Open Data India Watch

OPEN DATA INDIA WATCH – 2

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Stories

  • Hindu has a timeline of Indian Financial Ministers as part of budget article. Its been done using KnightLab’s timeline framework. Here is the direct link and source of the published Google Doc used for generating.
  • Controlled Vocabulary Services by Government of India. Useful if you want to standardize names in your project.
  • Devdatta Tengse presents SouthSideUp – Maps to Show A web mercator map with south Up and North at the Bottom.
  • Stories from a Database | Despair and Hope At Chhota Gubbara, which caters to tiny newborns, we had 101 babies. 55 were boys. 46 were girls. Not bad! Especially considering that the sex ratio at birth in Uttarakhand is an alarming 886 girls to 1000 boys, our figures seem to indicate that parents are almost as likely to seek help for their newborn girls as for their newborn boys. Statistically, in fact, the difference was insignificant.
  • Accessing Open Data Portal (India) using APIs by R-Bloggers – Most of the data-sets on the portal are available for manual download. Some of the data-sets though are also available to be accessed using APIs. In this post, I’ll go over how to access that data using APIs (specifically JSON API) in R.Again, the variety of R packages available makes this a not so difficult task. I’ve made use of mainly these packages – XML, RCurl, RJSONIO, plyr.
  • A look at how income affects consumption habits By Rukmini S and Sriram Sivaraman. Last week, the National Sample Survey Office, India’s official source of regular large-sample survey statistics on consumption, employment and other core socio-economic issues, put out its 558th report. The report is based on a nationally representative sample of over 1 lakh households in every state and UT, and measures the levels of consumption of various goods and services. As we’ve noted in the paper, the data points to a big revival in the functioning of India’s Public Distribution System. We also looked at how income circumscribes India’s food choices. That second story is the one we wanted to look at a little more closely today.
  • National Natural Resources Management System (NNRMS) has defined standards for GeoSpatial Data for India and its called NNRMS STANDARDS – A National Standard For EO Images, Thematic & Cartographic Maps, GIS Databases And Spatial Outputs (PDF).
  • Here’s why Tamil Nadu, Maharashtra, UP roads are death traps By Rukmini S and Sriram Sivaraman. The National Crime Records Bureau – India’s official source of police statistics – released its numbers for the last year earlier this week. One major part of the findings are, of course the crime statistics, particularly to do with crimes against women. But another fascinating part is what the police terms as ‘accidental deaths’, a catch-all phrase that covers everything from being bitten by a dog to a bomb explosion and suicides.
  • Data.Gov.In has a new visualization Engine to explore and visualize data. You can also add your data to enhance the visualization.

Data

  • Young Lives: School Survey, India, 2010-2011 – A school survey was introduced into Young Lives in 2010, following the third round of the household survey, in order to capture detailed information about children’s experiences of schooling. It addressed two main research questions:1. how do the relationships between poverty and child development manifest themselves and impact upon children’s educational experiences and outcomes? 2. to what extent does children’s experience of school reinforce or compensate for disadvantage in terms of child development and poverty?

World

  • No open data? No problem. 5 ways entrepreneurs are fueling open data in the developing world – On the entrepreneurial side, the World Bank’s Open Finances team has been exploring the commercial value of open data, and looking for opportunities to support entrepreneurs. These goals are achievable thanks to governments who have fostered innovation around public data by taking the step to open it. What happens when governments haven’t yet opened public data? Is it possible for entrepreneurs to take advantage of open data where it does not exist?
  • Alberto Cairo: Data journalism needs to up its own standards– The data visualization expert argues that FiveThirtyEight and Vox have overpromised and underdelivered — and that they need to treat their data with more scientific rigor.
Open Data India Watch

Open Data India Watch – 1

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Stories

Mapping Access to Toilets between Social Groups | Data Stories
The map below reflects that difference in access across districts. For each district, I calculated the percentage of dalit/tribal households with access to a toilet at home. I did the same calculation for households which were neither dalit nor tribal, as classified by the census. By dividing the two, we get a measure of how disparate the access is. For instance, in the district of Budaun, where the crime occurred, 15% of dalit homes according to the 2011 census, had access to a toilet at home, compared with 35% of non-dalit or non-tribal homes. This gives me a disparity measure of about 0.43 (15% divided by 35%). And so on for each district.

Why Punjab still holds aloft the flag of ‘new politics’
While the entire country appeared unimpressed by the Aam Aadmi Party and its promises, Punjab not only sent four of its candidates to the Lok Sabha, but as recent data shows, also overcame the rural-urban divide in its mandate for the party. Srinivasan Ramani explores why.

El Nino may cause weak monsoon & high prices; poses serious challenge to Modi government
As the chart on the next page (El Nino and the Indian Monsoon…) shows, strong El Nino conditions (the shaded region to the right) usually occur along with a weak monsoon. But note that there have been cases, most notably in 1997, when a very strong El Nino was accompanied by a normal monsoon.

Here’s What a Polarized Vote Looks Like
The chart below shows what that change means in a visual sense. It looks at the vote share of the biggest party in each of the 1500 or so polling stations in the constituency, and then plots those values according to how often they occur. So for instance, there were a relatively few polling stations where the largest party got 40% of the vote or below. There were many more with 60% or more of the vote in a booth. And so on. The number of polling stations where the largest party received any given vote share (from 0 to 1), can be read off the y-axis.

Average Daily Wage Rate in Rural India is up on data.gov.in for you to explore.

GoeBlr meet up in Bangalore

Other Good Reads

Visualizing Algorithms : Algorithms are a fascinating use case for visualization. To visualize an algorithm, we don’t merely fit data to a chart; there is no primary dataset. Instead there are logical rules that describe behavior. This may be why algorithm visualizations are so unusual, as designers experiment with novel forms to better communicate. This is reason enough to study them.

GeoBLR

The GeoBLR Sprint 1 – July 3, 6pm – 8pm

I’m excited to announce the first GeoBLR Sprint! The event is happening at The Center for Internet and Society on July 3, 6pm – 8pm. (RSVP)

During the July meetup, we are asking participants to bring their problems around maps and spatial data to the event. Some of Bangalore’s own data experts will be at the event, who will engage in a two hour problem solving exercise with the participants.

Have some map data that needs cleaning? Trouble with map projections or data formats? Looking for some data but not quite sure where to find it? Difficulty choosing colours for your map? May be we can help!

We encourage participants to get in touch with us prior to the event to talk about the issues that they would like to preset. Write to us on [email protected], or post a comment on our Meetup group, or write to me (me at sajjad dot in). We will select couple of  challenging problems and will recommend solutions for others.

http://www.meetup.com/GeoBLR/events/190931712/

See you at the event!

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If you are curious to know more about GeoBLR and why we are doing it, I wrote about it here.

Uncategorized

Democracy Datablog – Chandrashekhar Raman

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So it is done, done and dusted. It has been more than 2 week since the results came in, and quite a couple of weeks it has been, a time of celebration for some and introspection for others. The BJP capped its phenomenal campaign with a final tally of 282 seats, in the process making this the first election in 30 years where one party has been able to win a simple majority on its own.  In the last post, I rambled on wondering what kind of ‘wave’ would be needed to drive the BJP to the kind of victory the opinion polls predicted for the BJP. The semantic debate seems settled now, nothing less than ‘tsunami’ would do to explain the upsurge of support that the BJP was able to muster especially in the keys states of UP and Bihar, a tsunami that has shattered many tenets of Indian politics and left several questions in its wake.

READ THE REST OVER AT DEMOCRACY DATABLOG

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