Authors
High Level Panel of Experts on Food Security and Nutrition (HLPE-FSN)
Related Organizations
- Pages
- 156
- Published in
- Italy
Table of Contents
- Cover page 1
- Copyright 2
- Disclaimer 3
- HLPE Reports series 4
- Table of contents 5
- List of tables 8
- Table 1: FAIR data principles 111
- Annex Table 1: Examples of existing FSN data-related initiatives (including databases, repositories, data systems and analysis tools), organized by dimension of food security and nutrition 145
- Annex Table 2: Summary of risks, associated digital technologies, key stakeholders and risk mitigation measures 146
- Annex Table 3: List of countries grouped by date of last agricultural census on record* 150
- Annex Table 4: Care principles for indigenous data governance 153
- List of figures 8
- Figure 1: Framework for a systemic view of fsn to guide data collection and analysis 30
- Figure 2: Data-informed decision-making cycle 32
- Figure 3: How to structure a data-informed, decision-making process matrix 35
- Figure 4: Example of how to use the conceptual framework (theoretical guidance) and data-informed decision-making cycle (methodological guidance) for FSN 39
- List of boxes 9
- Box 1: FAO statistical system 42
- Box 2: The Agricultural Market Information System (AMIS) 43
- Box 3: Improving the analysis of fish data 45
- Box 4: GIEWS and other information systems 46
- Box 5: FAO's Hand-in-hand initiative 47
- Box 6: The 50 × 2030 Initiative to close the agricultural data gap 48
- Box 7: FAO's approach to mapping territorial markets 49
- Box 8: Data collection in conflict settings 51
- Box 9: FSN and the SDG monitoring frameword 53
- Box 10: Countdown to 2030 55
- Box 11: Global open data for agriculture and nutrition (GODAN) 56
- Box 12: An example of affordable, global data management platform: REDCap 58
- Box 13: The integrated food security phase classification (IPC) initiative 60
- Box 14: Exemplars in global health 61
- Box 15: The food system dashboard 62
- Box 16: The POSHAN Network 63
- Box 17: The high cost of FSN-relevant surveys 67
- Box 18: The complexity of nutrition assessments 69
- Box 19: On food safety data 69
- Box 20: The women empowerment in agriculture index 70
- Box 21: Satellite technologies for improved drought assessment (SATIDA) 70
- Box 22: Opportunities and risks in the use of automated data analysis 72
- Box 23: A critical view of FAO statistical support to Member Nations 75
- Box 24: SATIDA COLLECT 77
- Box 25: Tackling constraints in food composition data availability and quality 77
- Box 26: Definitions of new and emerging digital technologies 80
- Box 27: Examples of efforts that support data consolidation 84
- Box 28: Examples of the application of blockchain technology to FSN data 86
- Box 29: Challenges with digitalizing services and access: the case of India’s Aadhaar identification number 93
- Box 30: Personal data protection and the right to privacy 104
- Box 31: The EAF-Nansen Programme 113
- Box 32: Nepal's nutrition-sensitive livestock introduction programme 113
- Box 33: The Global agriculture and food security programme (GAFSP) 114
- Foreword 11
- Acknowledgments 13
- Abbreviations and acronyms 14
- Key messages 16
- Introduction 17
- Chapter 1. Setting the stage 24
- Defining key terms 25
- Data 25
- Analysis tools 26
- Data governance 28
- Conceptual framework 28
- Figure 1: Framework for a systemic view of fsn to guide data collection and analysis 30
- Data-informed decision-making cycle 32
- Figure 2: Data-informed decision-making cycle 32
- Using the conceptual framework and the data-informed decision-making cycle to address issues relevant for FSN 34
- Figure 3: How to structure a data-informed, decision-making process matrix 35
- Example 1: How to increase population-level fruit and vegetable (FV) consumption based on local FV supply chains? 37
- Figure 4: Example of how to use the conceptual framework (theoretical guidance) and data-informed decision-making cycle (methodological guidance) for FSN 39
- Chapter 2: A review of existing FSN data collection and analysis initiatives 40
- Illustrative overview of existing FSN data 41
- FSN data and information systems relevant at the distal (macro) level 41
- Box 1: FAO statistical system 42
- Box 2: The Agricultural Market Information System (AMIS) 43
- FSN data and information systems at the proximal (meso) level 44
- Box 3: Improving the analysis of fish data 45
- Box 4: GIEWS and other information systems 46
- Box 5: FAO's Hand-in-hand initiative 47
- Box 6: The 50 × 2030 Initiative to close the agricultural data gap 48
- FSN data and information systems at the immediate (micro) level 48
- Box 7: FAO's approach to mapping territorial markets 49
- Box 8: Data collection in conflict settings 51
- Challenges and opportunities for FSN data-informed decision making 52
- Challenges and opportunities for FSN data-informed decision making 52
- Box 9: FSN and the SDG monitoring frameword 53
- Set priorities for data 54
- Box 10: Countdown to 2030 55
- Gather, curate and disseminate date 56
- Box 11: Global open data for agriculture and nutrition (GODAN) 56
- Data analysis 56
- Poorly conceived or inappropriate measures, indicators or scales 56
- Inadequate data-collection designs 57
- Box 12: An example of affordable, global data management platform: REDCap 58
- Lack of harmonization and poor data quality 59
- Timeliness 59
