Centre for Internet and Society

Brindaalakshmi.K - Gendering of Development Data in India - Beyond the Binary #3

sumandro — 2020-06-30T09:48:48Z

For more details visit https://cis-india.org/raw/brindaalakshmi-k-gendering-of-development-data-in-india-beyond-the-binary-3

Bridging the Divide: Opportunities and Challenges

admin — 2008-10-11T10:27:58Z

This paper by Nirmita Narasimhan approaches the digital divide from multiple perspectives, looking at what "access" means and the factors responsible for the digital divide (income, gender, ethnicity, literacy and education, disability, law, etc.), surveys some digital divide initiatives in India, and presents some suggestions to tackle the divide.

For more details visit https://cis-india.org/publications-automated/cis/nirmita/Nirmita%20Narasimhan%20-%20Bridging%20the%20Divide

Breach Notifications

Admin — 2017-11-14T15:31:38Z

For more details visit https://cis-india.org/internet-governance/files/breach-notifications.pdf

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kaeru — 2026-03-14T04:30:47Z

For more details visit https://cis-india.org/internet-governance/blog/

Books and More are Relicensed to Creative Commons

subha — 2014-05-28T06:29:57Z

This blog post is cross-posted from Opensource.com. It was published on May 2, 2014.

Image by opensource.com

I began working with the Wikimedia Foundation in January 2012 for program and community support in India. With the Centre for Internet and Society's Access To Knowledge program, we focus on open access for scholarly publications to help communities enrich Wikipedia entries for Indic languages.

While I was negotiating with a few authors to relicense their copyrighted books to a Creative Commons license (a license that allows anyone to reuse, modify and use content), I began identifying certain areas of motivation for an author to donate their work as free content.

We worked closely with Goa University, Manik-Biswanath Smrutinyasa Trust, and the Institute of Odia Studies and Research.

Increasing open access for publications gained a lot when the government of India launched the National Repository of Open Educational Resources in August 2013 by the request of Wikimedia India. It generally takes a long time and much effort to negotiate with copyright holders for relicensing material as Creative Commons. But, when we do negotiate it, and win, the content is a permanent and valuable addition to open knowledge and the movement.

So far, authors might be avoiding open licensing because:

They think it might put them out of business because others could plagiarize and republish their work without attribution.
They think if they will lose ownership of the content due to the nature of open licenses, which allow reuse.

Open licensing should be important to authors because as more readers and reviewers get access to their books and other online content, the visibility of their work increases, allowing them to gain more respect and popularity. This can, in turn, help authors sell more of the reprints.

The "one book in every child's hand" campaign by Pratham Books was an initiative by a large publisher to license Indian langage books with a CC BY-SA license. The campaign's mission was to provide access to knowledge and good quality education of native Indian languages to students whose families cannot bear educational costs. Pratham Books gained a lot of attention globally and the campaign proved to be a sustainable model for publishers and free licenses.

Scholarly research publications are less prone to plagiarism because of their low retail value compared to mainstream fiction, self-help books, or travel and lifestyle books. Encyclopedic books have even less retail value. Thus, releasing content online under free licenses would not affect such scholarly works or encyclopedic print publications to a large extent.

Photo by Veethika Mishra, CC-BY-SA 4.0

Relicensing projects

Last year, Goa University applied a CC BY-SA 3.0 license to their four-volume encyclopedia, Konkani Vishwakosh. It is the largest encyclopedia compiled in the language. The book is being digitized on Konkani WikiSource, attracting new volunteers.
Manik-Biswanath Smrutinyasa relicensed eleven of the noted author Dr. Jagannath Mohanty's Odia books under a CC BY-SA 3.0 license.
Classical Odia is a 600+ page book of historical documents and manuscripts on Odia language and literary heritage of more than 2,500 years. The researchers Dr. Debiprasanna Pattanayak and Subrat Prusty moved from copyright to a CC BY-SA 3.0 license.
Two Odia language books by linguist Subrat Prusty have been relicensed to CC BY-SA 3.0. They are Jati, Jagruti O Pragati, and Bhasa O Jatiyata and have been digitized as well using ISCII standard fonts (not Unicode). ISCII standard fonts have glyphs with Indic characters that are actually replacements of the Latin characters by Indic characters.
A recent addition is the relicensing of the Kannada language encyclopedia published and copyrighted by Mysore University to a Creative Commons license.

The community and the publishers of books gain mutual benefits when more Indic language books are digitized, put online, and made freely available. By expanding online content and readership, a new life is given to many South Asian and non-Latin works, creating a revival for these languages and cultures.

Read the original post here.

For more details visit https://cis-india.org/openness/blog-old/opensource-education-may-2-2014-subhashish-panigrahi-books-and-more-are-relicensed-to-creative-commons

Book 4: To Connect : Digital AlterNatives with a Cause?

nishant — 2011-09-15T14:47:04Z

In Book 4, To Connect of the Digital (Alter)Natives with a Cause? series, we try to understand digital natives through their environment. Digital natives do not operate in a vacuum, their actions are shaped by the fast changing geo-political landscape, interaction with other actors and the global architecture of technology. In our Digital Natives with a Cause? research, it has become clear that at the heart of all digital natives discourse lies the question of power. Along with power, questions of race, class, gender and socio-economic situation cannot be ignored when talking about digital natives. We found that on one hand digital natives are destabilising existing power structures and challenging the status quo. On the other, the geo-political context in which digital natives live, affect their activities, beliefs and opinions. Then there are actors that can destroy, influence or support digital native activity which give rise to questions of control that resonate within this new generation

For more details visit https://cis-india.org/digital-natives/dnbook4

Book 3: To Act : Digital AlterNatives with a Cause?

nishant — 2011-09-15T14:40:51Z

In Book 3 of the Digital AlterNatives with a Cause? collective, we enter into dialogue with some of the severest and most heated debates around digital natives and their ability to effect change. To Act collides with the discourse on young people’s ability and role in technology mediated processes of change, heads-on. It deliberates on some very dense questions about how digital natives execute their visions of change using new forms of mobilisation of resources and sharing/production of information.

For more details visit https://cis-india.org/digital-natives/dnbook3

Book 2: To Think: Digital AlterNatives with a Cause?

nishant — 2011-09-15T14:35:43Z

We started the Digital Natives with a Cause? Knowledge programme, with a series of questions, which were drawn from popular discourse, research, practice, policy and experiences of people engaging with questions of youth, technology and change. Our ambition was to consolidate existing knowledge and to look at knowledge gaps which can be addressed in order to build new frameworks to understand the role that digital natives see themselves playing in their own understanding and vision of change. This Book 2 To Think, takes up the challenge of constructing new approaches and each essay in this book, through case-studies, analyses and divergent perspectives, offers a novel way of understanding processes of technology mediated citizen-driven change.

For more details visit https://cis-india.org/digital-natives/dnbook2

Bitcoin & Open Source with Aaron Koenig

praskrishna — 2014-02-06T01:40:24Z

Aaron Koenig, director of bitfilm.org and a global Bitcoin entrepreneur will give a talk at the Centre for Internet and Society, Bangalore on February 7 at 6.00 p.m.

Learn more about Bitcoin and its global path as we explore concepts and ideaologies behind the technology behemoth.


Above is an image of a Bitcoin Expert giving a presentation. Image source: http://bit.ly/1keLpwi

For more details visit https://cis-india.org/events/bitcoin-and-open-source-aaron-koenig

BIS on Smart Cities Indicators

praskrishna — 2016-11-30T15:56:58Z

For more details visit https://cis-india.org/internet-governance/files/bis-on-smart-cities-indicators.pdf

Bios and Photos of Speakers for Big Data in the Global South International Workshop

praskrishna — 2015-11-06T02:01:15Z

For more details visit https://cis-india.org/internet-governance/blog/big-data-global-south-international-workshop-bios-and-photos.pdf

Biometry Is Watching

praskrishna — 2011-04-02T12:08:26Z

In its first steps, the UID drive encounters practical problems, raises ethical questions, reports Sugata Srinivasaraju in Outlook.

Three women are fighting to take one chair in a classroom of a government school in Chelur village, in Gubbi taluka of Tumkur district. One sits on the lap of another and the third tries to push them both off the chair. What all three want is to be the first to be profiled under the Centre’s ambitious Aadhaar or unique identity number (UID) project. Their squabbling holds up the documentation by nearly 20 minutes, and the crowd outside, standing in line in the afternoon sun, grows restless. To calm them, the village revenue secretary orders the distribution of another round of buttermilk.

Chelur is one of four villages in the district picked for field trials before the 12-digit UIDs are assigned to people later in the year. Besides Tumkur, the pilot project is simultaneously running in seven villages of Mysore district. Each village has been given a target of 2,400-2,500 profiles to be completed in 20 days. This involves photographing the face, imaging the iris and scanning all ten digits of each person profiled and assigned a UID.

Villagers are enthusiastic about this rigorous profiling process even though there’s little awareness about the true purpose of the exercise. This is because of some falsehoods that have somehow spread in these areas. Nagamma, an elderly woman coming out after being profiled, thinks her eyes had been tested and found to be in perfect condition. Another middle-aged woman thought the exercise would bring her a new ration card—one that would entitle her family to an extra four kilos of rice. Some others were in a tizzy that if they didn’t undergo this “photography” their BPL cards would be taken away. Most, however, had queued up because they didn’t want to be left out of a sarkari exercise their neighbours were submitting to. Of the dozen people Outlook spoke to, only Muniswamy could tell us that this process would ensure that no one had more than one voter ID card or ration card—the way it should be, unlike some in his village who had illegally acquired two of each.

The village authorities have been doing little to counter the misinformation because their attention is focused on other compelling matters, like meeting the assigned target. This is an important issue because gram panchayat elections have been declared in Karnataka and lots of youngsters set off for campaigning early in the morning and would be difficult to locate for profiling.

