Taming velocity and variety simultaneously in big data with stream reasoning: tutorial

@article{Valle2016TamingVA,
  title={Taming velocity and variety simultaneously in big data with stream reasoning: tutorial},
  author={E. D. Valle and D. Dell'Aglio and A. Margara},
  journal={Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems},
  year={2016}
}
Many "big data" applications must tame velocity (processing data in-motion) and variety (processing many different types of data) simultaneously. The research on knowledge representation and reasoning has focused on the variety of data, devising data representation and processing techniques that promote integration and reasoning on available data to extract implicit information. On the other hand, the event and stream processing community has focused on the velocity of data, producing systems… Expand
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