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Russell Goldenberg

Russell Goldenberg talks to us about what it's like working at the Pudding, his journey from Comp Sci to creative computation, and drops some great tips for working on data viz projects.

Russell Goldenberg#

The Puddingwebsite@codenberg

Transcript#

Amelia:

So today we're talking to Russell Goldenberg, he's a Senior Journalist Engineer with me at The Pudding, creating data-driven essays. If you haven't heard of The Pudding, you should definitely check them out at pudding.cool. We make essays with data viz on really interesting topics. Yeah, I'd love to hear a little bit about how you got into the field, Russell.

Russell:

I'll give you a medium version of the story because I can talk too long sometimes, but basically my journey was I started out in computer science, so kind of a very traditional Comp Sci track in undergrad. Decided that it was a little bit too technical and conceptual for me in a lot of ways, once I got to the more advanced concepts. I happened to be taking some classes in visual arts with some more kind of programming explorations and stumbled upon the programming language Processing when it was in its alpha phase. That kind of keyed me into this other side of programming and doing more visually driven things and creative things. And I was much more into that. So that kind of changed my career trajectory into this field of... I called it like creative coding or like computational art. So I was very much following in the footsteps of people like Casey Reas, and other people doing artwork and installation work with computer programming. That landed me at a job at the Engagement Lab at Emerson college, where I was doing a mixture of front-end game development for civic engagement. And also doing, basically, these games where we create them for communities and about social issues, but then we get a lot of data from it. And so that's when I started actually playing around with presenting that data, having like no background in data visualization. So I was still kind of applying this visual art-way of looking at data. And then, really, I didn't get into the true field of data visualization or data journalism until I went to Open Viz Conf and I saw a reporter from the Boston Globe, Gabriel Florit. He spoke about basically how hard it was to do data viz on mobile, and it was a really interesting talk because realized this whole other challenge space of presenting information. So, yeah, I guess that's when I officially entered into data journalism and visualization. I applied for a job at the globe after seeing that. And that's where it began for me. So it was kind of a meandering path, just like that story just felt.

Amelia:

Oh, that's interesting. I'd like to hear the long version, but, that's definitely an interesting path. How do you think your day-to-day is different than if you had kept on with the typical Computer Science career path?

Russell:

I feel like I much more likely would have ended up in like a software development firm or shop. I didn't even take any classes related to web development. And my Computer Science track is very much like a... there's like one elective about it. So it wasn't even on my mind of doing anything on the web. And again, graphical programming was not something that was big in the undergraduate courses during the time, I feel like it's very different now. The landscape of opportunity in the college world and obviously any type of online learning. So I felt like, yeah, I think the path was really narrow, so I've probably wouldn't have ended up doing anything remotely similar to what I'm doing now.

Amelia:

And what does your day-to-day look like? Like how much do you spend coding or, doing art-like things.

Russell:

I'd say about half my day is spent actually programming. I spend a fair bit of time just doing a lot of research and like around... so as you mentioned, we tell like all sorts of data-driven stories at The Pudding. The one I'm working on now, I'm looking at the usage of the word "Oreo" in crossword puzzles and why it's so common and kind of contextualizing that because there's a big corpus of crossword puzzle data that I've been playing with. So a lot of it is just kind of really steeping myself in this domain that I have no expertise in. I'm a very immature crossword puzzle player, but I don't know a lot about crossword puzzle construction. So a lot of it is just doing background research, sometimes, reaching out to experts and interviewing them. And then, yeah, the other half is doing a lot of programming, putting together mock ups, writing the narrative for stories, and kind of, it's just a whole hodgepodge of kind of creative madness, I guess. I like to think that I could spend more than half of my time coding, but it ends up being a lot of obvious stuff than just coding.

Amelia:

Yeah. Half the time, that's a lot, though!

Russell:

Who knows if that's accurate.

Amelia:

We should all do time tracking. One thing I think a lot of people run into that's hard when they start doing data viz is... if you get this new dataset, it's going to be in this field that you know nothing about. and you're going to have to really quickly learn about: the context and the field and everything that has to do with that data set, like crossword symbols. Do you have any tricks for doing that? And you usually want to do it quickly because you don't want to spend too much time just doing that research.

 

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