In this edition of Media Matters, Fublis explores the innovative world of data journalism with Jiang Chuqin, a passionate advocate for the power of data analysis and visualization in storytelling. Jiang’s journey into data journalism began serendipitously but quickly evolved into a profound exploration of how numbers and visuals can uncover hidden stories and present complex ideas in engaging, accessible ways.
Her experiences include attending the prestigious NICAR conference and working on projects that blend investigative reporting with interactive data visualization. Jiang’s approach highlights the importance of adapting to emerging technologies, such as AI and machine learning, to create immersive narratives that resonate with audiences in a fast-paced digital world.
In this interview, Jiang shares valuable lessons, insights, and advice for aspiring data journalists, offering a glimpse into the evolving intersection of technology, storytelling, and journalism.
How did you develop your passion for data analysis and visualization in journalism?
Jiang Chuqin: My passion for data analysis and visualization in journalism developed quite unexpectedly. When I was choosing my college major, I had never even heard the term “data journalism.” I was admitted to the program largely because I performed well in the interviews and I could get in with lower Gaokao score requirements.
However, everything changed during the summer before I started college. I stumbled upon books about data visualization in my hometown library. I could not remember all the names but one might be Information is Beautiful, and it completely captivated me. The way those visuals are used to convey complex information in an engaging and accessible manner opened my eyes to the power of data in storytelling. I became incredibly excited about the possibilities that awaited me in the coming four years.
As I delved deeper into my studies, I realized how essential data analysis and visualization are for effective journalism. They provide a unique way to uncover insights and present information that can significantly impact public understanding. This blend of creativity and analytical thinking has fueled my passion ever since.
Can you share a project that’s especially memorable for you and shaped how you approach data reporting today? What made it stand out?
Jiang Chuqin: One project that stands out for me was a presentation I attended at NICAR (National Institute for Computer-Assisted Reporting, a data journalism conference in the United States) in 2022. The journalists from ProPublica and The Palm Beach Post did that project to bring light on the air pollution caused by burning sugar cane in Florida. The project remains one of my favourites because it exemplified solid data collection and analysis, coupled with a strong investigative angle that made it highly newsworthy.
What truly impressed me was how the project incorporated cool interactive data visualization to effectively communicate the story. The visuals not only made the complex data more accessible but also engaged the audience in a compelling way.
Since that experience, it has become my goal to create such a project with reporting, data analysis and interactive visualization. For my master’s degree project, I pitched a story idea about how climate change affects a type of bird in New York. I visited several islands where the bird habitats are located and gathered data from various government departments, NGOs, and scientists.
My mentor encouraged me to think visually from the very beginning. I created storyboards to conceptualize the type of interactive elements I wanted to include in the project. This led me to my first individual visual project using Scrollama and D3, which allowed me to effectively deliver the news story with those fancy techniques.
What do you find most rewarding about working with data in journalism? Is there something unique that keeps you excited about it?
Jiang Chuqin: What I find most rewarding about working with data in journalism is its ability to uncover hidden and original stories that might not be immediately apparent through traditional reporting methods. Data allows us to dig deeper, revealing patterns and trends that can provide a bigger picture.
Another unique aspect that keeps me excited is the power of visualization. Sometimes, one graphic can speak louder than several paragraphs of text. In our fast-paced world, people often have only a few seconds to engage with a story, and a well-crafted graphic can convey a large amount of information quickly and clearly. This ability to grab attention and communicate complex ideas effectively is incredibly impactful.
Moreover, the continuous evolution of data tools and technologies means that there is always something new to learn and explore. The dynamic nature of the field keeps my curiosity alive and motivates me to keep a very close eye on the latest advancements in tech.
Are there any trends in data journalism right now that genuinely excite you? What makes them interesting to you?
Jiang Chuqin: The rise of AI tools excites me the most. These advancements are making coding and data analysis significantly more accessible to individuals who may not have a background in programming. This development of technology opens up new possibilities for storytelling and analysis.
