Skip to content

Shilpa Pandit

Miss. Shilpa Pandit completed her Bachelors of Engineering (BE) in Computer Science from University of Mumbai and is currently pursuing MSc in Advanced Computer Science from University of St Andrews. The project on which she is currently working on for dissertation is called “A Time Capsule Visual Interface” (St Andrews Time Capsule Project) under the supervision of Professor Aaron Quigley.

The St Andrews Time Capsule project is motivated by the 600th anniversary of the University of St Andrews. The purpose of this project is to provide “an anthropological snapshot of every aspect of the University and the town of St Andrews”. The aim of project is to collect wide range of details about 600th anniversary and let people explore this data whenever required. The data can be collected from various sources such as Facebook pages, Twitter, emails, library browsing, photographs, etc. and will be stored in a virtual time-capsule.

The aim of this particular part of the project “A Time Capsule Visual Interface” is to develop an information visualization tool which will help users to explore the voluminous data which will be present in virtual time capsule. The architecture of the project is combination of two separately developed systems which will be connected using a plugin. One of the systems is this project deals with visualisation and other system will be graph database. A plugin will be responsible for transferring data between the two systems, rendering data from the graph database to the table format and modifying the database with the changes made through user interface. While rendering the data from graph database, we are assuming that output from the graph database will be in form of nodes and edges. As this application will be using publicly available data, the target users will be people who don’t have much knowledge about visualisation.Therefore, the visualisation which will be developed will be easy to understand and informative. The visualisation will be based on three aspects of data display ego-centric, temporal and geographic. Considering the temporal dimension, a user will be able to visualize data from particular period. In the geographic dimension, users can visualise data which is from a particular geographic location. In egocentric view, users can visualise data with respect to particular person. As the data is stored in a graph database in the form of nodes, edges and properties assigned with it a query on the database will be  based on the three criteria or properties present in the database or a combination. In this way, we aim to support a wide range of exploratory queries from the database.