Data collection and analysis tools for food security and nutrition
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outset to avoid collection of data whose purpose and utilization is unclear. Optimizing the data cycle for FSN is a key priority to reduce costs and enhance data-informed policy responses. The time from data collection to utilization can be decreased by developing analytical plans. Digital technologies and remote sensing hold enormous promise to reduce data collection costs, as does streamlined sampling. Finally, we must be open to change in technologies and processes for data collection, analysis and dissemination. As technologies advance, long-standing data collection systems must be adapted quickly and efficiently. In this respect, it is critical to harmonize data models and ontologies. Although some initiatives are already in place to coordinate existing data collection activities and their governance, greater internal and international coordination is needed to avoid the proliferation of disconnected data initiatives, which can lead to costly duplication of efforts and contribute to sending conflicting signals. To the extent possible, initiatives should promote the use of data, including qualitative data, generated by the private sector, civil society and academia, in addition to official statistics, but these sources should never be intended to substitute national data systems. The main call should not be for more data, but, rather, for actions that will ensure that data generated are relevant, timely and useful. To support the achievement of the SDGs, the United Nations Statistics Division (UNSD) is intensifying efforts to develop indicators and integrate geospatial and statistical data. However, not all countries have the same capability to establish food-data systems capable of collecting detailed, disaggregated data over time. Therefore, for these initiatives to succeed, efforts to modernize national statistics systems must be accompanied by assistance to countries with limited capabilities. To this effect, we recommend that: • organizations in the UN System develop minimum standards that set clear criteria for optimizing the use of existing data in the area covered in their respective mandate, streamlining the processes to be followed when using data for decision-making in FSN; [ 105 6 FINAL REFLECTIONS AND RECOMMENDATIONS and prioritize all types of remote and digital data and the development of appropriate data- management plans; • governments, using such standards, review existing national data-collection systems relevant for FSN , with the aim of identifying opportunities to streamline and modernize them, and enhance their efficiency and relevance; • academic institutions throughout the world coordinate to consolidate existing FSN data and respond to the need for continued innovation in the areas of data science and survey-based research to address FSN questions; • efforts to modernize national statistics systems in order to establish comprehensive, coordinated FSN data systems and to sustain the collection of the disaggregated and detailed data needed over time, be accompanied by technical and financial assistance to countries with limited capabilities ; • UN System organizations and donors establish a Global Food Security and Nutrition Data Trust Fund , to which governments of eligible countries and other stakeholders interested in generating and benefiting from data (including, for example, communities and organizations of Indigenous People) can apply, in order to obtain the necessary financial resources to establish FSN data plans; conduct FSN assessment surveys for specific communities; and create and own data dissemination platforms; • international organizations that produce key FSN data form a joint commission to harmonize and coordinate the release of datasets , avoiding the publication of competing datasets on important FSN domains (such as food commodity balances, food prices and market prospects, food security assessments, etc.); • all these initiatives devote priority and specific attention to the transfer of ownership of the used data and methodologies to the countries involved , promoting the institutionalization of such data systems in national platforms. INCREASE AND SUSTAIN INVESTMENT IN THE COLLECTION OF ESSENTIAL DATA FOR FSN This report illustrates the multiple types of data essential to diagnosing and informing FSN actions. Data are woefully lacking in most countries for agriculture, food environments, household-level food access and dietary intake and nutrition outcomes . Often, most data exist only in the form of national-level statistics and indicators, providing few insights into subnational differences, inequalities across population groups, and other variations that may hold relevance for FSN. Increased and sustained investment in sufficiently disaggregated data collection is therefore urgently needed to fill these gaps, accompanied by clear standards to enhance the granularity of data and ensure that those most likely to be affected by inequalities are appropriately represented. Such investments must be accompanied by concurrent investment in capacity, structures and institutions to ensure effective data-related activities from prioritization through utilization. To this effect, we make a strong plea to donors and governments for increased and sustained financial investment for the collection and consolidation of essential FSN data. Likewise, and recognizing the challenges in increasing investments, we recommend that: • governments, especially those of low- and middle-income countries where FSN data gaps are particularly large, elaborate national plans to define priorities for FSN data collection and analysis and to improve and optimize existing national data systems for FSN. Countries that require support should be supported both technically and financially by international organizations and donors, and should follow international standards, while preserving country ownership; • UN system agencies, in their respective areas of competence, develop specific guidance for governments and national statistics offices to 106 ] DATA COLLECTION AND ANALYSIS TOOLS FOR FOOD SECURITY AND NUTRITION streamline data collection in order to prioritize the collection of actionable data; • donors; private entities in the information, communication and industrial technology sectors; civil society groups; and academic research institutions invest in further refinement, validation and application of resource-saving data collection approaches , such as remote sensing, natural resource scanning by drones and digital data collection tools; • tools and technology that streamline and simplify data collection (such as REDCap) be used and promoted at all levels; • international organizations and academic research institutions improve existing analytic models and develop new ones to be employed in various areas of relevance for FSN decision- making, especially model-based approaches, in order to forecast future values of FSN determinants and outcomes, ensuring that such models are transparent and flexibly implemented so that they can generate predictions under clear, alternative scenarios (avoiding the use of black-box modelling). INVEST IN HUMAN CAPITAL AND IN THE NEEDED INFRASTRUCTURES TO ENSURE THE SUSTAINABILITY OF DATA PROCESSING AND ANALYTIC CAPACITY Investments specifically aimed at developing the human capital to collect, manage and analyse quality data, but also to synthesize and translate data