On Ontology: Poetic Assertions

Parmenides of Elea was a Greek philosopher who lived 2,500 years ago. His primary surviving work is a poem often referred to as “On Nature,” the objective of which is to separate truth from opinion. “What is” and “What is not.” Parmenides is considered one of the founders of the study of metaphysics and ontology: Ontos (ontoß) meaning “truth,” and logos (λόγος) related to symbolic conceptualizations, e.g. “words”. Subject to interpretation, of course.

What does this have to do with data and system integration? Well, the study of nature and truth has continued through the ages and is crucial when it comes to data, since the meaning of data is of paramount importance and is the central goal of an ontology. Ontologies define a language by which definitions of and relations among concepts are formalized, and by doing so allows data to be understood, providing the semantics, or meaning, behind the data.

There are several technologies that can be used to specify ontologies: RDF, OWL, SPARQL, and many more. Why use poetry? Being married to a poet, @mishiepoet, we discuss and experiment with this form of communication often, so writing more poetically is a natural outcome of my life experience. Poetry promotes a careful brevity, a focus on clarity, and a reverence for a subject that works well for complex topics. Poems do not have to rhyme, but devices such as meter, repetition, and form add interest, beauty, and fun to a subject for which you might not expect it.

When I became involved in a project to define an ontology using IEC CIM as the basis for an analytics platform, understanding and explaining these concepts became necessary, and the assertions started taking shape.

Without further ado, here is the first revision of “Assertions: On the Nature of Ontology.”

Assertions: On the Nature of Ontology

First principles are fundamental axioms

     that provide the basis for reasoning

Assertions are clear, attributed statements of belief,

     giving rise to confidence in truth

Love, concern for our world, is our highest authority,

     and is a precondition for all activity

Models are simplified representations of reality

     comprised of conceptual symbols

Objects express collections of organized,

     structured information about the world

Concepts define, describe, and relate entities and events,

     across time, space, and context

Ontologies are models of concepts in a domain

     that describe objects and their relationships

Ontologies support logical deductive and inductive reasoning

     of conclusions using inference

Ontologies include data and metadata:

     types, properties, relations, and instances

Requirements are expressions of fundamental,

     existing, and aspirational objectives

Requirements are prioritized by value, effort,

     urgency, and dependency

Designs distill and translate requirements

     into modular, implementable specifications

Schemas are ontologies that define data elements

     as symbolic tokens within a namespace context

Definitions specify the type, context, relations,

     domain, and range of model elements

Rules articulate assertions about the content, conditions,

     and expectations amongst concepts

Taxonomies define abstract-to-specific type categorizations

     within a domain

Relationships convey taxonomy,

     aggregation, composition, containment, and causality

Category dimensions provide the basis

     for summarization of event metrics

Definition of ontology provides semantic clarity

     for information models, enabling computation

Rules specified by assertion are transparent, certified,

     and governed by human stakeholders

Governing bodies form around topic collections

     with strong correlation of interrelationships

Modular design encapsulates functionality

     within versioned service interface boundaries

Service interface compatibility manages dependencies

     to enable independent enhancements

Implementations codify the translation

     of requirements and design into execution

Ontologies expose our understanding

     of the metaphysical nature of the universe

Assertions are ratified through publicly anonymized,

     fully auditable consensus

Through computation and disambiguation

     of ontologies, understanding can emerge

Poems use natural language. Natural language is necessary for facilitating discussions and specifications at the level of requirements and business rules. These specifications can then be expanded and translated into implementations. Large neural network natural language processing (NLP) technology is advancing rapidly, and someday, compilation of ontology assertions in carefully crafted English into a model that can support reasoning might be a task that a computer could perform. It could already be possible.

Are these statements cohesive, minimal, and sufficient?

No – far from it.  But they are a foundation for a beginning.

Please join the conversation! Which assertions do you agree or disagree with?

What would you add? Let us know your thoughts in the comments!

Xtensible Solutions supports energy utilities leveraging industry standards including the IEC CIM to build information models and platforms to solve today’s data integration challenges. Ontologies represent the next frontier in integration, and Xtensible is leading the way, applying machine learning, graph technology, agile methodologies, data governance, and distributed platforms to reduce integration friction and build the semantics management platform of the future.

Interested in learning more about the use of ontologies for data integration? Speak to a member of the Xtensible team.