According to official figures, Chelur has a population of 5,000, with 3,640 people above the age of 18. A random selection of 2,400 has been made from this to meet the UID target. The number seems small, but handling it at the village level can be demanding for the local authorities—there’s no police for crowd control, refreshments have to be distributed and the computerised work has to be done despite the power outages. Using generators has become inevitable, for the villages get hardly four or five hours’ power supply.

Another problem lies in obtaining the fingerprints of rural folk: most of them are engaged in manual labour or farm work and arrive with dirty palms that defeat the biometric reading machines. Pails of water, detergent and towels are provided for cleaning up. Much time is lost in such rescanning and it goes against the official estimate of five minutes for the young, nine for the elderly.

Prasanna Kumar, the village secretary, admits to the problems. “We did not make an open announcement for the UID pilot because we didn’t want to attract large crowds. We quietly prepared a random list of 2,400 people from the ration card database and went door-to-door to invite them,” he says. “We have left out people above the age of 80 and under 18. We told people this identity number will help them access various government schemes. Fingerprinting is the toughest problem. Initially people were reluctant, but suddenly they have become curious.”

H. Gnanesh, the tehsildar, says the ongoing step is only “concept testing”; the next will be rechecking, in which those already profiled will verify their identity details against what has been stored. Only after that will the UID be issued. In Chelur village, the concept testing ended on May 4; rechecking began the very next day.

Some NGOs observing the process have noted the lack of awareness in villagers. “They are clueless about what they are taking part in,” say Mahadev Prasad and Murthy, of the Basava Seva Trust. Murthy says fingerprinting is a big problem. He speaks of Hommaragalli, in Mysore district, where some foreign experts had to be called in to take a look at the scanning machines.

Then there are larger issues. Away from the surging crowds in Chelur, civil society organisations like the Centre for Internet & Society, the Alternative Law Forum and PUCL have been demanding greater dialogue. In fact, they have even suggested a review of the scheme. They argue there is no clarity on how the government proposes to store and secure personal and biometric data, given the fact that various agencies such as banks, telecom companies and government departments would potentially access it. Security is a huge concern also because the software, hardware and expertise of foreign companies is being used. These NGOs say the UID data, the National Population Registry and the NATGRID, when connected, could prove a grave threat to civil liberties.

“First, a centralised database, like the UID will create, has never been safe,” says Sunil Abraham of CIS. “It needs to be decentralised like our various mail servers. Second, we feel the collection of biometric data is happening at the wrong end of the pyramid. Instead of putting the poor through the process first, why not start with those with financial dealings of Rs 1 crore and above. Third, one study says 48 per cent of our people cannot remember a 12-digit ID. Fourth, we need privacy laws in place before the UID regime sets in.”

Those problems apart, even raising the level of the current exercise—from small samples of a few thousand each to profiling the billion-plus population of India—could place severe demands on our shaky administration. There’s a mountain to be moved.

Read the original article in the Outlook

For more details visit https://cis-india.org/news/biometry-is-watching

BigDog is Watching You! The Sci-fi Future of Animal and Insect Drones

maria — 2013-07-12T15:38:33Z

Do you think robotic aeroplanes monitoring us are scary enough? Wait until you read about DARPA´s new innovative and subtle way to keep us all under the microscope! This blog post presents a new reality of drones which is depicted in none other than animal and insect-like robots, equipped with cameras and other surveillance technologies.

This research was undertaken as part of the 'SAFEGUARDS' project that CIS is undertaking with Privacy International and IDRC.

Just when we thought we had seen it all, the US Defence Advanced Research Projects Agency (DARPA) funded another controversial surveillance project which makes even the most bizarre sci-fi movie seem like a pleasant fairy-tale in comparison to what we are facing: animal and insect drones.

Up until recently, unmanned aerial vehicles (UAVs), otherwise called drones, depicted the scary reality of surveillance, as robotic pilot-less planes have been swarming the skies, while monitoring large amounts of data without people´s knowledge or consent. Today, DARPA has come up with more subtle forms of surveillance: animal and insect drones. Clearly animal and insect-like drones have a much better camouflage than aeroplanes, especially since they are able to go to places and obtain data that mainstream UAVs can not.

India´s ´DARPA´, the Defence Research and Development Organisation (DRDO), has been creating UAVs over the last ten years, while the Indian Army first acquired UAVs from Israel in the late 1990s. Yet the use of all UAVs in India is still poorly regulated! Drones in the U.S. are regulated by the Federal Aviation Administration (FAA), whilst the European Aviation Safety Agency (EASA) regulates drones in the European Union. In India, the Ministry of Civil Aviation regulates drones, whilst the government is moving ahead with plans to replace the Directorate General of Civil Aviation (DGCA) with a Civil Aviation Authority. However, current Indian aviation laws are vague in regards to data acquired, shared and retained, thus not only posing a threat to individual´s right to privacy and other human rights, but also enabling the creation of a secret surveillance state.

The DRDO appears to be following DARPA´s footsteps in terms of surveillance technologies and the questions which arise are: will animal and insect drones be employed in India in the future? If so, how will they be regulated?

BigDog/LS3

Apparently having UAVs flying above us and monitoring territories and populations without our knowledge or consent was not enough. DARPA is currently funding the BigDog project, which is none other than a drone dog, a four-legged robot equipped with a camera and capable of surveillance in disguise. DARPA and Boston Dynamics are working on the latest version of BigDog, called the Legged Squad Support System (LS3), which can carry 400 pounds of gear for more than 20 miles without refuelling. Not only can the LS3 walk and run on all types of surfaces, including ice and snow, but it also has ´vision sensors´ which enable it to autonomously maneuver around obstacles and follow soldiers in the battle field. The LS3 is expected to respond to soldiers' voice commands, such as 'come', 'stop' and 'sit', as well as serve as a battery charger for electronic devices.

BigDog/LS3 is undoubtedly an impressive technological advancement in terms of aiding squads with surveillance, strategic management and a mobile auxiliary power source, as well as by carrying gear. Over the last century most technological developments have manifested through the military and have later been integrated in societies. Many questions arise around the BigDog/LS3 and its potential future use by governments for non-military purposes. Although UAVs were initially used for strictly military purposes, they are currently also being used by governments on an international level for civil purposes, such as to monitor climate change and extinct animals, as well as to surveille populations. Is it a matter of time before BigDog is used by governments for ´civil purposes´ too? Will robotic dogs swarm cities in the future to provide ´security´?

Like any other surveillance technology, the LS3 should be legally regulated and current lack of regulation could create a potential for abuse. Is authorisation required to use a LS3? If so, who has the legal right to authorise its use? Under what conditions can authorisation be granted and for how long? What kind of data can legally be obtained and under what conditions? Who has the legal authority to access such data? Can data be retained and if so, for how long and under what conditions? Do individuals have the right to be informed about the data withheld about them? Just because it´s a ´dog´ should not imply its non-regulation. This four-legged robot has extremely intrusive surveillance capabilities which may breach the right to privacy and other human rights when left unregulated.

Humming Bird Drone


Source: HighTech Edge

TIME magazine recognised DARPA for its Hummingbird nano air vehicle (NAV) and named the drone bird one of the 50 best inventions of 2011. True, it is rather impressive to create a robot which looks like a bird, behaves like a bird, but serves as a secret spy.

During the presentation of the humming bird drone, Regina Dugan, former Director of DARPA, stated:

"Since we took to the sky, we have wanted to fly faster and farther. And to do so, we've had to believe in impossible things and we've had to refuse to fear failure."

Although believing in 'impossible things' is usually a prerequisite to innovation, the potential implications on human rights of every innovation and their probability of occurring should be examined. Given the fact that drones already exist and that they are used for both military and non-military purposes, the probability is that the hummingbird drone will be used for civil purposes in the future. The value of data in contemporary information societies, as well as government's obsession with surveillance for ´national security´ purposes back up the probability that drone birds will not be restricted to battlefields.

So should innovation be encouraged for innovation’s sake, regardless of potential infringement of human rights? This question could open up a never-ending debate with supporters arguing that it´s not technology itself which is harmful, but its use or misuse. However the current reality of drones is this: UAVs and NAVs are poorly regulated (if regulated at all in many countries) and their potential for abuse is enormous, given that ´what happens to our data happens to ourselves....who controls our data controls our lives.´ If UAVs are used to surveille populations, why would drone birds not be used for the same purpose? In fact, they have an awesome camouflage and are potentially capable of acquiring much more data than any UAV! Given the surveillance benefits, governments would appear irrational not to use them.

MeshWorms and Remote-Controlled Insects


Source: NY Daily News

Think insects are creepy? Now we can have a real reason to be afraid of them. Clearly robotic planes, dogs and birds are not enough.

DARPA´s MeshWorm project entails the creation of earthworm-like robots that crawl along surfaces by contracting segments of their bodies. The MeshWorm can squeeze through tight spaces and mold its shape to rough terrain, as well as absorb heavy blows. This robotic worm will be used for military purposes, while future use for ´civil purposes´ remains a probability.

Robots, however, are not only the case. Actual insects are being wirelessly controlled, such as beetles with implanted electrodes and a radio receiver on their back. The giant flower beetle´s size enables it to carry a small camera and a heat sensor, which constitutes it as a reliable mean for surveillance.

Other drone insects look and fly like ladybugs and dragonflies. Researchers at the Wright State University in Dayton, Ohio, have been working on a butterfly drone since 2008. Former software engineer Alan Lovejoy has argued that the US is developing mosquito drones. Such a device could potentially be equipped with a camera and a microphone, it could use its needle to abstract a DNA sample with the pain of a mosquito bite and it could also inject a micro RFID tracking device under peoples´ skin. All such micro-drones could potentially be used for both military and civil purposes and could violate individuals´ right to privacy and other civil liberties.

