Published
Edited
Apr 4, 2020
md`# Data Visualization on Mountain Project`
gif = FileAttachment("maptypes.gif").image();
othermapfeatures = md`The map is also zoomable and has panning, as you zoom in, the Data (climbing areas) get broken down to more specific geolocations, and on the phone app, the symbols also let you know the name of the area and have a number in the middle which represents the amount of routes available in the area.
Once you find the area you want to go to, you can click the symbol, and it will take you to another page, where the route information, community feedback and other information can be looked up for specificity.`
gif2 = FileAttachment("mp.gif").image();
yosemite = FileAttachment("yosemite.png").image();
md ` ## Analysis
**Data Ink Ratio**: If we just consider the data of the climbing areas, at the different zoom levels, there is good data ink ratio, of course this depends on where you zoom in, if you hover over Yosemite National Park, there is a lot of data in little space, because of the amount of locations tagged there. Hoeweve it gets beter by zooming in.
**Data Density**: This really depeds on location, since it's a tool that encompasses the world, it depends on where you decide to investigate, in general at a Country leve you get very little density, and as you zoom and focus on articular areas, you get more and more density. If you consider an entire state, for example California, the data density tends towards certain locations, since we cannot climb in areas without slopes (in general).
**Lie Factor**: The surprising thing about the lie factor in this Visualization is not whether things are located in the right spot or not, in general the symbols are fairly accurate. However the lie factor is that not all data points that exist are represented. There are areas of climbing that the climbing community decides not to share with the app, and therefore is missing some data points. Routes are also being developed frequently and not necessarily added to the maps, making the data somewhat outdated.`
md`## Other Visualizations
While the main features of the app are the interactive map and the area specific website, there are [other visualizations](https://www.mountainproject.com/area/105833384/tuolumne-meadows) that allow us to get an idea of what we may be able to find in the area in terms of climbing types and difficulty ratings or weather patterns by month, to see when the best time to go would be. These also allow for some interaction.`
other1 = FileAttachment("other_interaction.jpg").image();
md ` ## Analysis
The analysis for this is for the pie chart, and the bargraph under it. The pie chart represents the type of climbing available (toprope is a variant of sport climbing, aid is a variant of trad climbing).
**Data Ink Ratio**: This Chart is taken slightly out of context, it is part of a larger page. However for the pie chart, the data ink ratio seems not quite right, the Aid section is a barely visible pixel line between the two green squares. There could probable be a better way of visualizing the distribution, it's likely that the designers did not want to put two bar graphs on top of each other.
The bar graph underneath represents a distribution of the levels of difficulty in the area. the data ink ratio is actually fairly high, it's mostly just the data. When you mouseover the bars, a tooltip says how many of that type of climb there is.
**Data Density**: There is not very high data density for the pie chart, it divides into 6 categories that are fairly easy to see, except for the Aid category which is pushed into a small sliver barely represented.
The data density on the bar graph is fairly low, it's a very simplistic scaled down bar graph with very little information on how to read it. It's mostly read from context.
**Lie Factor**: For both of these graphs there is a level of lie factor similar to the map described above. Mainly that there not all the data is necessarily encoded, meaning there may be more routes available than what is shown there. Though it's likely that the pie chart distribution might stay fairly the same if we included the missing data.
for The bar chart, the difficulty level distribution looks fairly similar in most climbing areas, with middle grades being the most abundant, the lie factor that may come into play is the difference between bar heights, not knowing what the represented numbers are without the tooltip can mean the bars may represent any number at all.`
md ` ## Attributions
All images were are from [Mountain Project](https://www.mountainproject.com/), either the website or accesed through my personal account on my phone. Mauntain Project is a free community built and maintained app backed by REI. `
md ` ## About the Author
###Enrique
I am a University of San Francisco Computer Science student, expecting to graduate May of 2020.
I chose this topic because rock climbing is a hobby I have and try to get out climbing as much as I can. Mountain Project has helped me get to places I was not aware even existed, and helped me get slightly better at the sport I enjoy. `
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