Big Data 4 Development


LIRNEasia was a core partner for Sri Lanka’s first national summit on “Foresight & Innovation for Sustainable Human Development” that was convened by UNDP and the Ministry of National Policies and Economic Affairs. Held in Colombo from 24-25 May 2016, the summit brought together more than 300 people from government, private sector, and civil society from all over the country. Developing foresight and fostering innovation is a priority for the government and underscored by the Prime Minster’s attendance at the event. I spoke on the first day after the opening. My talk was on the leveraging both new and traditional data if the goal is to get towards real-time responsiveness and enhanced resilience.
That’s the reaction I get when I speak of LIRNEasia’s big data research agenda – the part that focuses on communicable diseases, dengue in particular, and the use of mobile phones to reduce spread. By identifying areas of reported cases, “risk maps” can be developed for the implementation of preventive measures. The challenge is convincing health practitioners of the value of using mobile phone data and digitised data, among many others. A similar model was used with success in Pakistan in 2012. The World Bank reports; As usual dengue season came back in 2012.
“The Think Tanks and Civil Societies Program (TTCSP) at the University of Pennsylvania conducts research on the role policy institutes play in governments and civil societies around the world.” In its latest report LIRNEasia was listed under the category “Top Think Tanks in Southeast Asia and the Pacific” along with IPS, RCSS and CEPA from Sri Lanka and was only South Asian think tank to be listed under “Best Policy Study-Report Produced by a Think Tank ” which was focused on our work in Big Data for Development. We were the only Sri Lankan entity to be listed “Best Independent Think Tanks” in an unranked list of 144 global think tanks. The TTCSP works with leading scholars and practitioners from think tanks and universities in a variety of collaborative efforts and programs, and produces the annual Global Go To Think Tank Index that ranks the world’s leading think tanks in a variety of categories. This is achieved with the help of a panel of over 1,900 peer institutions and experts from the print and electronic media, academia, public and private donor institutions, and governments around the world.

