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• W2971016080 abstract "The smart technologies led by advances in artificial intelligence, machine learning, and the emerging data science in recent years are transforming many facets of society in profound ways. One of these affected areas is the experience of human dynamics in general and human mobility in particular with the growing maturity of smart technologies. The goal of this article is to critically examine the concepts of space and place in geography in general and in geographic information science (GIScience) in particular so that intelligent geographic information systems incorporating concepts of smart space and smart place can be developed to support human dynamics research. We argue that the current discussions on smart technologies are conceptually constrained due to their confinement to absolute space and physical place. By engaging research on smart technologies with geography and GIScience, we seek to move beyond the crude, and often simplistic, conceptualizations of space and place by synthesizing the multiple dimensions of both space and place. By doing so, we can better understand human dynamics through a synergistic perspective of both space and place. The space–place (splatial) framework proposed in this article will enable us to creatively study the human dynamics in the age of smart technologies. Our approach will not only allow us to better understand human dynamics but also advance and enrich our theoretical and methodological frameworks for studying smart technologies and the profound social impacts from a geographic perspective. Challenges for the implementation of the proposed framework are discussed and directions for future research are highlighted. Key Words: GIScience, human dynamics, place, space, splatial framework." @default.
• W2971016080 created "2019-09-05" @default.
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• W2971016080 date "2019-08-29" @default.
• W2971016080 modified "2023-10-02" @default.
• W2971016080 title "Understanding the New Human Dynamics in Smart Spaces and Places: Toward a Splatial Framework" @default.
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• W2971016080 doi "https://doi.org/10.1080/24694452.2019.1631145" @default.
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