that combines multiple levels or dimensions of hierarchies in different dimensions, creating a complex and multidimensional classification structure. Specifically within Centralpoint these three separate dimensions involve metadata, audience or departmental assignment and then security roles. Each of these selectors offers its own N-tiered, tree view of options allowing for all centralized information to cascade and reach each user, by audience, department, and security roles. Should one use belong 

Another way to describe this classification structure could be "Multi-Dimensional Hierarchical Classification" or "Nested Hierarchical Classification." These terms highlight the idea that the classification system involves multiple layers of hierarchies that are interconnected and nested within each other. This conveys the complexity and depth of the classification approach you're describing.


This results in a multi-tiered approach to managing your knowledge. It empowers you to distribute your information in a very granular way, to anyone (employees, clients, partners) from a singular, central point. Given that each multi selector is parental, this means that they are polyhierarchical (meaning more than tree, rather it considers the forest). Also, given that we employ three different (multi) selectors, it becomes Multi-Poly-Hierarchical. We didn't invent the term, it is simply what is called. The reason you may not have heard it before, is because we are the only vendor in the world to employ this architecture (fully, and to this level). It is also the only way that you will ever successfully centralize information within your organization, and with out it, will have to depend on multiple technology to simulate it.

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