Today we’re featuring a guest post by Ilana Barnes. Take it away, Ilana!
Data is out there. I would refrain from saying good data is out there, or even relevant data is out there. As Kim said, we are in the “year of the infographic,” and we are equally in the “year of the unruly excel document.” When one is lucky enough to receive large amounts of data that is relevant, they may stare down at their excel or SPS document and then say: “Now what?”
One type of data becoming increasingly accessible is addresses. More and more companies and organizations post their address online. They are aggregated up into somewhat tidy databases like RefUSA and OneSource, accessible on many college campuses and local public libraries. Once bound in the white pages, this address data is the meat of many new and exciting ways to research. With information about where companies are, you can find a great number of exciting things. For example, the location of food stores in Detroit can help you locate food deserts. The location of Targets in the United States can help you predict where next to put your big box store. I just had a chat yesterday with a professor who researches how industry is affected by natural disasters, using location-based disaster data and addresses as well as other indicators.
Working with data may not be a common task for all academic librarians, but there are a lot of possibilities once you start diving in. As a future Business Librarian, I learned about better ways of dealing with address data because so many students were asking location-based questions. Where do I put the Walmart? Which city has the most crime and where? For those who feel a little less steady diving into data-related questions, address data can be a good, solid place to start exploring. Beyond the reference desk, questions that librarians ask can be answered through use of address data. Where are comparable services to my library? Where are the different campuses of your university where you trying a specific information literacy strategy and where are the campuses of your partner institutions?
Sold on address data? Excellent! We’re going to go over some tools for working with address data. Firstly, if all you want to do is create a map of addresses, BatchGeo is an excellent tool for taking all those address and putting them on a Google map. You can code 150,000 address per IP per day, and create a Google map which you can then enhance using the Google interface, either drawing polygons or adding metadata. But what if you want to do some other visualizations?
Google Fusion Tables is an awesome product. Google Fusion Tables also can geocode addresses into a Google map.
Why I like Fusion Tables:
- Different types of visualization
- Sweet, sweet fusion. The merging capabilities of Google Fusion
- Collaboration. You can share your data sets relatively securely via Google Fusion Tables with research partners. This is great for us librarians, who often want to work together on large, spreadsheet heavy projects.
- You can link it up to Google Refine for those more squirrelly datasets.
Here’s an example with some roughly 300 gas stations in the city of Detroit.
Here is the data as it looks in Excel. Ugly.
Here’s what it looks like geocoded (editor’s note: for an interactive version of these charts, see Ilana’s blog):
Another view (this time using some sales data as well):
Another view (more pie charty). I understand this is a terrible pie chart, but it’s very aesthetically pleasing.
For a very effective run-through what makes Google Fusion Tables wonderful, check out this YouTube video from Google.
Ilana Barnes is Business Information Specialist (Assistant Professor of Library Science) at Purdue University since May 2012. In April, she graduated from the University of Michigan with a Masters of Science in Information. Her main research interests are information literacy, data, GIS and gamification. You can visit her website at http://ilanabarnes.com or follow her on Twitter, @librarianailana.