diff --git a/Screenshot .png b/Screenshot .png new file mode 100644 index 0000000..e83830d Binary files /dev/null and b/Screenshot .png differ diff --git a/Screenshot 2022-01-24 120846.png b/Screenshot 2022-01-24 120846.png new file mode 100644 index 0000000..dc11f09 Binary files /dev/null and b/Screenshot 2022-01-24 120846.png differ diff --git a/TabulaPeutingeriana.jpg b/TabulaPeutingeriana.jpg new file mode 100644 index 0000000..0c638e3 Binary files /dev/null and b/TabulaPeutingeriana.jpg differ diff --git a/image (1).png b/image (1).png new file mode 100644 index 0000000..0257215 Binary files /dev/null and b/image (1).png differ diff --git a/image.png b/image.png new file mode 100644 index 0000000..a44fa35 Binary files /dev/null and b/image.png differ diff --git a/ref-5.png b/ref-5.png new file mode 100644 index 0000000..79db6b6 Binary files /dev/null and b/ref-5.png differ diff --git a/week1.md b/week1.md index e69de29..1469317 100644 --- a/week1.md +++ b/week1.md @@ -0,0 +1,14 @@ +![weightgurus1](image.png) +![weightgurus2](image(1).png)image(1).png + +I'm doing my first reflection of the app Weight Gurus which syncs with my scale. +The scale uses impedance to measure several biometrics statistics, which can be viewed along with weight in a smoothed line graph. +The two metrics I have chosen to look at the graphs for are body fat percentage and muscle mass. +The first thing I noticed upon looking at the graph is that the scaling of the graph changes to fit the deviations of the value onto the screen. +In doing this the small changes in my body fat percentage end up looking large. +This is good for seeing changes but possibly makes the changes look bigger. +Generally I find that both of these stats track with my weight changes, with body fat going up when I gain weight and muscle mass going down. +However this is not always the case, and sometimes my weight gain does not directly correlate with body fat gain. +Another statistic that accounts for what amount of weight changes are owed to gain in fat vs muscle would be helpful. +This app allows you to see the trends generally but does not easily allow the user to determine what kind of weight was gained in detail. +This addition would be helpful athletes or other individuals trying to gain or lose a specific kind of weight. diff --git a/week2.md b/week2.md index e69de29..50b7a46 100644 --- a/week2.md +++ b/week2.md @@ -0,0 +1,12 @@ +https://biobot.io/data/ + +For my Week 2 reflection I am looking at the data visualized on Biobot's website. +Biobot is a company that looks at viral particles present in wastewater to predict covid outbreaks. +The data visualization on this site is a simple color coded line graph. +This is appropriate for the data that is be shown, and the meanning being communicated by it. +The main information that is attempted to be convayed by the chart is the level of covid partilces in the wastewater. +The chart also included the clinical levels of covid observed, likely to prove the validity of their findings as the clinical levels closely track to the wastewater levels. +The chart also provies the ability to compare different regions of the country, convayign this information through the channel of color coded lines. +Although the line graph is a simple and common data visualization technique, the viewer is able to get much more meaning form the graph thatnfrom a table of data. +Viewers can discern the rapid rise of several spikes, if levels are higher than they have been in the past, and how well clinical levels and wastewater levels are related all at a glance. +These less flashy visualizatino techniques are not to be underrated. diff --git a/week3.md b/week3.md index e69de29..e3404f7 100644 --- a/week3.md +++ b/week3.md @@ -0,0 +1,11 @@ +https://www.washingtonpost.com/health/interactive/2022/omicron-wave-spread-maps/ + +The data visualization that I have chosen for this week is a series of visualizations from the Washington Post about covid. +The first visualization is a simple line chart showing the number of cases in the US. +This is a fairly standard visualization, and contains the same information that the later visualizations expand upon. +As the viewer scrolls the view locks on a map of the US with case rates displayed on a county level, and progresses through time as the viewer continues to scroll. +The caserate color mapping uses two colors rather than a single color to increase visual clarity. +A Timeline showing the number of cases makes the viewers progress through time, showing the volume of cases giving additional context to the map. +The next noteworthy visualization is a map of the US with the trajectory of cases visible as an angled arrow. +This shows the same information as the previous graphic, but makes the change in case numbers at a certain time explicit, rather than showing the change as the user scrolls. +This visualization also shows the case level in the color of the arrows, allowing both trajectory and case level to be shown simultaneously. diff --git a/week4.md b/week4.md index e69de29..bdf2d6d 100644 --- a/week4.md +++ b/week4.md @@ -0,0 +1,13 @@ +![Tabula Peutingeriana](TabulaPeutingeriana.jpg) + +My week 4 reflection is on the Tabula Peutingeriana, a medieval map of roman roads on a 22ft long scroll. +This is a somewhat unique choice but I believe it to still be a data visualization. +The main data visualized was which cities are connected and how many days travel are in between them. +A road connecting cities is represented by a red line, and each day's travel is visualized by a hook on the line connecting them. +Given this the map was clearly meant to aid in travel planning, but with exclusive usage of roads depicted on the map, as the path of the road and the relative locations of cities are completely lost in this map. +The most notable