𝗡𝗼𝘁 𝗮𝗹𝗹 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗽𝗹𝗮𝘆 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗿𝗼𝗹𝗲

 

𝗡𝗼𝘁 𝗮𝗹𝗹 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗽𝗹𝗮𝘆 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗿𝗼𝗹𝗲.

When people hear the word ontology, they often imagine a single structure of classes and relationships.

But in practice, ontologies can be organized into different types, depending on their level of abstraction and purpose.

𝗧𝗵𝗲 𝗺𝗮𝗶𝗻 𝘁𝘆𝗽𝗲𝘀 𝗮𝗿𝗲:

𝗢𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲𝗺 𝗶𝘀 𝘂𝗽𝗽𝗲𝗿 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝗶𝗲𝘀.

They describe very general concepts such as:

• entity

• process

• event

• object

• relation

• time

Examples include Basic Formal Ontology (BFO) and Unified Foundational Ontology (UFO).

Their role is to provide a shared conceptual foundation across domains.

For example, concepts such as disease, city, patient, or sensor can all be aligned under broader categories.

𝗔𝗻𝗼𝘁𝗵𝗲𝗿 𝘁𝘆𝗽𝗲 𝗶𝘀 𝗱𝗼𝗺𝗮𝗶𝗻 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝗶𝗲𝘀.

These represent knowledge specific to a field.

Examples:

• healthcare

• education

• agriculture

• transportation

• epidemiological surveillance

A health ontology may define:

• fever as a symptom

• dengue as a disease

• mosquito as a biological vector

A well-known example is Infectious Disease Ontology (IDO).

𝗧𝗮𝘀𝗸 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝗶𝗲𝘀 focus on activities that can occur in multiple domains.

Examples:

• diagnosis

• classification

• recommendation

• monitoring

• decision support

Diagnosis exists both in medicine and industrial systems.

𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝗶𝗲𝘀 are built for concrete solutions.

They combine:

• domain knowledge

• local constraints

• operational objectives

For example, an ontology created to support epidemiological decision-making in arbovirus surveillance.

𝗪𝗵𝘆 𝗱𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿?

Because many projects try to model everything from scratch.

A more robust semantic architecture usually follows this logic:

𝗨𝗽𝗽𝗲𝗿 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝘆 → conceptual foundation

𝗗𝗼𝗺𝗮𝗶𝗻 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝘆 → specialized knowledge

𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝘆 → problem solving

𝗜𝗻 𝗔𝗜 𝗮𝗻𝗱 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺𝘀, this becomes even more relevant.

An ontology can help an expert agent understand that:

• fever and myalgia are symptoms

• notification delay affects trust

• clinical co-occurrence may represent semantic evidence

This means:

𝗶𝘁 𝗶𝘀 𝗻𝗼𝘁 𝗼𝗻𝗹𝘆 𝗮𝗯𝗼𝘂𝘁 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗶𝗻𝗴 𝘁𝗲𝘅𝘁

𝗶𝘁 𝗶𝘀 𝗮𝗯𝗼𝘂𝘁 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗶𝗻𝗴 𝗺𝗲𝗮𝗻𝗶𝗻𝗴

Ontologies are not only about describing knowledge.

They make integration, inference, and explanation possible.

🔹 𝗡𝗼𝘁𝗲: the examples in this post were developed with the support of Artificial Intelligence for illustrative purposes.

Referências: https://www.loa.istc.cnr.it/old/Papers/FOIS98.pdf?utm_source=chatgpt.com 

Guarino, N. (1998). Formal Ontology in Information Systems. 3–15. http://www.csc.liv.ac.uk/~pepijn/legont.html

 

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