Welcome to DataJourno

Welcome to DataJourno, a small but sincere initiative to popularize data journalism in India.

Data journalism is an idea whose time has come.

As a concept, it is certainly not new. For years, journalists have used data to support their stories, to analyze trends and once in a while, to create hypotheses to probe. The stories created through those means have been as popular and successful as any other story.

But a few things have changed in recent years which have raised a renewed interest in data journalism.

The most practical reason is the availability of tools that makes handling data far easier. Earlier, only those journalists who had a mastery over numbers could play with the data. Areas of journalism where this was important in any case—such as business journalism—saw fairly good examples of data journalism. This was also the reason why, in the minds of other journalists, data journalism came to be strongly associated with business journalism. But with the availability of easy-to-use tools these days, a journalist need not be an expert mathematician or statistician to analyze data and find out interesting trends. That suddenly makes data journalism a viable tool for any journalist.

Another reason which has raised interest in data journalism, of late, is the availability of plenty of data. Again, earlier, it is only listed business firms that released data. With the open data movement getting stronger and stronger, governments across the world are releasing far more data (mostly online these days). More importantly, those data are comparatively recent and can be meaningfully used. This makes the work of journalists far easier. They can focus on their core area—that is getting a scoop or analyzing a trend, based on their understanding of the area—without taking rounds of government ministries and agencies, just to get a report.

The third  phenomenon is the rise of social media. Social media combines the anecdotal with statistical. Earlier, a reporter spoke to a handful of people or media houses assigned time-consuming costly research work to market research agencies. Today, thanks to Twitter, Facebook, SurveyMonkey andLinkedIn, a journalist can create a poll in minutes and can get a significant number of responses in a matter of days, even hours. And it hardly costs anything. In such dipsticks, the role of data analyst has to be played by the writer, as there is no agency involved.

All these have pushed the journalist to the midst of a lot of data. And they are not complaining.

But a word of caution here. Data journalism is not primarily about data. It is about journalism. Just as you need nose for stories/news in any journalism, so do you need in data journalism. You are not a great data journalist if you are an expert in data crunching—there are many in those analytics/consulting companies who do that perhaps far better than you—but if you can do great stories using data. The final measure is how good is the story, not how good is the data analysis. In that sense, it is not anything drastically different from any other tools of journalism.

Here are some popular misconceptions about data journalism.

  1. Data journalism is about lots of numbers. You may just quote a single number in the final story, as long as that number tells you a story. In fact, the best stories are often those that are not number heavy. But numbers often take you to the story. Or, they make or break your hypothesis.
  2. Data journalism is about business journalism and social/developmental journalism. Not necessarily. True, traditionally, business journalists have done most of the data based stories. With the rise of open data, most of the good examples that you find today are  about governance/development/social indicators, they are by no means the only areas. Here is an Indian example of a very different area. Who is the actor for whom the great singer Mohd Rafi has sung maximum number of songs? The perception suggests it must be Dilip Kumar or Shami Kapoor. But analyze data and you find it is neither; not for that matter, even Rajendra Kumar. It is, Johny Walker. Now, that is a story. And now, that is example of data journalism. It often shows you a truth that may be very very counter intuitive. Isn’t that what every journalist wishes to do?
  3. Data journalism is about open data. A lot of good examples of data journalism that we are seeing today are those which use data from government and multilateral development agencies, that are made available to all proactively. That makes many associate data journalism with open data. Even Wikipedia, in it definition of data driven journalism refers to that. But that should not be the case. Data journalism should not concern itself with the source of the data. It is about a set of practices and tools.
  4. It is journalism with a cause. With the rise of open data, many NGOs and activists have used data and data analysis to bring accountability for public servants even initiate action in some areas, long ignored.  Many of them have used traditional media/own media to do good stories to argue their case and further the cause of development and governance. That is all very good. But the definition of data journalism should not be restricted by that. All that data journalism—or for that matter, any journalism—should strive for is a good story. Nothing more, nothing less.

Data journalism is here to stay. Hope, DataJourno will contribute in its own small way to further the cause.

Here are some thing what we plan to help in, as part of the community. We are looking for more ideas and suggestions.

  1. Showcase good examples of data journalism from Indian media
  2. Recognize the best among them
  3. Help journalists and students of journalism acquire skills in data journalism and data visualization by collaborating with employers and journalism schools
  4. Work actively with major sources of data including the government, NGOs, industry bodies, and research and consulting firms to make their data available to journalists
  5. Disseminate information about major happenings in data journalism globallly
  6. Make available resources to one and all in the community
  7. Help school children appreciate data and use visualization

The list would be modified based on your feedback and suggestions.

 

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