Abstract
ETL (Extraction-Transform-Load) tools, traditionally developed to operate offline, need to be enhanced to deal with various, fast, big and fresh data and be executed on the edge of the network during the acquisition process. In this dissertation we wish to develop facilities that from one side make easy, scalable and controllable the development of data acquisition plans that can be executed on the edge of the network during loading and transmission. From the other side, we wish to deal with the variety of the data and verify when the developed data acquisition plans adhere to the common semantics adopted in the Domain Ontology. These facilities are included in StreamLoader, a web application tailored for the specification and monitoring of sensor data acquisition plans.
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Ferrari, L. (2017). Dealing with Velocity and Variety in the Acquisition of Heterogeneous Sensor Data. In: Ciancarini, P., et al. Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10180. Springer, Cham. https://doi.org/10.1007/978-3-319-58694-6_35
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DOI: https://doi.org/10.1007/978-3-319-58694-6_35
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