Quality of life vital signs visual analysis 👁️ for Baltimore's neighborhoods using sources including Baltimore Neighborhood Indicators Alliance (BNIA-JFI)
Understand patterns with emphasis on housing equity, by slicing through the incredible amount of indicators data. ❔ Which indicators can we seek to change to have the greatest affect on housing access and population stability, and how we set targets for them?
View a dashboard of the indicators through an equitable housing lens on Tableau Public.
Baltimore Neighborhood Indicators Alliance, a program of Jacob France Institute of the University of Baltimore, is a product of many community focused organizations and residents coming together to research, survey, objectively assess quality of life and collectively imagine its future.
Kathryn Hurchla:
I have no formal affiliation with the Alliance. I began this project as a Data Analytics & Visualization MPS Student with MICA which is based in Baltimore City, from my home and office in Philadelphia about 90 miles or 145 km northeast as the crow flies. I've been an occasional visitor of Baltimore for over a decade, where I've travelled for data conferences 💼, to race cyclocross bicylces in Druid Hill Park 🚴, to visit friends 😄, and once and perhaps of most direct relevance as a volunteer touring communities and quality improvement initiatives with a Neighborhoods Now grant program partner Baltimore community organization through my service at the time (circa mid 2000's) as a member of an arts & culture subcommittee for Fairmount and Brewerytown Community Developent Corporations in my current homebase Philadelphia 🏚️
▶️ 🏘️.
Though not formally 'Sister Cities', I have long seen and learned from aligned experiences and histories of Philly and Baltimore. I always have my boots shined there in Penn Station, along with the warmest conversation and ask for some on the ground insider news. I ride MTA buses, and prefer a stretchy suit and a bike anyday. I still hold hope for the bike-share program JUMP. But I digress.
❣️ Did you know in 2019 Amtrak placed its bets on bypassing Philly, BMore Delaware's cities altogether to fast track New Yorkers to DC and back? Amtrak skips Philly with new non-stop Acela train from New York to Washington
If you're inclined to collaborate, fork and suggest improvements to code, or comment to report a problem or suggest a feature or topic, thank you.
In otherwords, I'm looking at what's happening where folk live all over the City map. BNIA-JFI and its Steering Committing established population stability as, essentially and in my own words, a pulse of Baltimoreans quality of life. Not leaving nor growing too fast, and leaving no neighborhood behind nor any neighbor from affording a choice of location and to stay. **I agree with their assessment that overcoming vacancy--with a target of no more than 4% of vacant homes--is a critical step.
- In particular, surface correlations that can act as actionable keys to opening wider pathways towards improvements in access to safe, affordable homes
- Across Baltimore which indicators and states (high/low/how much) appear to keep residents invested in keeping roots there?
To add to the story and set additional complimentary targets:
Which of these many other indicators have shown patterns when viewed together in a way not expected to happen on the basis of chance alone. When one indicator goes high, does another go lower? Do some appear to bring each other up, or down, repeatedly and in timing with one another. For example, does one change and then the other)
It's extremely important for us to acknowledge that correlation or any measure of information alone for that matter, cannot alone define a definite or finite cause amongst many known and unknown variables of any situation.
For more on that critical point, I recommend this article below on interpreting data when what we as humans really seek is to to find causes and solutions! Note I have no association with its author Charlie Kufs, and it reads with such simple clarity, yet depth and specifics I can put to use that I will personally be seeking out more of their writing on data and analysis.
ℹ️ https://bigdata-madesimple.com/how-to-tell-if-correlation-implies-causation/
The files of all indicators for the #VitalSigns18 2010-2018 have been downloaded and uploaded in this repository. Fortunate for us, BNIA-JFI already surveyed people living in Baltimore at landmark levels, and it belongs to national best practices setting associations. I'm not from Baltimore, but this data is comprehensive of different public and private sources, and development of the indicators feels legitimately to remain informed by the people the work aims to help, and those who the data represent.
ℹ️ For more information about BNIA-JF, its compiled data sources, or to access up to date and original data files or API, visit: https://bniajfi.org/
Python and Tableau Prep are used to prepare the data for visualization and correlation analysis. Visualization has been done with Tableau Desktop, and may extend to Python libraries (Matplotlib, Seaborn and related)
