Data and data-supported innovation are important tools for us to achieve the targets of the 2030 Agenda, and it is high time to amplify our efforts in this direction.
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This is part of the essay series: World Population Day 2024
As we cross the mid-way point of the 2030 Agenda for Sustainable Development, only 12 percent of the Sustainable Development Goals (SDGs) are on track. With less than six years to 2030, it is necessary to focus our efforts towards accelerating the progress on the 2030 Agenda and use every tool in our power to support the SDGs. Emerging technology solutions and data-based innovations can support inclusive, resilient, and sustainable growth.
Data can be used for tracing patterns in public health, improving the delivery of public services, supporting humanitarian missions, improving smart cities, and even promoting sustainable consumption. The theme for this World Population Day also highlights the importance of data and data collection for promoting sustainable growth. It is important to invest in data allowing the development of innovative solutions that can help build resilient and equitable future for all. However, the existence of data silos can drastically impact the benefits of the various data for development solutions.
Data can be used for tracing patterns in public health, improving the delivery of public services, supporting humanitarian missions, improving smart cities, and even promoting sustainable consumption.
This piece discusses the concept of data for development, explains the key reasons that lead to data in silos and how such data can affect the progress of the 2030 Agenda, and recommend steps that can reduce the silos.
While there is no singular definition of what data for development entails, the report Drivers of Data for Development conceptualises it as “the use of data to support socio-economic development interventions which include, policymaking, decision-making, investment, community engagement, equality, innovation among others.” Figure 1 summarises the concept of data for development.
Figure 1: Data for development
Source: Author’s own
Data can be used to accelerate and further the implementation of the 2030 Agenda for Sustainable Development in two ways: “Data on SDGs” and “Data for SDGs”. The former includes the use of data to measure and monitor the progress of the SDGs, while the latter refers to the use of intelligence extracted from data for developing effective and innovative solutions. Figure 2 illustrates how data can help support the 2030 Agenda.
Figure 2: How Data Science and Analytics can contribute to Sustainable Development?
Source: UN, Big Data for Sustainable Development
A data silo can be broadly defined as a situation when crucial datasets are stored and managed separately by different stakeholders and are not easily accessible to others. Such arrangements prevent the free flow of information among individuals, departments, governments and international organizations. There are several reasons that lead to siloing of data
Proprietary nature of data: A key reason for the existence of data silos is that several organisations treat data as a proprietary asset and are reluctant to share it with other stakeholders.
The lack of standardisation: Data is often stored in different systems and formats. These datasets lack consistency and use varied structures and formats leading to difficulties in data exchange.
The lack of interoperability and technological incompatibility: Data systems and platforms might lack interoperability and be unable to communicate and exchange information with one another. Integrating legacy systems and data in non-machine-readable formats may cause further difficulties with data sharing.
Data governance issues: Privacy policies and data governance frameworks can also lead to the siloing of data in certain cases. Laws may require data localisation and limit the flow of data from one organisation or geography to another. Differences in privacy and data protection policies of data holders may also cause data transfer issues.
Different data sets within the government can be managed, stored, and accessed in differing and inconsistent ways. This prevents the efficient harnessing of the data and the integration of different data sets thwarting comprehensive analysis. Data, when hosted in silos across a broad ecosystem, hinders accessibility and obstructs the flow of valuable insights and restrict comprehensive analytics. Segregation of different kinds of data can prevent comprehensive analysis and cause inefficient resource allocation.
Keeping data is silos can lead to redundancy and duplication of efforts. Different agencies may require similar data. They may have to invest resources for collecting similar kinds of data leading to redundant storage and increased costs. Putting data in silos can reduce the social and economic value of the said data.
Keeping data is silos can lead to redundancy and duplication of efforts. Different agencies may require similar data. They may have to invest resources for collecting similar kinds of data leading to redundant storage and increased costs. Putting data in silos can reduce the social and economic value of the said data.
Despite major push and efforts towards data collection for the SDGs, several indicators lack the necessary data required to monitor them, thereby creating blind spots for the policymakers.
The best way to prevent data silos is to focus on the three Cs—Collection, Coordination and Collaboration—that can create better data for sustainable development. To improve collection, different stakeholders can come together to collect information from a variety of sources in an interoperable format. It is important to ensure that data is accessible and usable by different stakeholders while reducing duplication of efforts. A coordinated data strategy can be developed to ensure that data is freely shared amongst different stakeholders. Additionally, new technology solutions can be introduced to facilitate data sharing. Further, it is important to ensure cross-sectoral coordination to ensure that data across sectors can be integrated to develop comprehensive insights. It is also important to create incentives for data sharing amongst the different players in the development ecosystem.
The best way to prevent data silos is to focus on the three Cs—Collection, Coordination and Collaboration—that can create better data for sustainable development.
Data and data-supported innovation are important tools for us to achieve the targets of the 2030 Agenda, and it is high time to amplify our efforts in this direction. We need to focus our efforts on improving data collection and collaborate with different stakeholders for better analysis and insights. Strengthening data ecosystems provides a better picture of the diversity of our societies and helps make policies to ensure that no one is left behind.
Basu Chandola is an Associate Fellow at the Observer Research Foundation.
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Basu Chandola is an Associate Fellow. His areas of research include competition law, interface of intellectual property rights and competition law, and tech policy. Basu has ...
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