The content, structural and technical flexibility of the AL!SE framework enables the flexible development of semantic application solutions – each adapted to the content and/or systemic requirements of the specific objective.
This variable applicability is supported by the relational logic inherent in the model: the possibility of meaningfully linking data, structures and systems. This functional principle – namely to combine smaller units according to defined laws to form larger meaningful units – is reflected in the structure of the AL!SE framework itself.
The modular structure
To put it simply: The AL!SE framework works according to the modular principle. This means that it consists of individual parts that run independently of each other and each take on individual, separate functions. Depending on the specific goal, these individual parts can be put together to form a functional whole: The result is an application that is precisely tailored to the requirements. In this context, programming takes place as an act of composition, so to speak.
From a technical point of view, the individual parts are micro-services that are related to one another via interfaces. The API management ensures that the separate services (which may well consist of different programming languages) can communicate with each other smoothly. The advantage of this is obvious: Such a model acts much more flexibly and can also be implemented much faster – since the individual services only have to be put together; the desired application does not have to be set up from scratch. In addition, the application “composed” in this way can be further developed just as easily, since the individual parts can be scaled and/or expanded separately from one another.
In summary, this means that semantic data models overcome boundaries through functional links in a variety of ways: informative, communicative and systemic. In this capacity, they support efficient information management at every data level and can also be precisely tailored to the specific requirements of the data due to their flexible, modular structure be adapted to practical use. You can find concrete examples of this in our use cases .
Semantics: individual solutions for individual goals.