Towards a New Architecture for Data Multilevels Interactive Visualization in Big Data Domains

The progress of the Big Data technology in the different domains continues to reveal, day after day, so many issues affecting this field. The data presentation is a part of these issues, because it is directly related to the user that requires visualization to facilitate the data collection as well as the analysis and the utilization of results as needed. However, implementing visualization requires a low latency. Therefore, many problems regarding the Big Data major characteristics, namely volume, variety and velocity arise and should be addressed. Knowing that each Big Data domain has specific peculiarities, it remains far from thinking of a generic solution to the visualization problem. This latter is manifested in different kinds. One of these kinds that is prevalent in Big Data domains is hierarchical visualization, which is based on presenting data by levels, while respecting the relations between them. In this paper, we propose an architecture composed of modules that cover the Big Data visualization process, taking into account the hierarchical relations between data. In order to valorise our proposal, we implement a prototype that supports the modules composing our architecture which are developed using different tools such as Scrapy and D3js libraries. The experimentation, which was carried out in the educational domain, showed its applicability to real systems.