Ontology for daily life

By Kim Ji-myung

The two statements, presented in totally different vocabularies, describe the same world; however, it is no longer the same one we used to know. There are two kinds of people on this earth — those who know about ontology and those who don’t. Meanwhile, world history will soon be remembered as “before the internet” and “after the internet.”

Machines have begun to understand what people speak or instruct, thanks to the many years of steady tutoring by humans. Terms like semantic web, digital data, autonomous learning, artificial intelligence (AI), and knowledge-sharing have been developed to express the smooth communication between men and machines.

After trying to understand what “ontology” is for the past three years, I came to a conclusion that we all are hostages of this concept. But being a hostage or a master of it, depends on how one deals with it.

The Korea Times has not mentioned much about ontology. But already in 2008, in an article datelined in New York, artificial intelligence expert Riza C. Barkan reported:

“In the not-so-distant future, students will be able to graduate from high school without ever touching a book. Twenty years ago, they could graduate from high school without ever using a computer.”

Since then, computer technology and the Internet have transformed the core principles of information, knowledge, and education, as Barkan said.

Recent duals between AI and humans in baduk (go) and chess games, and translation competence, have enlightened people about the advancements of AI. In technological and commercial dimensions, it is already deeply embedded in many products used in our daily living.

“An ontology is an explicit specification of a conceptualization.” is the most widely accepted definition by Tom R. Gruber in “Toward principles for the design of ontologies used for knowledge sharing,” a paper presented at the Padua workshop on Formal Ontology in March 1993.

According to Gruber, ontology means organized knowledge expressed clearly about things and their relationships. While the terms “specification” and “conceptualization” have caused much debate, the essential points of this definition of ontology are: An ontology defines (specifies) the concepts, relationships, and other distinctions that are relevant for modeling a domain.

The specification takes the form of the definitions of representational vocabulary (classes, relations, and so forth), which provide meanings for the vocabulary and formal constraints on its coherent use.

Why do we need ontology? Or why is it important?

Because people can no longer live totally outside the help or use of machines. Machines are trained to obey and serve people; AI serves to instill a kind of brain in the machines that should listen to their master, us.

For example, you cannot manage your inventory of your shop manually if it is not a small mom-and-pop store. You will use inventory control software to do that, which is designed for your store, based on ontology.

A paper published in the Journal Artificial Intelligence for Cultural Heritage in 2016 presented a domain ontology for historical research documents. This means that cultural heritage knowledge nodes will be recognized and the relationship among them will be analyzed so that they will be transformed into semantic digital data for machines to be able to handle.

This is news, as cultural heritage content has been considered to be the last type data able to be processed by machines, because of the heavy amount of contextual information and the heterogenous forms and provenances involved.

Just a few weeks ago, the government announced that an AI-based program will translate the Seungjeong-won Ilgi, the diary of the royal secretariat of the Joseon Kingdom (1392-1910) written in Chinese characters for 151 years, into modern Korean.

Digital Humanities scholars have anticipated this kind of breakthrough in research, aided by the digital competence of machines. They can crop big data and come up with fresh discoveries of hidden patterns behind resulting statistics.

Understanding ontology and the machine way of thinking has awakened me from my own fuzzy disorderly habit of reasoning. When atomized into data format, facts are clear and truths are evidence-based — and that is the chief value of ontology.

The writer is the chairwoman of the Korea Heritage Education Institute (K*Heritage). Her email address is

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