Author
Listed:
- Reid Cummings
- Jana Stupavsky
Abstract
Descriptive and diagnostic analysts more frequently utilize data visualization techniques to help frame and answer two key questions: “what happened?” and “why did it happen?” To comprehensively assess the quality of life in two neighboring Coastal Alabama counties, regional civic leaders identified 17 metrics that could help them interpret how the community is performing as a whole (the “what happened” question) and offer insights into areas needing improvement (the “why it happened” question), all with an eye toward long-term support of the community and its real estate values. A few examples of included metrics are crime, housing, poverty, high school graduation, obesity, infant and childhood mortality, and water and air quality. Our business research and services center, the South Alabama Center for Business Analytics, Real Estate, and Economic Development, joined the effort by developing and hosting a series of web-based, interactive, dynamic dashboards. We created multiple visualizations to address each metric using publicly available data sources to answer the “what happened” question. More importantly, because the community initiative’s goal is to spur conversations about addressing areas needing improvement, we took great care to design all dashboard visualizations to motivate and inform community improvement discussions that focus on “why it happened.” We did so by streamlining data comprehension and minimizing misinterpretation, offering a single question as the title of each visualization. Additionally, considering carefully the core visualization component techniques of spatialization and pre-attentive attributes, we worked to ensure that each visualization within the dashboard “family” had the same look and feel so that community leaders could spend their time working on discussing and promoting real community-based solutions rather than trying to interpret and explain differing visualization interfaces. We contend that better solutions to community problems help to ensure better community outcomes and help to ensure the values of real estate within a community.
Suggested Citation
Download full text from publisher
More about this item
Keywords
;
;
;
;
JEL classification:
- R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location
NEP fields
This paper has been announced in the following
NEP Reports:
Statistics
Access and download statistics
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arz:wpaper:2022_46. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Architexturez Imprints (email available below). General contact details of provider: https://edirc.repec.org/data/eressea.html .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.