“Big data can act as a force for greater political and societal empowerment and change but it necessitates data literacy and data-educated citizenry.”
Big data has become a buzzword now and all sorts of businesses, non-profits, governments, and other groups are now leveraging the torrent of digital data by analyzing it for their benefit. Among numerous benefits of Big Data, it provides new opportunities and possibilities such as improved operational efficiency, improved customer satisfaction, drive for innovation, and maximizing profits, etc. Big data also has the potential to help significantly improve the quality of life for much of the world’s population. This is why the governments and non-governmental organizations are using it to track progress and make sure their decisions are evidence-based; strengthen accountability; improve services, enhance operational efficiency, and most importantly, the early identification of risks and patterns, which lead us to bring sustainability.
Here we will be featuring the reports and analysis of the UN and SDG bodies focused on harnessing the Big Data for improving their understanding of certain topics and practices. The United Nations, governments, not-for-profits, and other groups are using big data to help achieve the UN’s sustainable development goals or SDGs — a set of 17 targets related to protecting the natural environment, reducing inequality, improving health outcomes, and other things that will make life better around the world.
There are many ways in which we could use data to improve our understanding of our progress towards the SDGs, determine how best to meet those targets, and ensure accountability. The United Nations has set up a task team to explore how to use big data to help achieve the SDGs. A survey by the task team found that big data projects most frequently focused on the “no poverty” goal and that mobile phone data was the most common data source. Pulse Lab Jakarta, a joint effort between the United Nations and the government of Indonesia, is working on various big data projects related to the SDGs. One of their projects is the Vulnerability Analysis Monitoring Platform for Impact of Regional Events (VAMPIRE) platform, which analyzes satellite imagery and creates maps that incorporate anomalies related to climate and rainfall to help track slow-onset climate changes.
Another project, the Manitoba Bioeconomy Atlas, comes from the International Institute for Sustainable Development and involves the creation of a web-based spatial inventory of biomass sources. Biomass producers can use the data to optimally locate biomass refineries, and biomass consumers can use it to source biomass and calculate costs.
There are many other potential uses for big data related to the SDGs. Mobile phone data, for instance, could be used to track the movement of populations, such as refugees, to improve preparations. Data analysis could help predict changes in food prices. The possibilities are virtually endless.
The opportunities related to big data are plentiful, but there are also numerous challenges and risks. Collecting, storing, and analyzing large amounts of data is in itself challenging. It requires advanced technology and infrastructure, which can be expensive. This limits the access of less developed countries to this technology. In the survey by the UN’s bid data task team, the team received much higher response rates from high-income countries than lower-income ones.
Privacy is another significant concern. It’s essential that those processing respect the rights of those they collect data from. The fact that much data is collected passively can complicate this. Even removing sensitive information from data sets may not always be enough to guarantee privacy, since people could be identified by combining information from multiple data sets. Those handling personal data need to take steps to protect subjects’ privacy.
The UN, through several of its groups, has issued recommendations and guidelines for the use of big data related to SDGs. Among the goals of these guidelines are ensuring privacy and increasing access to data worldwide. The private and public sectors, as well as countries and organizations from around the world, will have to work together to accomplish the UN’s SDGs and to ensure that we can take full advantage of the benefits big data and machine learning can provide related to achieving them.
The Data Revolution
With a host of SDG indicators to review, Big Data can easily supplement customary data sources to keep a better track of the development plans. The Sustainable Development Goals provide particular, time-bound, and computable objectives in collaboration with the national development strategies same as priorities. Though, with more than 230 SDG indicators; plenty of which need proper disaggregation by various parameters like location, gender, income, age, and a host of other appropriate dimensions – gathering the required granular data to review all SDGs as well as their objectives is not at all an easy feat for the existing national statistical systems (NSS). To understand the level of capability of the national statistical systems specifically for the SDG era, The United Nations Economic and Social Commission takes into account the 22 nations’ experience in disseminating the SDG indicators as well as using a host of different varieties of data sources.The national statistical organizations recently reported that disaggregation of the stats by location for plenty of different SDG indicators. Although, the disaggregation is pretty scant for a few of the SDG indicators. However, it is all the thinner when it comes to specifically the disabled population as well as the indigenous peoples.
