Scalable semantic aware context storage

• We analyse efficient ways to deal with unstructured information.
• Context information should be organized through a bottom-up characterization.
• We discussed and analyse four possible context storage solutions, and two context organization schemes.
• 1-dimension model leads to poor scalability and semantic extraction.

The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes’ diversity and propose a novel dd-dimension organization model. Our evaluation shows that dd-dimension model improves scalability and semantic extraction.