Multi-Layered Semantic Data Models

One of the basic terms in information engineering is data. In our approach, data item is defined as representation of an information atom stored in digital computers. Although an information atom can be considered as a subject-predicate-value triplet (Lassila, 1999), data is usually given only with its value representation. This fact can lead to definitions where data is just numbers, words or pictures without context. For example in (WO, 2007), data is given as information in numerical form that can be digitally transmitted or processed. It is interesting that we can often recognize that the term ‘data’ is used without any exact terminological definition with the effect that the term often remains confusing, sometimes even contradicting the definitions of the term presented. Sieber and Kammerer (2006) introduce a new interpretation of data containing several levels. The lowest level belongs to data instances that describe the form and appearance of symbols. The intermediate level is the level of representatives which includes the applied encoding system. The highest level is related to the meaning with context description. All three levels are needed to get to know the information atom. For example the symbol ‘36’ in a database determines only the value and representation system, but not the meaning. To cover the whole information atom, the database should store some additional data items to describe the original data. The main purpose of semantic data models is to describe both context and the main structure of data items in the problem area. These additional data items are called metadata. It is important to see that: