Extracting valuable information from raw data is especially difficult considering the velocity of growing data from year to year and the fact that 80% of data is unstructured. In addition, data sources are heterogeneous (various sensors, users with different profiles, etc.) and are located in different situations or contexts. This is why the Smart City infrastructure runs reliably and permanently to provide the context as a “public utility” to different services. Context-aware applications exploit the context to adapt accordingly the timing, quality and functionality of their services. The value of these applications and their supporting infrastructure lies in the fact that end-users always operate in a context: their role, intentions, locations and working environment constantly change. To address these aspects in the context of big data processing,
DataWay project will study the possibility to introduce new models for data representation and aggregations in order to optimize the reduction and retrieval process.
Tools like Amazon Kinesis or IBM Twitter Storm will be analyzed as possible solutions.