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Modeling the Internet of Things and People: A Foundational Approach



Spencer J. Breiner, Eswaran Subrahmanian, Ram D. Sriram


As we extend the reach of the Internet through sensing and automation, networked systems interact more and more of our daily lives, requiring much greater sensitivity to social networks and greater robustness in the face of human behavior. A tremendous amount of messy, heterogeneous data passes through such networks; integrating and applying that data so that it can be used for seamless interoperability and higher level reasoning requires conversion into some higher abstraction. To facilitate this conversation, we need standard information models which accurately capture objects, events, and other processes, and which support a variety of generic model operations such as linking, updating and scaling. In this paper, we argue that category theory, a branch of abstract mathematics, provides a firm conceptual foundation for information modeling which already meets most of these criteria. We close with a discussion of some challenges for exploiting category theory in applied contexts.
Proceedings Title
1st International Workshop on Semantic Interoperability for the IoT
Conference Dates
November 7-9, 2016
Conference Location


Internet of Things, Category Theory, Interoperability


Breiner, S. , Subrahmanian, E. and Sriram, R. (2016), Modeling the Internet of Things and People: A Foundational Approach, 1st International Workshop on Semantic Interoperability for the IoT, Stuttgart, -1 (Accessed July 23, 2024)


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Created November 1, 2016, Updated October 12, 2018