into actionable insights for decision-making are urgently needed. Among other capacity gaps, we must address the differential between high- and low-income countries, and between the private and public sectors, in terms of ability to exploit the enormous potential that resides in existing data, accessible through the internet via increasingly affordable technology. Adequate data literacy is needed, especially among policymakers who rely on the results of sophisticated models for data analysis to make policy or investment decisions. Promoting data literacy for the general population would also be a potent way to promote agency on the part of those whose FSN is at stake. Specific attention should be devoted to promoting sufficient minimum understanding of modern statistics and data science at all levels, for instance, by including these topics in school and academic curricula. To this effect, we recommend that: • targeted scholarship programmes be created by national governments – and adequately funded by donors – to allow young people from low-income countries, especially girls, to study science, technology, engineering and mathematics (STEM) disciplines; • governments take action to expand primary and secondary education curricula to include statistics and data science early in public education programmes ; • national statistics offices offer training opportunities to all staff, of all ages, to enhance their competences in using open- source software for data analysis, and reward demonstrated achievement; • UN System organizations and international research institutions contribute to eliminating language barriers , by expanding the set of languages in which relevant e-learning platforms are offered; • international organizations, in collaboration with academic institutions, establish criteria for the quality of e-learning materials for data science and create a framework providing objective quality assessment and ranking of existing, open-access on-line learning opportunities , to identify the best, up-to-date courses and draw attention where quality improvement is needed; • international organizations avoid crowding out local capacity , by making all efforts to work [ 107 6 FINAL REFLECTIONS AND RECOMMENDATIONS closely with young professionals from national public institutions whenever the need exists to analyse FSN data at national and subnational levels. IMPROVE DATA GOVERNANCE AT ALL LEVELS, PROMOTING INCLUSIVENESS TO RECOGNIZE AND ENHANCE AGENCY AMONG DATA USERS AND DATA GENERATORS Agency refers to the ability to identify one’s own data needs and to generate and use data to guide individual and collective decision- making in a two-way flow of data between the micro- and the macro levels. The inclusion of agency as one of the dimensions of FSN has important repercussions in the collection, analysis and use of data for FSN. It highlights, for example, how effective use of existing and new data will greatly benefit from concerted efforts to promote institutional and governance arrangements that favour data sharing at all levels and across all sectors involved in FSN, thus enhancing the agency of all those involved. We strongly subscribe to and support the call made by the 2021 World Development Report to work towards “a new social contract for data – one built on trust to produce value from data that are equitably distributed” (World Bank, 2021 p. 17). Thus, it is fundamental to enhance the role of data collection, analysis and utilization in giving voice to the people most affected by FSN policies, that is, to farmers and other food producers, to Indigenous Peoples, women, youth and vulnerable groups. A human- rights-based approach to FSN and to the realization of the right to food call for greater attention to citizens as right-holders and to their demand of accountability from the state as duty bearer in the realization of this right. Data can be an instrument of empowerment as it enables checks on the accountability of government actors and, as relevant, of the private sector. Recognizing the importance of agency for data users and generators and enhancing agency require a conducive policy environment and capacity development. Enhancing agency in data generation and access (especially through digital technologies) can help address ethical concerns linked to power imbalances in data ownership and control, and can contribute to reducing inequalities. To this effect, we recommend that: • governments, international organizations, civil society, private companies and research institutions, both public and private, comply with existing open-access principles for data and analysis tools , ensuring access to and reproducibility of relevant research results, and continually adapt to enhance data access, as open-access principles and guidance evolve; • all government data that refer to agriculture and FSN be treated as “open by default” as recently endorsed by the UN statistical commission; • governments and multilateral organizations in the UN System work to improve legal frameworks that protect sensitive data and privacy , developing accountability systems for their implementation; • FAO and other UN System organizations that have a mandate for agriculture, food and nutrition, develop a code of conduct for data generation and use, based on FAIR and CARE principles , that addresses the diversity of FSN data-governance-related issues – including power imbalances, inclusiveness, the operationalization of open access and transparency principles – for all types of actions in data generation, consolidation and utilization; and that FAO become a FAIR and CARE certifier for agriculture, food and nutrition datasets; • CFS explore the possibility of establishing one or more data trusts for food security and nutrition , where a subgroup of CFS members can act as trustees, receiving the legal right to make decisions – such as who has access to specific data and for what purposes – on behalf of the data owners; and that such a data trust 108 ] DATA COLLECTION AND ANALYSIS TOOLS FOR FOOD SECURITY AND NUTRITION may constitute the legal basis to support the sharing of data collected with funds obtained through the global FSN data trust fund; • CFS convene a workshop to assess the state of private data sharing in agriculture, food security and nutrition and consider exploring the possibility of piloting the aforementioned data trust for food security and nutrition; • appropriate collaborative data initiatives between governments, international organizations, civil society and private companies in the information and communication industry should be put in place to guarantee access to all relevant, non-personal, food security and nutrition data generated and stored by private agents; • upon justified request, personal data collected and stored by private agents be mandatorily made accessible to governmental and intergovernmental organizations for research and policy-guidance purposes , in a way that protects against misuse and violation of privacy and other individual rights; • when relevant, private and public sectors, together with all the previously mentioned actors, engage in analytical processes that incorporate the science–policy interface, through, for example, foresight analyses (e.g., Foresight4Food), DELPHI processes, or approaches that incorporate multiple analytical approaches to engage diverse stakeholders and policymakers (e.g. the INFORMAS approach for the study of food environments) . 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