Large Graph Data Visualisation on the Web

Graph databases provide a form of data storage that is fundamentally different from a relational model. The goal of this thesis is to visualize the data and determine the maximum volume that current web browsers are able to process at once. For this purpose, an interactive web application was implemented. Data are stored using the RDF (Resource Description Framework) model, which represents them as triples with a form of subject - predicate - object. Communication between this database, which runs on server and client is realized via REST API. The client itself is then implemented in JavaScript. Visualization is performed by using the HTML element canvas and can be done in different ways by applying three specially designed methods: greedy, greedy-swap and force-directed. The resulting boundaries were determined primarily by measuring time complexities of different parts and were heavily influenced by user's goals. If it is necessary to visualize as much data as possible, then 150000 triples were set to be the limiting volume. On the other hand, if the goal is maximum quality and application smoothness, then the limit doesn't exceed a few thousand