Data semantics is the study of the meaning and use of specific data in computer programming. It focuses on how a data object represents a concept or object in the real world. Semantic meaning occurs only when a group agrees on specific definitions for certain data types or words. The need for data semantics arose in the 1970s when the United States Air Force developed a program to help people communicate more clearly about the current manufacturing techniques they were using. It allows data workers to develop a clear and defined set of rules that everyone can understand and follow.
Man has always sought the meaning of life and this curiosity also extends to the world of language and data. Data semantics is the study of the meaning and use of specific data in computer programming and other areas that use data. When studying a language, semantics refers to what individual words mean and what they mean when put together to form sentences or phrases. In data semantics, the focus is on how a data object represents a concept or object in the real word.
Data semantics are highly subjective. If a person who has never worked with a computer database tries to extract information from it, the words and phrases used to access the database would be meaningless. Semantic meaning occurs only when a group agrees on specific definitions for certain data types or words. For others to grasp these semantic meanings, they cannot change. If the word “dog” referred one day to a four-legged furry animal and one day to a two-legged bird, it would lose its meaning and no one would know what another person meant when they said “dog.”
The need for data semantics arose in the 1970s when the United States Air Force developed a program to help people communicate more clearly about the current manufacturing techniques they were using. In this way, they could improve production processes. The program, known as the Integrated Computer-Aided Manufacturing (ICAM) program, employed methods known as IDEF (definition of integration) methods that produced various models of how the system should work.
An example of how data semantics help relate pieces of code or data to the real world is a library card catalog. Originally, book records were kept alphabetically on slips of paper in a filing cabinet. To look up a book, a customer leafed through the cards until he found the book title he wanted. In a computer database, a memory space to hold the title and information of a book can be thought of as a virtual version of the original paper title block.
While data semantics is highly abstract on many levels, it has a simple goal. It allows data workers to develop a clear and defined set of rules that everyone can understand and follow. Creating data semantics is similar to mapping the grammar and style rules that determine how words are used together to convey specific meaning.
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