Cross Fertilizing Data through Web of Things APIs with JSON LD
Internet of Things (IoT) data are mostly cloistered in closed IoT infrastructures and vertically integrated applications, failing to leverage the potential interlinking of corresponding APIs. We propose a data model based on JSON LD, in which semantics are added to Web of Things (WoT) APIs, enhancing their interoperability and evolvability by the composition of nested contexts factoring out shared generic categories. According to this model, we present the blueprint of a framework to automatically and iteratively enrich and interconnect WoT APIs, through a process of resource crawl, syntax extraction, semantic annotation and context generation. Based on our propositions, we demonstrate the idea of cross fertilizing data with a scenario involving three separate IoT infrastructures, showing how their data are linked and interoperated.
SALAD@ESWC