Big Data 4 Development

Samarajiva, R & Lokanathan, S.
Looks like what we wrote in EPW is having ripple effects. A cost-effective, intermediary method of collecting data has emerged in the form of direct source collection, in which individual citizens themselves are relied upon as the primary source of information. This is done through mobile network data, generated by all cellphones and includes information such as frequency and duration of calls, Internet plans and visitor location registry data. In cities buckling under the pressure of a growing population and facing a possible breakdown of infrastructure, this method of pre-informed planning allows the populace itself to contribute to the solution. LIRNEasia, a Sri Lanka-based think tank, has carried out an extensive study demonstrating the value of mobile network data.

Data visualization

Posted on January 12, 2016  /  0 Comments

One thing working on big data has done is to sensitize us to the power of visualization, especially using maps. Here is one that impresses, especially in view of our focus on urban development: Data viz extraordinaire Max Galka created this map using NASA’s gridded population data, which counts the global population within each nine-square-mile patch of Earth, instead of within each each district, state, or country border. Out of the 28 million total cells, the ones with a population over 8,000 are colored in yellow. That means each yellow cell has a population density of about 900 people per square mile—“roughly the same population density as the state of Massachusetts,” Galka writes in the accompanying blog post. The black regions, meanwhile, reflect sparser population clusters.
Returning from an expert meeting on big data n Bangkok, I was in the passenger seat on the way back from the airport. Looked up Google maps for the traffic. This feature has been available in Sri Lanka only for a few weeks. On the main roads, it was pretty accurate. Once we turned off to a busy, but not-a-principal road, the traffic indicator went blank.
ESCAP is part of the UN. By design, it is better positioned to work across silos than specialized agencies such as the ITU and WHO. One of the key points made about the sustainable development goals that were recently adopted is that they require working across silos. Big data naturally cuts across disciplinary boundaries. It transcends organizational silos.
In a few hours I’ll be speaking at a panel on how big data is already being used for sustainable development. ESCAP has pulled together an interesting group of people together to talk about how big data can help with the daunting task of measuring progress on the 169 targets that the UN has set for itself. The slides I will be using are here. Sorry they do not tell the full story since I have been asked to keep them to a minimum.
The Urban Development Authority of Sri Lanka and the Young Planners Association of Sri Lanka organized a workshop at the UDA premises on 4th December 2015 for LIRNEasia to share is ongoing research on leveraging mobile network big data for urban and transportation planning. The slides are available HERE.
Big data is sexy these days but still it’s a big deal to get coverage in the New York Times for research conducted in Rwanda. Josh’s work is complex and involves training data sets and also the use of multiple kinds of data. He and his colleagues relied on anonymized data on billions of interactions, including details about when calls were made and received and the length of the calls. The researchers also looked at when text messages were sent, and which cellphone towers the texts and calls were routed through in order to get a rough idea of geographic location. “So it’s the who, where and when of the call, but not the what or the why,” Dr.

What is big data?

Posted on November 18, 2015  /  0 Comments

I spent the last two days at a meeting on big data in the global south. The sixty people in the room had no shared understanding of big data, which led to some interesting discussions. Then someone stated that he wished big data would be defined. Big data is characterized by volume and variety. The third part of the 3 Vs, velocity, is irrelevant, as has been argued by many including Viktor Mayer-Schonberger.
I was a little surprised to be invited to a meeting on big data organized by the Institute of Technology and Society of Rio de Janeiro. But then I realized that the event was scheduled back to back with IGF 2015 in Joao Pessoa and that they were basically piggy-backing on the attraction of large numbers of international experts to Brazil in November 2015. With some effort, I was able to find a few people who were not lawyers participating in the event, but it was dominated by those of the legal persuasion. This meant that there was a presumption that laws and regulations were needed to avoid the bad things that could be imagined. Usually, what we have is a battle of imaginations.
Today I spoke at a session on Big Data for Development: Privacy Risks and Opportunities organized by UN Global Pulse and SIDA at Internet Governance Forum 2015. My presentation that sought to set the stage is here. Many interesting questions were raised, but I will here focus on one particularly uninformed one. The questioners (this is a synthesis of two questions) said that while the data holders may give data for free, they will start to charge for it soon. Therefore, it is important to ensure that the value of the data created by mobile users should be addressed and that users should get paid for their data.
Today I had the pleasure to talk about LIRNEasia’s ongoing multi-disciplinary big data for development research at the IDRC Asian Regional Office in Delhi. The work that we have been doing in this space has been funded primarily by IDRC. It was engaging talking to experts with interests in different domains (agriculture, health, governance, climate change adaptability, urban and transportation policy, electricity, livelihoods) working in India as well as elsewhere. The slideset I used is here.
It’s a little odd to use a concept like vertical integration but that seems to best explain what IBM is doing. IBM calls what Watson does “cognitive computing,” heralding an age of machines that supposedly think. What the company has not figured out is how to make this into an engine of growth. The tech giant has had years of shrinking revenue, but says its investments in Watson will take time to bear fruit. It will be picking up more talent in the deal.
As part of the International Development Research Centre (IDRC) distinguished lecture series, Sriganesh Lokanathan, Team Leader- Big Data Research at LIRNEasia will be giving a talk in Delhi (Ramalingaswami Conference Hall, International Development Research Centre, 208 Jor Bagh, New Delhi 110003) on Monday, 2nd November 2015. Sriganesh will be speaking on the topic of “Leveraging mobile network big data for developmental policy: opportunities & challenges.” Anyone who wishes to attend should RSVP to Pratibha Shukla – email or call +91-11-2461 9411 (extn: 7406) Program: 11.00 am        Welcome and introductions: Dr.

Two days debating big data privacy

Posted on October 26, 2015  /  0 Comments

I spent two challenging days at the first face-to-face meeting of the Privacy Advisory Group of UN Global Pulse in Den Haag. BIt was challenging because it was scheduled adjacent to a privacy commissioners’ conference and because the location was in Europe where privacy protection has been elevated to quasi-religious status. We as researchers are trying to solve problems that affect millions of people in developing countries such as traffic, unresponsive and poorly planned cities, the spread of diseases and so on. To us privacy and other harms matter, but in the foreground of our thinking we always place the social problems we are trying to solve. We attack the privacy problems because they get in the way of the larger purpose.
LIRNEasia CEO participated in two more events at the ITU Telecom World 2015 held in Budapest, Hungary. The ICT Economic and Industry Round Table aimed to look to the future to imagine with digital development would be.  Helani spoke about state investment into the backhaul infrastructure, and about private sector entry into connecting the unconnected through zero rating. The other panel today was titled The Data Rich, Decision Making Poor: How to use Big Data for Improved Government Action.  Helani showcased LIRNEasia’s Big Data research and our research inputs into the the Western Region Megapolis plan in Sri Lanka.