Semantics is a buzz word that continues to circulate the technology world. “Semantic web” or “semantic knowledge management” are terms that are discussed intensively. But what is actually meant by “semantics” and what role does semantics play in technical writing?
Semantics is the study of meaning. In other words, it examines how we understand words and the meaning relationships that exist between words.
So far, so simple. Then why is semantics a topic in technology? On the one hand, because without semantics, efficient access to content is barely possible. Only semantics makes content intuitively accessible. Semantics also helps to make content more machine readable and manageable. On the other hand, however, semantics is also a perennial issue in IT because the meaning is not as simple as you might think at first. For example, the meaning of words changes depending on the context in which they are used. “Seal” will be understood differently in a zoo brochure than in an installation manual for a machine. Conversely, the same meaning is often expressed by several words. An “instruction manual” is also called a “user guide”, or an “automobile” a “car”.
Technical writing departments are familiar with these problems, which is why many of them have been dealing with terminology for a long time. Terminology clearly specifies what a term means and which words are used to refer to the object for which the term stands.
Up to now there have mainly been two reasons for terminology work in technical writing: 1. The means of expression in texts should be specific and precise so that there can be no misunderstandings. 2. Well-maintained terminology should contribute to being able to quickly and easily produce translations.
For some time now, however, another aspect has been added to terminology work and the associated meaning definitions. This is because smart information and the trend towards digitalization demand more semantics in the content pools. The information can only be addressed and used in different contexts through explicit and very specific semantics. In order to achieve this, slightly more sophisticated organization principles than in conventional terminology work are needed.
Terms and meanings can be organized according to different principles. These principles are often represented as the “semantic ladder”. The higher the organization principle is on the ladder, the more semantics the model also contains (and the more effort that must be put into the creation).
On the bottom step is the organization of meanings in a glossary. This is a simple list of words and their explanations. Glossaries are already used in many companies today. One step higher are the taxonomies. Here, the words are not only listed but they are placed in an – unspecified – hierarchical structure. Taxonomies are also often used in content management.
A thesaurus, in turn, is a controlled vocabulary for concepts that are placed in a hierarchical relationship with one another as a broader term and narrower term. Semantic networks mark additional concept relations beyond purely hierarchical relations. For example, these can be relationships such as “opposite”, “X contains Y”, or even “X is suitable for Y”. Finally, on the top step are ontologies. They are explicit, formal specifications of a common conceptualization. Ideally, ontologies can therefore cover all semantic relationships of a topic.