https://www.google.com/publicdata/explore?ds=kf7tgg1uo9ude_&ctype=l&strail=false&bcs=d&nselm=h&met_y=population&scale_y=lin&ind_y=false&rdim=country&idim=country:US&idim=state:08&idim=county:08031&ifdim=country&hl=en&dl=en&ind=false

This reading was all about collecting data over time and displaying it in a visual way. Time in itself is always relative. We cannot measure time unless we have something to compare it to, and in contrast collecting data is only productive if we have reason to use it in an informative or impactful way. For project #2 I have been using graphical timelines provided by U.S. public data to view income and population growth in Colorado. This example above is Denver Counties population starting in the early 1900’s to present time. This has allowed me to visually understand the population growth in our area as apposed to deciphering numbers in front of me. Time lines will forever be an easy and understandable way to view data, regardless of the information at hand.

Variables & Title:

In my research I want to address gentrification in Denver cities. Particularly through out the past few decades within the 21st century. While Denver may have been a growing city in the 80’s and 90’s I find that we are now in the peak of its growth and are seeing the most change. I will contrast neighborhood demographics with average median income from the early 2000’s and present time. Looking deep into property value and the rising cost of living versus the stagnant value of wages in our county. By doing this I should be able to tell the story of a struggling community trying to catch up within a fast paced and growing market.

The title of my work is still to be determined. I want to focus on the unfairness of wages here and the fact that more wealthier parties can so easy move and displace those who have lived here so long. 

Media:

I believe the most beneficial way to present this data is through a linear timeline. Showing the forward progress of the economics of Denver in contrast to the lack of income in Denver families should be easy to read. I think this will visualize the problem in the most fluent way possible to an audience.

In regards to software I feel confident that Adobe Photoshop and Illustrator will be capable of providing the tools necessary to tell this story in a static piece. As this project concludes and we move into motion I believe After Effects will be the contender.

Typography:

In regards to type I have always leaned towards more modern fonts such as Futura, Arial Black, or other’s strong in bold headings. Completing a timeline I may need to include small text for information and other elements of this story. This may include more simple and easy to read fonts such as Helvetica that contrast well with the bold nature of headers and titles.

Visual Hierarchy:

I think in the story of gentrification it’s important to represent the increasing value of homes in the Denver metro area. In the early 2000’s home values were at a very constant rate and the market did not move around too much. As we fast forward to present time these values have in some cases grown almost $200k. I think this representation can largely take up my composition to contrast the smaller values of demographics still in their original areas of living and income wages.

Graphic Elements:

This topic is largely focused on money and social structure of community. I think using images of homes, people, and value of currency will most benefit my composition. These may be vector graphics or possibly photos of old and new homes and businesses in Denver.

https://www.visualcapitalist.com/air-traffic-network-map/

While there are thousands of examples of networks out there, the most outstanding and visually satisfying one that came into my head, was air traffic. As a child these networks were just fun maps to glance at and now as we learn about data and visual mapping I realize how complex these systems actually are. A plane may have just one route from start to finish but there are many other layers to this form of transportation that we can visualize through a network of data. Traffic control, departure and arrival times, passenger itineraries, are all apart of the grand scheme that makes up this intertwining web of flights across the world. The link above is data from 2017 showing airport connections at a global scale. Focusing on popular connection areas for international travel. This article is very informal and a wonderful example of a network system in real time today.

After completing project 1 I got a nice look at my data collection process and what I could have done differently, or in addition to my original process. After contemplating a bit more I figured it would have been beneficial to break down each category I made in regards to usage. I originally started with the categories of: Posting, Searching, Checking Notifications, as well as being bored on the app. Furthering these categories could have broken down my data even further making my work a 3 level collection instead of two. For example I could have differentiated my posting section to be: Posting to my profiles gallery, or posting to instagram stories. Along with this notifications could have been broken up further as well, making this category into something more like checking likes, followers, and comments, versus checking messages. I think these categorical changes to my qualifiable data would have benifited my project even further.

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This is the digital version of Project 1 for Creative Computation. I collected data this past week in regards to my activity on instagram. I use this social app for work, art, and my own personal profile. I learned that I primarily use this app when I’m bored proving my assumptions made prior to my data collection.

https://archive.nytimes.com/www.nytimes.com/interactive/2010/02/01/us/budget.html

Here is a large scale example of a Tree-map that was used in a real world scenario. The budget of the United States of America is quite an intimidating idea. To simplify this complex set of data from 2011 the New York Times turned to a Tree-Map for a more simplified and easy to read analysis. Like any other Tree-Map the large block is divided into sections whose size in relation to one another accounts for the amount of budget spent. Further more they are color coded depending on the increase or decrease in spending from the prior year in 2010. I was surprised to see the even amount of spending in Social Security and National Defense because everyone knows America is notorious for spending the majority of our budget on the military and other aggressive actions.

Thanks for joining me!

Creative Computation