The theme of my project is to focus on where earthquakes occur, how frequently they occur, and the depth, horizontal distance, and magnitude of these natural disasters.
Earthquakes pose a threat to everyone's lives. Every year earthquakes destroy homes, destroy cities, and can ultimately destroy lives. I have chosen to highlight these issues through my data visualizations as everyone can be a victim of an earthquake. The goal of this project is to showcase the devastating numbers of earthquakes that have occurred all over the world. Through these visuals, the audience is able to fully grasp just how powerful these earthquakes can become as all data points have a minimum magnitude of 5.5. You will see, as I have seen, there is an incredible number of earthquakes that strike the world each year. It is important that one is prepared for the next one around him/her, for it's only a matter of time.
As shown through visualization 1, there is a positive trend showing the gradual increase in the number of earthquakes occurring each year. The bar chart assists the audience in seeing the overall climb in frequency of these natural disasters.
For the interactivity of this graph, one will be able to slide either the left or right bar to see the number of earthquakes given for those specific years. This technique is known brushing. One can click on a non-highlighted section to view just that specific year. The range of years will be shown on top. The number for each graph is located above each bar in red.
For the first graph, I visualized the number of records and years from the dataset. The y-axis is the total number of records for a specific year, and the x-axis is the year itself. I implement a bar chart. I filtered the data to just include years and total numbers of records per year. This is the only visualization that has a filtered dataset from the original.
The goal behind my most in-depth visualization is to illustrate to the audience the prevalence of earthquakes along the fault lines. There is an enormous amount of data points that fall directly in between the tectonic plates. The varying sizes of the data points represent the difference in magnitude of each earthquake recorded in the dataset.
The interactivity for this assignment is that the user will be able to hover over an any datapoint, which will provide a table with the magnitude, depth, and date when the earthquake occurred. The highlighted point will have a springgreen stroke and bring the datapoint to the top of the map. One can also zoom and drag.
For the second graph, I plotted the datapoints on the graph using longitude and latitude. The size of the datapoints is determined by the magnitude. I also created differing colors to visualize the difference in magnitude a little easier. This graph is a symbol map.
The third visualization can be used in multiple ways of interpreting data from my dataset. The options are to compare the depth, horizontal distance, magnitude, and year. These four categories are crucial to furthering one's knowledge of an earthquake's traits.
This graph's interactivity is extremely important in determining how all of the data points stack up against each other. In this visual, the user will be able to compare depth, horizontal distance, magnitude, and year to see the trends or irregularities of certain values. One can hover over the data points (highlighted and lifted) to find the specific values being compared for that point.
For the third graph, I am using a scatterplot to compare depth, horizontal distance, magnitude, and year. These values can be chosen by the user for the x or y-axis.
The credit to the first visualization can be found here.
The credit to the second visualization can be found here.
The credit to the third visualization can be found here.
The feedback I received for this visualization was very helpful in creating the final version of the map. When describing my map to the two sets of groups it was clear that I would defnitely need to make some changes to really make my earthquake visualization better. Both groups decided that zoom would be really important in being able to see the smaller points on the map, especially because there are so many points. Another student instructed me that my colors were not helping me as much as they could. I took both of these comments into account and changed the country color, the ocean color, and both the color and size of the circles to make it easier to see the differences in magnitude. I also implemented an animation that drew the dots by their date, but during testing I found that it took way too long to load. For this reason I chose to get rid of the animation.
After two rounds of discussion, I dedided that most of the points in this graph were so close together that the this particular graph didn't show off the data well. I decided to go in a different direction, and do an interactive scatterplot that would compare similar categories. I decided to get rid of Azimuthal Gap, Depth Error, and Horizontal Error because the students said it didn't do much in their understanding.
John Murray Hi, my name is John Murray, and I am a senior at the University of San Francisco studying Computer Science. I plan on graduating in Spring of 2019. I am a huge Bay Area sports fan, avid coffee lover, and gym enthusiast. I’m hoping to pursue a Master’s Degree from the University of San Francisco as well.
The reason I chose to do my final project on earthquakes is that there has been a serious drought in California for earthquakes, and I wanted to learn more about how susceptible we are to them. It is not a question of if an earthquake will happen but when. This project will give me great insight on how frequently earthquakes occur and what likelihood we may experience one in the future. Hopefully not any time soon!
The original data set has 23K Rows, 21 Columns, and had a size of 612 KB. The data is from the National Earthquake Information Center (NEIC), which determines the location and size of all significant earthquakes that occur worldwide. The NEIC is devoted to providing scientists and the general public with an extensive seismic database. The dataset can be found here. The license for the dataset can be found here. The column titles by name are Latitude, Longitude, Type, Depth, Depth Error, Depth Seismic Stations, Magnitude, Magnitude Type, Magnitude Error, Magnitude Seismic Stations, Azimuthal Gap, Horizontal Distance, Horizontal Error, Root Mean Square, ID, Source, Location Source, Magnitude Source, and Status.
Latitude and Longitude are the locations points on the map that determine location. Depth is the distance below the earth's crust that is measured in kilometers. Horizontal distance is the distance for how long a earthquake occurs on the tectonic plates in kilometers. Magnitude is the force on the Richter Scale that is produced by an earthquake. All of these categories are recorded and then reported by the NEIC. I used Latitude, Longitude, Depth, Magnitude, and Date in my second visualization (Symbol Map), Date and Number of Records in my first visualization (Bar Chart), and Magnitude, Horizontal Distance, Depth, and Date in the third visualization (Scatterplot)
Not all of my visualizations required filtering of data, and if they did, I filtered after I downloaded the original dataset. For my first visualization (bar chart), I filtered the data to just include the year and total number of records for each year. For the second and third visualizations (Symbol map and scatterplot), I implemented all 23,412 records.