@incollection{Grum2020,
  author    = {Grum, Marcus},
  title     = {Managing human and artificial knowledge bearers},
  series = {Business modeling and software design : 10th International Symposium, BMSD 2020, Berlin, Germany, July 6-8, 2020, Proceedings},
  booktitle = {Business modeling and software design : 10th International Symposium, BMSD 2020, Berlin, Germany, July 6-8, 2020, Proceedings},
  editor    = {Shishkov, Boris},
  publisher = {Springer International Publishing AG},
  address   = {Cham},
  isbn      = {978-3-030-52305-3},
  doi       = {10.1007/978-3-030-52306-0_12},
  pages     = {182 -- 201},
  year      = {2020},
  abstract  = {As part of the digitization, the role of artificial systems as new actors in knowledge-intensive processes requires to recognize them as a new form of knowledge bearers side by side with traditional knowledge bearers, such as individuals, groups, organizations. By now, artificial intelligence (AI) methods were used in knowledge management (KM) for knowledge discovery, for the reinterpreting of information, and recent works focus on the studying of different AI technologies implementation for knowledge management, like big data, ontology-based methods and intelligent agents [1]. However, a lack of holistic management approach is present, that considers artificial systems as knowledge bearers. The paper therefore designs a new kind of KM approach, that integrates the technical level of knowledge and manifests as Neuronal KM (NKM). Superimposing traditional KM approaches with the NKM, the Symbiotic Knowledge Management (SKM) is conceptualized furthermore, so that human as well as artificial kinds of knowledge bearers can be managed as symbiosis. First use cases demonstrate the new KM, NKM and SKM approaches in a proof-of-concept and exemplify their differences.},
  language  = {en}
}
@inproceedings{GrumBlunkRojahnetal.2020,
  author    = {Grum, Marcus and Blunk, Oliver and Rojahn, Marcel and Fettke, Peter and Gronau, Norbert},
  title     = {Research challenges of knowledge modelling and the outline of a research agenda},
  series = {Knowledge in digital age : IFKAD 2020},
  booktitle = {Knowledge in digital age : IFKAD 2020},
  publisher = {The Arts of Business Institute},
  address   = {Matera, Italy},
  isbn      = {978-88-96687-13-0},
  issn      = {2280-787X},
  year      = {2020},
  language  = {en}
}
@inproceedings{VladovaUllrichSultanowetal.2023,
  author    = {Vladova, Gergana and Ullrich, Andr{\´e} and Sultanow, Eldar and Tobolla, Marinho and Sebrak, Sebastian and Czarnecki, Christian and Brockmann, Carsten},
  title     = {Visual analytics for knowledge management},
  series = {Informatik 2023},
  booktitle = {Informatik 2023},
  editor    = {Klein, Maike and Krupka, Daniel and Winter, Cornelia and Wohlgemuth, Volker},
  publisher = {Gesellschaft f{\"u}r Informatik e.V. (GI)},
  address   = {Bonn},
  isbn      = {978-3-88579-731-9},
  issn      = {1617-5468},
  doi       = {10.18420/inf2023_187},
  pages     = {1851 -- 1870},
  year      = {2023},
  abstract  = {The management of knowledge in organizations considers both established long-term processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.},
  language  = {en}
}