This week, we’re bringing you an interview with Pei Ying Loh, co-founder of Kontinentalist, a publication that uses data to tell nuanced stories that highlight the diversity of Asia.
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Since its start, Kontinentalist has found creative ways to tell stories on topics ranging from how the rubber industry in Singapore and Malaysia was shaped by colonialism, to Asia’s favourite alcoholic beverages. The team also offers workshops on the essentials of data storytelling, based on the tools they’ve used for their own stories.
We caught up with Pei Ying at the International Journalism Festival in early 2023. The full interview was edited for brevity and clarity. You can also listen to it here, or watch it here:
In Old News: What was the idea behind the Kontinentalist?
Pei Ying: We are a data-driven editorial publication and studio based in Singapore, and we're focused on covering Asian issues, trying to bridge the gap between the research sector and the public. When we first started, my co-founder, who is also our director, we wanted to build a platform, hopefully using some sort of a map to be able to distribute information free of charge to people in Southeast Asia to understand how geopolitical trends were affecting their daily lives. For example, impact on the environment, but also how jobs might be taken away or there might be opportunities for businesses.
The project we were really focused on was China's Belt and Road Initiative, which had only been really written or looked at from a very one-sided perspective from Western media and we wanted to sort of balance it. But not also from like a Chinese perspective. So I began to pull together the information to discuss this initiative, but it's really, really boring and very dry.
And that's when I chanced upon multimedia storytelling and data storytelling as an approach to present information in a much more visually engaging manner, but also in a more focused way. And then my team and I use like scrollytelling and Mapbox and things like that, and we became a bit addicted to the practice. And so since then we've really been focusing on transferring that skillset to all sorts of issues. Climate change, cultural trends, cultural phenomena, social justice, so on and so forth.
And we really want to focus on Asia combating, I guess, like Eurocentrism in the news and celebrate the diversity and beauty of Asian cultures in a meaningful way, in a meaningful way as well.
In Old News: You do a mix of stand-alone stories, and series. How do you decide what should be a series and what should be stand-alone?
Pei Ying: That's a that's a really good question. I will start with some background information first. We generally have four large umbrella themes that we try to park our stories under. The first one is what we call Asia debunked. So if we feel that there is a prevailing narrative, a myth, that it's not very helpful or very harmful narrative in both the way it portrays Asians or Asian culture, but in the discussion of the issue, we try to use data journalism as a way to demystify and to myth-bust, essentially.
So we've done things like, for example, like Asia gets a really bad reputation for shark fin consumption. But if we really look at the volume of shark meat trade, it's not necessarily Asia that's contributing to that. And I think that's an important discussion point that's often glossed over. So we have a section on Asia debunked. We also have what we call Future Asia, where we talk about, you know, what's in the future.
And that's where tech, climate change, infrastructural development, all of that goes into that theme. We also talk about Asian diversity. So we look at, for example, the relatively large umbrella that's got Asian societies. We look at cultural phenomena, pop culture trends, queer films, for example, sci fi, and use that as points of celebration of the uniqueness of diversity and complexity that Asia can bring to the forefront.
And then we have a very weird umbrella called Singapore Specials because we're based in Singapore, and it's really where anything and everything related to the country goes. Because of the sensitivity of the political climate in Singapore, it does make us reporting on a couple of things a bit challenging, legally speaking, but also in terms of the data resources available, it's quite scarce because open data is not very well practiced.
So we and end up doing a lot of historical investigations because a lot of people think historical material should be relatively not sensitive. And you can go look at it, especially if it's like colonial era type information. So that's how — and my background is in history, I was a history major — so that's how we ended up doing that particular story on rubber.
Most times we don't intentionally go into something to say like, ‘I'm going to do a series on this topic.’ But what often happens as we as we start doing research, we realize there's a lot of material here and it's too much to pack into one story. And that's when we decide to split things up into like a chapter one or chapter two and try and make it meaningful for the audience.
So I did chapter one as a part of trying to add to the conversation around Singapore celebrating — I don't know why we use the word celebrate — but like commemorating 200 years of colonization, or 200 years since we were colonized. It's a weird thing to commemorate. And, you know, a lot of it was focused on positive things.
And I wanted to talk a little bit about like something that was economic and rarely looked upon and rubber trade was one of them. But while I was preparing part one, I realized the narrative was very limited. It was a lot about ‘this White person did this thing’ and ‘this Chinese person did this thing.’ And they were both rich, privileged people.
And there was very little investigation into like the subaltern part of history, the people who really did the majority of the heavy lifting of the industry and how they were treated, what their economic conditions were like. And that led me to then through part two, which is just to really look at archival material, their wages... and all this is available, it's all in colonial archives.
So that's when I pulled up, you know, information around wages, their living conditions and other journal articles that have done similar investigations and, and to really understand there is a huge system of inequality and discrimination and that has strong links to present day society and how our society is configured in Singapore. And a lot of this like ‘the lazy indigenous person’ narrative that has been perpetuated.
And I felt it was important to use history to address that.
In Old News: How do you decide that a story is a fit for the Kontinentalist? Does it have to fit under one umbrella or are there other factors that you consider?
Pei Ying: So we generally try to fit into those four umbrellas. And we’ve also communicated that to our audience quite clearly. When we approach something, we talk about why it's important for us, especially in our newsletters. We discuss why these identities or negotiating or discussing these issues is important to us as a company and what our mission is.
But in terms of what we really dedicate our time to, we want pieces that have a long shelf life. So a lot of our stories take a long time to develop, at least three to six months, very often, and like ten different people working on a single story at a time. So it doesn't feel right to invest that much into something that will be forgotten next week.
