Resources should also be more effectively coordinated. Donors should ease countries’ access to funding by creating a new funding stream to support the data revolution for development. Donors are increasingly aligning their contributions with NSDSs, which highlight key priority investments. To ensure maximum coordination and coherence, this funding stream could be a multi-donor trust fund, administered by the World Bank but governed by a broad range of stakeholders, including the UN. This fund should also seek to align with similar endeavors, such as the World Health Organization and the World Bank’s Global Civil Registration and Vital Statistics Scaling Up Investment Plan 2015-2024, as well as to direct resources towards underfunded areas, such as gender statistics and management information systems in the education and health sectors. This new funding stream should also seek to drive improvements in monitoring over time and to foster innovation.
HOW TO FUND AID FOR STATISTICS
A recent inventory of financial instruments created by Open Data Watch identified a wide range of existing mechanisms currently used to support statistical capacity building. They identified seven major types:
Multilateral lending-country focus
Bilateral, multilateral, or organizational support in form of technical assistance
Multi-Donor Trust Fund (MDTF) – Country executed
Multi-Donor Trust Fund (MDTF) – Host agency executed
Multi-Donor Trust Fund (MDTF) – Host agency or partner executed
Special development grant
The inventory identified 31 financing mechanisms contributing approximately US$264 million per year in aid to statistics. Financing gaps were identified in several areas, such as gender statistics, data innovations, and open data initiatives. Most importantly, the study identified significant gaps in spending for low-income countries. The report estimates that donors will need to double current contributions through grant-based trust funds to meet needs for the Post-2015 Development Agenda.
Replenishing the existing financial instruments will go a long way in responding to many demands coming from the data revolution. However, the Open Data Watch study also recommends that donors focus on developing multi-donor trust funds for new funding streams to promote alignment with national priorities and reduce duplication between donors.
Adapted from Open Data Watch Aid for Statistics: An Inventory of Financial Instruments.16
Embracing the Data Revolution
As highlighted by the IEAG, new data collection and monitoring technologies are becoming rapidly available. These innovations will dramatically advance national statistical offices’ and the international community’s ability to monitor the impacts of development programs, in addition to informing the way they are designed and implemented. High-resolution satellite imagery, mobile devices, biometric data, and crowdsourced citizen reporting will change official data collection processes and the design of the programs they monitor. Take for example, satellite imagery. The cost of high-resolution image acquisition is falling while the availability of images and capacity for automated processing are increasing. There are many applications for earth observation data: harvest prediction, disaster response, and food security issues; monitoring geographic patterns and disease transmission corridors with geospatial determinants; measuring population density and the spread of new settlements; and mapping and planning transportation infrastructure.
Many surveys are now being conducted on digital mobile platforms.17 This practice reduces the time and cost of data collection. Is also improves accuracy, simplifies collection of GIS and image data, streamlines integration with other information streams, and opens up the possibility of incorporating micro-chip based sensors into survey processes. Innovation is not just about adopting new technologies, it is also about improving existing ones.
"The bourgeoning “data revolution” movement should seize on the opportunity to strengthen national statistical systems in the region from the ground up, focusing on underlying political economy issues that have slowed progress on data for decades."
Delivering on the Data Revolution in Sub-Saharan Africa18
Many countries are innovating by expanding the use and impact of data through open data platforms, encouraging citizens to use data to track the quality of their services and to monitor private and public performance. Others are innovating by setting up partnerships for different skill set groups to work together towards a common goal, from research design to data production and analysis. These and other innovations will drive new approaches for achieving the SDGs, from pinpointing specific communities and households for health initiatives to integrating real-time monitoring of natural resources into allocation schemes, and tracking government and donor investments. In spite of the upfront costs of software, hardware, and training, such innovations have huge potential to lower SDG monitoring costs over time.
SATELLITE IMAGERY IMPROVING REAL-TIME MONITORING
The SDGs will depend on more geospatial and earth observations data than the MDGs. Satellite imagery is increasingly available for free at a moderate resolution, and at a cost for high-resolution sources. Satellite products have the potential to be utilized in monitoring more than 23 potential SDG indicators, ranging from measuring global air quality to crop and forest cover, to disaster impacts, and water resources.
