Semantic Model
A Semantic Model is a knowledge representation that helps create abstract representations (that support understanding tasks and semantic interpretations).
- AKA: Conceptual Framework, Conceptualization, Conceptual Schema.
- Context:
- It can typically contain Concept Records through semantic structure.
- It can typically represent Semantic Relations through concept interactions.
- It can typically enable Machine Understanding through concept formalization.
- It can typically support Reasoning Process through logical framework.
- It can typically guide Knowledge Organization through domain representation.
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- It can often provide Shared Understanding through common conceptualization.
- It can often improve System Interoperability through ontological alignment.
- It can often support Inference Task through semantic reasoning.
- It can often facilitate Knowledge Transfer through conceptual mapping.
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- It can range from being an Informal Semantic Model to being a Formal Semantic Model, depending on its formalization level.
- It can range from being a Domain Specific Model to being a General Knowledge Graph, depending on its knowledge scope.
- It can range from being a Rule Based Model to being a Statistical Model, depending on its representation approach.
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- It can be produced by a Concept Modeling System with concept modeling capability.
- It can abide by some Semantic Modeling Methodology.
- It can have Verification Methods through logical consistency.
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- Examples:
- Knowledge Representation Models, such as:
- Domain Models, such as:
- Mental Models, such as:
- Specialized Models, such as:
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- Counter-Examples:
- Physical Models, which are tangible representations.
- Simulation Models, which are dynamic executions.
- Logical Data Models, which are implementation specific.
- Raw Data Structures, which lack semantic interpretation.
- See: Semantic Model, Knowledge Model, Domain Model, Ontological Framework, Mental Model.
References
2023
- (Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/Conceptual_model Retrieved:2023-7-23.
- A conceptual model is a representation of a system. It consists of concepts used to help people know, understand, or simulate a subject the model represents. In contrast, a physical model focuses on a physical object such as a toy model that may be assembled and made to work like the object it represents.
The term may refer to models that are formed after a conceptualization or generalization process. Conceptual models are often abstractions of things in the real world, whether physical or social. Semantic studies are relevant to various stages of concept formation. Semantics is basically about concepts, the meaning that thinking beings give to various elements of their experience.
- A conceptual model is a representation of a system. It consists of concepts used to help people know, understand, or simulate a subject the model represents. In contrast, a physical model focuses on a physical object such as a toy model that may be assembled and made to work like the object it represents.
2023
- (Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/Conceptual_model#Conceptual_model_vs Retrieved:2023-7-23.
- Conceptual Models and semantic models have many similarities, however the way they are presented, the level of flexibility and the use are different.
Conceptual models have a certain purpose in mind, hence the core semantic concepts are predefined in a so-called meta model. This enables a pragmatic modelling but reduces the flexibility, as only the predefined semantic concepts can be used. Samples are flow charts for process behaviour or organisational structure for tree behaviour.
Semantic models are more flexible and open, and therefore more difficult to model. Potentially any semantic concept can be defined, hence the modelling support is very generic. Samples are terminologies, taxonomies or ontologies.
In a concept model each concept has a unique and distinguishable graphical representation, whereas semantic concepts are by default the same.
In a concept model each concept has predefined properties that can be populated, whereas semantic concepts are related to concepts that are interpreted as properties.
In a concept model operational semantic can be built-in, like the processing of a sequence, whereas a semantic model needs explicit semantic definition of the sequence.
The decision if a concept model or a semantic model is used, depends therefore on the "object under survey", the intended goal, the necessary flexibility as well as how the model is interpreted. In case of human-interpretation there may be a focus on graphical concept models, in case of machine interpretation there may be the focus on semantic models.
- Conceptual Models and semantic models have many similarities, however the way they are presented, the level of flexibility and the use are different.
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Conceptual_schema Retrieved:2015-8-4.
- A conceptual schema is a high-level description of a business's informational needs. It typically includes only the main concepts and the main relationships among them. Typically this is a first-cut model, with insufficient detail to build an actual database. ...
2013
- http://en.wikipedia.org/wiki/Conceptual_model
- In the most general sense, a model is anything used in any way to represent anything else. Some models are physical objects, for instance, a toy model which may be assembled, and may even be made to work like the object it represents. Whereas, a conceptual model is a model that exists only in the mind. Conceptual models are used to help us know and understand the subject matter they represent.
The term conceptual model may be used to refer to models which are formed after a conceptualization process in the mind. ...
- In the most general sense, a model is anything used in any way to represent anything else. Some models are physical objects, for instance, a toy model which may be assembled, and may even be made to work like the object it represents. Whereas, a conceptual model is a model that exists only in the mind. Conceptual models are used to help us know and understand the subject matter they represent.