It doesn't feel right to put so much effort into something that will get maybe a lot of clicks on a single day, but tomorrow would be lost in the news cycle. So I think for us, we care more about the quality of the experience and whether or not we are contributing meaningfully to a conversation. And that's a piece of reference that people come to repeatedly over time.
And that is really our measurement of success. So we will look at if our articles have been cited in other journal articles that people have referenced to create other things. And that's how we know we've made it. We've done a good thing and that's what we really aim for. And we try to — whoever pitches us — we try to steer them towards that direction and we assess whether or not there is that, I guess, that timeless quality or what we call evergreen quality before we decide to go further into that.
In Old News: How do you make decisions around your visualisations? And where do you draw inspiration from?
Pei Ying: I think admittedly when I first started, I wasn’t very careful about this and I was kind of like I'm a newbie to the field, I'm really excited. So I used Flourish and a lot of the cool tools. And there was also a lot of, I guess, desire to want to mimic what's been done in the U.S. and even in Europe in better and more well-established data journalism outfits. So like The Pudding or South China Morning Post and Reuters and things like that. But I think now that we've really honed in on the meaning of what we do, our team of designers have also been very purposeful in creating an entire internal guideline and document on how to design our visualizations and how to design our outputs, really.
And I think the focus is really about uplifting Asian communities and not repeating tropes. Be very careful about that. So for example, if you just Google, I mean, no offense to The Economist, for example, but if you just Google Economist and China, you'll get all the covers that are the same. It's always pandas, dragons, red flag, communism, some degree of like, you know, like socialist realism, propaganda style imagery.
And that's perpetuating an immense... I mean, China has a lot of problems, but that is perpetuating an image that is a disservice to a lot of people who live in that country in a culture that might be very easily misunderstood across the world and obviously an attribution to hate crime as well to some degree. I mean, I think for us, we want to be able to portray these issues in a language, so in an art form, that is unique to those cultures that it comes from or in a way that respects them with dignity and things like that.
So for example, in the story that we did on Chinese names, so we looked at a database of Han Chinese names instead of just doing a simple like bar chart to talk about how several names have greater popularity, we used a Chinese chessboard as an opportunity to visualise things, so we use the grid system of a Chinese chessboard to represent how some characters are more represented and how some characters are less represented, and essentially trying to use local art forms to represent and visualise data.
In Old News: You also share a lot of resources and behind-the-scenes of your work. If someone is interested in learning from the work you do, what is the best way for them to do that?
Pei Ying: So we've grappled with this quite a little bit. I mean, even within the team, we still feel like we've done what we can, but we still feel like the learning curve is very steep even for ourselves, where we compare ourselves to like The New York Times or The Washington Post and things like that.
And I think what I've now learned is that the fancy stuff only does probably not even half the job. Like the fancy stuff, the scrollytelling, the animations, they're all nifty tricks that will draw the reader in and make something visually engaging for what is really at the core of everything [which] is a good story and a good investigative question or a good question and you're trying to answer that. It's not just like you are oddly curious about one very niche thing, but you know, it's it's a shared curiosity and bouncing off of that to look into data and see how you can, I guess, answer your question with data.
It's a fairly frivolous example, but in Singapore our Prime Minister has earned a nickname for wearing pink all the time and people have this impression that he loves to wear pink and it's a slightly homophobic nickname, Pinky. And we wanted to talk about that from a data perspective. So we colour picked all his t-shirts from YouTube and made a data visualization and analysed if he indeed wore pink all the time. And you know, it is a well-worn color, but it's often just confirmation bias. So that was something that we did.
And you essentially you never know what questions can be answered with data. But it's most important to start with a question that people actually have and want to know the answer to first. And that's what we usually recommend as a step one and to not be too hung up about creating fancy visualizations and things like that.
We also have a workshop, we call it Data Storytelling 101, where it's really designed to be as friendly as possible to people who have never touched data ever before, they've never seen an Excel sheet before this workshop. So we go through the basics of how you can compose a data story in just a couple of slides and it's supposed to be really beginner friendly.
We've had people who are journalists but also corporate communications, civil servants, even, you know, data scientists, data analysts. [It’s] a ten hour course and it's two days. And that's also a step that we recommend if you are looking for like a no code fuss-free entry into data storytelling.
In Old News: Is there anything else that you want to share that we might have missed?
Pei Ying: I think for us, we are always very open to collaboration. So that's one. We try... we actually reduced the amount of stories that we produce because it is very taxing on the team. So we try to do 10 to 12 big stories a year on our website and we try to make each one a meaningful collaboration of either a nonprofit or an individual who is able to bring something unique to the table, either through a perspective or unique data set that we don't have access to.
So that's something that we're always very open to: collaborations. We're also trying to build a tool that is, we've got some money from Google News Initiative, to run on this for a little while. But we're building essentially a data storytelling platform slash content management service slash community type thing similar to Medium, where you're able to pull together a data story with relative ease.
And it's supposed to give you a little guidance tips and tools, and also for you to learn from a community of data storytellers. So that's going to be launched quite soon, probably around the end of the year. So do keep an eye out for that if you're interested. We're very interested to talk to other media companies who want to use it.
And lastly, we're trying to build a community of data storytellers and journalists within the Southeast Asian media. So if that's also something that you’re interested in, please do get in touch with me on social media channels. I think on Twitter it’s @kontinentalist_ and on Instagram it’s @kontinentalist. I am a weirdo who checks our social media every day, all the time.
So I'm always there but you can also email us at hello [at] kontinentalist.com.