What is Semantic Data

The semantic data model is a software engineering model based on relationships between stored symbols and the real world.

The data is organized in such a way that it can be interpreted meaningfully without human intervention. Semantic data has a history dating back to the 1970’s and is currently used in a wide variety of data management systems and applications.

How Does Semantic Data Work?

Data is organized based on binary models of objects, usually in groups of three parts: two objects and their relationship. For example, if one wanted to represent a cup sitting on a table, the data organization might look like this: CUP TABLE. The objects (cup and table) are interpreted with regard to their relationship (sitting on). The data is organized linearly, telling the software that since CUP comes first in the line, it is the object that acts. In other words, the position of the word tells the software that the cup is on the table and not that the table is sitting on the cup. Databases designed around this concept have greater applicability and are more easily integrated into other databases.

History of Semantic Data

In the 1970’s, the US Air Force implemented the Integrated Computer-Aided Manufacturing Program for the purpose of applying technology to increase manufacturing productivity. Out of this program grew an interest in semantic data. Methods of data organization were developed, including functional, informational and dynamic. Functional models focus on how the data represents objects or activities within the environment. Informational models are concerned with the organization and semantics of the environmental information. The dynamics model deals with how time affects the conditions within the environment.

Goals of Semantic Data

Semantic data systems are designed to represent the real world as accurately as possible within the data set. Data symbols are organized linearly and hierarchically to give certain meanings like the one described above. By representing the real world within data sets, semantic data allow machines to interact with worldly information without human interpretation.

Applications of Semantic Data

Semantic data is very promising for the enterprise world. Database Management Systems can be integrated with one another and compared. For example, since a company’s entire infrastructure is represented within the data model, the model can be compared to those of the company’s vendors to identify areas of inconsistency and possible improvement. This would help streamline the relationship between company and vendors, making database sharing and integration much simpler. Environments and systems can also be organized graphically within a database to give a more visually-based representation of that system or environment. Recently, a semantic language called Gellish was developed as a formal language to represent data models. Gellish can be interpreted solely by computers and needs no human interaction.