TY - BOOK A1 - Wätzoldt, Sebastian A1 - Giese, Holger T1 - Modeling collaborations in self-adaptive systems of systems BT - terms, characteristics, requirements, and scenarios N2 - 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. N2 - Steigende Anforderungen zum Funktionsumfang und der Flexibilität von Systemen führt zur Integration von zuvor isolierten Systemlösungen zu sogenannten System of Systems (SoS). Weiterhin sollten solche SoS adaptive Eigenschaften aufweisen, die es ihm ermöglichen auf sich ändernde Anforderungen und Umwelteinflüsse zu reagieren. Weil SoS aus unterschiedlichen, unabhängigen Subsystemen zusammengesetzt sind, die wiederum das übergeordnete SoS zu beliebigen Zeitpunkten erweitern oder verlassen können, ist das SoS durch eine variable Systemstruktur gekennzeichnet. Weiterhin definieren sich der Funktionsumfang des SoS und dessen Potenzial aus den enthaltenen Subsystemen. Solche komplexen Systemzusammenstellungen erfordern neue Untersuchungstechniken, um die Interaktion der einzelnen Subsysteme, die Kopplung von geteilten Daten und den Einfluss von lokalen Adaptionsstrategien auf das Gesamtsystem besser verstehen zu können. In diesem Bericht formulieren wir aktuelle Forschungsfragen mit dem Fokus auf der Modellierung von Interaktionen zwischen verschiedenen Systemteilen innerhalt eines SoS. Weiterhin definieren wir wichtige Systemtypen und Begriffe aus diesem Bereich durch das Zusammentragen aktueller Literatur. Nachdem wir ein gemeinsames Verständnis über SoS geschaffen haben, leiten wir typische SoS Eigenschaften und allgemeine Anforderungen für eine Modellierungssprache für Kollaborationen ab. Zusätzlich führen wir eine Literaturstudie durch, in der wir ein breites Spektrum von realen Szenarios und existierenden Frameworks zusammentragen, an denen wir die aufgezeigten SoS Eigenschaften diskutieren. Abschließend beschreiben wir den Stand der Wissenschaft bezüglich existierender Modellierungssprachen, die sich mit Kollaborationen in verschiedenen Arten von Systemen, wie SoS, beschäftigen. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 96 KW - modeling KW - collaboration KW - system of systems KW - cyber-physical systems KW - feedback loops KW - adaptive systems KW - Modellierung KW - Kollaborationen KW - System of Systems KW - Cyber-Physical Systems KW - Feedback Loops KW - adaptive Systeme Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-73036 SN - 978-3-86956-324-4 SN - 1613-5652 SN - 2191-1665 IS - 96 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Chujfi-La-Roche, Salim A1 - Meinel, Christoph T1 - Matching cognitively sympathetic individual styles to develop collective intelligence in digital communities JF - AI & society : the journal of human-centred systems and machine intelligence N2 - 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. KW - argumentation research KW - cyber humanistic KW - cognition KW - collaboration KW - knowledge building KW - knowledge management KW - teamwork KW - virtual groups Y1 - 2017 U6 - https://doi.org/10.1007/s00146-017-0780-x SN - 0951-5666 SN - 1435-5655 VL - 35 IS - 1 SP - 5 EP - 15 PB - Springer CY - New York ER -