An Indian Data Journalism Showcase: #HHDelhi’s Experience

2013-07-14 16.59.40We just wrapped Hacks/Hackers New Delhi’s “data journalism showcase.”  A few takeaways.

We began by trying, inadequately, to define “data journalism.” A few practical definitions:

-Using data to source story ideas

-Using data to visualize stories

Although both of these are part of data journalism, they don’t define data journalism.  The data journalism handbook says the following, “What makes data journalism different to the rest of journalism? Perhaps it is the new possibilities that open up when you combine the traditional ‘nose for news’ and ability to tell a compelling story, with the sheer scale and range of digital information now available.”

Realistically, there’s no effective difference between the great data-driven stories of today and those of yesterday, except that technology allows writers the ability to process a lot more data more quickly and effectively than before, and the increasing visibility of “open data” means that content that was previously off-limits is now fair game.

Insights from the presenters:

Avinash Celestine of ET has been patiently mining the Indian government’s census and NSS data in order to pick out and explore broad socioeconomic trends on his blog. The project he highlighted was a post in which he’d separated women’s labor force participation by rural and urban areas, and found contrasting trend lines for each. (Rural women are withdrawing from the labor force more markedly than urban women are.)  He correctly pointed out the connection between womens’ employment and economic cycles, but also mentioned that the data don’t tell us one important fact: whether women want to withdraw from the labor force or not.

His broader point was that data is conceptual, and each one of his blog posts begins with a question (the question isn’t determined by the data, although the answer is).

Data Source: NSS,

Tools: D3 database of visualizations, Tableau Public (free)

Themes: 1. using tools that can quickly clean and graph data and 2. paying equal attention to what data say and what they don’t

Cordelia Jenkins of Mint presented the winning project from the GEN Editor’s Lab hackathon in Delhi, “Slum Economics.”  The project is a comprehensive, searchable database that presents information and statistics about slums. The project is an app (similar in scope to some World Bank data apps). It’ll take three months of development before it’s ready for the public, although the team demo-ed the basic functions at the Editor’s Lab event.

Data source: Indian slum data

Themes: you need a developer to build more complex apps and visualizations, the free tools won’t cut it; data still can’t sub for on-the-ground reporting

Neeta Verma of NIC and, on the Indian government’s extremely robust new data portal, which includes all sorts of functions, including embeddable visualizations.  Downside: not a lot of data available yet, nothing being done (as of now) about standardizing the manner in which data are presented.

Theme: at least it’s not in PDF format!

Ravi Bajpai of Down to Earth has been churning out visualizations for the D2E blog, including this one on perceptions of corruption in various Asian countries.  For this post, he isolated South Asia country data and compared these countries to each other and to global averages. An interesting treatment, and one that made for a very engaging post since every one of his infographics was interactive. This led to some discussion as to how much interactive graphics increased a post’s popularity, and Bajpai’s conclusion was that the graphics increased traffic, time on page, and share-ability on social media.

Data source: various surveys

Tools: Data wrapper, Tableau (free)

Theme: you can produce good-looking, share-able data journalism in a hurry

Guneet Narula of DataMeet on various projects that the collective’s members are undertaking, including the Geohackers blog, and the India Water Portal. His prez led to some discussion of possible collaborations with H/H, since most of their group comprises people from a technical/coding background. Most of them are not looking at journalism, perse, but at cool things that can be done with data.

Tools: Leaflet, MapBox

Theme: It’s not that hard to understand the basics of the coding

Overall takeaway: data journalism is far more vibrant in India than I thought when I set out to organize this showcase.  Even if we don’t have the answers, a lot of people are asking the right questions.  The increasing availability of data – the govt portal is an important and significant step in a more transparent direction, provided truly significant datasets find their way to the site – means that there are very valuable lessons/stories to be found in the numbers.

When I look at the Guardian’s data journalism awards recap, however, I notice the broad and audacious scope of the questions that some news organizations are tackling.  Whether it’s La Nacion’s enormous database of senatorial spending or Thomson Reuters’ epic chart of political/economic power in China, I think we in India could afford to ask even bigger questions than we’re currently asking.  The great thing about data is its scope – so let’s take further advantage of that.

Want to see what other people had to say about the Meetup? Check out the excellent Storify.

One thought on “An Indian Data Journalism Showcase: #HHDelhi’s Experience

  1. 1. Indian media organisations will have decide on how important is data journalism to the overall scheme of things in their online news operations – the resources they can plough into it and what kind of a team they can build.

    2. Create the right kind of platforms for it.

    3. Promote data journalism in a focused way.

    Finally it is not about data journalism alone; these questions relate to their vision of online journalism itself.

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