Now, most of the NSOs have happily acknowledged that the only technique through which they will be able to fulfill SDGs’ disaggregated data needs is to make good use of innovative procedures and data sources.
Plenty of governmental bodies are already using small area estimation (SAE) techniques which are aimed to enhance the direct survey approximations particularly small areas (or tiny sub-populations) with supplementary data inputs like the census records). SAE methods help to attain more granular information on poverty or nutrition. Some popular NSOs also provided information about their current level of existing photo/satellite images, phone data, web-scraped costs, online cost data, same as social media data. Plenty of the respondents see Big Data as a fruitful new way to address the not so happening data gaps for SDGs. However, just a very few numbers have Big Data projects at the moment.
Big Data gathered from a host of search engines, electronic gadgets, social media, as well as from a variety of sensors tracking gadgets and satellite images now offer a novel information source to the NSSs, which includes 3 Vs volume, velocity, as well as variety. And, this beautifully supports the statistics, which are gathered from traditional sources. Big data is currently being explored sequentially for many different types of development purposes.
A large number of the respondents see For example, in Jakarta, Twitter interactions on the cost of rice have offered a ground-breaking way to review the actual costs. In the Philippines, World Bank is working in collaboration with the ride-hailing service supplier to launch the Open Traffic Initiative. They are presently using the company’s driver data to get almost real-time traffic information and related statistics, like flow, speed, as well as information about the delays at intersections. This information will help to study critical parts of traffic management.
The United Nations Statistics Division has already developed a thorough record of Big Data projects. And this inventory contains both previous as well as the existing undertakings based on the making use of scanner information from the supermarket chains as well as other retailers. It also includes information about the online prices attained from web scraping. It is used to generate price catalogs in many countries.
To ensure that access to insights from big data across many industries is widely available, public-private partnership is the key to operationalize the concept of ‘data philanthropy,’ whereby companies’ data can be safely and responsibly used for sustainable development and humanitarian action. For example, in 2016, Global Pulse formed a partnership with the social media network Twitter. Every day, people around the world send hundreds of millions of tweets in dozens of languages. Such social conversations contain real-time information on many issues, including food costs, the availability of jobs, access to health care, quality of education, and reports of natural disasters. The partnership will allow UN development and humanitarian agencies to turn the public data into actionable information to aid communities around the globe. Other examples of partnerships include the GSMA’s “Big Data for Social Good” initiative, which leverages mobile operators’ big data capabilities to address humanitarian crises, including epidemics and natural disasters; Data for Climate Action, a competition that connected researchers around the world with data and tools from leading companies to enable data-driven climate solutions; and Data Collaboratives, a new form of collaboration beyond the public-private partnership model, in which participants from different sectors (and companies in particular) exchange their data to create public value.Big Data is a very fresh and innovative way to fill in the present data gaps for SDGs. It just that we have to expand its usage. More and more projects will also have to start using the power of Big Data analytics solutions as well.
However, with all its boons, there are certain risks associated with the use of big data by development bodies, such as the fundamental elements of human rights must be safeguarded to realize the opportunities presented by big data: privacy, ethics, and respect for data sovereignty require us to assess the rights of individuals along with the benefits of the collective. Much new data is collected passively – from the ‘digital footprints’ people leave behind and from sensor-enabled objects – or is inferred via algorithms. Because big data is the product of unique patterns of behavior of individuals, the removal of explicit personal information may not fully protect privacy. Combining multiple datasets may lead to the re-identification of individuals or groups of individuals, subjecting them to potential harms. Proper data protection measures must be put in place to prevent data misuse or mishandling.
