ISSS608 2017-18 T3 Assign Chen Pin-an

Mini-Challenge 2 Overview: Like a Duck to Water

Background	Data Preparation	Visualization	Observations & Insights	Project Groups

Introduction: VAST 2018 MC2

Last year, the Kasios Furniture Company was implicated in environmental damage to the Boonsong Lekagul Wildlife Preserve for both dumping toxic waste and polluting the air with chemicals from its manufacturing process. But Kasios is not taking these accusations lying down, and they deny any accusation of industrial waste dumping! Kasios’ spokespersons state that there isn’t any ground contamination near the remote ranger station that was suggested by last year’s mini-challenge 1 and 3 participants, and they have inspected that area and found it as pristine as the rest of the preserve.

Outraged ornithology professors from Mistford College journeyed out to look over the dumping site themselves and perform soil analyses. They returned to report that the site looked like there had been recent excavation and building activities going on. Boonsong Preserve rangers later confirmed that a new ranger station was being built at that site! Soil samples taken from the site were inconclusive in detecting Methylosmolene (the toxic manufacturing chemical in the suspected dumping) or any other contaminant, as new top soil had been trucked in.

Challengee

With a primary piece of evidence against Kasios now gone, investigators will need to take another approach. Professors in the Mistford College Hydrology Department have come forward with several years of water sensor readings from rivers and streams in the preserve. These samples were taken from different locations scattered throughout the area and contain measurements of several chemicals of possible interest, but they have never been analyzed due to lack of funding. Could visual analytics help reveal something in this data that could make up for the soil evidence that was destroyed?

Your task is to investigate the hydrology data from across the Preserve. You are given a map of the Preserve (with the same base as last year’s challenge), with named sampling sites indicated on the map (the names have local significance but are just mnemonics for your study) You are also provided with readings from each sampling station over time for several different chemicals and water properties.

Methodology

Time Series Analysis

Calendar Chart

The Calendar Chart will be used to explore the cycle, variability and trend of the migration data. From the calendar chart, a user can see the entire duration of either a group or the individual bird’s journey over the required time period as desired.

Line Chart

We will use the line chart based on the time, such as year, month, day and hour, to further explore the flight pattern of group and individuals, as well as how differences in individual characteristics such as sex and adulthood affect flight pattern.

Scatter Plot

Scatter plots show how much one variable is affected by another. It allows us to find out the correlation between them. In addition, it helps to identify outliers in the data set.

Geographic Analysis

Map

Various different map views will provide the visualization of the locations which the birds visit during the duration of their flight path.

Bin Chart

The bin chart will show the amount of time birds spend at each place. Coloring will be used to differentiate the time period, so that the user is able to tell the location at which the bird spends the longest time at.

Circular Migration Flow Plots

A circular migration plot displays a large amount of information on the flow of Osprey in a global/regional system as representations of position, size, and color.

Data Sets

1. Bird migration data “Osprey North and South America” available at:
https://www.movebank.org/panel_embedded_movebank_webapp

2. Environment data “Osprey North and South America” available at:
https://www.movebank.org/panel_embedded_movebank_webapp

Tools selection/package

ggplot2

ggplot2 is a system for creating graphics, based on The Grammar of Graphics. Here we are going to use the ggplot2 to make the calendar chart, line chart and scatter plot.

gganimate

gganimate is a package based on the ggplot2. It can show an animation of a ggplot2 object that contains a frame aesthetic. The frame aesthetic will determine which frame the animation is shown in.

ggmap

ggmap is a package to show the spatial data visualization. It can retrieve various online sources (e.g. Google Maps) for user to download and use as layers within the ggplot2 plotting system.

circlize

circlize is a package to show multi-layered annotations of one or more scales and relationships. It can create figures from data from genomics to visualizing migration.

move

move is a R package for accessing movebank data and visualize and statistically analyze animal movement data. It is useful to build the animal tracking model and help answer ecology questions.

tibbletime

tibble package is an extension to partition an index column by time and change the periodicity of a time-based tibble. This allows easily changing from a daily dataset to a monthly or yearly dataset.

lubridate

lubridate is an R package that makes it easier to work with dates and times. It can easily handle the timestamps including both the date and time to help address time series problems.

References

1. Graph Analytics: Visualizing and Analyzing Network Data:
https://slides.com/tskam/isss608-lesson10_ay2017-18t3/fullscreen#/

2. Visualizing and Analyzing Time-Oriented Data:
https://slides.com/tskam/isss608-lesson08_ay2017-18t3/fullscreen#/

3. Andrienko, N., & Andrienko, G. 2013a. Visual analytics of movement: An overview of methods, tools and procedures. Information Visualization, 12(1), 3–24

4. N Sander, GJ Abel, R Bauer, J Schmidt. 2014. Visualising migration flow data with circular plots. Vienna Institute of Demography, Working Papers

5. D. Spretke, H. Janetzko, F. Mansmann, P. Bak, B. Kranstauber, S. Davidson and M. Mueller. 2011. Exploration through Enrichment: A Visual Analytics Approach for Animal Movement. Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 421–424