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Testing and experimentation are crucial for promoting innovation and buildingsystems that can evolve to meet high levels of service quality. IoT data thatbelong to users and from which their personal information can be inferred arefrequently shared in the background of IoT systems with third parties forexperimentation and building quality services. This data sharing raises privacyconcerns especially since in most cases the data are gathered and sharedwithout the user's knowledge or explicit consent or for different purposes thanthe one for which the data were initially gathered. With the introduction ofGDPR, IoT systems and experimentation platforms that federate data fromdifferent deployments, testbeds and data providers must be privacy-preserving.The wide adoption of IoT applications in scenarios ranging from smart cities toIndustry 4.0 has raised concerns with respect to the privacy of users' datacollected using IoT devices. Many experimental smart city applications are alsousing crowdsourcing data. Inspired by the GDPR requirements, we propose an IoTontology built using available standards that enhances privacy, enablessemantic interoperability between IoT deployments and supports the developmentof privacy-preserving experimental IoT applications. On top, we proposerecommendations on how to efficiently use the ontology within IoT testbed andfederating platforms. Our ontology is validated for different qualityassessment criteria using standard validation tools. We focus on"experimentation" without loss of generality, because it covers scenarios fromboth research and industry, that are directly linked with innovation.

GDPR-inspired IoT Ontology enabling Semantic Interoperability, Federation of Deployments and Privacy-Preserving Applications