With an increasing flood of data and at the same time changing requirements, making the relevant information available in the right context to a customer and within the company for the respective development-, technical- and service-departments is a key success factor for many companies and at the same time an enormous challenge. The problem with folders and filing data in tree structures is that information about an object is scattered across different aspects. Access to this information is only possible if the respective aspects are known. In a semantic network, each object exists only once, all information about this object comes together at this point and it can still be accessed within different contexts. Such a network can be changed at any time and further aspects can be added as needed: semantic machine learning, in order to be able to react flexibly to new requirements. Semantic networks combine functions of ontologies, topic maps, taxonomies and thesauri. They model complex relationships and directly transform large amounts of structured and unstructured content into networked units of knowledge. In this way, computer-readable and computer-usable knowledge bases are created. The creation and maintenance of semantic networks is demand-driven and interactive between humans and computers. …

With an increasing flood of data and at the same time changing requirements, making the relevant information available in the right context to a customer and within the company for the respective development-, technical- and service-departments is a key success factor for many companies and at the same time an enormous challenge. The problem with folders and filing data in tree structures is that information about an object is scattered across different aspects. Access to this information is only possible if the respective aspects are known. In a semantic network, each object exists only once, all information about this object comes together at this point and it can still be accessed within different contexts. Such a network can be changed at any time and further aspects can be added as needed: semantic machine learning, in order to be able to react flexibly to new requirements. Semantic networks combine functions of ontologies, topic maps, taxonomies and thesauri. They model complex relationships and directly transform large amounts of structured and unstructured content into networked units of knowledge. In this way, computer-readable and computer-usable knowledge bases are created. The creation and maintenance of semantic networks is demand-driven and interactive between humans and computers. …

The Bosch Group is a leading global supplier of technology and services. It employs roughly 402,600 associates worldwide (as of December 31, 2021). The company generated sales of 78.7 billion euros in 2021. Its operations are divided into four business sectors: Mobility Solutions, Industrial Technology, Consumer Goods, and Energy and Building Technology. At 128 locations across the globe, Bosch employs some 76,100 associates in research and development, of which more than 38,000 are software engineers. Juergen Ebmeyer joined Bosch in 2005 and is the Corporate Process Owner of the Bosch Experts Organization. He managed change projects to create divisional Centers of Competence and coordinates the Bosch-wide Centers of Competence. Lothar Maier works for Bosch since 2005 and is the IT Infrastructure Application Owner of the Bosch Experts Organization. He additionally supports the Bosch organization with further KM tools and methods as e.g. Expert Debriefing moderation.