- Box 13: The integrated food security phase classification (IPC) initiative 60
- Data protection 60
- Heavy reliance on quantitative data 60
- Box 14: Exemplars in global health 61
- Translate data and use for decision-making 61
- Box 15: The food system dashboard 62
- Using data for decision-making requires buyinand involvement on the part of those with theresponsibility to make decisions, and clarity onthe decisions to be made 62
- Box 16: The POSHAN Network 63
- Chapter 3. Constraints, bottlenecks (and some solutions) for effective use of FSN data 64
- Insufficient resources for data collection and analysis 65
- Financial constraints 66
- Box 17: The high cost of FSN-relevant surveys 67
- Inadequate research infrastructure 67
- Box 18: The complexity of nutrition assessments 69
- Box 19: On food safety data 69
- Box 20: The women empowerment in agriculture index 70
- Box 21: Satellite technologies for improved drought assessment (SATIDA) 70
- Human-resource constraints 70
- Constraints related to data collection 70
- Constraints related to the lack of data processing, analytical and dissemination capabilities 71
- Box 22: Opportunities and risks in the use of automated data analysis 72
- Inadequate institutional arrangement and data governance 73
- Constraints that limit stakeholder engagement 73
- Constraints related to the lack of coordination among agencies 74
- Box 23: A critical view of FAO statistical support to Member Nations 75
- Constraints that create a lack of transparency and of appropriate regulatory frameworks 76
- Box 24: SATIDA COLLECT 77
- Box 25: Tackling constraints in food composition data availability and quality 77
- Chapter 4. New and emerging digital technologies for FSN data 78
- Landscape and relevance of new and emerging digital technologies to FSN 79
- Landscape and relevance of new and emerging digital technologies to FSN 79
- Box 26: Definitions of new and emerging digital technologies 80
- Define/refine evidence priorities and questions 81
- Review, consolidate, collect and curate data 82
- Box 27: Examples of efforts that support data consolidation 84
- Box 28: Examples of the application of blockchain technology to FSN data 86
- Translate data into results, insights and conclusions 88
- Disseminate, share, review, discuss results, refine insights and conclusions* 88
- Use results, insights and conclusions to make decisions 89
- Risks associated with digital technologies for FSN and their mitigation 91
- Ethics, data protection, trust, justice and identity 91
- Box 29: Challenges with digitalizing services and access: the case of India’s Aadhaar identification number 93
- Quality of data 95
- Interoperability of data 96
- Capacity, equity, scalability and sustainability 96
- Chapter 5. Institutions and governance for FSN data collection, analysis, and use 98
- Issues of relevance for data governance 100
- The debate on the nature of data and the role of data markets 100
- The questions of data ownership and the social value of data 102
- Box 30: Personal data protection and the right to privacy 104
- Priority objectives for FSN data-governance initiatives 106
- Achieving adherence to global standards and harmonization of data 106
- Ensuring adequate mechanisms are in place to protect individual and collective rights 108
- Relevant recent initiatives on data governance for FSN 110
- World Bank open data 110
- Open science initiatives and the FAIR and CARE data principles 110
- Table 1: FAIR data principles 111
- Global strategy to improve agricultural and rural statistics 112
- Initiatives in stakeholder collaboration 112
- Box 31: The EAF-Nansen Programme 113
- Box 32: Nepal's nutrition-sensitive livestock introduction programme 113
- Box 33: The Global agriculture and food security programme (GAFSP) 114
- Greater attention to data quality issues 114
- Challenges to data governance from data-driven technologies 114
- Solutions to enhance FSN data governance 115
- Streamlining transnational and national data governance for FSN 115
- Inclusive approach to data governance 115
- Increasing transparency and governance of official statistics for FSN 115
- Partnership agreements to manage and share digital data 116
- Chapter 6. Final reflections and recommendations 117
- Create greater demand for data for decision-making among governments, policymakers and donors 119
- Optimize and, if needed, repurpose current data-related investments, while increasing collaboration between international organizations, governments, civil society, academia and the private sector, to harmonize and maximize the sharing of existing FSN data 120
- Invest in human capital and in the needed infrastructures to ensure the sustainability of data processing and analytic capacity 122
- Improve data governance at all levels, promoting inclusiveness to recognize and enhance agency among data users and data generators 123
- References 125
- Glossary 140
- Annexes 145
- Annex Table 1: Examples of existing FSN data-related initiatives (including databases, repositories, data systems and analysis tools), organized by dimension of food security and nutrition 145
- Annex Table 2: Summary of risks, associated digital technologies, key stakeholders and risk mitigation measures 146
- Annex Table 3: List of countries grouped by date of last agricultural census on record* 150
- Annex Table 4: Care principles for indigenous data governance 153
- Blurb 156