Security vs. Privacy: The wrong debate

09/11 was not only a pioneering date for the U.S., but also for India and most countries in the world. The War on Terror unleashed a global wave of surveillance to supposedly enable the detection and prevention of crime and terrorism. Governments on an international level have been arguing over the last decade that the use of surveillance technologies is a prerequisite to safety. However, security expert, Bruce Schneier, argues that the trade-off of privacy for security is a false dichotomy.

Everyone can potentially be a suspect within a surveillance state. Analyses of Big Data can not only profile individuals and populations, but also identify ‘branches of communication’ around every individual. In short, if you know someone who may be considered a suspect by intelligence agencies, you may also be a suspect. The mainstream argument “I have nothing to hide, I am not a terrorist’ is none other than a psychological coping mechanism when dealing with surveillance. The reality of security indicates that when an individual’s data is being intercepted, the probability is that those who control that data can also control that individual’s life. Schneier has argued that privacy and security are not on the opposite side of a seesaw, but on the contrary, the one is a prerequisite of the other. Governments should not expect us to give up our privacy in exchange for security, as loss of privacy indicates loss of individuality and essentially, loss of freedom. We can not be safe when we trade-off our personal data, because privacy is what protects us from abuse from those in power. Thus the entire War on Terror appears to waged through a type of phishing, as the promise of ´security´ may be bait to acquire our personal data.

Since the 2008 Mumbai terrorist attacks, India has had more reasons to produce, buy and use surveillance technologies, including drones. Last New Year´s Eve, the Mumbai police used UAVs to monitor hotspots, supposedly to help track down revellers who sexually harass women. The Chennai police recently procured three UAVs from Anna University to assist them in keeping an eye on the city´s vehicle flow. Raj Thackeray´s rally marked the biggest surveillance exercise ever launched for a single event, which included UAVs. The Chandigarh police are the first Indian police force to use the ´Golden Hawk´ - a UAV which will keep a ´bird´s eye on criminal activities´. This new type of drone was manufactured by the Aeronautical Development Establishment (one of DRDO's premier laboratories based in Bangalore) and as of 2011 is being used by Indian law enforcement agencies.

Although there is no evidence that India currently has any animal or insect drones, it could be a probability in the forthcoming years. Since India is currently using many UAVs either way, why would animal and/or insect drones be excluded? What would prevent India from potentially using such drones in the future for ´civil purposes´? More importantly, how are ´civil purposes´ defined? Who defines ´civil purposes´and under what criteria? Would the term change and if so, under what circumstances? The term ´civil purposes´ varies from country to country and is defined by many political, social, economic and cultural factors, thus potentially enabling extensive surveillance and abuse of human rights.

Drones can potentially be as intrusive as other communications surveillance technologies, depending on the type of technology they´re equipped with, their location and the purpose of their use. As they can potentially violate individuals´ right to privacy, freedom of expression, freedom of movement and many other human rights, they should be strictly regulated. In Europe UAVs are regulated based upon their weight, as unmanned aircraft with an operating mass of less than 150kg are exempt by the EASA Regulation and its Implementation Rules. This should not be the case in India, as drones lighter than 150kg can potentially be more intrusive than other heavier drones, especially in the case of bird and insect drones.

Laws which explicitly regulate the use of all types of drones (UAVs, NAVs and micro-drones) and which legally define the term ´civil purposes´ in regards to human rights should be enacted in India. Some thoughts on the authorisation of drones include the following: A Special Committee on the Use of All Drones (SCUAD) could be established, which would be comprised of members of the jury, as well as by other legal and security experts of India. Such a committee would be the sole legal entity responsible for issuing authorisation for the use of drones, and every authorisation would have to comply with the constitutional and statutory provisions of human rights. Another committee, the Supervisory Committee on the Authorisation of the Use of Drones (lets call this ´SCAUD´), could also be established, which would also be comprised by (other) members of the jury, as well as by (other) legal and security experts of India. This second committee would supervise the first and it would ensure that SCUAD provides authorisations in compliance with the laws, once the necessity and utility of the use of drones has been adequately proven.

It´s not about ´privacy vs. security´. Nor is it about ´privacy or security´. In every democratic state, it should be about ´privacy and security´, since the one cannot exist without the other. Although the creation of animal and insect drones is undoubtedly technologically impressive, do we really want to live in a world where even animal-like robots can be used to spy on us? Should we be spied on at all? How much privacy do we give up and how much security do we gain in return through drones? If drones provided the ´promised security´, then India and all other countries equipped with these technologies should be extremely safe and crime-free; however, that is not the case.

In order to ensure that the use of drones does not infringe upon the right to privacy and other human rights, strict regulations are a minimal prerequisite. As long as people do not require that the use of these spying technologies are strictly regulated, very little can be done to prevent a scary sci-fi future. That´s why this blog has been written.

For more details visit https://cis-india.org/internet-governance/blog/big-dog-is-watching-you

Big Data, People's Lives, and the Importance of Openness

nishant — 2013-07-03T04:23:11Z

Openness has become the buzzword for everything in India right now. From the new kids on the block riding the wave of Digital Humanities investing in infrastructure of open knowledge initiatives to the rhetoric of people-centered open government data projects that are architected to create 'empowered citizens', there is an inherent belief that Opening up things will make everything good.

This blog post was published in DML Central on June 24, 2013.

I am not an Open-data party pooper. In fact, I firmly believe that opening up data – through hardware, through software, through intellectual property regimes on content – and enabling access to information and data is one of the most basic needs of the information age. I also advocate for strong policies that curb corporate and government control and monopolies over data and information. Along with my colleagues at the Centre for Internet and Society, and the many networks we work with, I have thought of myself as an open data advocate and have worked towards examining openness not only at the level of content, but also openness in infrastructure and conditions of access, distribution and storage. More than ever, it is necessary to build systems of Open Data that not only have distributed, collective and ethical ownership but also ensure the fair use and integration of information in our everyday life – especially given the sinister age of relentless remembering, as lives get incessantly archived through ubiquitous and pervasive technologies of portable computing.

Having said that, there is a strange thing happening around Openness right now. Openness seems to have been separated from the fact that it is a response to things being gated and closed. Openness, as it is being deployed right now, in e-government initiatives or rapid digitization processes in university libraries, seems to suggest that Openness is merely about making things in the physical format available in the digital medium. Hence, for example, the National Mission for Education through Information and Communication Technologies, India’s largest flagship government initiative to build learning conditions of the future, is investing almost all of its budget on digitizing historical and local language material in digitally intelligible and legible records that can be easily distributed. While the effort at building the infrastructure and preserving this material is absolutely worth supporting, making it the be-all and end-all of Open data initiatives is symptomatic of what I call the ‘politics of the benign’. We need to realize that Openness is not merely about making already available content in physical formats in the digital domain. Openness is about battles with Intellectual Property Regimes, which charge an extraordinary amount of money for high-value knowledge to anybody who wants to access it. In other words, openness is not about digitizing our grandparents’ pictures; it is about claiming access to knowledge and information hidden behind paywalls and gateways that is often produced using public resources.

As you can imagine, the perpetuation of this politics of benign fits many agendas; there are numerous stakeholders and actors who seek to neuter the radical nature of demands made by the Openness movements while retaining the vocabulary of political change. And that is why, if you look at the ways in which openness debates have changed, they get immediately deflected to questions around infrastructure, access, last-mile, etc. – which are all presented to us as the infrastructure of being political and being open. In the last few years, especially with Digital Humanities emerging as the playground where politics is not allowed, I find too many instances where the Humanities and Social Sciences questions get morphed into similar sounding questions that pretend to be the same but dislocate the political content and intention from the engagement.

One of the ways this works really well is by a separation of data from the lived reality of people. Data is seen as something that is out there – something that is about the real rather than the real. It is seen as an abstraction, which, when it further enters the circuits of pretty visualizations and graphic representations, becomes so entrenched in questions of reading and coding that it often becomes a surrogate for the larger realities that it is supposed to intervene in. So, for example, in India, the concerns around agriculture infrastructure and conditions of the farmers have easily been replaced by agriculture informatics – leading to a strange paradox where the states with the highest community informatics infrastructure also have the highest incidences of farmer suicides. I am not suggesting there is a cause-and-effect relationship here. However, it is a telling story that the community informatics infrastructure which was supposed to change the bleak realities of agriculture and farming in India has definitely not changed the nature of the reality it set out to solve.

Or in a similar vein, the ways in which the landscape of education is changing in the country, because of the emergence of the digital as the new organizing principle and in some instances, the raison de etre for building education infrastructure also needs to be examined. So, for instance, India has seen a rapid improvement of the Gross Enrollment Ratio in education that measures the annual intake and successful completion of education programs by students in the country. The GER shows that with remote education processes, the attempts at building distributed learning environments and the building of digital infrastructure has led to more students in different parts of the country getting enrolled in formal education systems. There is a celebration that more children are entering schools and colleges and are also in a state of socio-economic mobility. There is a clear causal relationship established in producing digital infrastructure and greater access to education and learning resources for an emerging information society like India.

However, this particular mode of looking at education, through the lens of access and inclusion, is no longer able to reflect on the core concerns that education institutions in the country were historically supposed to address. If the primary function of education was to address the questions of inequity, uneven modernity, disparate wealth distribution, and widespread socio-cultural conservatism, these are no longer questions that are featured in the Data-Technology driven education programs. These problems, which have been at the center of education debates in the country – leading to widespread affirmative action and violent resistance to it – have now been reformulated around quantifiable parameters of intake, credits, employability, affordability, accessibility, merit, etc. So there is silence about the nature of the students who enter education. There is an implicit push for the disinvestment of the state from education resources in favor of privatization. We remain enamored by the numbers joining the system, without worrying about the categories of discrimination – caste, gender, sexuality, language, location – that have affected the quality, intention and function of education. These issues have become moot points, to be replaced by visualizations and data sets that remain opaque in looking at the negotiations of identity politics and the need to embed education processes in lived realities of the students who enter formal education.

