A future for digital public goods for monitoring SDG indicators

In the past decade, the availability and knowledge of digital tools and resources have rapidly improved worldwide. Nevertheless, the differences in capacity and priorities will likely be a problem for any development process working to produce DPGs for SDG indicators, which are intended for global use. The survey results highlighted that more than 30% of the experts believe a single program or a single agency is not in a position to facilitate the development of the diverse range of DPGs necessary for generating SDG indicators. Rather, this endeavor requires international and multi-stakeholder cooperation. Based on these opinions, the authors developed a consensus on the need for a cooperative framework applying a participatory approach that should observe the principles of the universality of science in accordance with the first Core Principle identified in Table 1.

Considering Key Actions 1.1 and 1.2, which promote open science, inclusivity, consultations, joint contributions, and shared benefits, this paper suggests a community-supported open-source development approach that will improve innovation and novelty in methods and processes. Supported by a UN-driven recognition program, talent at all skill levels could be encouraged to participate in this community-led development process.

The community approach provides a multi-stakeholder development process that not only provides a strong process to identify, sort, and develop mainstream DPGs for SDGs, but also creates an opportunity to hear from stakeholders from different scales and perspectives. If properly managed, it has the potential to also address the paradoxes identified regarding scaling challenges of DPGs³⁶. The community-based approach also supports the idea of a continual development process that enables new ideas to flourish and to be recognized.

A more detailed, tentative flowchart of the proposed process is provided in Fig. 1. The current framework is by no means complete and devoid of any flaws, but nevertheless there is strong potential for using this process to create mechanisms for supplying and scaling DPGs to different communities globally. The following section highlights important challenges that were identified by the authors during discussions and provides suggestions on the key actions to address these challenges.

Proposed community-driven open-science process to develop DPGs for SDG indicators.

Organizational challenges

DPG development that applies the open-science paradigm and is supported by the DPG community at large would be an attractive solution for addressing many implementation issues. This kind of governance scheme would provide the necessary bottom-up approach that is suggested by Key Action 2.1 of Table 1 (Core Principle 2). In addition, it would help encourage highly talented data scientists, programmers, and digital technology experts to voluntarily participate in devising novel solutions, as indicated by Core Principle 3. However, organizing and streamlining these efforts could prove very challenging. In the absence of a designated team, an open-source development environment could lead to competing methods and products. Addressing this challenge will require efficient Quality Assurance and Control (QA/QC) mechanisms (Core Principle 5). Similarly, a community-based development approach could improve the efficiency of the development process, particularly one in which expert volunteers collaborate with research and academic institutions to broaden the scope of development against defined goals and deadlines.

Some of these governance challenges could be solved by appointing product leaders for the separate classes of DPGs as defined by DPGA (i.e., models, content, data, software, and standards). These managers could be designated by the various agencies that manage and maintain the different SDG indicators. The designated product leaders would work as focal persons for collecting community input, while having a clear understanding of the SDG indicators at hand and the related auditing requirements. Finally, they might help organize the community development process, as per Key Action 3.2, and provide relevant guidance to community developers and serve as a preliminary QA/QC. Subsequently, in a second phase of the development process, a “Committee of Experts” could be established to evaluate the different digital products received and act as a higher level of QA/QC in keeping with Key Actions 5.1 and 5.2. The Committee of Experts could select a list of viable products to be tested and verified by National Statistical Offices (NSO) for compliance and applicability (see Fig. 1). In addition, they could help achieve Key Action 5.3. After verification from NSOs, the product could be adopted through a designated political forum for SDG evaluation reporting purposes by interested countries and organizations.

In the development process discussed, however, there are possibilities for duplications of effort. Acting on Core Principle 4 (Key Actions 4.1, 4.2, and 4.3) will provide the necessary resources and information to avoid possible duplications. A descriptive and open catalog of ongoing developing efforts should help potential developers understand which ideas are truly innovative, thus saving time and avoiding unnecessary effort.

