What Is Ontology Engineering?

Ontology engineering in computer science, information science, and systems engineering is the field that studies methods and methods of constructing ontology: the formal representation of a set of concepts within a domain and the relationships between these concepts. Large-scale representations of abstract concepts such as actions, time, physical objects, and beliefs will become an example of ontological engineering. Ontology engineering is one of the fields of applied ontology, which can be regarded as the application of philosophical ontology. The core ideas and goals of ontology engineering are also the core of conceptual modeling.

"Ontology engineering aims to clarify the knowledge contained in software applications, as well as knowledge in companies and business processes in specific domains. Ontology engineering provides a direction for solving interoperability problems caused by semantic barriers, namely business terms and software Definition-related obstacles. Ontology engineering is a set of tasks related to domain-specific ontology development. "
You can automatically process information that software agents cannot interpret by adding rich semantics to the appropriate resources, such as video files. One of the ways to formally conceptualize a knowledge domain is to use a machine-interpretable ontology, which is provided in or based on RDF, RDFS, and OWL to provide structured data. Ontology engineering is the design and creation of this ontology, it not only contains a list of terms (controlled vocabulary); they contain terms, assertions, and axioms of relationships, used to define concepts (classes), individuals and roles (attributes) (TBox respectively) , ABox and RBox). Ontology engineering is a relatively new research area that involves the ontology development process, the ontology life cycle, the methods and methods for building ontology, and the tool suites and languages that support them. One common way to provide the basis of ontological logic is to formalize the axioms of description logic, which can then be converted to any serialization of RDF, such as RDF / XML or Turtle. In addition to describing axioms of logic, ontology may also contain SWRL rules. Concept definitions can be mapped to any type of resource or resource segment in RDF, such as images, videos, and areas of interest to annotate objects, people, etc. and link them with cross-knowledge bases, ontology and related resources. LOD data set. This information is based on human experience and knowledge and is valuable for promoters who automatically interpret complex and fuzzy content, such as the visual content of multimedia resources. Application areas of ontology-based reasoning include, but are not limited to, information retrieval, automatic scene interpretation, and knowledge discovery.
Ontology language is a formal language for coding ontology. Ontology has many such languages, including proprietary and standards-based languages:
General logic is the ISO standard 24707, which is a specification of a series of ontology languages that can be accurately converted to each other.
The Cyc project has its own ontology language CycL, which is based on first-order predicate calculus and some higher-order extensions.
The Gellish language includes its own extended rules, thus integrating ontology with the ontology language.
IDEF5 is a software engineering method for developing and maintaining a usable and accurate domain ontology.
KIF is a syntax of first-order logic based on S expressions.
Rule Interchange Format (RIF), F-Logic and its successor ObjectLogic combine ontology and rules.
OWL is a language for making ontology statements, as the subsequent development of RDF and RDFS, and early ontology language projects, including OIL, DAML, and DAML + OIL. OWL is intended for use through the World Wide Web, and all its elements (classes, attributes, and individuals) are defined as RDF resources and identified by URIs.
OntoUML is an educated language for specifying a reference ontology.
SHACL (RDF SHapes Constraints Language) is a language for describing RDF data structures. It can be used with RDFS and OWL or standalone.
XBRL (Extensible Business Reporting Language) is a syntax for expressing business semantics.
Life sciences are booming, and biologists use it to understand their experiments. In order to infer correct conclusions from experiments, ontology must be optimally structured for the knowledge base they represent. The structure of the ontology needs to be constantly changed so that it is an accurate representation of the underlying domain.
Recently, an automated method was introduced into the engineering ontology in life sciences, such as Gene Ontology (GO). It is one of the most successful and widely used biomedical ontology. Based on information theory, it reconstructs the ontology so that the level represents the desired specificity of the concept. Similar information-theoretic approaches have also been used for optimal partitioning of gene ontology. Given the mathematical nature of such engineering algorithms, these optimizations can be automated to generate principles and scalable architectures to reconstruct ontology such as GO [1]
  • DOGMA
  • DogmaModeler
  • KAON
  • OntoClean
  • HOZO
  • Protégé (software)
  • TopBraid Composer
  • TopBraid EDG
  • HCOME: Human-centered c ollaborative o ntology e ngineering m ethodology (http://semanticweb.org/wiki/SharedHCONE.html and HCOME-3O)

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