The AL!SE framework is based on a functional structure whose individual elements support a targeted enrichment of data.
The advantage : data receive an informative and meaningful added value. Relationships between data can be recognized and mapped; separate strands of information combine into a meaningful whole; and data can be used in a targeted, systematic and practice-oriented manner.
Responsible for this is an orderly interaction of semantic siles & ontologies and the resulting network structures.
Siles: semantic files
Siles are semantically enriched files. In contrast to files, siles not only contain data, they also describe it in more detail. For this purpose, functional metadata is assigned to the existing data. This metadata defines the content, but also the properties and functions of the associated data. The information content of data is revealed, an essential dimension of the data content is described: its meaning .
This procedure has several advantages: Data can be clearly identified and thus saved, searched and found more easily. In addition, the possibility of unambiguous identification in the form of semantic objects allows the formation of more complex information structures – by linking siles with other siles in a targeted manner. This is done using the laws of ontology.
In addition to linking data to metadata in the form of meaning-enriched siles, siles can in turn be linked to other siles. This gives the linking structure an additional, larger dimension. More complex symbols emerge from meaningful units. Data turns into information, information forms information flows; Supporting information structures are created . And these structures define the resulting data model of the concrete application.
To put it simply: the ontology describes which elements can be linked together, how and when: in the form of semantic triples (the knowledge graph-based subject-predicate-object constructions). The free design of the ontology (or the linking of several ontologies) guarantees a variable adaptation of the semantic framework in the form of concrete data models or applications.
Both with regard to siles and ontology, the semantic relational logic enables the meaningful linking of data on a wide variety of information levels. Data is placed in meaningful relationships with one another.
Relationships between data, statements and facts can be formed, presented and understood. Viewed visually, the diverse linking of individual units takes place in the form of (semantic) networks – visualized by the nodes and edges of knowledge graphs.
This important property is reflected in the concrete application areas of semantic models. They are suitable for representing any networked real-world domains cleanly and robustly.
The specifically suitable solution can, of course, include several functions and/or an adapted combination of these functions. After all, individual objectives require individual solutions. No problem thanks to the variability of semantic data models. As our previous successful projects make clear.
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