Exploration and Visualization in the Web of Big Linked Data: A Survey of the State of the Art

TL;DR

This survey reviews the current state of exploration and visualization systems for large Linked Data, highlighting challenges, approaches, and how existing systems meet modern requirements in scalability and usability.

Contribution

It provides a comprehensive overview of recent approaches and systems in Linked Data visualization, identifying gaps and future directions in scalability and user interaction.

Findings

Most systems address scalability challenges effectively.

Current systems vary in how well they meet modern requirements.

There is a need for more integrated exploration and visualization tools.

Abstract

Data exploration and visualization systems are of great importance in the Big Data era. Exploring and visualizing very large datasets has become a major research challenge, of which scalability is a vital requirement. In this survey, we describe the major prerequisites and challenges that should be addressed by the modern exploration and visualization systems. Considering these challenges, we present how state-of-the-art approaches from the Database and Information Visualization communities attempt to handle them. Finally, we survey the systems developed by Semantic Web community in the context of the Web of Linked Data, and discuss to which extent these satisfy the contemporary requirements.