Paper Type

Complete

Paper Number

PACIS2026-1679

Description

While Internet of Things (IoT) data platforms are becoming central to managing heterogeneous data across organizational boundaries, consolidated design guidance remains fragmented. Addressing this gap, this study conducts an Artificial Intelligence (AI)-assisted systematic literature review of 53 papers. Using an IoT Data Value Chain lens, we develop a structured problem framework and derive 33 functional and non-functional design requirements. The findings show an uneven distribution of challenges across the lifecycle: while early stages like data collection and storage are technically well-addressed, semantic interoperability, cross-platform data exchange, and ecosystem governance remain persistent open issues. The study contributes design-oriented guidance that supports the architectural shift from device-centric to data-centric IoT infrastructures, connecting them to emerging federated data ecosystems.

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10-IoT

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Jul 5th, 12:00 AM

Designing IoT Data Platforms: A Structured Problem Analysis and Requirements Derivation

While Internet of Things (IoT) data platforms are becoming central to managing heterogeneous data across organizational boundaries, consolidated design guidance remains fragmented. Addressing this gap, this study conducts an Artificial Intelligence (AI)-assisted systematic literature review of 53 papers. Using an IoT Data Value Chain lens, we develop a structured problem framework and derive 33 functional and non-functional design requirements. The findings show an uneven distribution of challenges across the lifecycle: while early stages like data collection and storage are technically well-addressed, semantic interoperability, cross-platform data exchange, and ecosystem governance remain persistent open issues. The study contributes design-oriented guidance that supports the architectural shift from device-centric to data-centric IoT infrastructures, connecting them to emerging federated data ecosystems.