These problems are not new. And the intention of this articulation is not to deny the power of digital technologies or the opportunities they produce. Instead, it is a call to say that we need to stop thinking of data – an abstraction, an artifact, a manual product – as a natural state of being. We need to remind ourselves that engagement with data is not a sterile engagement, rendered beautiful through visualizations and infographics that can make reality intelligible. It is perhaps time to realize that Data has replaced People as the central concern of being human, social and political. Time to start re-introducing People back into debates around Data, and acknowledging that Data Informatics is People Informatics and data wars have a direct effect on the ways in which people live. And Die.

Banner image credit: sugree http://www.flickr.com/photos/73462957

For more details visit https://cis-india.org/openness/blog-old/dml-central-june-24-2013-nishant-shah-big-data-peoples-lives-and-importance-of-openness

Big Data in the Global South - An Analysis

tanvi — 2016-01-24T02:54:45Z

I. Introduction

"The period that we have embarked upon is unprecedented in history in terms of our ability to learn about human behavior." [1]

The world we live in today is facing a slow but deliberate metamorphosis of decisive information; from the erstwhile monopoly of world leaders and the captains of industry obtained through regulated means, it has transformed into a relatively undervalued currency of knowledge collected from individual digital expressions over a vast network of interconnected electrical impulses.[2] This seemingly random deluge of binary numbers, when interpreted represents an intricately woven tapestry of the choices that define everyday life, made over virtual platforms. The machines we once employed for menial tasks have become sensorial observers of our desires, wants and needs, so much so that they might now predict the course of our future choices and decisions.[3] The patterns of human behaviour that are reflected within this data inform policy makers, in both a public and private context. The collective data obtained from our digital shadows thus forms a rapidly expanding storehouse of memory, from which interested parties can draw upon to resolve problems and enable a more efficient functioning of foundational institutions, such as the markets, the regulators and the government.[4]

The term used to describe a large volume of collected data, in a structured as well as unstructured form is called Big Data. This data requires niche technology, outside of traditional software databases, to process; simply because of its exponential increment in a relatively short period of time. Big Data is usually identified using a "three V" characterization - larger volume, greater variety and distinguishably high rates of velocity. [5] This is exemplified in the diverse sources from which this data is obtained; mobile phone records, climate sensors, social media content, GPS satellite identifications and patterns of employment, to name a few. Big data analytics refers to the tools and methodologies that aim to transform large quantities of raw data into "interpretable data", in order to study and discern the same so that causal relationships between events can be conclusively established.[6] Such analysis could allow for the encouragement of the positive effects of such data and a concentrated mitigation of negative outcomes.

This paper seeks to map out the practices of different governments, civil society, and the private sector with respect to the collection, interpretation and analysis of big data in the global south, illustrated across a background of significant events surrounding the use of big data in relevant contexts. This will be combined with an articulation of potential opportunities to use big data analytics within both the public and private spheres and an identification of the contextual challenges that may obstruct the efficient use of this data. The objective of this study is to deliberate upon how significant obstructions to the achievement of developmental goals within the global south can be overcome through an accurate recognition, interpretation and analysis of big data collected from diverse sources.

II. Uses of Big Data in the Global Development

Big Data for development is the process though which raw, unstructured and imperfect data is analyzed, interpreted and transformed into information that can be acted upon by governments and policy makers in various capacities. The amount of digital data available in the world today has grown from 150 exabytes in 2005 to 1200 exabytes in 2010.[7] It is predicted that this figure would increase by 40% annually in the next few years[8], which is close to 40 times growth of the world's population. [9] The implication of this is essentially that the share of available data in the world today that is less than a minute old is increasing at an exponential rate. Moreover, an increasing percentage of this data is produced and created real-time.

The data revolution that is incumbent upon us is characterized by a rapidly accumulating and continuously evolving stock of data prevalent` in both industrialized as well as developing countries. This data is extracted from technological services that act as sensors and reflect the behaviour of individuals in relation to their socio-economic circumstances.

For many global south countries, this data is generated through mobile phone technology. This trend is evident in Sub Saharan Africa, where mobile phone technology has been used as an effective substitute for often weak and unstructured State mechanisms such as faulty infrastructure, underdeveloped systems of banking and inferior telecommunication networks.[10]

For example, a recent study presented at the Data for Development session at the NetMob Conference at MIT used mobile phone data to analyze the impact of opening a new toll highway in Dakar, Senegal on human mobility, particularly how people commute to work in the metropolitan area. ^{^[11]} A huge investment, the improved infrastructure is expected to result in a significant increase of people in and out of Dakar, along with the transport of essential goods. This would initiate rural development in the areas outside of Dakar and boost the value of land within the region.^{^[12]} The impact of the newly constructed highway can however only be analyzed effectively and accurately through the collection of this mobile phone data from actual commuters, on a real time basis.

Mobile phones technology is no longer used just for personal communication but has been transformed into an effective tool to secure employment opportunities, transfer money, determine stock options and assess the prices of various commodities.[13] This generates vast amounts of data about individuals and their interactions with the government and private sector companies. Internet Traffic is predicted to grow between 25 to 30 % in the next few years in North America, Western Europe and Japan but in Latin America, The Middle East and Africa this figure has been expected to touch close to 50%.[14] The bulk of this internet traffic can be traced back to mobile devices.

The potential applicability of Big Data for development at the most general level is the ability to provide an overview of the well being of a given population at a particular period of time.[15] This overcomes the relatively longer time lag that is prevalent with most other traditional forms of data collection. The analysis of this data has helped, to a large extent, uncover "digital smoke signals" - or inherent changes in the usage patterns of technological services, by individuals within communities.[16] This may act as an indicator of the changes in the underlying well-being of the community as a whole. This information about the well-being of a community derived from their usage of technology provides significantly relevant feedback to policy makers on the success or failure of particular schemes and can pin point changes that need to be made to status quo. [17]The hope is that this feedback delivered in real-time, would in turn lead to a more flexible and accessible system of international development, thus securing more measurable and sustained outcomes. [18]

The analysis of big data involves the use of advanced computational technology that can aid in the determination of trends, patterns and correlations within unstructured data so as to transform it into actionable information. It is hoped that this in addition to the human perspective and experience afforded to the process could enable decision makers to rely upon information that is both reliable and up to date to formulate durable and self-sustaining development policies.

The availability of raw data has to be adequately complemented with intent and a capacity to use it effectively. To this effect, there is an emerging volume of literature that seeks to characterize the primary sources of this Big Data as sharing certain easily distinguishable features. Firstly, it is digitally generated and can be stored in a binary format, thus making it susceptible to requisite manipulation by computers attempting to engage in its interpretation. It is passively produced as a by-product of digital interaction and can be automatically extracted for the purpose of continuous analysis. It is also geographically traceable within a predetermined time period. It is however important to note that "real time" does not necessarily refer to information occurring instantly but is reflective of the relatively short time in which the information is produced and made available thus making it relevant within the requisite timeframe. This allows efficient responsive action to be taken in a short span of time thus creating a feedback loop. [19]

In most cases the granularity of the data is preferably sought to be expanded over a larger spatial context such as a village or a community as opposed to an individual simply because this affords an adequate recognition of privacy concerns and the lack of definitive consent of the individuals in the extraction of this data. In order to ease the process of determination of this data, the UN Global Pulse has developed taxonomy of sorts to assess the types of data sources that are relevant to utilizing this information for development purposes.[20] These include the following sources;

Data Exhaust or the digital footprint left behind by individuals' use of technology for service oriented tasks such as web purchases, mobile phone transactions and real time information collected by UN agencies to monitor their projects such as levels of food grains in storage units, attendance in schools etc.

Online Information which includes user generated content on the internet such as news, blog entries and social media interactions which may be used to identify trends in human desires, perceptions and needs.

Physical sensors such as satellite or infrared imagery of infrastructural development, traffic patterns, light emissions and topographical changes, thus enabling the remote sensing of changes in human activity over a period of time.

Citizen reporting or crowd sourced data , which includes information produced on hotlines, mobile based surveys, customer generated maps etc. Although a passive source of data collection, this is a key instrument in assessing the efficacy of action oriented plans taken by decision makers.

The capacity to analyze this big data is hinged upon the reliance placed on technologically advanced processes such as powerful algorithms which can synthesize the abundance of raw data and break down the information enabling the identification of patterns and correlations. This process would rely on advanced visualization techniques such "sense-making tools"[21]

The identification of patterns within this data is carried out through a process of instituting a common framework for the analysis of this data. This requires the creation of a specific lexicon that would help tag and sort the collected data. This lexicon would specify what type of information is collected and who it is interpreted and collected by, the observer or the reporter. It would also aid in the determination of how the data is acquired and the qualitative and quantitative nature of the data. Finally, the spatial context of the data and the time frame within which it was collected constituting the aspects of where and when would be taken into consideration. The data would then be analyzed through a process of Filtering, Summarizing and Categorizing the data by transforming it into an appropriate collection of relevant indicators of a particular population demographic. [22]

The intensive mining of predominantly socioeconomic data is known as "reality mining" [23] and this can shed light on the processes and interactions that are reflected within the data. This is carried out via a tested three fold process. Firstly, the " Continuous Analysis over the streaming of the data", which involves the monitoring and analyzing high frequency data streams to extract often uncertain raw data. For example, the systematic gathering of the prices of products sold online over a period of time. Secondly, "The Online digestion of semi structured data and unstructured data", which includes news articles, reviews of services and products and opinion polls on social media that aid in the determination of public perception, trends and contemporary events that are generating interest across the globe. Thirdly, a 'Real-time Correlation of streaming data with slowly accessible historical data repositories,' which refers to the "mechanisms used for correlating and integrating data in real-time with historical records."[24] The purpose of this stage is to derive a contextualized perception of personalized information that seeks to add value to the data by providing a historical context to it. Big Data for development purposes would make use of a combination of these depending on the context and need.

