I’m in the midst of creating a series of YouTube videos nohow to access census data. The first one I have created is on my channel. Check it out! https://youtu.be/vqlDaIeRe0c
Maptime PHL is holding a special event on 5/30/15 about mapping food resources in OpenStreetMap.
Our second meetup for the month of May is on a special day,Saturday, because we have some special guests in town to lead the session.
Sterling Quinn, a PhD student at Penn State’s Department of Geography, along with a few other folks from the department are traveling all the way from Happy Valley to teach us about the relationship between OpenStreetMap (OSM) and Philly food resources.
Following a presentation by Sterling about his research on this topic, we will spend the rest of the event adding local food related resources to OSM as well as improving the data which exists already.
As always, no prior experience necessary. simply an interest in maps and learning new things! so mark your calendars, set aside a few hours of your Saturday afternoon, and let’s map and learn together.
for a sneak peek at some of what we’ll be discussing, you can also check out this OSM 101 presentation from our first ever meetup and find other OpenStreetMap related info on the maptime lessons and resources page.
Food and drinks provided by Azavea, our super cool and awesome sponsor.
note: MaptimePHL events are Bring Your Own Laptop (BYOL). If you would like to attend but bringing a laptop is an issue, contact one of the organizers via email – firstname.lastname@example.org – and we will find a way to make it work.
Super cool use of GIS and historical census records. Making history come alive!
The Digital Harrisburg working group is pleased to announce a beta version of an interactive map of Harrisburg in 1900/1901 hosted at ArcGIS Online. This map and the data it contains was developed as a collaboration between faculty and students at Messiah College and Harrisburg University of Science and Technology. The Historical Society of Dauphin County generously provided JPEG scans of the entire 1901 Harrisburg Title Company Atlas (the layer visible as the historical map of the city) and Ancestry.com provided access to the United States census data records for 1900. Working from the census data, Messiah College students created a complete database of the population in 1900, while GIS students from Messiah and Harrisburg University created building polygons and individual census record points in GIS mapped to the level of individual properties.
What you can do with the site:
The interactive website offers a high-resolution map of…
View original post 603 more words
From the Philadelphia Inquirer. Delaware is not included for some reason.
Today I found a blog from The Wall Street Journal about how the zip code that you live in could dictate who you are. Mapping behemoth ESRI mashed Census data along with marketing data from GfK Mediamark Research & Intelligence and tries to predict what you will buy according to the zip code you live in.
The mapping piece is beautiful, the map moves smoothly and the graphics are top notch. The descriptions of the socio-economic levels are stereotypical and questionable.
I did some spot checking around my area in South Jersey to see how the data compares to my own local knowledge. I gave to say that in the zip code that I live in ESRI did get the fact that there are a lot of apartment dwellers in my hometown correct. What they did not get right was the fact that a lot of these apartment dwellers are not millennials, instead they are middle class families. Looking at the Census data can tell you that.
I also found the categories in the “Top Tapestry Segments” incredibly insensitive and stereotypical.
Case in point: Camden City Zip Code 08110
This area in Camden is broken down into:
36% American Dreamers: Basically foreign born married couples and older people
30% Parks and Rec: People who live in older more established communities
18% Urban Villages: Recent immigrants who do not speak fluent English
The Urban Village description is the one I find most offensive. “Shopping for trendy clothes for the whole family is important so we can be fashionable”. Why is this connected to the urban poor? Why play up to stereotypes? I think that this map has some really good uses but I think that it delivers its message poorly.
Check out the map here and feel free to leave your comments.
The NY Times published an article that uses Facebook “likes” by zip code to map out college football loyalty. It’s interesting to see how the mapped data shows whole states where one college dominates while some states are carved up into niches. Check out what team your neighbors are rooting for.
An Oregon cartographer by the name of David Imus spent 6,000 hours to create an absolutely brilliant wall map of the US. He places labels in ways that are useful and easy to read (no algorithms used). Imus captured important bits of info that are generally ignored like ferry routes and his attention to detail is amazing. I’m hoping to be able to purchase one in the future.
Read Slate’s article on the map here.