Month: September 2014

Indians feel safe and like where they stay…relationships is the issue

Gallup has just released what it calls the inaugural Gallup-Healthways Global Well-Being Index (2013). Positioned as a “global barometer of individuals’ perceptions of their well-being”, the research measures the perceptions of 133,000 individuals spread across 135 countries. India ranks 71 in the list of 135 countries.

The well-being index is organized into five elements:

  • Purpose: liking what you do each day and being motivated to achieve your goals
  • Social: having supportive relationships and love in your life
  • Financial: managing your economic life to reduce stress and increase security
  • Community: liking where you live, feeling safe, and having pride in your community
  • Physical: having good health and enough energy to get things done daily

In analyzing the results of the index, Gallup classifies responses as “thriving” (well-being that is strong and consistent), “struggling” (well-being that is moderate or inconsistent), or “suffering” (well-being that is low and inconsistent).

This chart shows the percentage of Indians think that they are thriving in each of the five elements that the research measures, shown against percentage of people in South Asia and in the world who think the same.


The chart depicts percentage of people who think they are thriving

This just challenges some of the assumptions that we have about ourselves. Lets leave the two elements where India’s perception compares well with global/regional perception and focus on the three where it differs significantly.

  1. Social: We always take pride in our strong family life. But the findings challenge that as far lower Indians think they are thriving in having “supporting relationships” and “love” in their lives as compared to even our neighbors.
  2. Financial: Once again, Indians have a far lower perception about their financial well-being than the world and their neighbors. But that is not surprising considering this survey was conducted in the thick of the “policy paralysis” and economic slowdown.
  3. Community: This also surprises, though pleasantly. Despite all the government bashing that we do and the extraordinary self criticism of our society that we indulge in, we have the best perception of our well-being where government and society have a role to play. We like where we live more than others; we feel safe where we live more than than others; and we have more pride in our community than others have in theirs. 





DJ Anti-Showcase: Mismatching Story and Visualization

Traditional media seems to have suddenly woken up to the need of having its “presence” in data journalism. The irony is, few understand the opportunity and how it could potentially impact journalism. But no one wants to give it a miss; it is the coolest thing in the business.

Visualization, the most tangible face of data journalism is the fanciest thing to do. And most of the easy to use and cheap/free tools are slso available to do that. So why not?

This story from Hindustan Times, BJP’s loss in UP worse than it seems, is a great example of how visualization should not be made. The story which analyzes the recent bypolls data to argue that BJP actually lost a lot of vote share is a decent story. It achieves one thing. It negates any argument that BJP’s loss is because of some other party pulling more because of some other factors; or the loss is not because of vote share loss but because of arithmetic reasons. That’s a fairly timely story.

But the visualization that goes with it neither proves this point nor adds any information to the story. It is a completely different comparison between how much votes BJP got in different constituencies and a comparison of those votes, which actually is completely meaningless.

In short, the visualization that accompanies the story is not only unrelated to the storyline, it is of no use. A good visualization, says visualization guru, Alberto Cairo, should be beautiful, functional and insightful. If it is not insightful, it is still a story; a boring story. But this one is not even functional. What’s the point of comparing votes in different constituencies?

A visualization depicting a side by side comparison of BJP’s vote in last election and this one would have simply communicated the idea. In fact, what has been represented as two visuals, could be combined to make the point that the story is making.





DJ Showcase: Final Work of Participants in ICFJ Data Journalism Workshop

The three day ICFJ Data Journalism workshop in Delhi held between 5th to 7th September 2014 culminated in all the participants being divided into groups to work on real life stories using freshly learnt techniques in data scraping, cleaning and visualization. Ideas ranged from Narendra Modi’s popularity on Twitter to changing pattern of media ownership; from transformation of India into a cashless economy to the changing definition of middle class in India.

Here are examples of some of the work that various teams produced at the end of the workshop.

Complaints against police (An Infographic on statistics on complaints against police and conviction rates)

Cashless in India (A data-based story on how India is turning to electronic transactions)

Class Calculator (A tool to calculate which economic category a consumer belongs based on consumption pattern)

Inside Media (An investigation into how ownership patterns have changed in top six most valuable  media companies in India)

Terror Statistics (A data-based story on the cost of conviction on terror cases)

There were more such. Some of them were

Online Video Advertising: The Reality

Crime Against Women in India

Narendra Modi vs Other Global Leaders: Popularity on Twitter

Modi Teri Ganga Maili (Ganga Action Plan)

They either do not have their work available online or if they have, Datajourno does not have those links.

First Data Journalism Bootcamp Starts in Delhi

A 3-day data journalism bootcamp, co-hosted by the International Center for Journalists, the Hindustan Times, Hacks/Hackers New Delhi, Data{Meet} and the 9.9 School of Communication started on Friday in the National Capital Region of Delhi, India. The program—the first of its kind—has managed to attract a mix of veteran data journalists, young media professionals, data science enthusiasts, developers and designers.

More than 60 participants are participating in the workshop, which is seeing some good cross fertilization of ideas among journalists from different types of media and techies. The speakers and mentors are the who’s who of Indian open data/data journalism community, while some of the most well-known data journalists and professionals are participating in the program.

Over the next two days, the participants will work on real life stories involving data.

David Lemayian from Code for Africa giving a few smart tips


DJ Showcase: Times of India (03 September 2014)

The Times of India’s regular STATOISTICS column in its print edition is a consistent effort to popularize infographics based stories. A good infographic, says visualization guru Albert Cairo, should be beautiful, functional and insightful. Most of the TOI infographics are beautiful and functional. But the “insight” or the “story” is often missing.

What’s a story? Something that is unusual (“man bites a dog”), counter-intuitive or in the other extreme, establishes something that people have somehow believed but there is no direct evidence.

Rarely does a great story comes from one source. You may get an idea. But then, you make a hypothesis, test it out by getting more information from new sources or verifying some of the already obtained information.

Data journalism is no different. Once in a while, if you are lucky, you can get a good story from a single dataset. You have to juxtapose a couple of datasets; may be some investigation is required. The “insight” or the “USP” of the story often comes from that. Even some basic observations about exceptions, predominant trend are a good starting point.

Look at this infographics

Almost in all food items (and these are not basic food items like rice, wheat, vegetables or dal) urban India outscores rural India. That is not surprising per se. But there are exceptions. Fish is something where rural India scores. Apple remains primarily an urban fruit while tropical fruits like guava or mango (the desi fruits) are consumed equally by rural and urban India.

A good starting point for a great story is often: why? And this (or any single) dataset won’t answer that. Some of the best data journalism ideas come from single datasets, but great ideas need great execution to make them great stories.