When information is in the wrong place, it is essentially worthless. Kathrin Konkol and Erik Paul Konietzko explain how semantic data structures serve to optimize the data flow within companies.
One would assume that information is available in abundance. Where is the challenge?
Konietzko:
Although most employees in a company speak the same language, there is still a kind of Babylonian language labyrinth between departments: The designers use different names for components than the assembly workers. Each department also has its own software, which leads to imbalances in the flow of information.
Konkol:
And through good visual depiction, complex issues can become easier to comprehend. This is where suitable visualizations help to relieve the cognitive burden on experts. They make complex structures tangible without simplifying the contained information or losing artifacts of the development. This way, misunderstandings can be identified and corrected at a very early stage. And it also becomes clear whether the chosen semantics are actually effective.
Semantic data structures form the basis of your solution. What are those?
Konietzko:
One example: In the project Cockpit 4.0 which we carried out with Rolls-Royce – involving the production of turbines – we linked information from the design stage with that from the assembly. Which problems occurring in assembly can be traced back to missing information from the design? And how can we feed findings about this back to the design team? We have created an ontology to illustrate these connections. You can think of it like a mind map. The nodes represent the information, the edges show the relationships between the nodes. This is what we call semantic data structures.