Reflecting on race, data, and our world

I hope that everyone has had a chance to read the new blog post by our own @SusanCS, Using 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.

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AeronZentner

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

https://www.kaggle.com/

chris_love

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: https://twitter.com/abmakulec/status/1268951844098801666

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.

chris_love

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

SusanCS

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.

chris_love

Adding my recent article on this subject https://medium.com/@chrisluv/exploring-blacklivesmatter-in-5-charts-e579b07c0dba (using Alteryx to prep and blend data before visualising in Tableau)

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