The data set that I am looking into is the data hosted by the National Register of Historic Places and Historic Albany Foundation. I am currently taking a course that focuses on the preservation of historical sites. I find the work that goes behind registering, rebuilding, and preserving historical buildings very compelling, and I feel that working on the data tables relating to this subject would be just as compelling.
Questions:
How can we categorize state and federal historic sites to be easily filtered by various categories such as alphabetical, year approved for register, etc.?
What kind of visual charts could be created using these tables? (My guess is that a geographical table would be a comfortable fit for these data tables.)
How can we track any potential intersections of data between the National Register and the Albany Foundation?
2 replies on “Module 6 Post”
We touched base about this on Zoom, but just a couple of thoughts so you can refer back if you need to:
– intersections between the Historic Albany Foundation and Natl Register entries is probably going to need to be done by hand, and I suspect there’s very little overlap bc the HAF locations are mainly private homes
– there is a lot of geographic data there, but think about what knowing geographic distribution actually tells you (remember, you need to make some kind of argument in your project). Tableau’s map layers has an option to include modern census data and the Natl Register data is all recent enough that that should be an easy comparison (Map > Map Layers > Data Layer > census tract/zip code/county/state/whatever)
– related to making an argument, remember that your project should not be primarily aimed at making your data simply browseable. Yes, alphabetic sorting can make it easier to find a site, but that doesn’t tell you anything about your data and doesn’t make an argument. Think about contextualizing the data with further research (are there spikes in years when properties are rejected or removed? Who was president/what was the financial situation of the national register at that time?)
– You can also think about supplementing the Natl Register dataset with further information pulled off Wikipedia, which has an API
And re: pulling data off wikipedia, it looks like most pages for Natl Register buildings have year built, area, and architechtural style, which are not in the spreadsheet, and which could give you more info to work with: https://en.wikipedia.org/wiki/Albert_Albers_Barn We can chat about steps for pulling that data and combining it with your spreadsheet if you want to go that way.