In an increasingly interconnected world, there is a need to prepare students to become more knowledgeable of different cultures and global matters. Furthermore, in a time which is characterized by disinformation, information literacy becomes more important than ever before. By taking into account transnational perspectives in learning these topics, e-learning provides us with the opportunity to connect students who otherwise would not have the chance to meet and get into knowledge related discourse with each other. In this context, the project „Intercultural perspectives on Information Literacy“ (IPIL) aims to realize a transnational learning community in which students from different countries engage in knowledge building discourse to foster intercultural learning and information literacy. The first IPIL course was conducted in winter term 2019/2020. Since then multiple transnational courses and workshops have been carried out. The last course took place in the winter semester 2021/2022. The didactical structure of IPIL follows a constructivist socio-cultural approach of knowledge building and knowledge creation in which learners from different higher education institutions with diverse cultural backgrounds engage in learning related discourse on topics related to information literacy. To enable such learning, the learning environment is structured into three levels (community, learning cycles, group learning task) …

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. …