(i) Policy Formulation

The world today has become increasingly volatile in terms of how the decisions of certain countries are beginning to have an impact on vulnerable communities within entirely different nations. Our global economy has become infinitely more susceptible to fluctuating conditions primarily because of its interconnectivity hinged upon transnational interdependence. The primordial instigators of most of these changes, including the nature of harvests, prices of essential commodities, employment structures and capital flows, have been financial and environmental disruptions. [25] According to the OECD, " Disruptive shocks to the global economy are likely to become more frequent and cause greater economic and social hardship. The economic spillover effects of events like the financial crisis or a potential pandemic will grow due to the increasing interconnectivity of the global economy and the speed with which people, goods and data travel."[26]

The local impacts of these fluctuations may not be easily visible or even traceable but could very well be severe and long lasting. A vibrant literature on the vulnerability of communities has highlighted the impacts of these shocks on communities often causing children to drop out of school, families to sell their productive assets, and communities to place a greater reliance on state rations.[27] These vulnerabilities cannot be definitively discerned through traditional systems of monitoring and information collection. The evidence of the effects of these shocks often take too long to reach decision makers; who are unable to formulate effective policies without ascertaining the nature and extent of the hardships suffered by these in a given context. The existing early warning systems in place do help raise flags and draw attention to the problem but their reach is limited and veracity compromised due to the time it takes to extract and collate this information through traditional means. These traditional systems of information collection are difficult to implement within rural impoverished areas and the data collected is not always reliable due to the significant time gap in its collection and subsequent interpretation. Data collected from surveys does provide an insight into the state of affairs of communities across demographics but this requires time to be collected, processed, verified and eventually published. Further, the expenses incurred in this process often prove to be difficult to offset.

The digital revolution therefore provides a significant opportunity to gain a richer and deeper insight into the very nature and evolution of the human experience itself thus affording a more legitimate platform upon which policy deliberations can be articulated. This data driven decision making, once the monopoly of private institutions such as The World Economic Forum and The McKinsey Institute [28] has now emerged at the forefront of the public policy discourse. Civil society has also expressed an eagerness to be more actively involved in the collection of real-time data after having perceived its benefits. This is evidenced by the emergence of 'crowd sourcing'[29] and other 'participatory sensing' [30] efforts that are founded upon the commonalities shared by like minded communities of individuals. This is being done on easily accessible platforms such as mobile phone interfaces, hand-held radio devices and geospatial technologies. [31]

The predictive nature of patterns identifiable from big data is extremely relevant for the purpose of developing socio-economic policies that seek to bridge problem-solution gaps and create a conducive environment for growth and development. Mobile phone technology has been able to quantify human behavior on an unprecedented scale.[32] This includes being able to detect changes in standard commuting patterns of individuals based on their employment status[33] and estimating a country's GDP in real-time by measuring the nature and extent of light emissions through remote sensing. [34]

A recent research study has concluded that "due to the relative frequency of certain queries being highly correlated with the percentage of physician visits in which individuals present influenza symptoms, it has been possible to accurately estimate the levels of influenza activity in each region of the United States, with a reporting lag of just a day." Online data has thus been used as a part of syndromic surveillance efforts also known as infodemiology. [35] The US Centre for Disease Control has concluded that mining vast quantities of data through online health related queries can help detect disease outbreaks " before they have been confirmed through a diagnosis or a laboratory confirmation." [36] Google trends works in a similar way.

Another public health monitoring system known as the Healthmap project compiles seemingly fragmented data from news articles, social media, eye-witness reports and expert discussions based on validated studies to "achieve a unified and comprehensive view of the current global state of infectious diseases" that may be visualized on a map. [37]

Big Data used for development purpose can reduce the reliance on human inputs thus narrowing the room for error and ensuring the accuracy of information collected upon which policy makers can base their decisions.

(ii) Advocacy and Social Change

Due to the ability of Big Data to provide an unprecedented depth of detail on particular issues, it has often been used as a vehicle of advocacy to highlight various issues in great detail. This makes it possible to ensure that citizens are provided with a far more participative experience, capturing their attention and hence better communicating these problems. Numerous websites have been able to use this method of crowd sourcing to broadcast socially relevant issues[38]. Moreover, the massive increase in access to the internet has dramatically improved the scope for activism through the use of volunteered data due to which advocates can now collect data from volunteers more effectively and present these issues in various forums. Websites like Ushahidi[39] and the Black Monday Movement [40] being prime examples of the same. These platforms have championed various causes, consistently exposing significant social crises' that would otherwise go unnoticed.

The Ushahidi application used crowd sourcing mechanisms in the aftermath of the Haiti earthquake to set up a centralized messaging system that allowed mobile phone users to provide information on injured and trapped people.[41] An analysis of the data showed that the concentration of text messages was correlated with the areas where there was an increased concentration of damaged buildings. [42] Patrick Meier of Ushahidi noted "These results were evidence of the system's ability to predict, with surprising accuracy and statistical significance, the location and extent of structural damage post the earthquake." [43]

Another problem that data advocacy hopes to tackle, however, is that of too much exposure, with advocates providing information to various parties to help ensure that there exists no unwarranted digital surveillance and that sensitive advocacy tools and information are not used inappropriately. An interesting illustration of the same is The Tactical Technology Collective[44] that hopes to improve the use of technology by activists and various other political actors. The organization, through various mediums such as films, events etc. hopes to train activists regarding data protection and privacy awareness and skills among human rights activists. Additionally, Tactical Technology also assists in ensuring that information is used in an appealing and relevant manner by human rights activists and in the field of capacity building for the purposes of data advocacy.

Observed data such as mobile phone records generated through network operators as well as through the use of social media are beginning to embody an omnipotent role in the development of academia through detailed research. This is due to the ability of this data to provide microcosms of information within both contexts of finer granularity and over larger public spaces. In the wake of natural disasters, this can be extremely useful, as reflected by the work of Flowminder after the 2010 Haiti earthquake.[45] A similar string of interpretive analysis can be carried out in instances of conflict and crises over varying spans of time. Flowminder used the geospatial locations of 1.9 million subscriber identity modules in Haiti, beginning 42 days before the earthquake and 158 days after it. This information allowed researches to empirically determine the migration patterns of population post the earthquake and enabled a subsequent UNFPA household survey.[46] In a similar capacity, the UN Global Pulse is seeking to assist in the process of consultation and deliberation on the specific targets of the millennium development goals through a framework of visual analytics that represent the big data procured on each of the topics proposed for the post- 2015 agenda online.[47]

A recent announcement of collaboration between RTI International, a non-profit research organization and IBM research lab looks promising in its initiative to utilize big data analytics in schools within Mombasa County, Kenya.[48] The partnership seeks to develop testing systems that would capture data that would assist governments, non-profit organizations and private enterprises in making more informed decisions regarding the development of education and human resources within the region. Äs observed by Dr. Kamal Bhattacharya, The Vice President of IBM Research, "A significant lack of data on Africa in the past has led to misunderstandings regarding the history, economic performance and potential of the government." The project seeks to improve transparency and accountability within the schooling system in more than 100 institutions across the county. The teachers would be equipped with tablet devices to collate the data about students, classrooms and resources. This would allow an analysis of the correlation between the three aspects thus enabling better policy formulation and a more focused approach to bettering the school system. [49] This is a part of the United States Agency for International Development's Education Data for Decision Making (EdData II) project. According to Dr Kommy Weldemariam, Research Scientist , IBM Research, "… there has been a significant struggle in making informed decisions as to how to invest in and improve the quality and content of education within Sub-Saharan Africa. The Project would create a school census hub which would enable the collection of accurate data regarding performance, attendance and resources at schools. This would provide valuable insight into the building of childhood development programs that would significantly impact the development of an efficient human capital pool in the near future."[50]

A similar initiative has been undertaken by Apple and IBM in the development of the "Student Achievement App" which seeks to use this data for "content analysis of student learning". The Application as a teaching tool that analyses the data provided to develop actionable intelligence on a per-student basis." [51] This would give educators a deeper understanding of the outcome of teaching methodologies and subsequently enable better leaning. The impact of this would be a significant restructuring of how education is delivered. At a recent IBM sponsored workshop on education held in India last year , Katharine Frase, IBM CTO of Public Sector predicted that "classrooms will look significantly different within a decade than they have looked over the last 200 years."[52]

(iii) Access and the exchange of information

Big data used for development serves as an important information intermediary that allows for the creation of a unified space within which unstructured heterogeneous data can be efficiently organized to create a collaborative system of information. New interactive platforms enable the process of information exchange though an internal vetting and curation that ensures accessibility to reliable and accurate information. This encourages active citizen participation in the articulation of demands from the government, thus enabling the actualization of the role of the electorate in determining specific policy decisions.

The Grameen Foundation's AppLab in Kampala aids in the development of tools that can use the information from micro financing transactions of clients to identify financial plans and instruments that would be be more suitable to their needs.[53] Thus, through working within a community, this technology connects its clients in a web of information sharing that they both contribute to and access after the source of the information has been made anonymous. This allows the individual members of the community to benefit from this common pool of knowledge. The AppLab was able to identify the emergence of a new crop pest from an increase in online searches for an unusual string of search terms within a particular region. Using this as an early warning signal, the Grameen bank sent extension officers to the location to check the crops and the pest contamination was dealt with effectively before it could spread any further.[54]

(iv) Accountability and Transparency

Big data enables participatory contributions from the electorate in existing functions such as budgeting and communication thus enabling connections between the citizens, the power brokers and elites. The extraction of information and increasing transparency around data networks is also integral to building a self-sustaining system of data collection and analysis. However it is important to note that this information collected must be duly analyzed in a responsible manner. Checking the veracity of the information collected and facilitating individual accountability would encourage more enthusiastic responses from the general populous thus creating a conducive environment to elicit the requisite information. The effectiveness of the policies formulated by relying on this information would rest on the accuracy of such information.