An important organizational challenge will be to fund support systems (Core Principle 4). There have been growing calls by the UN, for example, during its World Data Forum 2021, for more effective investments from governments, the private sector, civil society, and the philanthropic community to help strengthen data systems; for example, via commitment to the Bern Data Compact for the Decade of Action on the Sustainable Development Goals (https://unstats.un.org/sdgs/hlg/Bern-Data-Compact/). More recently, the Hangzhou Declaration: Accelerating progress in the implementation of the Cape Town Global Action Plan (CTGAP) for Sustainable Development Data (https://www.un.org/en/desa/un-world-data-forum-closes-hangzhou-declaration-charting-accelerated-progress-implementation) states that one of the new priorities has been identified as, “Innovation and modernization of national data and statistical systems, with particular focus on addressing the monitoring needs of the 2030 Agenda for Sustainable Development,” as well as, “Dissemination and use of sustainable development data”. Based on these developments, there is potential for governments to pool funds to establish support systems under a credible framework. One such framework is the World Bank-supported Global Data Facility (GDF). The World Bank’s policy briefing has launched two data financing mechanisms, including the UN-hosted Complex Risk Analytics Fund, to support open data ecosystems for crises-related applications, and funding to low- and middle-income countries for investment in data systems³⁷. Therefore, there are potential mechanisms and institutions that are being set up to facilitate similar efforts and provide a framework that can be built upon for development of support systems for this community-driven open-science process. Considering that the World Bank announced a campaign to raise $500 million USD over 10 years for data research³⁷, it will likely be an attractive prospect for governments and the private sector to fund support systems and to share data samples in return for working solutions that can be implemented locally or duplicated in other regions with minimal effort in the spirit of collaborative development, provided the QA/QC systems are satisfactory.

There are also existing online programs, such as Google Earth Engine, CASEarth Big Earth Data Platform, Global Earth Observation System of Systems, UN Global Pulse, and GDF, that can be used to organize and host support systems needed for the community-driven process^38,39,40,41. Alternatively, initiatives such as Invest in Open Infrastructure (IOI) argue for community-owned open infrastructure to promote research. These initiatives rely on external funding and donors to support specific projects and provide interesting opportunities to identify and organize community-driven DPG projects under international frameworks such as the UN. Despite uncertainty regarding the exact sources of funding, there are encouraging signs that institutions such as the World Bank and the UN are leading new initiatives to attract public and private funding to support development of data infrastructure and resources that can also support the proposed community-driven approach toward DPGs for SDGs.

Data and model standardization challenges

SDG indicators are quantitative assessments of economic, environmental, and social progress. Developing any DPG related to SDG indicators therefore requires access to relevant datasets, as introduced by Core Principle 4. One issue is that several SDG indicators still lack sufficient data. Additionally, the adoption of a community-supported framework for open science might prevent different statistical agencies from openly sharing data due to national legal restrictions on security, privacy, and commercial laws. For software and model development, this data sharing challenge may be mitigated by developing a set of standardized datasets that are publicly accessible, with the aim of testing and evaluating the performance of new methods, which is a common practice within the data science community. The best performing models and methods using standard metrics and standardized datasets can then be used by NSOs, according to their digital environments, to verify performance for relevant scales. This solution would help achieve Core Principle 2 (see L3 in Fig. 1). Alternatively, encouraging the use of publicly available resources, notably remote sensing data, might help mitigate data access issues and support the development of globally usable multi-scale products.

Several experts highlighted the importance of data and model standardization and the interoperability therein. This is because, traditionally, diverse formats and systems have been used for data collection by a plethora of organizations in multiple countries due to their differences in purpose and utilized instruments. Furthermore, heterogeneity also exists between and among the public and the private sectors. As a result, the data and model frameworks governing the collection and analysis of data related to SDG indicators are characterized by heterogeneous and changing capabilities. All this diversity complicates the standardization and interoperability processes among different regions, especially for community-driven development, as discussed in this study.

Open science and the collaborative development process highlighted in this paper would benefit from the initiation of a UN program to develop a database that collects data samples while preserving the formats and structure of relevant datasets of different countries and systems on SDG indicators. This action could strengthen the work of the developer community and enable the data science community to understand the structure and formats of a wide range of datasets. Furthermore, this would serve to develop programs and processes to create standard datasets, to fill in some data gaps using alternative sources, and to devise interoperability and standardization solutions, while also supporting the objectives of Key Action 5.4.

