IS428 2017-18 T1 Assign Lim Jian Quan Jaren

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Assignment Overview: Overview of the Assignment & Details

Assignment Dropbox: Dropbox with links to other peer's assignments

Link Description
Filter dates with the use of time range slider
To provide flexibility for analysts to choose the time period that they are interested to analyse.
The use of checkboxes or dropdown list requires the analyst to check/uncheck each date manually which is time-consuming. As such, a time range slider is preferred.
  1. The date/time field have to be duplicated with its data type set to “date”
  2. Add the new field to be filtered.
Filter each floor/zone using a single selection drop down list
To allow analysts to concentrate on the data collected from each level with the use of a single selection.
Use of a drop down list also allow analysts to easily choose the building level that they are interested to analyse.
  1. Configure the filter selection to be a single selection drop down list
Change and zoom of floor plans based on each floor filter
To allow for easy reference of mapping each building data elements with each zone.
When a user filters from one floor to another, the floor plan also changes to provide for quick and easy reference. Due to the space constraint, each floor plan has to be zoomed for users to identify and see the zone areas clearly.
  1. Create calculated fields for the x and y axis.
  2. Put the 2 calculated fields into the worksheet view.
  3. To hide the mark, set the colour as transparent.
  4. Navigate to Maps > Background Images. Add the floor plans into the background images and configure it according to the filter condition.
  5. Put the “floor” attribute as a filter.

Problem & Motivation

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 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 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 analyse these datasets. These datasets includes air sampler data, meteorological data, and locations maps provided by the state government, which has been monitoring the gaseous effluents from the factories through a set of sensors distributed around the factories.

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.

Specific Task

  • 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.

Dataset Analysis & Transformation Process

Datasets Provided (Sensor Data, Sensor Location, Meteorological Data)

Additional Information Provided

Interactive Visualisation

Results

Task #1

Task #2

Task #3

References

Comments