DEAN 690_Week 9

Assignment: Week 9

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An explanation of data visualization by storytelling.

EXCLUSIVE - Storytelling through data visualization – From museum displays to autonomous system interfaces

http://www.opengovasia.com/articles/7460-exclusive---storytelling-through-data-visualisation-from-museum-displays-to-autonomous-system-interfaces

Details as the following statement:

Challenge:

1^st data size

2^nd interface of open datasets websites

3^rd telling stories

Computing resources:

Expensive facilities: Computed Tomography scanner.

Ideas of public oriented use:

A science center which is similar as research center are providing astronomical data for storytelling.

Interactive communication of science evolving:

1^st Micro-level

            Take human cell as example, the author mentions exploring data and the molecular structure inside a cell.

2^nd Time

            Using statics data at time resolution and then intrigue audiences to visualize data. The author said “If you are going to visualise things, like blood flow, dynamically over time, then you have to replace say 20 GB of data on your scan for each time-step in the animation. “

Dataset

This dataset contains Radioactivity in Fish from 2011-2016 in Canada. It must can create different graphs to compare different years’ values.

Topic: Health Canada Analyses of the Radioactive Content of Fish Samples from Canada’s West Coast

http://open.canada.ca/data/en/dataset/d1b39de7-e525-4cfa-a605-af38bf174555

Questions

41. What is NLP? How is it related to Machine Learning?

Natural Language processing is using machine to interpret human language. Human produce a system to understand what human want to say. Then, machine learning is compute questions’ pattern and build a system to solve problems automatically. Therefore, Natural language is in machine learning field.

Reference:

[1] M. Jordan and T. Mitchell, "Machine learning: Trends, perspectives, and prospects", Science, vol. 349, no. 6245, pp. 255-260, 2015.

News

This news proposes an issue about data science to support policy making. It mentions Google and Facebook working on predictive analytics and supporting decision making. This news also takes Amazon and Apple as example to use machine learning to give services for customers. Thus, these ideas and tech supports could provide public policy new method on order to make better decision.

Topic: Collecting extensive data on you can improve policy making

https://www.thestar.com/opinion/commentary/2017/03/27/collecting-extensive-data-on-you-can-improve-policy-making.html

A news mentioned about Capital Bikeshare dataset and Capital Bikeshare GPS Study.

Link: http://technical.ly/dc/2016/06/22/check-cool-capital-bikeshare-visualizations/

Project Idea

From the link, data visualization includes 7 steps: Acquire, Parse, Filter, Mine, Represent, Refine, and Interact.

Acquire means obtaining the dataset.

Parse is to structure data and then separate categories.

Filter means cleaning data.

Mine is related to statistics or data mining to find patterns and understand meaning of dataset. Represent is creating simple graphs, such as line graphs, bar charts, and so on.

Refine focus on remodel the visualization graphs and also includes simple graphs.

Interact means give brain storming on new graphs in the future.

Topic: The Data Visualization Process

Link: https://www.dashingd3js.com/the-data-visualization-process