An example of this is Chequeado, a non-profit Argentinean media outlet that specializes in fact-checking. It works on a model of crowd sourcing information on the basis of which it has fact checked everything from the live presidential speech to congressional debates that have been made open to the public. [55] It established a user friendly public database, DatoCHQ, in 2014 which allowed its followers to participate in live fact-checks by sending in data, which included references, facts, articles and questions, through twitter. [56] This allowed citizens to corroborate the promises made by their leaders and instilled a sense of trust in the government.

III. Big Data and Smart Cities in the Global South

Smart cities have become a buzzword in South Asia, especially after the Indian government led by Prime Minister Narendra Modi made a commitment to build 100 smart cities in India[57]. A smart city is essentially designed as a hub where the information and communication technologies (ICT) are used to create feedback loops with an almost minimum time gap. In traditional contexts, surveys carried out through a state sponsored census were the only source of systematic data collection. However these surveys are long drawn out processes that often result in a drain on State resources. Additionally, the information obtained is not always accurate and policy makers are often hesitant to base their decisions on this information. The collection of data can however be extremely useful in improving the functionality of the city in terms of both the 'hard' or physical aspects of the infrastructural environment as well as the 'soft' services it provides to citizens. One model of enabling this data collection, to this effect, is a centrally structured framework of sensors that may be able to determine movements and behaviors in real-time, from which the data obtained can be subsequently analyzed. For example, sensors placed under parking spaces at intersections can relay such information in short spans of time. South Korea has managed to implement a similar structure within its smart city, Songdo.[58]

Another approach to this smart city model is using crowd sourced information through apps, either developed by volunteers or private conglomerates. These allow for the resolving of specific problems by organizing raw data into sets of information that are attuned to the needs of the public in a cohesive manner. However, this system would require a highly structured format of data sets, without which significantly transformational result would be difficult to achieve.[59]

There does however exist a middle ground, which allows the beneficiaries of this network, the citizens, to take on the role of primary sensors of information. This method is both cost effective and allows for an experimentation process within which an appropriate measure of the success or failure of the model would be discernible in a timely manner. It is especially relevant in fast growing cities that suffer congestion and breakdown of infrastructure due to the unprecedented population growth. This population is now afforded with the opportunity to become a part of the solution.

The principle challenge associated with extracting this Big Data is its restricted access. Most organizations that are able to collect this big data efficiently are private conglomerates and business enterprises, who use this data to give themselves a competitive edge in the market, by being able to efficiently identify the needs and wants of their clientele. These organizations are reluctant to release information and statistics because they fear it would result in them losing their competitive edge and they would consequently lose the opportunity to benefit monetarily from the data collected. Data leaks would also result in the company getting a bad name and its reputation could be significantly hampered. Despite the individual anonymity, the transaction costs incurred in ensuring the data of their individual customers is protected is often an expensive process. In addition to this there is a definite human capital gap resulting from the significant lack of scientists and analysts to interpret raw data transmitted across various channels.

(i) Big Data in Urban Planning

Urban planning would require data that is reflective of the land use patterns of communities, combined with their travel descriptions and housing preferences. The mobility of individuals is dependent on their economic conditions and can be determined through an analysis of their purchases, either via online transactions or from the data accumulated by prominent stores. The primary source of this data is however mobile phones, which seemed to have transcend economic barriers. Secondary sources include cards used on public transport such as the Oyster card in London and the similar Octopus card used in Hong Kong. However, in most developing countries these cards are not available for public transport systems and therefore mobile network data forms the backbone of data analytics. An excessive reliance on the data collected through Smart phones could however be detrimental, especially in developing countries, simply because the usage itself would most likely be concentrated amongst more economically stable demographics and the findings from this data could potentially marginalize the poor.[60]

Mobile network big data (MNBD) is generated by all phones and includes CDRs, which are obtained from calls or texts that are sent or received, internet usage, topping up a prepaid value and VLR or Visitor Location Registry data which is generated whenever the phone is question has power. It essentially communicates to the Base Transceiver Stations (BSTs) that the phone is in the coverage area. The CDR includes records of calls made, duration of the call and information about the device. It is therefore stored for a longer period of time. The VLR data is however larger in volume and can be written over. Both VLR and CDR data can provide invaluable information that can be used for urban planning strategies. [61] LIRNEasia, a regional policy and regulation think-tank has carried out an extensive study demonstrating the value of MNBD in SriLanka.[62] This has been used to understand and sometimes even monitor land use patterns, travel patterns during peak and off seasons and the congregation of communities across regions. This study was however only undertaken after the data had been suitably pseudonymised.[63] The study revealed that MNBD was incredibly valuable in generating important information that could be used by policy formulators and decision makers, because of two primary characteristics. Firstly, it comes close to a comprehensive coverage of the demographic within developing countries, thus using mobile phones as sensors to generate useful data. Secondly, people using mobile phones across vast geographic areas reflect important information regarding patterns of their travel and movement. [64]

MNBD allows for the tracking and mapping of changes in population densities on a daily basis, thus identifying 'home' and 'work' locations, informing policy makers of population congestion so that thy may be able to formulate policies with respect to easing this congestion. According to Rohan Samarajiva, founding chair of LIRNEasia, "This allows for real-time insights on the geo-spatial distribution of population, which may be used by urban planners to create more efficient traffic management systems."^{^[65]} This can also be used for the developmental economic policies. For example, the northern region of Colombo, a region inhabited by the low income families shows a lower population density on weekdays. This is reflective of the large numbers travelling to southern Colombo for employment. ^{^[66]}Similarly, patterns of land use can be ascertained by analyzing the various loading patterns of base stations. Building on the success of the Mobile Data analysis project in SriLanka LIRNEasia plans to collaborate with partners in India and Bangladesh to assimilate real time information about the behavioral tendencies of citizens, using which policy makers may be able to make informed decisions. When this data is combined with user friendly virtual platforms such as smartphone Apps or web portals, it can also help citizens make informed choices about their day to day activities and potentially beneficial long term decisions. ^{^[67]}

Challenges of using Mobile Network Data

Mobile networks invest significant sums of money in obtaining information regarding usage patterns of their services. Consequently, they may use this data to develop location based advertizing. In this context, there is a greater reluctance to share data for public purposes. Allowing access to one operator's big data by another could result in significant implications on the other with respect to the competitive advantage shared by the operator. A plausible solution to this conundrum is the accumulation of data from multiple sources without separating or organizing it according to the source it originates from. There is thus a lesser chance of sensitive information of one company being used by another. However, even operators do have concerns about how the data would be handled before this "mashing up" occurs and whether it might be leaked by the research organization itself. LIRNEasia used comprehensive non-disclosure agreements to ensure that the researchers who worked with the data were aware of the substantial financial penalties that may be imposed on them for data breaches. The access to the data was also restricted. [68]

Another line of argumentation advocates for the open sharing of data. A recent article in the Economist has articulated this in the context of the Ebola outbreak in West Africa. " Releasing the data, though, is not just a matter for firms since people's privacy is involved. It requires governmental action as well. Regulators in each affected country would have to order operators to make their records accessible to selected researchers, who through legal agreements would only be allowed to use the data in a specific manner. For example, Orange, a major mobile phone network operator has made millions of CDRs from Senegal and The Ivory Coast available for researchers for their use under its Data Development Initiative. However the Political will amongst regulators and Network operators to do this seems to be lacking."[69]

It would therefore be beneficial for companies to collaborate with the customers who create the data and the researchers who want to use it to extract important insights. This however would require the creation of and subsequent adherence to self regulatory codes of conduct. [70] In addition to this cooperation between network operators will assist in facilitating the transference of the data of their customers to research organizations. Sri Lanka is an outstanding example of this model of cooperation which has enabled various operators across spectrums to participate in the mobile-money enterprise.[71]

(ii) Big Data and Government Delivery of Services and Functions

The analysis of Data procured in real time has proven to be integral to the formulation of policies, plans and executive decisions. Especially in an Asian context, Big data can be instrumental in urban development, planning and the allocation of resources in a manner that allows the government to keep up with the rapidly growing demands of an empowered population whose numbers are on an exponential rise. Researchers have been able to use data from mobile networks to engage in effective planning and management of infrastructure, services and resources. If, for example, a particular road or highway has been blocked for a particular period of time an alternative route is established before traffic can begin to build up creating a congestion, simply through an analysis of information collected from traffic lights, mobile networks and GPS systems.[72]

There is also an emerging trend of using big data for state controlled services such as the military. The South Korean Defense Minister Han Min Koo, in his recent briefing to President Park Geun-hye reflected on the importance of innovative technologies such as Big Data solutions. [73]

The Chinese government has expressed concerns regarding data breaches and information leakages that would be extremely dangerous given the exceeding reliance of governments on big data. A security report undertaken by Qihoo 360, China's largest software security provider established that 2,424 of the 17,875 Web security loopholes were on government websites. Considering the blurring line between government websites and external networks, it has become all the more essential for authorities to boost their cyber security protections.[74]

The Japanese government has considered investing resources in training more data scientists who may be able to analyze the raw data obtained from various sources and utilize requisite techniques to develop an accurate analysis. The Internal Affairs and Communication Ministry planned to launch a free online course on big data, the target of which would be corporate workers as well as government officials.[75]

Data analytics is emerging as an efficient technique of monitoring the public transport management systems within Singapore. A recent collaboration between IBM, StarHub, The Land Transport Authority and SMRT initiated a research study to observe the movement of commuters across regions. ^{^[76]} This has been instrumental in revamping the data collection systems already in place and has allowed for the procurement of additional systems of monitoring.^{^[77]} The idea is essentially to institute a "black box" of information for every operational unit that allows for the relaying of real-time information from sources as varied as power switches, tunnel sensors and the wheels, through assessing patterns of noise and vibration. ^{^[78]}

