| Summary: | There has been an increase in the amount of data collected in the past few years. There has been research that has gone into finding innovative ways to discover knowledge and to visualize useful information from the data collected. The Final Year Project aims to create a front-end application that will be used to visualize expert networks. In this report, we will be using examples from an expert network of the professors from the School of Computer Science and Engineering, Nanyang Technological University. Each professor will have a research group that they belong to, research interests that they have, universities that they have studied in and the funding bodies that they have received funding from as their characteristics. The front-end application will be used to study the relationships between the professors. There were some issues and challenges with finding the libraries suitable for the project due to a plethora of visualization libraries in Javascript. Proper research has to be conducted to choose a library in order to make the front-end application as user friendly and as easy for extension of features as possible. Also, we aim to find ways to integrate a network graph with the world map, and due to the lack of research materials, innovative ways to integrate and visualize them together need to be thought up. The final front-end application is named SAMMIE Expert Visualizer, and it was developed with the philosophy of user-friendliness to visualize an expert network. SAMMIE Expert Visualizer is also quite versatile and should be able to work with any backend application written in any language as long as the backend application sends data to it using the agreed-upon JSON format from the REST API, and the expert network is similar to the current expert network of professors. SAMMIE Expert Visualizer will also allow the network graph and the world map to be studied separately. Both the network graph and the world map are zoomable and interactive. Hence, connections between the experts could be adequately studied. Rigorous testing was conducted to ensure that SAMMIE Expert Visualizer is behaving as expected. However, there are some limitations. The current implementation does not integrate the network graph and the world map properly as the two visualizations still appear to be incohesive. More work can be carried out to make the visualizations appear to be more integrated. The current implementation is also based on the expert network of professors from School of Computer Science and Engineering of Nanyang Technological University, so more work will need to be conducted to make the application more versatile for more general purposes. Lastly, the front-end application has to be deployed eventually, and the current work has only been done in a local environment. Deploying the front-end application could lead to new issues such as security problems and more work has to be carried out to solve them.
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