Topics and Coverage of the Book
As indicated in the previous paragraph, complex systems are omnipresent in everyday life with the introduction and presence of information technology within areas such as social networks, the Internet of Things, online banking, big data, traffic control and transportation, smart cities, logistics, military aviation, military command and control, robotics, big data informatics, distributed learning, augmented reality, emergency crisis management, intelligence, and cyber security, to name just a few prominent industries. Because distributed work almost always involves people in planning, decision making, operations, safety, and financial interests, there is a prime need for (1) human-centered understanding and (2) implementing cognitive-systems level considerations within information science/information technology designs. As these needs require timely integration of interdisciplinary (and often nested) topics the LLF provides a holistic and sustainable approach to leverage researcher and designer activities toward distributed work concepts that are sound, testable, as well as implementable for revision, resilience, and adaptation.
The book chapters cover what an integrated LLF and approach consist of through relevant and current research topics, application of apropos methods, and development of specific cases as studies; and specifically will answer the following questions: Why is the living laboratory important for implementing cognitive systems within a given context? How can I utilize the living laboratory for various fields of practice and work domains? How does human system integration/team system integration emerge within a dynamic, living environment? How is cognition understood in terms of information science and living systems metaphors? How can information, technology, and people be synthesized in a meaningful way using multiple methodological approaches? What is the basis for interdisciplinary research and design where human-centered knowledge and technology development, theory and practice, models and use, scenarios and simulations and are all considered holistically and kept in proper balance to insure that problems are both learned and solved within the constraints of many impinging variables and factors.