In addition to this there are numerous projects in place that seek to utilize Big Data to improve city life. According to Carlo Ritti, Director of the MIT Senseable City Lab, "We are now able to analyze the pulse of a city from moment to moment. Over the past decade, digital technologies have begun to blanket our cities, forming the backbone of a large, intelligent infrastructure." ^{^[79]} The professor of Information Architecture and Founding Director of the Singapore ETH Centre, Gerhart Schmitt has observed that "the local weather has a major impact on the behavior of a population." In this respect the centre is engaged in developing a range of visual platforms to inform citizens on factors such as air quality which would enable individuals to make everyday choices such as what route to take when planning a walk or predict a traffic jam. ^{^[80]} Schmitt's team has also been able to arrive at a pattern that connects the demand for taxis with the city's climate. The amalgamation of taxi location with rainfall data has been able to help locals hail taxis during a storm. This form of data can be used in multiple ways allowing the visualization of temperature hotspots based on a "heat island" effect where buildings, cars and cooling units cause a rise in temperature. ^{^[81]}

Microsoft has recently entered into a partnership with the Federal University of Minas Gerais, one of the largest universities in Brazil to undertake a research project that could potentially predict traffic jams up to an hour in advance. ^{^[82]} The project attempts to analyze information from transport departments, road traffic cameras and drivers social network profiles to identify patterns that they could use to help predict traffic jams approximately 15 to 60 minutes before they actually happen.^{^[83]}

In anticipation of the increasing demand for professionals with requisite training in data sciences, the Malaysian Government has planned to increase the number of local data scientists from the present 80 to 1500 by 2020, through the support of the universities within the country.

IV. Big Data and the Private Sector in the Global South

Essential considerations in the operations of Big Data in the Private sector in the Asia Pacific region have been extracted by a comprehensive survey carried out by the Economist Intelligence Unit.[84] Over 500 executives across the Asia Pacific region were surveyed, from across industries representing a diverse range of functions. 69% of these companies had an annual turnover of over US $500m. The respondents were senior managers responsible for taking key decisions with regard to investment strategies and the utilization of big data for the same.

The results of the Survey conclusively determined that firms in the Asia Pacific region have had limited success with implementing Big Data Practices. A third of the respondents claimed to have an advanced knowledge of the utilization of big data while more than half claim to have made limited progress in this regard. Only 9% of the Firms surveyed cited internal barriers to implementing big data practices. This included a significant difficulty in enabling the sharing of information across boundaries. Approximately 40% of the respondents surveyed claimed they were unaware of big data strategies, even if they had in fact been in place simply because these had been poorly communicated to them. Almost half of the firms however believed that big data plays an important role in the success of the firm and that it can contribute to increasing revenue by 25% or more.

Numerous obstacles in the adoption of big data were cited by the respondents. These include the lack of suitable software to interpret the data and the lack of in-house skills to analyze the data appropriately. In addition to this, the lack of willingness on the part of various departments to share their data for the fear of a breach or leak was thought to be a major hindrance. This combined with a lack of communication between the various departments and exceedingly complicated reports that cannot be analyzed given the limited resources and lack of human capital qualified enough to carry out such an analysis, has resulted in an indefinite postponement of any policy propounding the adoption of big data practices.

Over 59% of the firms surveyed agreed that collaboration is integral to innovation and that information silos are a huge hindrance within a knowledge based economy. There is also a direct correlation between the size of the company and its progress in adopting big data, with larger firms adopting comprehensive strategies more frequently than smaller ones. A major reason for this is that large firms with substantially greater resources are able to actualize the benefits of big data analytics more efficiently than firms with smaller revenues. These businesses which have advanced policies in place outlining their strategies with respect to their reliance on big data are also more likely to communicate these strategies to their employees to ensure greater clarity in the process.

The use of big data was recently voted as the "best management practice" of the past year according to a cumulative ranking published by Chief Executive China Magazine, a Trade journal published by Global Sources on 13th January, 2015 in Beijing. The major benefit cited was the real-time information sourced from customers, which allows for direct feedback from clients when making decisions regarding changes in products or services. [85]

A significant contributor to the lack of adequate usage of data analytics is the belief that a PhD is a prerequisite for entering the field of data science. This misconception was pointed out by Richard Jones, vice president of Cloudera in the Australia, New Zealand and the Asean region. Cloudera provides businesses with the requisite professional services that they may need to effectively utilize Big Data. This includes a combination of the necessary manpower, technology and consultancy services.^{^[86]} Deepak Ramanathan, the chief technology officer, SAS Asia Pacific believes that this skill gap can be addressed by forming data science teams within both governments and private enterprises. These teams could comprise of members with statistical, coding and business skills and allow them to work in a collaborative manner to address the problem at hand.^{^[87]} SAS is an Enterprise Software Giant that creates tools tailored to suit business users to help them interpret big data. Eddie Toh, the planning and marketing manager of Intel's data center platform believes that businesses do not necessarily need data scientists to be able to use big data analytics to their benefit and can in fact outsource the technical aspects of the interpretation of this data as and when required.^{^[88]}

The analytical team at Dell has forged a partnership with Brazilian Public Universities to facilitate the development of a local talent pool in the field of data analytics. The Instituto of Data Science (IDS) will provide training methodologies for in person or web based classes. ^{^[89]} The project is being undertaken by StatSoft, a subsidiary of Dell that was acquired by the technology giant last year. ^{^[90]}

V. Conclusion

There have emerged numerous challenges in the analysis and interpretation of Big Data. While it presents an extremely engaging opportunity, which has the potential to transform the lives of millions of individuals, inform the private sector and influence government, the actualization of this potential requires the creation of a sustainable foundational framework ; one that is able to mitigate the various challenges that present themselves in this context.

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. It is therefore vital to employ the appropriate expertise in assessing and interpreting this data. The significant lack of a human resource to capital to analyze this information in an accurate manner poses a definite challenge to its effective utilization in the Global South.

The legal and technological implications of using Big Data are best conceptualized within the deliberations on protecting the privacy of the contributors to this data. The primary producers of this information, from across platforms, are often unaware that they are in fact consenting to the subsequent use of the data for purposes other than what was intended. For example people routinely accept terms and conditions of popular applications without understanding where or how the data that they inadvertently provide will be used.[91] This is especially true of media generated on social networks that are increasingly being made available on more accessible platforms such as mobile phones and tablets. Privacy has and always will remain an integral pillar of democracy. It is therefore essential that policy makers and legislators respond effectively to possible compromises of privacy in the collection and interpretation of this data through the institution of adequate safeguards in this respect.

Another challenge that has emerged is the access and sharing of this data. Private corporations have been reluctant to share this data due to concerns about potential competitors being able to access and utilize the same. In addition to this, legal considerations also prevent the sharing of data collected from their customers or users of their services. The various technical challenges in storing and interpreting this data adequately also prove to be significant impediments in the collection of data. It is therefore important that adequate legal agreements be formulated in order to facilitate a reliable access to streams of data as well as access to data storage facilities to accommodate for retrospective analysis and interpretation.

In order for the use of Big Data to gain traction, it is important that these challenges are addressed in an efficient manner with durable and self-sustaining mechanisms of resolving significant obstructions. The debates and deliberations shaping the articulation of privacy concerns and access to such data must be supported with adequate tools and mechanisms to ensure a system of "privacy-preserving analysis." The UN Global Pulse has put forth the concept of data philanthropy to attempt to resolve these issues, wherein " corporations [would] take the initiative to anonymize (strip out all personal information) their data sets and provide this data to social innovators to mine the data for insights, patterns and trends in realtime or near realtime."[92]

The concept of data philanthropy highlights particular challenges and avenues that may be considered for future deliberations that may result in specific refinements to the process.

One of the primary uses of Big Data, especially in developing countries is to address important developmental issues such as the availability of clean water, food security, human health and the conservation of natural resources. Effective Disaster management has also emerged as one of the key functions of Big Data. It therefore becomes all the more important for organizations to assess the information supply chains pertaining to specific data sources in order to identify and prioritize the issues of data management. [93] Data emerging from different contexts, across different sources may appear in varied compositions and would differ significantly across economic demographics. The Big Data generated from certain contexts would be inefficient due to the unavailability of data within certain regions and the resulting studies affecting policy decisions should take into account this discrepancy. This data unavailability has resulted in a digital divide which is especially prevalent in the global south. [94]

Appropriate analysis of the Big Data generated would provide a valuable insight into the key areas and inform policy makers with respect to important decisions. However, it is necessary to ensure that the quality of this data meets a specific standard and appropriate methodological processes have been undertaken to interpret and analyze this data. The government is a key actor that can shape the ecosystem surrounding the generation, analysis and interpretation of big data. It is therefore essential that governments of countries across the global south recognize the need to collaborate with civic organizations as well technical experts in order to create appropriate legal frameworks for the effective utilization of this data.

[1] Onella, Jukka- Pekka. "Social Networks and Collective Human Behavior." UN Global Pulse. 10 Nov.2011. <http://www.unglobalpulse.org/node/14539>

[2] http://www.business2community.com/big-data/evaluating-big-data-predictive-analytics-01277835

[3] Ibid

[4] http://unglobalpulse.org/sites/default/files/BigDataforDevelopment-UNGlobalPulseJune2012.pdf

[5] Ibid, p.13, pp.5

[6] Kirkpatrick, Robert. "Digital Smoke Signals." UN Global Pulse. 21 Apr. 2011. <http://www.unglobalpulse.org/blog/digital-smoke-signals>

[7] Helbing, Dirk , and Stefano Balietti. "From Social Data Mining to Forecasting Socio-Economic Crises." Arxiv (2011) 1-66. 26 Jul 2011 http://arxiv.org/pdf/1012.0178v5.pdf.

