Cities are areas where Big Data is having a real impact. Predictions say that cities will generate over 4.1 terabytes per day per square kilometer of urbanized land area by 2016. Handling efficiently such amounts of data and processing them in a real-time is already a challenge. A combination of tools integrated in a real-time data processing platform provides support for intelligent Smart City applications, for actively and autonomously adaptation and smart provision of services and content, using the advantages of contextual information. We will present the scientific motivation of DataWay project by clearly highlighting the approached problems related to real-time processing, high-throughput data management, self-* techniques and smart cities applications. The following aspects will be revealed:

  1. the importance of the problem from the scientific, technologic, socio-economic or cultural point of view;
  2. the difficulty elements of the problem;
  3. the limits of the current approaches.

One of the important issues existing in service-oriented systems is to eliminate the human factor involvement through the use of devices that can collect and analyze the context that will send information to a control system servers, which after a processing phase (most often in real time), will generate automatic actions that will be translated into reactions of individuals. Existing scenarios are based on Vehicular Cloud connectivity to a central system, one of current research issues being decentralized communication and ad-hoc analysis of data collected.

The main objectives of DataWay project are oriented on Making sense of Big DataHigh-throughput data management, and Self-* properties as intelligent support for Big Data reduction.