Concept-Oriented Model and Query Language

TL;DR

This paper introduces the concept-oriented model (COM) and a new query language (COQL) that leverage principles like duality, inclusion, and order to enhance data modeling, navigation, analysis, and inference capabilities.

Contribution

It presents a novel data modeling approach and query language based on concepts and partial ordering, enabling advanced logical navigation and multidimensional analysis.

Findings

COM and COQL effectively support logical navigation, multidimensional analysis, and inference.

The approach simplifies complex data relationships through concept inclusion and ordering.

Demonstrated applications include logical navigation, cube creation, and inference procedures.

Abstract

We describe a new approach to data modeling, called the concept-oriented model (COM), and a novel concept-oriented query language (COQL). The model is based on three principles: duality principle postulates that any element is a couple consisting of one identity and one entity, inclusion principle postulates that any element has a super-element, and order principle assumes that any element has a number of greater elements within a partially ordered set. Concept-oriented query language is based on a new data modeling construct, called concept, inclusion relation between concepts, and concept partial ordering in which greater concepts are represented by their field types. It is demonstrated how COM and COQL can be used to solve three general data modeling tasks: logical navigation, multidimensional analysis and inference. Logical navigation is based on two operations of projection and de-projection. Multidimensional analysis uses product operation for producing a cube from level concepts chosen along the chosen dimension paths. Inference is defined as a two-step procedure where input constraints are first propagated downwards using de-projection and then the constrained result is propagated upwards using projection.