Ideally, we would have had findings. But we are in the middle of research, so what we can present is work in progress: problems that have been faced; those that have been solved; those we’re still working on; etc. Hopefully, once we get our hands on the needed epidemiological data we will present findings in a few months. We are grateful to the incoming President of the Commonwealth Medical Association, Professor Vajira Dissanayake, for creating this opportunity for us. The presentation was made at a session chaired by Dr Hasitha Tissera, the Head of the Epidemiology Unit of the Ministry of Health.
I hope to write more about the insightful discussions at the workshop convened by LIRNEasia and CIS. For now, here are the slides I used to frame the discussion on Harms from Surveillance, (In)security, and impacts upon Privacy and Competition. Image source.
With support from the International Development Research Centre of Canada, LIRNEasia and the Center for Internet and Society are today convening a meeting of researchers working on aspects of big data for development in the Global South. The hope is that we will be able to contribute to shaping a research and policy agenda and map out a path for productive collaboration. A document was prepared as the basis for discussion. Here is an excerpt: However, it is important that those engaged in policy analysis make the effort to understand what data is available, in what formats and what is being done with it. For example, the mobile networks in developing countries are different from those in developed economies.
One of our current priorities is to work with the National Statistical Agency to see how we can complement official statistics instruments on socio-economic monitoring. China watchers are not collaborating with the NSO. They are trying to second guess it. I was wondering though, wouldn’t we be happy if we got these kinds of correlations? “Big data provide an increasingly comprehensive and timely lens” on the world’s second-largest economy, the analysts wrote, adding a caveat that such indicators should be interpreted with caution.
There appeared to be a problem with loading the slideset, so I went to Plan B. I was just about to do a big data talk with no slides. That is the first learning: always have a Plan B and be ready to improvise. This being Oxford, I thought they could access the slides off the Internet. But then the technical problem was solved and I gave a conventional talk.
In our big data for development work, we collaborate with data-savvy economists as well as economists who can code. Within Sri Lanka, we have not found them, but we keep looking. But looks like this is the future of economics. But what the tech economists are doing is different: Instead of thinking about national or global trends, they are studying the data trails of consumer behavior to help digital companies make smart decisions that strengthen their online marketplaces in areas like advertising, movies, music, travel and lodging. Tech outfits including giants like Amazon, Facebook, Google and Microsoft and up-and-comers like Airbnb and Uber hope that sort of improved efficiency means more profit.
I was asked to make one point about the way forward at the closing session of the excellent e agriculture solutions forum organized by the FAO and ITU offices in Bangkok. Here is what I said (more or less, but this is the jist): Big data in agriculture We have come a long way from being fixated on radio as the be all and end all of ICTs in agriculture. We are fortunate to be living in an age when we can even take smartphones for granted in Myanmar, a country still listed as an LDC and one which went from 10 mobile connections per 100 people to over 80 in less than two years. Our own surveys (early 2015) showed that 63 percent of all mobile owners in Myanmar had smartphones, with more computing power than the computers we used just a decade ago. The mean price of a handset was USD87, with the largest number being in the USD 50 range.
As part of our big data work, we have been looking at sources other than mobile network big data for socio-economic monitoring. Night lights images from satellites was the favorite. But I’ve been always skeptical, partly because of looking down from the New Delhi-Colombo flight which flies through the middle of India and then right down the island from Jaffna. The intensity of the lights is so much higher in southern India, than in Sri Lanka. This story is about daytime images taken by satellites.
Lokanathan, S., Kreindler, G., de Silva, N. D., Miyauchi, Y.
In our article published last year on big data for urban development in the developing world, we said At one extreme of smart-city initiatives lies the vision of a centrally coordinated city resting on pervasive use of specialized sensors (e.g., one under each parking space; multiple sensors at intersections), real-time or non-real-time analysis of the resultant big-data flows, and reliance on mathematical models. South Korea’s Songdo is the exemplar. Reports of plans for green-field developments indicate that the Modi government is leaning toward this vision.
In our teleuse surveys, we found that missed calls beat out texts in some countries (e.g., Bangladesh v Philippines). One explanation is that there are more illiterate people in the countries where missed calls predominate. Qualitative research found that a lot of texting did not involve literate work, mostly it was forwarding messages sent by others.
LIRNEasia is currently hosting Dr Ayumi Arai from the University of Tokyo’s Center for Spatial Information Science. She is also a Research Fellow with LIRNEasia collaborating on our big data for development research in Sri Lanka. We took the opportunity to organize a lecture for her yesterday (14th July 2016) for the senior staff of the Department of Census and Statistics (DCS) Sri Lanka, as preamble to a longer discussion with the department to collaborate with LIRNEasia and our partners on big data and official statistics in Sri Lanka. Dr Arai’s talk was on her ongoing Dynamic Census research work in Bangladesh which utilizes mobile network big data and official statistics to provide spatio-temporal insights on the socio-economic and demographic characteristics of the population at high granularity and high frequency. The slides from her talk are available HERE.
I am speaking on a big data panel at the 21st ITS Biennial Conference in Taipei, described below: If Big Data can open up opportunities at the same time it raises serious policy issues. Big Data raises concerns about the protection of privacy and other values and may drive a rethink of traditional approaches to data governance: a shift from trying to control the data itself to focusing on the uses of data. Prevalent data standard protection may have become higher as legal standard may be inadequate. Openness of the data and data ownership are pending issues. Besides, the rise of the “Data Barons” is triggering market concentration and data oligopolies issues: “Dark Side of market concentration and data oligopolies.
LIRNEasia has been at the forefront of big data analysis for development in Sri Lanka, conducting in-house analysis to generate actionable insights across a range of policy domains. On 6th May 2016, LIRNEasia and the Health Informatics Society of Sri Lanka jointly convened a planning meeting on building better models for forecasting the propagation of infectious disease such as dengue in Sri Lanka. The meeting was intended to lay the foundation for a multi-disciplinary collaboration engaging health informatics specialists, epidemiologists, and data scientists to identify research priorities and opportunities. The participants included the following: Madhushi Bandara, Junior Researcher, LIRNEasia Prof Vajira Dissanayake (Health Informatics Society of Sri Lanka, Biomedical Informatics Programme – Postgraduate Institute of Medicine) Dr. M.
A early paper based on LIRNEasia’s work on big data was presented at the 2014 CPRsouth conference in Maropeng, South Africa. The journal article based on that has just been published. The abstract: Rapid urban population growth is straining transportation systems. A big data–centric approach to transportation management is already a reality in many developed economies, with transportation systems being fed a large quantity of sensor data. Developing countries, by contrast, rely heavily on infrequent and expensive surveys.
The 4th Circuit Court of Appeals upheld what is known as the third-party doctrine: a legal theory suggesting that consumers who knowingly and willingly surrender information to third parties therefore have “no reasonable expectation of privacy” in that information — regardless of how much information there is, or how revealing it is. Research clearly shows that cell-site location data collected over time can reveal a tremendous amount of personal information — like where you live, where you work, when you travel, who you meet with, and who you sleep with. And it’s impossible to make a call without giving up your location to the cellphone company. “Supreme Court precedent mandates this conclusion,” Judge Diana Motz wrote in the majority opinion. “For the Court has long held that an individual enjoys no Fourth Amendment protection ‘in information he voluntarily turns over to [a] third part[y].