Difference between revisions of "ISSS608 2017-18 T3 Assign Miko Tan Mei Jia Data Preparation"
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<font size="5"><font color="#373f51">'''Methodology & Dashboard Design'''</font></font> | <font size="5"><font color="#373f51">'''Methodology & Dashboard Design'''</font></font> | ||
+ | ==Approaching the problem== | ||
+ | <p>To investigate hydrology data for soil contamination, specific chemical contaminants should be surfaced for analysis. This is especially important considering there are a total of 106 measures in the given hydrology data. Research was done to find the key contaminants in soil that are in close proximity to industrial sites, and have significant environment impact. </p> | ||
+ | |||
+ | <p> In addition to the toxic manufacturing chemical Methylosmolene, heavy metals have been identified as key industrial contaminants of soil and the following will be analysed: | ||
+ | |||
+ | *Arsenic | ||
+ | *Cadmium | ||
+ | *Chromium | ||
+ | *Nickel | ||
+ | *Cobalt | ||
+ | *Manganese | ||
+ | *Copper | ||
+ | *Lead | ||
+ | *Mercury | ||
+ | *Selenium | ||
+ | *Zinc | ||
+ | |||
+ | The selection of heavy metals is based on the text ''Heavy Metals in Soils: Trace Metals and Metalloids in Soils and their Bioavailability, Third Edition'' edited by Brian J. Alloway. | ||
+ | |||
+ | <p>A dashboard is created to visualize the hydrology data in a way such that the 3 questions in the Mini-challenge may be answered. The dashboard is designed for Mistford College professors to analyse historical data from water sensors in the preserve. </p> | ||
+ | |||
+ | <p><b>1. Characterize the past and most recent situation with respect to chemical contamination in the Boonsong Lekagul waterways.</b></p> | ||
+ | A control chart showing sensor readings over time will be used to look at the trends in chemical contamination in the preserve. | ||
+ | |||
+ | <p><b>2. Finding anomalies in the waterway samples dataset and proposing data collection changes. </b></p> | ||
+ | A highlight table showing data taken by sensor readings will be used to find anomalies in the data. | ||
+ | |||
+ | <p><b>3. Recommending changes in sampling strategy. </b></p> | ||
+ | The dashboard will be used as a whole to identify areas of improvement in the hydrology data. | ||
+ | |||
==Dashboard Design== | ==Dashboard Design== | ||
− | + | [[File:Dashboard.png|600px|center]] | |
<p>View the interactive Tableau dashboard here: [(insert link here) Link to tableau dashboard]</p> | <p>View the interactive Tableau dashboard here: [(insert link here) Link to tableau dashboard]</p> | ||
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<tr> | <tr> | ||
<td><b> 2. Control Chart: Setting limits for sensor readings </b> | <td><b> 2. Control Chart: Setting limits for sensor readings </b> | ||
− | <br> | + | <br>Average readings over time are plotted and coloured by station location. Reference lines are added to visually alert the user when there is a statistically significant change to the reading of a selected measure. These reference lines are the overall average and upper/lower limits (3 standard deviations above/below the mean). |
− | <br>Clicking on a reading on the | + | <br>Clicking on a reading on the chart will highlight the reading on the other charts. |
</td> | </td> | ||
<td>[[File:ControlChart.png|500px|center]]</td> | <td>[[File:ControlChart.png|500px|center]]</td> | ||
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<tr> | <tr> | ||
<td><b> 3. Boxplot: Distribution of sensor readings </b> | <td><b> 3. Boxplot: Distribution of sensor readings </b> | ||
− | <br>A boxplot showing the distribution of sensor readings by location is created in order to detect statistical outliers in the sensor readings | + | <br>A boxplot showing the distribution of sensor readings by location is created in order to detect statistical outliers in the sensor readings. |
<br>Clicking on a reading on the boxplot will highlight the reading on the other charts. | <br>Clicking on a reading on the boxplot will highlight the reading on the other charts. | ||
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<tr> | <tr> | ||
− | <td><b> 4. Filters</b> | + | <td><b> 4. Highlight chart: Showing trends in readings over time by location </b> |
+ | <br>A highlight chart showing the change in readings over time by location is created to achieve a visual overview of measure values over time. | ||
+ | </td> | ||
+ | <td>[[File:HighlightChart.png|500px|center]] | ||
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td><b> 5. Filters</b> | ||
<br>Users of the dashboard would be able to choose the date aggregation level (by day, week, month, quarter or year), select a date range during which the sensor readings were taken and select a particular chemical to monitor. The units of measurement for the selected chemical is also shown. | <br>Users of the dashboard would be able to choose the date aggregation level (by day, week, month, quarter or year), select a date range during which the sensor readings were taken and select a particular chemical to monitor. The units of measurement for the selected chemical is also shown. | ||
<br> | <br> |
Revision as of 02:55, 8 July 2018
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Methodology & Dashboard Design
Approaching the problem
To investigate hydrology data for soil contamination, specific chemical contaminants should be surfaced for analysis. This is especially important considering there are a total of 106 measures in the given hydrology data. Research was done to find the key contaminants in soil that are in close proximity to industrial sites, and have significant environment impact.
In addition to the toxic manufacturing chemical Methylosmolene, heavy metals have been identified as key industrial contaminants of soil and the following will be analysed:
- Arsenic
- Cadmium
- Chromium
- Nickel
- Cobalt
- Manganese
- Copper
- Lead
- Mercury
- Selenium
- Zinc
The selection of heavy metals is based on the text Heavy Metals in Soils: Trace Metals and Metalloids in Soils and their Bioavailability, Third Edition edited by Brian J. Alloway.
A dashboard is created to visualize the hydrology data in a way such that the 3 questions in the Mini-challenge may be answered. The dashboard is designed for Mistford College professors to analyse historical data from water sensors in the preserve.
1. Characterize the past and most recent situation with respect to chemical contamination in the Boonsong Lekagul waterways.
A control chart showing sensor readings over time will be used to look at the trends in chemical contamination in the preserve.
2. Finding anomalies in the waterway samples dataset and proposing data collection changes.
A highlight table showing data taken by sensor readings will be used to find anomalies in the data.
3. Recommending changes in sampling strategy.
The dashboard will be used as a whole to identify areas of improvement in the hydrology data.
Dashboard Design
View the interactive Tableau dashboard here: [(insert link here) Link to tableau dashboard]
Methodology
Description | Illustration |
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1. Symbol Map: Mapping out sensor readings by location
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2. Control Chart: Setting limits for sensor readings
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3. Boxplot: Distribution of sensor readings
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4. Highlight chart: Showing trends in readings over time by location
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5. Filters
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