Annex

Table 1: Comparison of other theoretical frameworks. Modified from Jolliffe et al. (2023)

Area	WDI Framework (2024)	Fantom & Khokhar (2014)	Joliffe et al. (2021)	Statistics Canada (2017)	OECD (2011)	UN (2019)	Biemer (2010)
Adequate Coverage	Complete	Completeness	Complete	Coverage			Completeness
	Frequent		Frequent	Viability
	Timely	Timeliness	Timely	Timeliness & punctuality	Timeliness& punctuality	Timeliness & punctuality	Timeliness/ punctuality
High Quality	Granular	Extent of detail	Granular	Granularity
	Accurate	Accuracy	Accurate	Accuracy & reliability	Accuracy, reliability	Accuracy & reliability; Methodological soundness	Accuracy
	Comparable	Comparability	Comparable	Standardization or conformance		Comparability	Comparability
	Not Redundant
Easy to Use	Accessible	Accessibility	Accessible	Accessibility	Openness/ transparency	Accessibility	Accessibility
	Understandable	Clarity	Understandable	Processability and understandability		Clarity; Transparency	Usability/ interpretability
	Interoperable	Coherence	Interoperable	Combinability or likability	Coherence	Coherence	Coherence
Trusted & Relevant	Impartial	Plausibility	Impartial	Perception of authority, impartiality & trustworthiness	Credibility; objectivity; integrity; impartiality	Impartiality & objectivity	Credibility
	Confidentiality protected	Confidentiality	Confidential	Security. Protection of sensitive information	Confidentiality protected	Statistical confidentiality & data security
	Development Relevance	Relevance	Appropriate	Relevance & usefulness	Relevance & usefulness	Relevance	Relevance
			Other	Quality assurance; reproducibility; contact ability	Effective stakeholder engagement	Many, see table note

Note: This figure is inspired by, and takes some information from, Jolliffe et al. (2023) & Marker (2017). The UN framework has many other attributes most of which are related to managing the statistical system and hence do not relate to the framework of this paper: Coordinating the national statistical system, managing relationships, managing statistical standards, professional independence, adequacy of resources, commitment to quality, appropriate statistical procedures, managing the respondent burden, and cost-effectiveness.

Table 2: WDI Metadata Required Fields

Field	Definition
Definition	Detailed definition of the indicator.
Definition references	Links/sources for the definition.
Development Relevance	Development relevance and importance of the indicator.
Methodology	Methodology used to calculate/derive the indicator.
Statistical concept	Statistical concepts and standards applied.
Measurement unit	Unit of measurement for the indicator.
Aggregation method	Method for aggregating the indicator across geographic levels.
Sources	Data sources used to compile the indicator.
Aliases	Different names/aliases for the indicator separated by semicolons.
Alternate Identifiers	Any other identifiers used for the indicator in source databases.

Table 3: Mapping Between WDI Criteria Dimensions and World Bank Data Quality Policy Principles

Area	Dimension	Data Quality Policy Principle
Easy to Use	Accessible	Access, Dissemination, and Storage (h)
	Understandable	Transparency (d)
	Interoperable	Inter-operability (l)
Trusted & Relevant	Impartial	Impartiality and Independence (a)
	Confidentiality Protected	Responsible Data Management (b)
	Development Relevance	Relevance (e)
Adequate Coverage	Complete	Efficient Data Collection (i)
	Frequent	Efficient Data Collection (i)
	Timely	Access, Dissemination, and Storage (h)
High Quality	Accurate	Verifiability (c)
	Comparable	Coherence and Comparability (f)
	Granular	Coherence and Comparability (f)
	Not Redundant	Coherence and Comparability (f)