What I find particularly interesting is that, despite the availability of these powerful tools, many reporters still struggle to envision the potential uses of data in their work. There remains a noticeable gap between traditional reporting and data-driven journalism. However, I believe that as AI tools become more prevalent, this gap can start to close.
What new tools or technologies are you curious to explore in data reporting? Anything that you think could change the way stories are told?
Jiang Chuqin: I was particularly excited about the launch of VisionPro and similar technologies because the platforms we use to consume news can significantly impact how stories are told. Over time, we’ve seen a shift from newspapers to the web and then to mobile, with some countries skipping the web era entirely to go straight to mobile. This evolution has transformed the journalism industry in different countries, and most newsrooms nowadays are striving to adopt more digitalization solutions.
As tools like VisionPro become more prevalent, I believe data journalists will need to adapt by learning how to present data in new ways, such as in 3D formats or through virtual and augmented reality. This could create more immersive experiences that enhance storytelling and engage audiences on a deeper level.
It might sound a bit far off, but we should never underestimate the speed of technological development. Innovations that once seemed distant can quickly become reality.
How do you think AI and machine learning might change the field of data journalism?
Jiang Chuqin: As I mentioned earlier, AI tools can simplify coding tasks for traditional reporters and small newsrooms, allowing them to focus on storytelling rather than the technicalities of data analysis and visualization.
I think there will be a near future where simple graphics can be generated and published automatically with some short prompts, which can enable any journalist to analyze data and present information quickly and effectively.
Machine learning also opens up exciting possibilities for investigative reporting. For instance, one newsroom has trained models to identify sexual assault messages in dating apps, providing insights into the risks faced by young women in a more solid manner. Additionally, newsrooms have used bots on social media to analyze biases in political narratives and to engage with citizens to report local air quality at certain times of day.
These innovative applications demonstrate the vast potential of AI and machine learning in enhancing data journalism and driving impactful storytelling.
What’s one valuable lesson you’ve learned in data journalism that you wish you’d known when you started?
Jiang Chuqin: Collecting data always takes much longer than the visualization process. I tended to underestimate the time and effort required to source reliable data initially.
Moreover, data is never perfect. In a lot of cases, data is incomplete, which makes the cleaning process crucial yet time-consuming. Data can be biased too. It’s essential to approach data with a critical eye and be prepared to invest significant time in ensuring its accuracy and integrity before moving on to analysis and visualization. Understanding these challenges upfront would have helped me set more realistic expectations.
How do you approach the challenge of presenting complex data in a way that’s accessible and engaging for readers?
Jiang Chuqin: I always prioritize the story first and the data second. I believe that the narrative should guide how the data is presented, ensuring that it resonates with readers and captures their interest.
What has been one of the toughest challenges you’ve faced as a data reporter, and how did you work through it?
Jiang Chuqin: Data journalism is still very new to many parts of the world. Not many newsrooms have a specific team dedicated to data reporting. This makes it difficult to find a position that focuses solely on data without having to consider other options and opportunities.
To navigate this challenge, I took on text reporting jobs while actively seeking out data elements in my work. By integrating data analysis into my reporting, I was able to maintain my focus on data journalism while gaining valuable experience and expanding my skill set. This approach helped me build a diverse portfolio and showcase the importance of data in storytelling.
For young journalists interested in this field, are there certain skills or tools you’d recommend focusing on to get started in data reporting?
Jiang Chuqin: I believe the fundamental starting point is to understand how to read, interpret, and analyze data. It’s essential to begin with some basic statistical concepts, as this will provide a solid foundation for your work.
For data analysis, don’t underestimate basic tools like Excel and Tableau. For data visualization specifically, I suggest trying out DataWrapper and RAWGraphs. These tools are user-friendly and can help you get comfortable with different types of charts and the data inputs they require.
If you have an interest in coding, there are numerous online resources available to help you learn the basics of programming languages like Python or R. These languages are widely used in data analysis.
