Towards Semantic Model Extensibility in Interoperable IoT Data Exchange Platforms

Abstract

Data exchange platforms and marketplaces are gain- ing popularity as next-generation IoT data monetization and discovery solutions. They utilize different information models to represent heterogeneous data in a uniform and interoperable manner. Those platforms have the need to dynamically extend and enrich their semantic models in order to accommodate new data offerings. Using the BIG IoT semantic models and the resulting knowledge graph as the basis, we propose a new approach to incorporate user-defined semantic annotations into the model on the fly, which firstly makes them usable before their incorporation into an official release of the model, and secondly minimizes the efforts required from ontology engineers in the model evolution phase. The process of new annotation inclusion is based on the dynamic generation of user interface elements (e.g. web forms) from annotation patterns stored in the BIG IoT knowledge graph. By filling in such web forms, a cooperative user creates an unambiguous description of a new concept meaning and connects the concept with related ones, thus, preserving knowledge graph integrity and model consistency.