There is also a risk of growing inequality and bias. Major gaps are already opening up between the data haves and have-nots. Without action, a whole new inequality frontier will split the world between those who know, and those who do not. Many people are excluded from the new world of data and information by language, poverty, lack of education, lack of technology infrastructure, remoteness or prejudice, and discrimination. There is a broad range of actions needed, including building the capacities of all countries and particularly the Least Developed Countries (LDCs), Land-locked Developing Countries (LLDCs), and Small Island Developing States (SIDS).
Big Data for Development and Humanitarian Action
In 2015, the world embarked on a new development agenda underpinned by the Sustainable Development Goals (SDGs). Achieving these goals requires integrated action on social, environmental, and economic challenges, with a focus on inclusive, participatory development that leaves no one behind. Critical data for global, regional, and national development policymaking is still lacking. Many governments still do not have access to adequate data on their entire populations. This is particularly true for the poorest and most marginalized, the very people that leaders will need to focus on if they are to achieve zero extreme poverty and zero emissions by 2030, and to ‘leave no one behind in the process. Big data can shed light on disparities in society that were previously hidden. For example, women and girls, who often work in the informal sector or at home, suffer social constraints on their mobility and are marginalized in both private and public decision-making. Much of the big data with the most potential to be used for the public good is collected by the private sector. As such, public-private partnerships are likely to become more widespread. The challenge will be ensuring they are sustainable over time, and that clear frameworks are in place to clarify roles and expectations on all sides.
Achievement of the SDGs in our digital world will require recognition of the need not only to prevent misuse of data but also to ensure that when data can be used responsibly for the public good, it is.
The Secretary-General’s Independent Expert Advisory Group on a Data Revolution for Sustainable Development (IEAG) has made specific recommendations on how to address these challenges, calling for a UN-led effort to mobilize the data revolution for sustainable development, by:
- Fostering and promoting innovation to fill data gaps.
- Mobilizing resources to overcome inequalities between developed and developing countries and between data-poor and data-rich people.
- Leadership and coordination to enable the data revolution to play its full role in the realization of sustainable development.
The uptake of big data analytics is accelerating across the UN system with a growing number of UN agencies, funds, and programmes implementing and scaling operational applications for development and humanitarian use. The UN Development Group has issued general guidance on data privacy, data protection, and data ethics concerning the use of big data, collected in real-time by private sector entities as part of their business offerings, and shared with UNDG members to strengthen operational implementation of their programmes to support the achievement of the 2030 Agenda.
The first UN World Data Forum held in January 2017 brought together over 1,400 data users and producers from the public and private sectors, policymakers, academia, and civil society to explore ways to harness the power of data for sustainable development. It produced important outcomes, including the launch of the Cape Town Global Action Plan for Sustainable Development Data. The next meeting will be held in October 2020.
In short, Big data can potentially revolutionize current official statistical systems in one of several ways: a) Entirely replace existing statistical sources such as surveys; b) Partially replace existing statistical sources such as surveys; c) Provide complementary statistical information in the same statistical domain but from other perspectives; d) Improve estimates from statistical sources, and e) Provide completely new statistical information in a particular statistical domain.
However, it is sure that this data revolution will also have few loopholes, such as it cannot completely replace the traditional surveys because it requires to fine-tune models to ground realities. Then we need to pay particular attention to ‘representativity’ of these new data sources that are being leveraged i.e. how accurately it reflects the population. Marginalization in the real world can often result in marginalization in the digital world beyond just issues of access to technologies or being represented in the digitized data. Similarly, the developing economies, in particular, have much lower levels of ‘datafication’ than developed economies, thus there is a need to have an equal focus on their digitization for the realization of SDGs –which is a global agenda.
In a nutshell, big data can act as a force for greater political and societal empowerment and change but it necessitates data literacy and data-educated citizenry. For this, we have to promote literacy in the age of big data and see this as a building block to contribute to the SDGs through Big Data. This will require much more sustained and strategic engagement and investments and be much more disruptive of current decision-making processes and political structures than developing Big Data and SDG pilots, which may nonetheless serve a real purpose, but if and only if they are part of a broader and more complex vision.