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8.4 The Data Interoperability 291
Fig. 8.5 Semantic interoperability for Internet-connected objects.
processes. However, the data collected by different sensors and devices from
the real world is dynamic, the quality of data can vary over different devices
and through the time, the data is location and time dependent and there are large
number of resources than can create deluge of heterogeneous data. This makes
processing, integrating and interpreting the real world data a challenging task.
While objects in IoT can be integrated into the service and application
domain and devices can sense the environment, change the status of the
objects, and respond to events, interpreting the data for managing the resources
and their communication with each other and enabling seamless interaction
between high-level services and devices are complex tasks that involve different
technologies and solutions. Considering the fact that many of the devices
and resources in IoT are heterogeneous, interoperability between different
devices and their data is one of the key issues in this domain. The research
in this area has recently gained momentum and is supported by new communication
protocols, standards and methods that consider the dynamicity and
heterogeneity of the underlying devices and resources and enable internetworking
and interactions on IoT. However, the current IoT data communications
often rely on binary or syntactic data models that are often unable to
provide machine-interpretable meanings for the data. This hinders the creation
of common tools and mechanisms to process and interpret the IoT data on a