The amount of data in our world has been exploding. Hence, integrating, managing and analyzing large amounts of data â i.e. big data - will become a key issue for businesses for better operating and competing in todayâs markets. We strongly believe that big data are really useful if used in a smart way. So we introduce the concept of Smart Data that is web and enterprise structured and unstructured big data with explicit and implicit semantics that leverages context to understand intent for better driving business processes and for better and more informed decisions making. This paper proposes a language able to give a representation of big data based on ontologies and a system that implements an approach capable to satisfy the increasing need for efficiency and scalability in semantic data management. The proposed MANTRA Language allows for: (i) representing the semantics of data by knowledge representation constructs; (ii) acquiring big data from disparate heterogeneous sources (e.g. data bases, documents), integrating and managing them; (iii) reasoning and querying with big data. The syntax of the proposed language is partially derived from logic programming, but the semantic is completely revised. The novelty of the language we propose is that a class can be thought of as a flexible collection of structurally heterogeneous individuals that have different properties (schema-less). The language also allows executing efficient querying and reasoning for revealing implicit knowledge. These have been achieved by using a triple-based data persistency model and a scalable No-SQL storage system.
['Ermelinda Oro', 'Massimo Ruffolo', 'Pietro Gentile', 'Giuseppe Bartone']
Towards a Language for Representing and Managing the Semantics of Big Data