IS428 2017-18 T1 Assign Peh Jing Yuan

Link to assignment: Assignments

Link to dropbox: Assignment Dropbox

Overview

Mistford is a mid-size city is located to the southwest of a large nature preserve. The city has a small industrial area with four light-manufacturing endeavors. Mitch Vogel is a post-doc student studying ornithology at Mistford College and has been discovering signs that the number of nesting pairs of the Rose-Crested Blue Pipit, a popular local bird due to its attractive plumage and pleasant songs, is decreasing! The decrease is sufficiently significant that the Pangera Ornithology Conservation Society is sponsoring Mitch to undertake additional studies to identify the possible reasons. Mitch is gaining access to several datasets that may help him in his work, and he has asked you (and your colleagues) as experts in visual analytics to help him analyze these datasets.

Mitch Vogel was immediately suspicious of the noxious gases just pouring out of the smokestacks from the four manufacturing factories south of the nature preserve. He was almost certain that all of these companies are contributing to the downfall of the poor Rose-crested Blue Pipit bird. But when he talked to company representatives and workers, they all seem to be nice people and actually pretty respectful of the environment.

In fact, Mitch was surprised to learn that the factories had recently taken steps to make their processes more environmentally friendly, even though it raised their cost of production. Mitch discovered that the state government has been monitoring the gaseous effluents from the factories through a set of sensors, distributed around the factories, and set between the smokestacks, the city of Mistford and the nature preserve. The state has given Mitch access to their air sampler data, meteorological data, and locations map. Mitch is very good in Excel, but he knows that there are better tools for data discovery, and he knows that you are very clever at visual analytics and would be able to help perform an analysis.

The Task

General Task

The four factories in the industrial area are subjected to higher-than-usual environmental assessment, due to their proximity to both the city and the preserve. Gaseous effluent data from several sampling stations has been collected over several months, along with meteorological data (wind speed and direction), that could help Mitch understand what impact these factories may be having on the Rose-Crested Blue Pipit. These factories are supposed to be quite compliant with recent years’ environmental regulations, but Mitch has his doubts that the actual data has been closely reviewed. Could visual analytics help him understand the real situation?

The primary job for Mitch is to determine which (if any) of the factories may be contributing to the problems of the Rose-crested Blue Pipit. Often, air sampling analysis deals with a single chemical being emitted by a single factory. In this case, though, there are four factories, potentially each emitting four chemicals, being monitored by nine different sensors. Further, some chemicals being emitted are more hazardous than others. Your task, as supported by visual analytics that you apply, is to detangle the data to help Mitch determine where problems may be. Use visual analytics to analyze the available data and develop responses to the questions below.

The Specific Tasks

• Characterize the sensors’ performance and operation. Are they all working properly at all times? Can you detect any unexpected behaviors of the sensors through analyzing the readings they capture?Limit your response to no more than 9 images and 1000 words.

• Now turn your attention to the chemicals themselves. Which chemicals are being detected by the sensor group? What patterns of chemical releases do you see, as being reported in the data? Limit your response to no more than 6 images and 500 words.

• Which factories are responsible for which chemical releases? Carefully describe how you determined this using all the data you have available. For the factories you identified, describe any observed patterns of operation revealed in the data. Limit your response to no more than 8 images and 1000 words.

Background Information

The four manufacturing factories south of the nature preserve which Mitch is suspicious of the chemical releases and these are their coordinates:

Factory	X	Y
Roadrunner Fitness Electronics	89	27
Kasios Office FurnituExample	90	21
Radiance ColourTeExample	109	26
Indigo SoExample ardExample	120	22

In addition, these are the chemicals detected by the sensors and their following descriptions are below:

• AGOC-3A – New environmental regulations, and consumer demand, have led to the development of low-VOC and zero-VOC solvents. Most manufacturers now use one or more low-VOC substances and Mistford’s plants have wholeheartedly signed on. These new solvents, including AGOC-3A, are less harmful to human and environmental health.

• Appluimonia – An airborne odor is caused by a substance in the air that you can smell. Odors, or smells, can be either pleasant or unpleasant. In general, most substances that cause odors in the outdoor air are not at levels that can cause serious injury, long-term health effects, or death to humans or animals. However, odors may affect your quality of life and sense of well-being. Several odor-producing substances, including Appluimonia, are monitored under this program.

