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Reflecting on race, data, and our world

Alteryx Alumni (Retired)

I hope that everyone has had a chance to read the new blog post by our own @SusanCSUsing Data to Seek Racial Justice and Transparency. If you haven't yet, I would recommend you take a few minutes to check it out. It's insightful, eye-opening, and potentially a bit surprising.


Susan's piece has an impact due to the subject matter, but that impact is without a doubt heightened by current events. It certainly brings up several follow-up questions for me, and I'm guessing it does for you as well. 


What other data sources are available that could enhance this topic and provide more clarity? What could local data tell me about my region, and would that mesh with my own experience? Does diving into this impact my perspective in a meaningful way?


This discussion is likely to bring up a mix of emotions within the community, and I look forward to respectful engagement and hearing your thoughts around what this says to you as both a data professional and as an individual.



Will Machin
Community Management Team Lead
6 - Meteoroid

That is a very engaging data visualization. I usually would recommend Kaggle as a great site to obtain large public datasets.

12 - Quasar

Thanks for starting the discussion Will, this is a very important topic and Susan's article is very welcome.


Data is a great leveller in times of crisis, I've been reminded recently of Daniel Moynihan's famous quote: "Everyone is entitled to his own opinion, but not his own facts". Data can help surface those facts and ensure that the discussions and conversations we have are properly grounded. I think everyone here as a data analyst can talk to the power of data in these discussions.


Clearly one thing to be conscious of as people use the resources in Susan's article is to ensure we are treating the data and discussions with fairness. There are several things we can and should do:


1. We need to amplify the voices of Black designers and analysts but it is a conversation for everyone to take part in


2. If you're building resources / datasets / visualisations, we need seek feedback and involve Black friends and colleagues, but be respectful of their time   and efforts, particularly at such a sensitive time.


3. Be clear on your intentions, are you sharing information or looking to enable action? Offer clear and tangible actions people can take to learn more and make change.


4. Be ruthlessly objective, do your sources have bias? Act like a data journalist and question everything.


Amanda Makulec has shared more on this topic:


I'd love to know what plans people in this community have for analysing this topic, what other resources there are people have found and how we can collaborate to make a difference. I'd love the Alteryx community to lead the way here.


Clearly, though it's a very difficult topic, with much of the data being nuanced and with implicit bias included already, we aren't going to solve everything overnight, but this is an important time in history and we should look to grab it with both hands to capitalise on the movement and strength of feeling.


Personally I'm looking at educating myself, I'm by no means perfect and so am looking at reading a lot and starting with some very simple sets of analysis and questions. I'll share these as I make progress.


In the meantime I'd love to see more participation on the topic, and also hear some from some of the Black voices in our community.

12 - Quasar

@AeronZentner have you found any good kaggle sets on racism / bias in particular?

6 - Meteoroid

Kaggle has the following datasets


U.S. Education Datasets: Unification Project: K-12 financial, enrollment, and achievement data in one place


Diversity Index of US counties:Simpson Diversity Index to quantify racial diversity of US counties


Race classification: Images of faces of different races used for for Computer vision to classify the faces based on race


Demographics of Academy Awards (Oscars) Winners: Race, religion, age, and other demographic details Oscar winners since 1928


US Adult Income: Data set of adult income


COVID-19 data by race


Minneapolis Police data related to interactions by race

12 - Quasar

Thanks Aaron, really grateful for you spending your time pulling these out. 


Personally I've been focussed firstly on educating myself, I watched 13th last night on Netflix which was really eye-opening, especially as someone outside the US. I'm also using the WSJ dataset on police killings to do some initial work and look at some of the statistics, but these supplemental datasets will be really useful as I dive further into the data available..

Alteryx Alumni (Retired)

Thank you @WillM@AeronZentner, and @chris_love for sharing your thoughts and resources here.


Similar to Chris, I've been working to educate myself and listen. As a small step, the latest podcast episode is focused on highlighting Black voices in tech. I kept the episode short so that subscribers can instead use that time to support these voices and engage in the resources they provided.


@chris_love made a great point yesterday in saying: "4. Be ruthlessly objective, do your sources have bias? Act like a data journalist and question everything."


Interestingly, the recommendation that our own Data Science Journalist @SusanCS shared in the podcast was Algorithmic Justice League, an organization that raises awareness about bias and harmful AI. They're currently featuring a documentary on their website titled, "Coded Bias". 


There is a screening of "Coded Bias" and Q&A panel happening this week at the Human Rights Watch Film Festival. I'll definitely be tuning in! 


Check out this interview with the documentary's writer and director, Shalini Kantayya:



The other recommendations from today's podcast episode are linked in the show notes but I'll list them here for visibility:


6 - Meteoroid

I would also suggest watching the film Just Mercy. It is also an excellent choice.

Alteryx Alumni (Retired)

Screen Shot 2020-06-10 at 9.12.32 AM.png

One more set of resources I just learned about: The latest Data is Plural email newsletter had a link to this Reddit thread discussing the sources and creation of this map of BLM protests/vigils around the world. There are additional relevant datasets linked and described in their newsletter archive.

12 - Quasar

Adding my recent article on this subject (using Alteryx to prep and blend data before visualising in Tableau)