Scientific Variables Ontology

Core Ontological Concepts

The following is a brief overview of the core concepts of the Scientific Variables Ontology. For more detailed descriptions, please see the specification pages (coming soon). More details about the methodology and motivation for the ontology design process will be presented in an upcoming paper. As with all ontologies, as more information is brought to light, it is possible that some of these concepts and their interrelationships will change slightly and that new relationships will be introduced. The core concepts presented here comprise the building blocks that were deemed necessary for creating a modular, mix-and-match ontology that could be used to construct variables in the natural sciences. These concepts were determined after analysis and iterative inspection of over forty thousand variables identified in the fields of environmental chemistry, hydrology, atmospheric science, geology, and several other fields.

The two foundational concepts of the ontology are Phenomenon and Property. A phenomenon is something that is observed to happen or exist and a property is a quality or characteristic of something. A phenomenon may manifest itself or be detectable through one or more of the following elements: its substance (class: Matter), its form or shape or spatial extent (class: Form), its member objects, actors or participants (class: Body, which comprises of Matter and Form), its function (class: Role) or the processes in which its members participate (class: Process). When a property is attributable to a phenomenon and takes on a value, it is known as an attribute (class: Attribute). The value of an attribute identifies the state of a phenomenon. A third core concept is the Abstraction. An abstraction is any mental, human-conceived concept that is used as a model or interpretation of phenomena.

A phenomenon-property pair is called a variable (class: Variable). There are some good arguments for treating isolated quantities (i.e., quantitative property values) as variables in modeling. For a detailed discussion on this idea, please see section 4.3 of the Ontology for Engineering Mathematics (Gruber and Olsen, 1994).