attribute of this map is that it is projected onto a 22ft long scroll, completely distorting the geography but preserving the relevant information. +Although the continents can still be determined, and the shape of Italy is relatively preserved, doing anything beyond identifying them is impossible. +The benefits of this projection is that the user can explore only a section of the map where they plan to travel without needing to see unnecessary locations. +Similarly this map does not dilute the travel time with information "unnecessary" in this context, like geographical location or total road distance. +Although strange looking this scroll is a very efficient way to communicate the relevant information for a classic road trip, without extraneous information, and overcoming the limitations of the medium it was written on. +Lessons can be learned from this bit of ancient data visualization as for how to strip away unnecessary data and meet the constraints imposed by how the user will view the visualization. diff --git a/week5.md b/week5.md index e69de29..bf96128 100644 --- a/week5.md +++ b/week5.md @@ -0,0 +1,13 @@ + ![Minard's Visualization Of Napoleon's 1812 March](ref-5.png) + +My Week 5 visualization, inspired by our focus on maps last week, is on Minard's famous visualization of Napoleon's invasion of Russia. +This visualization communicates 6 different channels of data, the number of Napoleon's troops, the distance traveled, temperature, latitude and longitude, direction of travel, and location relative to specific date. +The location (latitude and longitude) is shown by the path drawn over a map with respect to several major landmarks. +The troop number is showns by the width of the path. +The distance traveled is shown by the lengths of the path and the legend in the bottom right. +The direction is shown through the color of the path, with the lighter color being the army advancing, and the darker color the retreat. +This channel of information is particularly interesting, because it is never explicitly stated but to anyone who knows the story of what is being visualized the meaning is clear. +And finally temperature is shown in a line chart at the bottom. +Rather than the x axis representing time it represents the longitude of the army, with lines drawn to the location the temperature was recorded at. +The dates are explicitly labeled under each reading. +Temperature is only shown in relation to the retreating path, a choice that makes sense as both visualizing both directions would lead to overlap in the graph as longitudes were traversed by the army twice, and because the temperature was most relevant on the retreat, when winter took its toll on the army. diff --git a/week6.md b/week6.md index e69de29..faf338a 100644 --- a/week6.md +++ b/week6.md @@ -0,0 +1,12 @@ +https://www.crisisgroup.org/content/conflict-ukraines-donbas-visual-explainer + +This website has several data visualizations on it which seek to raise awareness of the conflict that was ongoing in Ukraine's eastern regions for several years. +The first is a map that visualizes casualties in different regions. +The map has a slider which allows the time range to be selected. +The number of casualties is communicated through the hue of the region. +The color automatically shifts to reflect the new range of casualties per region when the time frame is changed, which makes it difficult to determine changes in casualties over time with the slider. +The map is also missing other information like the borders between Ukraine and Russia, with the borders of provinces being more clear. +There is later a breakdown of the causes of death by month, using a stacked bar chart. +It is difficult to discern a clear pattern from this data presented in this way. +It also has the same category coded for in two colors, and a slider to select time ranges that is similarly useful for exploration of the data. looking at a smaller section of the same stacked bar chart does not reveal anything. +The final chart is a line chart of reported explosions, with the dates of ceasefires marked. This is a good visualization, with the marked dates of ceasefires corresponding to noticeable drops in explosions. diff --git a/week7.md b/week7.md index e69de29..733a730 100644 --- a/week7.md +++ b/week7.md @@ -0,0 +1,10 @@ +![image](Screenshot .png) + +This visualization communicates the number of refugees and fleeing Ukraine and their destinations. +The number of refugees and their destination is communicated by the arrows, with their width representing the number and their location denoting their destination. +The fact that the arrows branch off from an original path with a width representing the total number of refugees aids in discerning the proportions of refugees going to each location. +The refugees heading towards Russia are denoted with a seperate arrow, which is also colored gray to the other arrows' yellow. +This editorial choice is likely to represent that they are fleeing to the nation which is instigating the conflict, meaning that their impact on geopolitics will be different. +In this light it is interesting that Belarus is included within the bundle of yellow arrows headed primarily towards westward facing nato affiliated nations, as they are a russia aligned state that has aided in the invasion. +The arrow for the 34,000 refugees headed to other European countries are not included in the main bundle of arrows, which makes the usefulness of using the branching arrows to discern proportionality. +If I were to redesign this I would include the arrow for the other European countries between the arrow for Poland and the arrow for Belarus, having it continue through poland. I would also move the label for the total refugee count further right, allowing the original width of the yellow arrow to be more easily seen.