[MUSIC] The popular phrase, "a picture is worth a thousand words," is a relatively recent expression. But the idea that images can be an effective component to or substitute for text, is probably as old as writing itself. When the term visualization is used today, it usually refers as a method for contextualizing data, enabling people to apply their prior experiences, perceptual and cognitive abilities, to draw conclusions about phenomena in the real world. One of the classic data visualizations was produced by French engineer Charles Minard. In his Carte Figurative, Minard uses casualty data to illustrate the facts of Napoleon's disastrous 1812 campaign. You can trace the troop size by following the tan line from the army's starting point at 422,000 men strong at the left through a series of losses over time as the soldiers march towards Moscow. The black line indicates their retreat. And there's a dramatic loss of 22,000 lives over the Berezina River. It is strikingly apparent that the dark line narrows almost by half. Along the bottom of the graphic, the temperature drops to 30 degrees below 0 as the army made their way back to Kovno with only 10,000 men. Minard's achievement here is expertly illustrating a multivariant time-space story in a concise way. This graphic depicts six different dimensions: latitude, longitude, directions of movement, time, temperature, and the size of the troop. It is regarded as the "best statistical graphic ever drawn." Data visualization in newspapers wasn't common until technical advances later in the 19th century. But even as far back as the 1840s, newspapers were experimenting with it. The Tribune of 1849 published on its front page a line chart, tracking the deaths in New York City from the cholera epidemic that summer. At that time, a bigger obstacle than the production difficulties were the Tribune's readers themselves. It is unlikely that everyday New Yorkers in the 1840s would have been familiar with statistical graphs. Therefore, a New York Daily Tribune writer wrote a 300-word annotation underneath the chart to teach readers how to read a line chart. The annotation doesn't just describe the information the chart is conveying, but guides the reader on how to read the line chart. For example, the annotation explains the basics such as the coordinates and axis labels, quoting "each half-inch along bottom line represents a week, and the dates are placed under each." They also explain that the slope of the lines represent the change between data points, saying "their upward and downward slopes represent whether the deaths during those weeks have increased or decreased, rapidly or slowly." Five years later, John Snow made his famous map of the London cholera outbreak around the Broad Street pump. In the 1850s, cholera was believed to spread by bad air. But Dr. Snow believed it was a water-borne disease, during a serious outbreak in London Soho district in 1854. Snow recorded cholera deaths on a simple map to test his theory. And it became obvious that they were clustered around the Broad Street public water pump. The local council was convinced to disable the pump, and the number of new cases sharply declined, confirming Snow's theory. And here today, Snow's mapping is widely regarded as a milestone in the study of the geographic distribution of diseases. Although data visualization in news is nothing new, we have seen an explosion in information and tools to help create data visualizations in the past decades. The growth of data visualization can be largely attributed to three factors: The environment, the demand, and the collaboration. First, in the Internet and digital era, the explosion of data has brought a complementary need for tools to analyze it. With the OPEN Government Data Act, the increase of open data helps enrich data visualizations. Second, data-driven journalism is no longer a nice addition to the publisher; it is a necessity. Besides knowing what happened at a certain place at a particular moment in time, readers also want to be able to understand and explore the context behind the moment. Therefore, journalists are finding ways to adapt to the challenge of telling stories with data. There is also a cross-disciplinary collaboration. With experience in charting data, infographic designers are well suited to bring data visualization to journalism. Researchers in visualization are helping by building tools for non-experts. The emergence of new tools makes the process of creating online visualizations easier. Specifically, several newsrooms have taken important action to make data an important part of their reporting and coverage. In 2009, the Guardian launched Data Blog. The goal of the Data Blog is to share data and visualisations to the general public. The Guardian encouraged re-use and mashups of their data. Readers can submit apps and visualizations that they have created. In 2014, the New York Times launched The Upshot. One of the reasons they are doing this is because of the new opportunity the Internet and the spread of digital data has created for journalists. As the world now produces much more data, and personal computers can analyze it so quickly, they dedicated a section for database reporting in the daily news cycle. They want to "help readers to better navigate the news using data, graphics and technology." There are also a growing number of communities among the general public. In less than five years, Reddit's data visualization community, /r/DATAISBEAUTIFUL, hit 10 million subscribers, and ranked as the top 38 subreddits based on the number of subscribers. That is a community for people to share and talk about visaul representations of data, that effectively convey information. Graphic desks, which used to be treated as a subfield outside the work of newsrooms, are becoming a core part of the newsrooms' operation. Newsrooms and media companies have been actively recruiting people to join the graphic teams. We can check LinkedIn. Those people often have various titles: data journalists, news artists, graphic reporters, data scientists, developers, etc. Although each of thess jobs have different focuses, they share common job responsibilities and requirements. The job description here pretty much shows the workflow and skill set you should have before embarking on a data virtualization career. So, for job responsibilities, here is the summary. You have to be able to acquire, refine and analyze data. Create innovative cross-platform illustrations, animations and graphics. Able to work independently and collaborate with editorial reporters, investigative reporters, web developers and engagement teams to produce visual stories and determine the best strategy for increasing reach through data driven stories. And you also have to be able to develop tools and publishing workflows for the newsroom to standardize the analytic processes. For job requirements, you have to have a vision on how to make data both beautiful and comprehensible. You also need to demonstrate that you are able to use your data analytic and visualization skills to help break big stories. Or reveal compelling insights that adds to intelligent conversation around the news. You have to understand theories of design for humans. Although newsrooms don't have a restriction on the particular language you have to use to produce graphics, you are expected to be technically savvy on the whole creation process-- from data storage to data analytics, design and development. You have to be technically adept at acquiring, building, refining and analyzing data. You have to be familiar with databases and the current scripting language and technology in data analytics, such a Python, R, SQL. You have to be able to put design concept into execution. For example, create interactive graphics using JavaScript, static graphics using Illustrator, mapping using QGIS, and web developing using HTML, CSS. So you get the idea. Besides design news graphics as expected, you are required to be a full fledged journalist, and work closely with reporters and editors. There's so much to learn, but I can assure you that the skill sets you learn are rewarding, even if you work in other industries. In this class, we will think how to think like a data journalist. Learn about the visual presentation of data, how and why it works, and how to do it the right way. In the end, you will be able to make graphs like The New York Times or FiveThirtyEight. And so you can embed your beautiful, interactive charts in your publications, blog posts, and websites.
