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Ontological Engineering as a Next Step in Computer Science and Engineering.

Introduction

In the realm of information science and artificial intelligence, ontological engineering plays a crucial role in shaping how systems understand and interpret data. Ontological engineering involves the creation, maintenance, and application of ontologies—structured frameworks that define the relationships between concepts within a domain.

What is Ontological Engineering?

Ontological engineering is the process of developing ontologies. An ontology is a formal representation of a set of concepts within a domain and the relationships between those concepts. It provides a shared vocabulary that can be used to model the domain and enables different systems and organizations to understand and use the data consistently.

Key Components of Ontologies

1. Classes (or Concepts): These are the fundamental building blocks representing entities within a domain.
2. Relations: These define how classes are related to one another.
3. Attributes: These provide additional information about classes and relations.
4. Instances: Specific examples of classes.
5. Axioms: Rules that define the properties and constraints of the ontology.

1. Interoperability: Facilitates communication between disparate systems by providing a common understanding of data.
2. Data Integration: Enhances the ability to combine data from different sources, ensuring that the data is interpreted correctly.
3. Knowledge Sharing: Promotes the sharing of domain knowledge across various platforms and applications.
4. Improved Search and Retrieval: Ontologies improve the accuracy and efficiency of information retrieval systems by providing context to data.

Applications of Ontological Engineering

1. Semantic Web: Ontologies are fundamental to the Semantic Web, which aims to make internet data machine-readable.
2. Artificial Intelligence: Ontologies enable AI systems to understand and reason about data more effectively.
3. Healthcare: Used to integrate and interpret medical data from various sources, improving patient care and research.
4. E-commerce: Enhances product search and recommendation systems by understanding product attributes and customer preferences.

Challenges in Ontological Engineering

1. Complexity: Building comprehensive ontologies can be complex and time-consuming.
2. Scalability: Ensuring ontologies can scale with growing data and requirements.
3. Maintenance: Keeping ontologies up-to-date with evolving domain knowledge.
4. Consistency: Maintaining consistency in large and distributed ontologies can be difficult.

1. Ontology Editors: Tools like Protégé help in the creation and management of ontologies.
2. Reasoners: Software like Pellet or Hermit that can infer logical consequences from an ontology.
3. Ontology Languages: OWL (Web Ontology Language) is commonly used for defining ontologies.

Conclusion

Ontological engineering is a vital discipline in the information age, enabling systems to understand, integrate, and utilize data effectively. As technology continues to evolve, the role of ontologies in bridging data and knowledge will become increasingly significant, driving advancements in AI, data science, and beyond.

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.

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• 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.

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• 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.

Design

History says that the first notable effort at systematizing the design process emanated from Aristotle and the important theories he established through his findings on metaphysics. He rejected the then prevailing theories of leading thinkers because none of those theories was sufficiently analytical and none came to grip with the question of the existence of things everywhere. He theorized that for every artifact, there were four reasons or causes that gave rise to its existence. The four causes are, namely, (i) material cause, (ii) formal cause, (iii) efficient cause, and (iv) final cause. The material cause refers to the material of which the object is made of. Formal cause refers to the shape or the configuration assumed by the object material. Efficient cause refers to the purpose and function for which the object was brought into existence, answering the basic question, "what is it being made for"?

The term design has been defined in several ways including the followings.

"Design is the quest for simplicity and order."

"Explicit in the term design are the concepts of order and organization."

"Design is the process of inventing artifacts that display a new physical order, organization and form in response to function."

"Design is a conscious and intuitive effort directed toward the ordering of the functional, material and visual requirements of a problem."

"Design is a statement of order and organization. Its goal is unity. It must hold together. It is an expression of the human ubiquitous quest for order."

"Design implies intention, meaning and purpose."

"The planning and patterning of any act towards a desired, foreseeable end constitutes the design process."

"Designing is creative problem solving."

Finally the working definition to be employed is that design is the conscious, human process of planning physical things that display a new form in response to some predetermined need. Further, this activity implies a creative, purposeful, systematic, innovative and analytical approach to a problem which distinguishes between serious design and idle speculation.

DESIGN PROCESS

The design process varies from industry to industry. It also takes different forms in response to the product or system to be developed and the resources that are available. However, in spite of the apparent differences, there remains a consistent sequential progression at the heart of most design processes, only the magnitude of effort, emphasis and technique differ as follows

The most important design criteria are those set by the potential market, the available manufacturing facilities and constraints, if any, in the form of legal obligation, Possibly the most significant contribution made by the computer to the design process is its ability to communicate and modify designs with speed and efficiency. However, Computer Aided Design (CAD) and its integration with databases and other information systems go beyond simply revising a drawing.

A company offering standardized products will have no special design requirement to respond to a customer requirement. For non-standardized products and equipment, information, skill and intention are often required to reach an acceptable specification for both the customer and the manufacturer. There should be no room for vagueness at the specification stage. The power and flexibility provided by the CAD system, 2-D or 3-D drawing packages allow a highly interactive and controlled process. It is necessary to meet the agreed specification in function, price delivery, durability, esthetics and other factors imposed by the customer.