An Associative Engines Based Approach Supporting Collaborative Analytics in the Internet of Cultural Things

In this paper we illustrate an integrated approach supporting an information system which combines Business Intelligence, Big Data, Internet of Things, GeoSpatial information processing, multimedia resources, structured and unstructured content analysis with Semantic techniques, and Social Network Analysis. This system exploits the specific opportunities provided by Associative in-memory technologies in the context of Cloud Computing and Collaborative processes and experiments the use of semantic technologies to mitigate the efforts involved in merging, and analyzing information incoming from different sources. The primary aim is supporting Cultural Heritage (CH) Asset crowdsourcing, promotion, publication, management and usage. Preliminary results are reported from ongoing experimentation, focused on visitors interests and behaviour analysis performed by monitoring, comparing and combining information from different types of populations and visits: on-site ad-hoc (exhibitions, museums, cultural events, etc.), territorial (eg. Historical downtown, touristic areas including relevant CH resources) and Virtual - Worldwide Internet based visits.