Capacity, politics, and acceptability challenges

Several experts underlined the need for capacity building in all countries, and in particular developing countries, starting with landlocked and small island states. The survey results suggest that some regional and societal constraints and technical differences may reduce the ability to develop and adopt DPGs for SDG indicators. The open science approach, integrated with programs for the development of human resources and supported by international organizations and the UN, can contribute to rapidly improving the technological capacity of competent organizations in different countries. This, however, needs to be organized in parallel with digital infrastructure and accessibility development programs, which are considered under the Secretary-General’s Roadmap for Digital Cooperation. More generally, all DPGs approved at L2 (Fig. 1) should be supported by a user-oriented training program for educational and skill development in line with Core Principle 6.

Another major challenge the experts highlighted was the legislative and political obstacles that must be overcome to improve cooperation between countries. This action needs to be addressed by different stakeholders. The Multi-Stakeholder Forum on Science, Technology and Innovation for the SDGs (STI Forum), convened by the United Nations Economic and Social Council (ECOSOC), is an important platform to support this process and to improve accessibility to technology for developing nations to build their capacity toward digital development. Political, social, and governance challenges were also highlighted as part of the grand challenge of building institutional trust around the development of open-source projects. Efforts at the policy level (Fig. 1, L4) can help streamline this process. Additionally, through community-supported open-source projects, it will be possible to recognize and adopt a variety of implementation choices. Pilot studies and demonstration cases by NSOs, based on the proposed solutions, can help inform decision-makers of a scientific consensus using the best implementation methods (Key Action 5.3).

Way forward

Rapid global progress in science and technology has been the primary driver for unprecedented development, innovation, and progress in human society. These innovations have demonstrated advantages in a variety of societal, economic, cultural, and environmental aspects. In particular, digital technologies and their applications have heavily impacted all levels of socio-economic classes around the world in the past few years.

As such, the experts in the conducted survey agree that DPGs have enormous potential to facilitate global sustainable development. Experts highlighted how big data, artificial intelligence, geospatial data, and the latest digital technology tools are crucial for a wide range of applications related to monitoring and managing natural and human systems. Based on the analyzed responses and suggestions, this report proposes six fundamental principles and several related key actions necessary for the systematic development of DPGs for the generation and maintenance of the SDG indicators.

These core principles are provisional but provide a good starting point for initiating a comprehensive dialogue highlighting DPGs for the SDGs as a concept. Future actions include refinement of the core principles and the development of a consensus to facilitate the key actions introduced. The Summit of the Future and the Digital Compact provide opportunities to discuss these concepts and gather global support for the actions suggested in this manuscript to achieve the 2030 Agenda for Sustainable Development. The propagation and implementation of these principles require a global platform and support from intergovernmental mechanisms.

The best chance to create a reasonable and standardized framework for developing DPGs lies in cooperation between multiple stakeholders and the UN. Actions for the further discussion of possible processes and standards, the collection of existing problems and promising solutions, and the collection of further suggestions and comments from the international community can contribute to this cooperation. It is also necessary to coordinate activities between multinational initiatives focusing on the broad theme of DPGs for the SDGs on the one hand and open science challenges on the other. Once the discussion is finalized and a viable system has been produced, the last hurdle will be political commitment to implement the strategy; this will be essential to harness the full potential that DPGs offer in achieving the SDGs.

The presented analysis offers a preliminary process inspired by expert comments and based on the core principles inferred from the survey responses for an open-source development environment required to build a system of DPGs for SDG indicators. The process aims to inspire innovation by engaging a community of talent that can contribute expertise to the creation of a grassroots movement working toward global sustainability. The process would incorporate the necessary QA/QC measures and policy oversight to ensure multi-stakeholder engagement at national and international levels. The community-driven open-science process proposed is a step toward organizing international efforts to direct research on a larger scale and could be highly valuable as we move forward into the second half of the 2030 Agenda for Sustainable Development. There is great potential in the proposed approach to ensure that digital resources relevant to monitoring SDGs are regularly updated to incorporate rapid developments in science and technology, ensuring that their benefits remain accessible around the world to support information, science-driven policy, and decision support systems.