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A higher-order data flow model for heterogeneous Big Data

Simon Price, Peter A Flach, A higher-order data flow model for heterogeneous Big Data. IEEE International Conference on Big Data (BigData 2013). ISBN 978-1-4799-1292-6, pp. 569–573. October 2013. PDF, 194 Kbytes. External information

Abstract

We introduce a data flow model that supports highly parallelisable design patterns, but which also has useful properties for analysing data serially over extended time periods without requiring traditional Big Data computing facilities. The model ranges over a class of higher-order relations which are sufficiently expressive to represent a wide variety of unstructured, semi-structured and structured data. Using JSONMatch, our web service implementation of the model, we show that the combination of this model and higher-order representation provides a powerful and extensible framework that is particularly well suited to analysing Big Variety data in a web application context.

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