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International audience ; Internet of Things (IoT) is one of the key technologies in the industry 4.0 era and promotes the interconnection of numerous data sources in several sectors such as ecology, agriculture, or healthcare. Meanwhile, each entity within these connected environments carries its unique requirements and individual goals. For connected environments to gain greater legitimacy among end users, service-oriented systems must adopt a new paradigm that allows end users to move from being passive consumers to actively participate in monitoring their own data at different stages of its lifecycle. In this context, a usage model based on ontological reasoning can be integrated within a data provenance mechanism to help create a trust worthy environment. In this paper, we introduce a vision for democratizing service-oriented systems. We discuss potential new directions that need to be pursued in the area of data management. Then, we review existing schemes applied in IoT data provenance and rely on the requirements to discuss their strengths and weaknesses. Finally, we summarize a number of potential solutions to direct future research.

International audience ; Internet of Things (IoT) is one of the key technologies in the industry 4.0 era and promotes the interconnection of numerous data sources in several sectors such as ecology, agriculture, or healthcare. Meanwhile, each entity within these connected environments carries its unique requirements and individual goals. For connected environments to gain greater legitimacy among end users, service-oriented systems must adopt a new paradigm that allows end users to move from being passive consumers to actively participate in monitoring their own data at different stages of its lifecycle. In this context, a usage model based on ontological reasoning can be integrated within a data provenance mechanism to help create a trust worthy environment. In this paper, we introduce a vision for democratizing service-oriented systems. We discuss potential new directions that need to be pursued in the area of data management. Then, we review existing schemes applied in IoT data provenance and rely on the requirements to discuss their strengths and weaknesses. Finally, we summarize a number of potential solutions to direct future research.