NisargDesai's Idea / Prospect

The term "ontology" has its roots in philosophy but has also found significant application in information science and technology. Here’s an explanation of its meaning in both contexts:

Philosophical Context

• Definition: In philosophy, ontology is the branch of metaphysics concerned with the nature and relations of being. It deals with questions about what entities exist or can be said to exist and how such entities can be grouped and related within a hierarchy.
• Focus: Ontology in philosophy is focused on the study of existence, reality, and the nature of being.
• Key Questions: Examples include "What is existence?", "What does it mean for something to be?", and "How do different entities relate to each other within the framework of reality?"

Information Science and Technology Context

• Definition: In information science and technology, an ontology is a formal, explicit specification of a shared conceptualization. It provides a structured framework to model a domain by defining the types of entities, their properties, and the relationships between them.
• Focus: Ontology in this context is focused on the representation and organization of knowledge to enable better data sharing, integration, and analysis.
• Components:
  • Classes (or Concepts): The categories of things in the domain.
  • Relations: How classes are related to one another.
  • Attributes: Properties of classes and relations.
  • Instances: Specific examples of classes.
  • Axioms: Rules that define the properties and constraints of the ontology.

Etymology

• Origin: The word "ontology" is derived from the Greek words "ontos" (being) and "logia" (study of). Thus, it literally means the study of being or existence.

Usage in Technology

• Semantic Web: Ontologies are crucial for the Semantic Web, allowing data to be shared and reused across application, enterprise, and community boundaries.
• Artificial Intelligence: They enable AI systems to understand and reason about data, providing a foundation for knowledge representation.
• Data Integration: Ontologies help in combining data from different sources, ensuring that the data is interpreted correctly and consistently.

Example in Technology

Imagine a medical ontology that includes concepts such as diseases, symptoms, treatments, and relationships like "has symptom" or "is treated by." This ontology would help different healthcare systems and applications share and understand medical data consistently, improving patient care and research.

In summary, ontology, whether in philosophy or technology, is about understanding and defining the nature and structure of entities and their relationships. In technology, this understanding is formalized to facilitate better data management, integration, and utilization.

• 
  

• Below are just a phases but each phases needs to pass through some tough decision this linked article about what to keep in mind when make decision once to start and progress this process.

• 

• In my experience most important aspect of making decision in product engineering is to ask your self 4 questions.

• 0.is this feasible to do this things now by time,resources, money and priority?

• 1.by doing this am I making this product useful and usable and adaptable? 2.by doing this am I making this product efficient, secure and scale-able? 3.by doing this am I making this product more maintainable, repairable and manageable/distribute-able?
  

• this are the answers of the questions in order you need to think from 0 to 3.
  

• if answer of 0 is positive than you need to make all other question`s answer positive and deliver at the end.

• I have seen a lot of article that go through data gathering and following trend and a lots of other non user/consumer/customer concentric approach.

• that what exactly contemporary time problem and that's how market is become more of gimmicky products instead of actual useful or even more innovative products.

• by following trends and investment flows only one sided advancement goes in product engineering and that raise the bubble and sometimes even turn into economical disaster.

• I hope my this prospects will help to keep simple and ideal when it come to making decision during the Product engineering.