• Chlorodinine – Corrosives are materials that can attack and chemically destroy exposed body tissues. Corrosives can also damage or even destroy metal. They begin to cause damage as soon as they touch the skin, eyes, respiratory tract, digestive tract, or the metal. They might be hazardous in other ways too, depending on the particular corrosive material. An example is the chemical Chlorodinine. It has been used as a disinfectant and sterilizing agent as well as other uses. It is harmful if inhaled or swallowed.

• Methylosmolene – This is a trade name for a family of volatile organic solvents. After the publication of several studies documenting the toxic side effects of Methylosmolene in vertebrates, the chemical was strictly regulated in the manufacturing sector. Liquid forms of Methylosmolene are required by law to be chemically neutralized before disposal.

The Data

The data available consists of sensor readings from a set of air-sampling sensors and meteorological data from a weather station in proximity to the factories and sensors. The factories and sensors locations are provided in terms of x,y coordinates on a 200x200 grid, with (0,0) at the lower left hand corner (southwest). The sensors map shows the locations of the sensors and factories by number for the sensors and by name for the factories. The datasets given will go through some data cleaning in order to be visualized using Tableau:

• Sensor Data.xlsx
• Sensor Location.xlsx
• Meteorological Data.xlsx

Data Cleaning

The following are the steps to clean the datasets as mentioned above:

No.	File	Steps Taken
1	Meteorological Data.xlsx
2	Meteorological Data.xlsx
3	Sensor Location.xlsx	Change the file name to Location Data.xlsx
4	Location Data.xlsx
5	Location Data.xlsx
6	Location Data.xlsx
7	Location Data.xlsx
8	Sensor Data.xlsx

Data Configuration (Tableau)

Minor configuration needs to be done in order to build and link the data sources to one another effectively. Below are the steps:

No.	File	Steps Taken
1	Location Data.xlsx, Sensor Data.xlsx
2	Meteorological Data.xlsx

Interactive Visualization

Link to the interactive visualization: <to be uploaded>

The dashboard is built for screen resolution width of 1366. Please ensure your screen resolution width is set to this in order to have the best experience.

The following are some of the interactivity elements and charts used throughout the dashboards and the rationale behind them. User can read this or simply skip into using the visualization tool as instructions will be given in each dashboard.

Homepage

Feature	Usage	How to build?
Tableau Story Mode	To provide user the flexibility of moving from one dashboard to the other easily. Control shows the flow of how this visualization tool should be used.	Create new story on tableau Add 4 “stories” on the story and make the first story an introduction and other 3 stories containing one dashboard each
Introduction	Introduce why this visualization is made	Simply insert a text object.
Aim to achieve	Inform user what this visualization tool aims to achieve	Simply insert a text object.
Instruction	Teach the user how to use this visualization tool	Simply insert a text object.

Overview

Feature	Usage	How to build?
Dashboard description	To provide user some information of what this current dashboard aims to do and includes an instruction on using it. Each dashboard has its respective dashboard description.	Simply insert a text object.
Filter by chemical	To allow user to filter the data by chemical. If the user wants to view the chemical readings of a certain chemical, he can simply select from the dropdown list and choose that chemical. Therefore, the use of this filter allows the user to analyze each chemical’s readings instead of summation of all the chemicals’ readings.
Chart description	To provide user some information what this chart shows and includes an instruction on how to see more details. Each chart has its respective chart description.	Simply edit the title of the chart.
A: Trellis Plot	This trellis plot allows the user to visualize the selected chemical’s readings across the 9 monitors. The readings are in hours and across the 3 months’ worth of data collected.	-

Identifying Patterns from Different Perspective

Cycle Plot

Calendar Heatmap

Feature	Usage	How to build?
Filter by sensor	To allow user to filter the data by sensor. If the user wants to view the chemical readings of a certain sensor, he can simply select from the dropdown list and choose that sensor. Therefore, the use of this filter allows the user to analyze chemical readings from each sensor instead of summation of all the chemicals’ readings.
Viewing Format	To provide user another alternative to view the Weekday/Week cycle plot by having a “calendar heatmap”
A: Cycle Plot	These cycle plots of each chemical allow the user to visualize the selected sensor’s chemical readings. With cycle plots, it may be easier to identify certain patterns to these chemical readings.	-
B: Calendar Heatmap	These calendar heatmap of each chemical allow the user to visualize the selected sensor’s chemical readings. With calendar heatmap, it may be easier to identify certain patterns to these chemical readings. This is another alternative to the cycle plot as some user prefers to view in heatmap.	-

Drill and Discover

Comments

Any comments are welcomed.

Credits

Nil