“Wrestling with the past”: How Chris Dalla Riva uncovered the deeper story in Rolling Stones’ GOAT music album rankings
At first glance, it’s just a list — a familiar sight to music lovers and critics everywhere, another ranking of the 500 greatest albums of all time by Rolling Stone magazine, created in 2003, 2012 and 2020. But upon closer inspection, it becomes clear that this is no ordinary list.
In “What Makes an Album the Greatest of All Time?,” an interactive story published by The Pudding, Chris Dalla Riva and Matthew Daniels sought out to analyze music’s best over the decades. In doing this, they revealed something deeper: hidden biases connected to the age, gender and race of the voters who judged and inevitably shaped how we remember and honor famous albums. The innovative scrollytelling piece from The Pudding allows visitors to visually explore which albums have made themselves a permanent fixture on the list, which albums were most popular among voters, the demographics and potential bias of the voters, and much more.
Storybench spoke with main contributor Dalla Riva, a musician and data journalist, about his specific stylistic intentions for this interactive scrollytelling piece, the process and challenges of the time-consuming creation, and biases he and Daniels uncovered from the judges who ranked this list.
The following interview has been edited for length and clarity.
How did this project come about?
Matt found that some person online just had a public Google Sheet that had Rolling Stone’s pop albums lists from all three times that they’ve constructed these lists. So that had basically the rankings, the year the rankings occurred, the album and the artist. The bulk of what we did was just attaching a bunch of data to each album. So when did [the album] come out? Like, how old was the artist when it was released? Who was the artist? What was their gender, stuff like that. When did the artist’s first album come out? So that [process of manually expanding the dataset] took a couple weeks. And Matt and I tag-teamed that. And then he also put together a data set of all the voters, and we attached their birth [year], the birth year of each writer [and other demographic information].
Did you have any specific stylistic intentions going into this piece?
One of the initial concepts was [it would feel]f like you’re digging through a bin of records, which we didn’t adhere to exactly, but that for me was important. How can we show all this data, but in a way where you’re looking at these very tangible objects that people are familiar with, connect with, and have deep emotion for? Like the cover of “Abbey Road,” or the cover of “My beautiful, dark, twisted fantasy.”
The data itself is indicative of the story. But it’s about making the data come to life in a way that is different from when I initially cooked up a couple bar charts and line charts. It tells the same story, but [it’s more] engaging.
What was your main challenge in this process?
There was definitely a lot of back and forth, before we even started working on the design, about what we wanted the piece to say. I believe there was a whole section or two that was cut. And then again, how do you display the data using album covers? How do you show this data with album covers in a way that tells the story and isn’t deceptive, because you are dealing with hundreds of albums? So we had to come up with a way to display them, such that if you’re looking at this on your phone, you’re still going to be able to get something out of it, because it’s a lot of information, a lot of pictures. Especially the last piece where we show who the voters are and where they ranked albums, because you’re showing hundreds of faces of voters and also hundreds of albums.
Can you speak about the voters or judges in your piece and any potential biases they carry?
When we got to the judges, that was where I felt like the visuals could really shine. What we wanted to do was just show the faces, and then the reader can do whatever, gaining a lot of data just by looking at the mosaic of photos.
People get mad online about any great music lists, especially Rolling Stone’s, and I definitely held that perspective that it’s just riddled with biases to some degree, and it’s not even a good list. I thought we were able to lay out [this idea] really well that, yes of course it’s littered with biases based on who the people are, where they’re from, what they look like, when they were born, etc. But also by the end, [you] can come away with this perspective that even though the process is really messy and imperfect, it does do a decent job at wrestling with the past and trying to figure out what is important from the past. That was something I found by the end [to be] really, really powerful – like the past isn’t some static object, we’re always trying to figure out what it means and what’s important from it. This piece conveys that.
Do you have anything else you would like to add?
This [project with Matthew] was a lot of fun. Despite all of the manual aggregation of data that’s not always fun, when you look at it at the end, it looks cool. I hope people look at this and can see how we wrestle with the past. And additionally, put on an album they’ve never heard before.
Because at the end of the day, that’s what it’s about. Good tunes.
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