For example, Surface Water and Ocean Technology (SWOT) is a new mission to be launched in 2020 by the United States National Aeronautics and Space Administration (NASA) and the French Centre National d’Études Spatiale (CNES). The primary SWOT instrument has the ability to map water elevation and areal extent at an unprecedented spatial resolution and at a global scale, observing the details of the ocean’s surface topography, as well as its terrestrial water bodies. A team of hydrologists recently published a study showing the potential application of SWOT by monitoring Mali’s Sélingué dam. They incorporated virtual SWOT observations of reservoir and river levels into a modeling framework that simulated the hydrologic conditions on either side of the dam. The results demonstrated that incorporating altimetry data into this framework improves estimates of water levels and discharge, potentially helping resource managers ensure optimal reservoir releases.19 New satellite imagery is one example of emerging technology that offers significant opportunities for a global water monitoring platform.
Figure 4: There are numerous options for new technology and data collection innovations that could advance monitoring of the SDGs. This figure summarizes key tools identified to offer immediate Post-2015 opportunities.
The cost of high-resolution image acquisition is falling, while the availability of images and capacity for automated processing are increasing. There are many applications for such data across multiple goals, such as predicting harvests, disaster response, earth observations, and food security situations; monitoring geographic patterns and likely transmission corridors of diseases that have geospatial determinants; measuring population density and the spread of new settlements; as well as mapping and planning transportation infrastructure.
Mobile Network Call Records
The rapid increase in cell phone users has opened new flows of data that have been used in post-crisis response, like during Haiti’s 2010 earthquake to the recent climate data challenge. There is growing potential for systematic use of this data for sustainable development objectives.
Global connectivity has created the opportunity for wide-scale participation in data collection and data processing, with applications in road mapping, land cover classification, human rights monitoring, price tracking, species inventories, and disaster response planning; with new uses unfolding regularly.
The increasing use of smart metering systems for energy and water distribution, that transmit usage information over communications networks, create novel capabilities to measure and manage service provision. Enel’s Telegestore system in Italy is one of the largest and most successful examples.
Smartphone and Tablet-based Data Collection
As described in SDSN’s Indicators and a Monitoring Framework for the Sustainable Development Goals report, many surveys are now being conducted on digital mobile platforms. This practice reduces the time and cost for data collection, improves accuracy, simplifies collection of GIS and image data, streamlines integration with other information streams, and opens up the possibility of incorporating microchip based sensors into survey processes.
New uses have been discovered for data sources emerging from processes that are not explicitly designed for such purposes, such as social media, cell phone records, commercial transactions, and traffic records. Proven applications have been developed in a range of areas including crisis response, urban planning, and public health management.
NIGERIA EXPANDS ITS STATISTICAL TOOLKIT FOR MDGS INTO SDGS
The government of Nigeria has a very active statistics office, completing annual labor force, health, household, and agriculture surveys. It has scored significantly higher than other IDA-eligible countries on the World Bank’s Statistical Capacity Indicator, receiving a score of 72.2 in 2015—compared to the average IDA-eligible country score of 62.20 Nigeria’s government has gone beyond traditional MDG monitoring instruments and implemented new data collection approaches that are being used to complement official statistics in a national effort to improve MDG implementation. Under the President’s MDG office, the government deployed mobile-phone-equipped enumerators to each region of the country to collect georeferenced inventories of health, education, and water facilities, including both basic location information and attribute data on the quality and capacities of each facility. They have now documented 250,000 facilities and effectively linked this data to planning via their MDG debt-relief local grants programs. This model serves to demonstrate potential new data inputs for the SDGs.21 Georeferenced facility surveys could cover waste treatment plants, bus stops, schools, water points, health facilities, agricultural infrastructure, and more. Nigeria’s example shows that cellular devices are efficient tools for rapid collection of data and are capable of generating new geospatial data resources for SDG monitoring systems.
Monitoring the SDG agenda will require substantive improvements in national statistical capacity. Collecting recurrent, quality data on the varied dimensions of sustainable development also requires that we innovate and seek to modernize statistical systems. The Financing for Development conference is a unique moment for governments to commit resources, both financial and technical, and to forge partnerships that capture the benefits of the data revolution in support of the SDGs.
Since May 2013, when the High-Level Panel on the Post-2015 Development Agenda called for a “data revolution for sustainable development,” there has been an outpouring of reviews, studies, and blog posts on this topic. A World That Counts, issued at the end of 2014, is the most comprehensive. There has also been follow-up work led by the UN statistical community, as well as donor-supported special studies, such as the PARIS21 review of the status of the data revolution in developing countries.22 Data for Development— produced by SDSN, Open Data Watch, and partners—is the most recent contribution to this discussion. It offers concrete estimates of overall costs and a framework for understanding the core data needs.