2013
- Wikipedia http://en.wikipedia.org/wiki/Conceptual_model_(computer_science)
- A mental model captures ideas in a problem domain, while a conceptual model represents 'concepts' (entities) and relationships between them. A Conceptual model in the field of computer science is also known as a domain model. Conceptual modeling should not be confused with other modeling disciplines such as data modelling, logical modelling and physical modelling. The conceptual model is explicitly chosen to be independent of design or implementation concerns, for example, concurrency or data storage. The aim of a conceptual model is to express the meaning of terms and concepts used by domain experts to discuss the problem, and to find the correct relationships between different concepts. The conceptual model attempts to clarify the meaning of various, usually ambiguous terms, and ensure that problems with different interpretations of the terms and concepts cannot occur. Such differing interpretations could easily cause confusion amongst stakeholders, especially those responsible for designing and implementing a solution, where the conceptual model provides a key artifact of business understanding and clarity. Once the domain concepts have been modeled, the model becomes a stable basis for subsequent development of applications in the domain. The concepts of the conceptual model can be mapped into physical design or implementation constructs using either manual or automated code generation approaches. The realization of conceptual models of many domains can be combined to a coherent platform.
A conceptual model can be described using various notations, such as UML or OMT for object modelling, or IE or IDEF1X for Entity Relationship Modelling. In UML notation, the conceptual model is often described with a class diagram in which classes represent concepts, associations represent relationships between concepts and role types of an association represent role types taken by instances of the modelled concepts in various situations. In ER notation, the conceptual model is described with an ER Diagram in which entities represent concepts, cardinality and optionality represent relationships between concepts. Regardless of the notation used, it is important not to compromise the richness and clarity of the business meaning depicted in the conceptual model by expressing it directly in a form influenced by design or implementation concerns.
This is often used for defining different processes in a particular Company or Institute.
- A mental model captures ideas in a problem domain, while a conceptual model represents 'concepts' (entities) and relationships between them. A Conceptual model in the field of computer science is also known as a domain model. Conceptual modeling should not be confused with other modeling disciplines such as data modelling, logical modelling and physical modelling. The conceptual model is explicitly chosen to be independent of design or implementation concerns, for example, concurrency or data storage. The aim of a conceptual model is to express the meaning of terms and concepts used by domain experts to discuss the problem, and to find the correct relationships between different concepts. The conceptual model attempts to clarify the meaning of various, usually ambiguous terms, and ensure that problems with different interpretations of the terms and concepts cannot occur. Such differing interpretations could easily cause confusion amongst stakeholders, especially those responsible for designing and implementing a solution, where the conceptual model provides a key artifact of business understanding and clarity. Once the domain concepts have been modeled, the model becomes a stable basis for subsequent development of applications in the domain. The concepts of the conceptual model can be mapped into physical design or implementation constructs using either manual or automated code generation approaches. The realization of conceptual models of many domains can be combined to a coherent platform.
2009
- (WordNet, 2009) ⇒ http://wordnetweb.princeton.edu/perl/webwn?s=conceptualization
- S: (n) conceptualization, conceptualisation, formulation (inventing or contriving an idea or explanation and formulating it mentally)
- S: (n) conceptualization, conceptualisation, conceptuality (an elaborated concept)
- http://en.wiktionary.org/wiki/conceptualization
- 1. the act of conceptualizing, or something conceptualized
- (WordNet, 2009) ⇒ http://wordnetweb.princeton.edu/perl/webwn?s=conceptualize
- S: (v) gestate, conceive, conceptualize, conceptualise (have the idea for) "He conceived of a robot that would help paralyzed patients"; "This library was well conceived"
- http://en.wiktionary.org/wiki/conceptualize#Verb
- 1. To interpret a phenomenon by forming a concept
- 2. To conceive the idea for something
2007
- (Obitko, 2007) ⇒ Marek Obitko. (2007). “Translations between Ontologies in Multi-Agent Systems", Ph.D. dissertation, Faculty of Electrical Engineering, Czech Technical University in Prague. http://obitko.com/tutorials/ontologies-semantic-web/specification-of-conceptualization.html
- A conceptualization can be defined as an intensional semantic structure that encodes implicit knowledge constraining the structure of a piece of a domain. Ontology is a (partial) specification of this structure, i.e., it is usually a logical theory that expresses the conceptualization explicitly in some language. Conceptualization is language independent, while ontology is language dependent. The use can be illustrated in the figure below - it shows how an ontology restricts (i.e., defines) possible use of constructs used in the description of the domain. Notice that ontology does not have to express all the possible constraints - the level of details in conceptualization depends on the requirements of the intended application and expressing conceptualization in ontology in addition depends on the used ontology language.
1993
- (Gruber, 1993) ⇒ Tom Gruber. (1993). “A translation approach to portable ontology specifications." Knowledge Acquisition, 2(5):199--220.
- A conceptualization is an abstract, simplified view of the world that we wish to represent for some purpose. Every knowledge base, knowledge-based system, or knowledge-level agent is committed to some conceptualization, explicitly or implicitly. An ontology is an explicit specification of a conceptualization..
1983
- (Norman, 1983) ⇒ Donald A. Norman. (1983). “Some Observations on Mental Models." Mental models 7, no. 112
- … A conceptual model is invented to provide an appropriate representation of the target system, appropriate in the sense of being accurate, consistent, and complete.
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