Big Data Visualization System Design and Research of Interaction between Colorectal Cancer and Drinking Water
Date Issued
2016
Date
2016
Author(s)
Wang, Hao
Abstract
The core of this thesis, Data visualization, is a way of user communication with data. Using D3.js tools to build this disease mapping system, which allows user to feel the change of the data by events selection and animation. With the Disease Map function, users are able to observe the distribution of the disease in spatial aspect. With the Disease Trend function, users are able to read the prevalence, count, and average age etc. of any city in time scope. These functions, also provide a interface to compare data between different cities. Loading environment database dynamically, binding with Hybrid Bubble Chart function by observing the position and the radius change of the Bubbles at different time points and let users be able to feel whether is there any relative trend between environment attributes and the disease occurrence. We used Nation Health Insurance Research Database (NHIR) as the database of this system which contains medical records of a million patients. In order to deal with this enormous amount of patient data, we select MongoDB, which is a distributed document NoSQL database. With mapreduce technique we can run complicated operations. Eliminating those data which doesn’t fit the query condition, then restructure the data by geographical distribution. By using Cache system to keep our database away from busy accessing to increase the query efficiency. We also applied MVC framework to make this system more expendable and able to load specified prediction module or function module depend on the ICD-9 code user input.
Subjects
Nation Health Insurance Research Database
NoSQL Database
Disease Mapping
Big Data
Data Visualization
SDGs
Type
thesis
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