@book{WaetzoldtGiese2015,
  author    = {W{\"a}tzoldt, Sebastian and Giese, Holger},
  title     = {Modeling collaborations in self-adaptive systems of systems},
  number    = {96},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-324-4},
  issn      = {1613-5652},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-73036},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {72},
  year      = {2015},
  abstract  = {An increasing demand on functionality and flexibility leads to an integration of beforehand isolated system solutions building a so-called System of Systems (SoS). Furthermore, the overall SoS should be adaptive to react on changing requirements and environmental conditions. Due SoS are composed of different independent systems that may join or leave the overall SoS at arbitrary point in times, the SoS structure varies during the systems lifetime and the overall SoS behavior emerges from the capabilities of the contained subsystems. In such complex system ensembles new demands of understanding the interaction among subsystems, the coupling of shared system knowledge and the influence of local adaptation strategies to the overall resulting system behavior arise. In this report, we formulate research questions with the focus of modeling interactions between system parts inside a SoS. Furthermore, we define our notion of important system types and terms by retrieving the current state of the art from literature. Having a common understanding of SoS, we discuss a set of typical SoS characteristics and derive general requirements for a collaboration modeling language. Additionally, we retrieve a broad spectrum of real scenarios and frameworks from literature and discuss how these scenarios cope with different characteristics of SoS. Finally, we discuss the state of the art for existing modeling languages that cope with collaborations for different system types such as SoS.},
  language  = {en}
}
@article{ChujfiLaRocheMeinel2017,
  author    = {Chujfi-La-Roche, Salim and Meinel, Christoph},
  title     = {Matching cognitively sympathetic individual styles to develop collective intelligence in digital communities},
  series = {AI \& society : the journal of human-centred systems and machine intelligence},
  volume    = {35},
  journal   = {AI \& society : the journal of human-centred systems and machine intelligence},
  number    = {1},
  publisher = {Springer},
  address   = {New York},
  issn      = {0951-5666},
  doi       = {10.1007/s00146-017-0780-x},
  pages     = {5 -- 15},
  year      = {2017},
  abstract  = {Creation, collection and retention of knowledge in digital communities is an activity that currently requires being explicitly targeted as a secure method of keeping intellectual capital growing in the digital era. In particular, we consider it relevant to analyze and evaluate the empathetic cognitive personalities and behaviors that individuals now have with the change from face-to-face communication (F2F) to computer-mediated communication (CMC) online. This document proposes a cyber-humanistic approach to enhance the traditional SECI knowledge management model. A cognitive perception is added to its cyclical process following design thinking interaction, exemplary for improvement of the method in which knowledge is continuously created, converted and shared. In building a cognitive-centered model, we specifically focus on the effective identification and response to cognitive stimulation of individuals, as they are the intellectual generators and multiplicators of knowledge in the online environment. Our target is to identify how geographically distributed-digital-organizations should align the individual's cognitive abilities to promote iteration and improve interaction as a reliable stimulant of collective intelligence. The new model focuses on analyzing the four different stages of knowledge processing, where individuals with sympathetic cognitive personalities can significantly boost knowledge creation in a virtual social system. For organizations, this means that multidisciplinary individuals can maximize their extensive potential, by externalizing their knowledge in the correct stage of the knowledge creation process, and by collaborating with their appropriate sympathetically cognitive remote peers.},
  language  = {en}
}