Using Big Data for the Sustainable Development Goals
The statistical community has the obligation of exploring the use of new data sources, such as Big Data, to meet the expectation of the society for enhanced products and improved and more efficient ways of working. Big Data could also support the monitoring of the Post-2015 development goals by improving timeliness and relevance of indicators without compromising their impartiality and methodological soundness. The report of the Global Working Group on Big Data for Official Statistics to the Statistical Commission (E/CN.3/2015/4) provides additional background to the work of the task team.
The recent report of the Independent Expert Advisory Group (IEAG) on the Data Revolution for Sustainable Development defines the data revolution for sustainable development as the integration of data coming from new technologies with traditional data, in order to produce relevant high-quality information, with more detail and at higher frequencies to foster and monitor sustainable development. This revolution also entails the increase in accessibility to data through much more openness and transparency, and ultimately more empowered people for better policies, better decisions and greater participation and accountability, leading to better outcomes for the people and the planet.
The IEAG report also includes a proposal to contribute to the adoption of best practices for improving the monitoring of the new sustainable development goals (SDGs), identify areas where common data-related infrastructures could address capacity problems, and improve efficiency, encourage collaborations, identify critical research gaps and create incentives to innovate.
Statistical agencies should choose data sources with regard to quality, timeliness, costs and response burden, and Big Data sources fall within this scope. To monitor certain indicators Big Data could have the potential to be as relevant, more timely and more cost effective than traditional data collection methods, and could make the data cycle match the decision cycle. The work on Big Data should contribute to the adoption of best practices for improving the monitoring of the new SDGs under the Post-2015 development agenda. Some of the new indicators or proxies of those indicators could be based on Big Data sources with improved timeliness and granular social and geo-spatial breakdown.
This is consistent with the Decision of the 45th session of the Statistical Commission in 2014, which recognized that Big Data constitute a source of information that cannot be ignored. To achieve this, the Commission created a Global Working Group on Big Data for Official Statistics to explore the use of Big Data, identify examples, assess methodologies, address concerns related to quality and confidentiality, and develop guidelines. The terms of reference for the Global Working Group on Big Data for Official Statistics state:
In an era of limited budgets and declining responses to households and business surveys, the statistical community has recognized the potential use of Big Data for official statistics to better fulfil the mandate of providing timely and relevant statistics on the economy, society and the environment for decision making, research and public debate. At the same time the statistical community is conscious that in order to be able to take advantage of innovative data sources, it needs to adequately address issues pertaining to methodology and technology, legislation, privacy, management and finance. Moreover, it is of the utmost importance to create an environment where the public trust in the use of Big Data for official statistics is established and where privacy and confidentiality of personal information can be assured.
The main objective of the Task Team is to provide concrete examples of the potential use of Big Data for monitoring the indicators associated with the Sustainable Development Goals (SDGs). To this end, it will conduct surveys, research and a few country pilots on the subject and produce a report on its findings by December 2015.
- Survey to identify which of the 169 SDG targets could use Big Data, as well as proposals of Big Data-specific indicators related to the SDG, which may be different to the current set of indicators based on traditional sources of data
- Make an inventory of past and ongoing research work on Big Data that could be used to calculate one or more SDGs
- Pilot research in 1-2 countries on calculating 2-3 SDG indicators using Big Data
- Presentation at the Big Data Conference of UAE
- Write report of the Working Group
- World Bank
- Global Pulse
- University of Pennsylvania
- Data-Pop Alliance
- NASA/Jet Propulsion Laboratory
- DESA, UN
- Paris 21