LIRNEasia partners with UNDP on SDGs

Posted on April 27, 2016  /  0 Comments

On 18th April 2016 LIRNEasia inked its Memorandum of Understanding with UNDP on areas of cooperation for the first national summit on foresight and innovation for Sustainable Human Development titled “Visioning Sri Lanka #2030NOW”. The summit will be held in Colombo from 24-25th May 2016. In addition to LIRNEasia and UNDP, other core partners for this two day conference include The Ministry of National Policies and Economic Affairs, Secretariat for Science, Technology and Innovation (COSTI) of the Ministry of Science, Technology and Research, the United Nations Global Compact Network of Sri Lanka, Sarvodaya, and the Ceylon Chamber of Commerce. Collectively the partners will work towards mainstreaming the use of foresight and facilitating innovation in Sri Lanka so as to successfully implement the Sustainable Development Goals (SDGs). LIRNEasia will help to develop the direction and outcomes of the conference and facilitate the discussion on improving the use of data and particularly big data in both monitoring as well as achieving the sustainable development goals.
Yesterday Sriganesh and I had the pleasure of presenting LIRNEasia’s big data work at the 3rd session of the Colombo Big Data Meetup, a prominent local meetup group focusing on big data and data science, domains still very much in their infancy in Sri Lanka. We spoke to a diverse audience of nearly 150 IT professionals, academics, statisticians and enthusiasts. The presentation was followed by a panel discussion which included Sriganesh, Dr. Shehan Perera of the Computer Science Department of University of Moratuwa, and myself. The discussion touched on a range of topics including practical aspects of running a successful big data operation,  learning data science, democratization of data and collective privacy.
For many, daily travel is a product of routines that have been established over time. From commuting, getting the kids to school and back home to the occasional shopping trip much of our movements follow a predictable pattern. Attempts to map human movement in different regions across the world using emerging sources of big data such as mobile network call detail records (CDR) show that in general aggregate human movements change very little from one week day to another or from one weekend to another. Our work on human mobility using a large CDR dataset have shown that Sri Lanka is no different. However during some days of the year such as during festivals, holidays and natural disasters routine travel behavior gives way to unique travel behavior.
The Economist carries an account of a new way of measuring inflation based on big data. Not applicable to our countries yet. But a watching brief is justified. The new index completely misses changes in offline prices and spending on things like petrol and rent. It will not replace the CPI any time soon.
We are aware that the UN has identified tourism data as priority area in terms of exploring the potential of big data to contribute to the work of national statistical organizations (NSOs). However, this was not something we took on, given our programmatic priorities which are urban development, improved socio-economic monitoring and epidemiology. When we were asked to share ideas on tourism data and a few other areas by a major business group, we did apply our minds to the problem. Here is the slideset. What are the key ideas?
Over the last few days I had the opportunity to present our thoughts on leveraging big data for development at two different venues in Ottawa, Canada. The first was at the headquarters of Global Affairs Canada on 11th March 2016, where I along with the head of UN Global Pulse spoke to an audience of about 100 people that included staff from Global Affairs and IDRC, as well as Canadian academics and researchers. The slides I used are available HERE. The second opportunity was today (14th March 2016) at the headquarters of IDRC, where I had the opportunity to share some of work with IDRC staff from different developmental domains. The slides that I used are available HERE.
The NYT Sunday Review carries a fascinating piece on how US and European wildlife officials are using the full panoply of ICTs and big data analytics to manage eco-systems and human-animal conflict. I’ve always felt that Beniger’s discussion of control was central to any realistic understanding of what is happening with big data and ICTs. What happens with animals today may happen with humans tomorrow. Starting in the early 2000s, the recovery program employed ancient and contemporary technology: Net-guns, fired from helicopters, were used to capture bighorn outfitted with collars that carried both GPS and VHF radio transmitters; professional hunters, meanwhile, tracked and darted every mountain lion in the area to outfit them with collars that carried VHF radio transmitters. Biologists at computer monitors began to watch bighorn movements.
That’s title of a report Sriganesh Lokanathan and I completed for the New Venture Fund. Here is an extract from the executive summary. Much of the discussion of the socio-economic implications of behavioral data has focused on the inclusion of more citizens and more aspects of their lives within the sphere of control enabled by pervasive data collection. Effective public policy rests on good information about problems and the efficacy of the deployed solutions. Governments obtained such information through National Statistical Organizations (NSOs) in the 19th and 20th Centuries.
We have always said that big data is about control, in the soft form first described by James Beniger. Information and control are closely connected. Beniger (1986, pp. 7-8) states that the twin activities of information processing and reciprocal communication (or feedback) are inseparable from the concept of control. Control is defined in the broadest sense as “purposive influence toward a predetermined goal.
It’s always a pleasure to hear LIRNEasia research cited by others.  Its even more pleasing when the person mentioning it is a senior government official (in this case the Chairman of Mongolia’s National Statistics Office) and that too at a briefing for senior government officials at Mongolia’s Parliament. Without knowing that LIRNEasia too was in the room, Chairman Mendsaikhan showcased some of LIRNEasia’s ongoing big data research as examples that were relevant for Mongolia and which should be ideally replicated. The briefing was part of a series of events on Data for Development held in Ulaanbaatar on 24th and 25th Feb 2016. The events were jointly organized by the World Bank and the Cabinet Secretariat of Mongolia, who had invited me to share our experience in leveraging big data for development in Sri Lanka.
Daniel Solove’s work forms the basis of our recent analyses of big data privacy. It is impressive that he pulls together a comprehensive analysis of the implications of the passing of Justice Scalia for the third-party doctrine within a day. Justice Scalia’s opinion in Jones actually provides very little protection against government location tracking. Only the physical affixing of a GPS device to a car violates the 4th Amendment according to his view. But under the third party doctrine, the government can readily obtain GPS data from third parties that provide GPS services without a physical trespass to the car.
As befitting an article on BIG data, the writer of this piece, done for Center for Internet and Society, is liberal with superlatives. A colossal increase in the rate of digitization has resulted in an unprecedented increment in the amount of Big Data available, especially through the rapid diffusion cellular technology. The importance of mobile phones as a significant source of data, especially in low income demographics cannot be overstated. This can be used to understand the needs and behaviors of large populations, providing an in depth insight into the relevant context within which valuable assessments as to the competencies, suitability and feasibilities of various policy mechanisms and legal instruments can be made. However, this explosion of data does have a lasting impact on how individuals and organizations interact with each other, which might not always be reflected in the interpretation of raw data without a contextual understanding of the demographic.
I first talked about the competitive issues of big data at the 2013 IGF in Bali. In actual fact the competitive implications of a subset, utility customer information, were discussed back in 1992. But it was rare to think that there was anything to talk about other than privacy. Finally, the message seems to be getting through. The concern is that while data can give a business competitive advantage, unique treasure troves of data can provide one player with unique insight and, potentially that can be translated into market power.