PERCEPTION: Semantics in a Big Data Analytics Platform

Perception is the process by which an individual selects, organizes and interprets received stimuli to give them a meaning. This project addresses the selection, organization and interpretation of results of Big Data analysis through Semantics. The term "Big Data" refers to data that can not be processed or analyzed using traditional techniques. Big Data analysis allows to extract information from these data. Many software solutions around the Apache Hadoop project are solving encountered problems through this and other complementary projects. Ideally, these advances allow to easy the access o Big Data, bringing it closer to SMEs, but the rapid development of these technologies and the lack of qualified professionals currently make SMEs have difficulties to take advantage of those technologies. The building of framewoks aimed at Big Data analysis, which allow reusing of solutions and algorithms, will make these technologies more accessible. Business Intelligence or BI comprises a set of strategies and tools focused on managing and creating knowledge through the analysis of existing data in an organization. BI tools are based on the use of an information system that is built with different data from production process, with information related to the business and economic data. This set of tools and methodologies have in common information accessibility, decision-making support, and focus to the end user. The full interconnection between the results of Big Data analysis and BI has to deal with the problem of establishing the relationship between these results and the data models used by technical analysis and dashboards of BI applications. The automatic interpretation of results of the Big Data analysis, by exposing their semantics and preserving the context of how they have been produced, are some of the challenges to be addressed when trying to add these results to business processes. In this scenario, the concept of Smart Data emerges. It is defined as the result of the process of analysis performed to extract relevant information and knowledge from Big Data, including context information and using a standardized format. By context we mean all the relevant (meta) information to interpret the analysis results. This will lead to the enforceability of these results and thus facilitating their interpretation, the easy integration with other structured data, the integration of the Big Data analysis system with the BI systems, the interconnection (in a standardized way, at a lower cost and a higher accuracy and reliability) of third parties algorithms and services, etc. The PERCEPTION project proposed here aims at integrating the techniques and results of Big Data analysis with a metadata layer of the data being analyzed, of the analysis technique, and of the domain where this is applied, by introducing the concept of Smart Data as basic idea to break the barriers to access to Big Data technologies.
Resources: 
Research lines: 
(Smart) Big Data
Status: 
Ongoing project
Financing: 
Public
Start date: 
01/2015
End date: 
12/2017
Scope: 
National
Reference: 
TIN 2014-58304-R