TY  - CHAP
A1  - Grum, Marcus
ED  - Shishkov, Boris
T1  - Managing human and artificial knowledge bearers
BT  - the creation of a symbiotic knowledge management approach
T2  - Business modeling and software design : 10th International Symposium, BMSD 2020, Berlin, Germany, July 6-8, 2020, Proceedings
N2  - 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.
KW  - knowledge management
KW  - artificial intelligence
KW  - neuronal systems
KW  - design of knowledge-driven systems
KW  - symbiotic system design
Y1  - 2020
SN  - 978-3-030-52305-3
SN  - 978-3-030-52306-0
U6  - https://doi.org/10.1007/978-3-030-52306-0_12
SP  - 182
EP  - 201
PB  - Springer International Publishing AG
CY  - Cham
ER  - 
TY  - CHAP
A1  - Grum, Marcus
A1  - Blunk, Oliver
A1  - Rojahn, Marcel
A1  - Fettke, Peter
A1  - Gronau, Norbert
T1  - Research challenges of knowledge modelling and the outline of a research agenda
T2  - Knowledge in digital age : IFKAD 2020
KW  - knowledge management
KW  - process modelling
KW  - research challenges
Y1  - 2020
SN  - 978-88-96687-13-0
SN  - 2280-787X
PB  - The Arts of Business Institute
CY  - Matera, Italy
ER  - 
TY  - CHAP
A1  - Vladova, Gergana
A1  - Ullrich, André
A1  - Sultanow, Eldar
A1  - Tobolla, Marinho
A1  - Sebrak, Sebastian
A1  - Czarnecki, Christian
A1  - Brockmann, Carsten
ED  - Klein, Maike
ED  - Krupka, Daniel
ED  - Winter, Cornelia
ED  - Wohlgemuth, Volker
T1  - Visual analytics for knowledge management
BT  - advantages for organizations and interorganizational teams
T2  - Informatik 2023
N2  - 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.
KW  - knowledge management
KW  - visual analytics
KW  - knowledge transfer
KW  - teamwork
KW  - knowledge management system
KW  - tacit knowledge
KW  - explicit knowledge
Y1  - 2023
SN  - 978-3-88579-731-9
U6  - https://doi.org/10.18420/inf2023_187
SN  - 1617-5468
SP  - 1851
EP  - 1870
PB  - Gesellschaft für Informatik e.V. (GI)
CY  - Bonn
ER  -