Semantic Data Modeling
What is Semantic Data Modeling?
Semantic data modeling is the process of creating a data model that clearly and explicitly defines the meaning of the data being stored. This is typically done by defining the relationships between different types of data and the concepts that they represent, as well as the properties and attributes of those concepts.
A semantic data model is typically expressed using a formal language or notation, such as the Resource Description Framework (RDF) or the Web Ontology Language (OWL). These languages are used to define the concepts and relationships in the data model and to annotate the data with additional information about its meaning and context.
Semantic data modeling is used to create data models that are more flexible and expressive than traditional data models, and that can support more complex and sophisticated queries. It is particularly useful for creating data models that are used in knowledge management systems, where the meaning and context of the data are important.