[8] Manyika, James, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh andAngela H. Byers. "Big data: The next frontier for innovation, competition, and productivity." McKinsey

Global Institute (2011): 1-137. May 2011.

[9] "World Population Prospects, the 2010 Revision." United Nations Development Programme. <http://esa.un.org/unpd/wpp/unpp/panel_population.htm>

[10] Mobile phone penetration, measured by Google, from the number of mobile phones per 100 habitants, was 96% in Botswana, 63% in Ghana, 66% in Mauritania, 49% in Kenya, 47% in Nigeria, 44% in Angola, 40% in Tanzania (Source: Google Fusion Tables)

[11] http://www.brookings.edu/blogs/africa-in-focus/posts/2015/04/23-big-data-mobile-phone-highway-sy

[12] Ibid

[13] <http://www.google.com/fusiontables/Home/>

[14] "Global Internet Usage by 2015 [Infographic]." Alltop. <http://holykaw.alltop.com/global-internetusage-by-2015-infographic?tu3=1>

[15] Kirkpatrick, Robert. "Digital Smoke Signals." UN Global Pulse. 21 Apr. 2011 <http://www.unglobalpulse.org/blog/digital-smoke-signals>

[16] Ibid

[17] Ibid

[18] Ibid

[19] Goetz, Thomas. "Harnessing the Power of Feedback Loops." Wired.com. Conde Nast Digital, 19 June 2011. <http://www.wired.com/magazine/2011/06/ff_feedbackloop/all/1>.

[20] Kirkpatrick, Robert. "Digital Smoke Signals." UN Global Pulse. 21 Apr. 2011. <http://www.unglobalpulse.org/blog/digital-smoke-signals>

[21] Bollier, David. The Promise and Peril of Big Data. The Aspen Institute, 2010. <http://www.aspeninstitute.org/publications/promise-peril-big-data>

[22] Ibid

[23] Eagle, Nathan and Alex (Sandy) Pentland. "Reality Mining: Sensing Complex Social Systems",Personal and Ubiquitous Computing, 10.4 (2006): 255-268.

[24] Kirkpatrick, Robert. "Digital Smoke Signals." UN Global Pulse. 21 Apr. 2011. <http://www.unglobalpulse.org/blog/digital-smoke-signals>

[25] OECD, Future Global Shocks, Improving Risk Governance, 2011

[26] "Economy: Global Shocks to Become More Frequent, Says OECD." Organisation for Economic Cooperationand Development. 27 June. 2011.

[27] Friedman, Jed, and Norbert Schady. How Many More Infants Are Likely to Die in Africa as a Result of the Global Financial Crisis? Rep. The World Bank <http://siteresources.worldbank.org/INTAFRICA/Resources/AfricaIMR_FriedmanSchady_060209.pdf>

[28] Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute,June 2011<http://www.mckinsey.com/mgi/publications/big_data/pdfs/MGI_big_data_full_report.pdf>

[29] The word "crowdsourcing" refers to the use of non-official actors ("the crowd") as (free) sources of information, knowledge and services, in reference and opposition to the commercial practice of

outsourcing. "

[30] Burke, J., D. Estrin, M. Hansen, A. Parker, N. Ramanthan, S. Reddy and M.B. Srivastava. ParticipatorySensing. Rep. Escholarship, University of California, 2006. <http://escholarship.org/uc/item/19h777qd>.

[31] "Crisis Mappers Net-The international Network of Crisis Mappers." <http://crisismappers.net>, http://haiti.ushahidi.com and Goldman et al., 2009

[32] Alex Pentland cited in "When There's No Such Thing As Too Much Information". The New York Times.23 Apr. 2011<http://www.nytimes.com/2011/04/24/business/24unboxed.html?_r=1&src=tptw>.

[33] Nathan Eagle also cited in "When There's No Such Thing As Too Much Information". The New YorkTimes. 23 Apr. 2011. <http://www.nytimes.com/2011/04/24/business/24unboxed.html?_r=1&src=tptw>.

[34] Helbing and Balietti. "From Social Data Mining to Forecasting Socio-Economic Crisis."

[35] Eysenbach G. Infodemiology: tracking flu-related searches on the Web for syndromic surveillance.AMIA (2006)<http://yi.com/home/EysenbachGunther/publications/2006/eysenbach2006cinfodemiologyamia proc.pdf>

[36] Syndromic Surveillance (SS)." Centers for Disease Control and Prevention. 06 Mar. 2012.<http://www.cdc.gov/ehrmeaningfuluse/Syndromic.html>.

[37] Health Map <http://healthmap.org/en/>

[38] see www.detective.io

[39] www.ushahidi.com

[40] www.facebook.com/BlackMondayMovement

[41] Ushahidi is a nonprofit tech company that was developed to map reports of violence in Kenya followingthe 2007 post-election fallout. Ushahidi specializes in developing "free and open source software for

information collection, visualization and interactive mapping." <http://ushahidi.com>

[42] Conducted by the European Commission's Joint Research Center against data on damaged buildingscollected by the World Bank and the UN from satellite images through spatial statistical techniques.

[43] www.ushahidi.com

[44] See https://tacticaltech.org/

[45] see www. flowminder.org

[46] Ibid

[47] http://post2015.unglobalpulse.net/

[48] http://allafrica.com/stories/201507151726.html

[49] Ibid

[50] Ibid

[51] http://www.computerworld.com/article/2948226/big-data/opinion-apple-and-ibm-have-big-data-plans-for-education.html

[52] Ibid

[53] http://www.grameenfoundation.org/where-we-work/sub-saharan-africa/uganda

[54] Ibid

[55] http://chequeado.com/

[56] http://datochq.chequeado.com/

[57] Times of India (2015): "Chandigarh May Become India's First Smart City," 12 January, http://timesofi ndia.indiatimes.com/india/Chandigarh- may-become-Indias-fi rst-smart-city/articleshow/ 45857738.cms

[58] http://www.cisco.com/web/strategy/docs/scc/ioe_citizen_svcs_white_paper_idc_2013.pdf

[59] Townsend, Anthony M (2013): Smart Cities: Big Data, Civic Hackers and the Quest for a New Utopia, New York: WW Norton.

[60] See "Street Bump: Help Improve Your Streets" on Boston's mobile app to collect data on roadconditions, http://www.cityofboston.gov/DoIT/ apps/streetbump.asp

[61] Mayer-Schonberger, V and K Cukier (2013): Big Data: A Revolution That Will Transform How We Live, Work, and Think, London: John Murray.

[62] http://www.epw.in/review-urban-affairs/big-data-improve-urban-planning.html

[63] Ibid

[64] Newman, M E J and M Girvan (2004): "Finding and Evaluating Community Structure in Networks,"Physical Review E, American Physical Society, Vol 69, No 2.

[65] http://www.sundaytimes.lk/150412/sunday-times-2/big-data-can-make-south-asian-cities-smarter-144237.html

[66] Ibid

[67] Ibid

[68] http://www.epw.in/review-urban-affairs/big-data-improve-urban-planning.html

[69] GSMA (2014): "GSMA Guidelines on Use of Mobile Data for Responding to Ebola," October, http:// www.gsma.com/mobilefordevelopment/wpcontent/ uploads/2014/11/GSMA-Guidelineson-

protecting-privacy-in-the-use-of-mobilephone- data-for-responding-to-the-Ebola-outbreak-_ October-2014.pdf

[70] An example of the early-stage development of a self-regulatory code may be found at http:// lirneasia.net/2014/08/what-does-big-data-sayabout- sri-lanka/

[71] See "Sri Lanka's Mobile Money Collaboration Recognized at MWC 2015," http://lirneasia. net/2015/03/sri-lankas-mobile-money-colloboration- recognized-at-mwc-2015/

[72] http://www.thedailystar.net/big-data-for-urban-planning-57593

[73] http://koreaherald.com , 19/01/2015

[74] http://www.news.cn/, 25/11/2014

[75] http://the-japan-news.com , 20/01/2015

[76] http://www.todayonline.com/singapore/can-big-data-help-tackle-mrt-woes

[77] Ibid

[78] Ibid

[79] http://edition.cnn.com/2015/06/24/tech/big-data-urban-life-singapore/

[80] Ibid

[81] Ibid

[82] http://venturebeat.com/2015/04/03/how-microsofts-using-big-data-to-predict-traffic-jams-up-to-an-hour-in-advance/

[83] Ibid

[84] https://www.hds.com/assets/pdf/the-hype-and-the-hope-summary.pdf

[85] http://www.news.cn , 14/01/2015

[86] http://www.techgoondu.com/2015/06/29/plugging-the-big-data-skills-gap/

[87] Ibid

[88] Ibid

[89] http://www.zdnet.com/article/dell-to-create-big-data-skills-in-brazil/

[90] Ibid

[91] Efrati, Amir. "'Like' Button Follows Web Users." The Wall Street Journal. 18 May 2011.

<http://online.wsj.com/article/SB10001424052748704281504576329441432995616.html>

[92] Krikpatrick, Robert. "Data Philanthropy: Public and Private Sector Data Sharing for Global Resilience."

UN Global Pulse. 16 Sept. 2011. <http://www.unglobalpulse.org/blog/data-philanthropy-public-privatesector-data-sharing-global-resilience>

[93] Laney D (2001) 3D data management: Controlling data volume, velocity and variety. Available at: http://blogs. gartner.com/doug-laney/files/2012/01/ad949-3D-DataManagement-Controlling-Data-Volume-Velocity-andVariety.pdf

[94] Boyd D and Crawford K (2012) Critical questions for Big Data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication, & Society 15(5): 662-679.

For more details visit https://cis-india.org/internet-governance/blog/big-data-in-the-global-south-an-analysis