A Distributed and Scalable Solution for Applying Semantic Techniques to Big Data

摘要

The digital revolution changes the way culture and places could be lived. It allows users to interact with the environment creating an immense availability of data, which can be used to better understand the behavior of visitors, as well as to learn about tlieir thoughts on what the visit creates excitement or disappointment. In this context, Big Data becomes immensely important, making possible to turn this amount of data in information, knowledge, and, ultimately, wisdom. This paper aims at modeling and designing a scalable solution that integrates semantic techniques with Cloud and Big Data technologies to deliver context aware services in the application domain of the cultural heritage. The authors startedfrom a baseline framework that originally was not conceived to scale when huge workloads, related to big data, must be processed. They provide an original formulation of the problem and an original software architecture that fulfills bothfunctional and not-functional requirements. The authors present the technological stack and the implementation of a proof of concept.