Quality Assurance Principles

1. Outcome

This Circular establishes consistent quality assurance (QA) principles that are referenced by all other circulars in the Technical Guidance. Readers will understand the six dimensions of data quality relevant to ocean accounts, the four categories of uncertainty in ecosystem accounting, and the documentation standards required for transparent and credible accounts.

2. Requirements

This Circular requires familiarity with:

• TG-0.1 General Introduction – for the conceptual framework

3. Guidance Material

3.1 Purpose of Quality Assurance

Quality assurance in ocean accounting serves multiple purposes:

1. Credibility: Ensuring accounts meet standards expected of official statistics
2. Transparency: Enabling users to understand the basis for reported values
3. Comparability: Facilitating meaningful comparisons across time, space, and jurisdictions
4. Usability: Helping decision-makers understand the reliability of information
5. Improvement: Providing a basis for progressive enhancement of data and methods

Ocean accounts integrate data from diverse sources—environmental monitoring, economic statistics, social surveys, geospatial observations, and customary knowledge systems. Each source has different quality characteristics, and accounts compilation must address these differences systematically.

3.2 Six Dimensions of Data Quality

The SEEA EA identifies six dimensions of data quality relevant to environmental-economic accounting (para 2.86). These apply directly to ocean accounts:

3.2.1 Relevance

Definition: The degree to which the data serve to address the purposes for which they are sought by users.

Ocean accounts considerations:

• Do the accounts address the policy questions being asked?
• Are the spatial and temporal resolutions appropriate for the intended use?
• Are the ecosystem types and economic sectors adequately disaggregated?

Example: An ocean account designed to inform marine spatial planning needs fine spatial resolution, while one supporting national budget processes may require less geographic detail but more robust monetary estimates.

3.2.2 Timeliness

Definition: The length of time between the data reference period and availability of the information.

Ocean accounts considerations:

• How current are the environmental monitoring data?
• Are there lags between economic activity and its recording in accounts?
• How frequently are accounts updated?

Example: Satellite-derived ecosystem extent data may be available within months, while comprehensive economic surveys may have 1-2 year lags.

3.2.3 Accuracy

Definition: The degree to which the data correctly describe the phenomena they were designed to measure.

Ocean accounts considerations:

• What are the measurement errors in environmental monitoring?
• How reliable are sampling-based estimates of fish stocks or ecosystem condition?
• What are the error margins for economic survey data?

Example: Fish stock assessments may have wide confidence intervals; accounts should report these rather than point estimates alone.

3.2.4 Coherence

Definition: The degree to which data from different sources or compiled using different methods can be reliably combined and compared.

Ocean accounts considerations:

• Are classifications consistently applied across data sources?
• Are spatial boundaries aligned between environmental and economic data?
• Are accounting periods synchronized?

Example: Economic data by industry may not align perfectly with spatially-defined ecosystem service flows; bridging tables may be needed.

3.2.5 Interpretability

Definition: The availability of information to help users understand and properly use the data.

Ocean accounts considerations:

• Are methods and assumptions clearly documented?
• Are metadata standards applied?
• Are definitions consistent with international standards?

Example: Accounts should specify which ecosystem service classification is used (e.g., CICES, SEEA EA) and how services were measured.

3.2.6 Accessibility

Definition: The ease with which users can access and use the data.

Ocean accounts considerations:

• Are accounts published in accessible formats?
• Are underlying data available for users who need more detail?
• Are there access restrictions (e.g., for confidential business data)?

Example: Accounts may be published in summary form with detailed underlying data available on request or through data portals.

3.3 Institutional Environment

Beyond the six dimensions of data quality, the SEEA EA emphasizes the quality of the institutional environment in which data are compiled (para 2.86). This includes:

• Independence: Statistical compilation free from political interference
• Mandate: Clear legal or institutional authority for accounts production
• Resources: Adequate funding and staffing
• Coordination: Effective arrangements between data-producing agencies
• Standards: Adherence to international statistical standards and principles

3.4 Four Categories of Uncertainty

The SEEA EA identifies four categories of uncertainty particularly pertinent to ecosystem accounting (para 2.90). All apply directly to ocean accounts:

3.4.1 Physical Measurement Uncertainty

Uncertainty related to the physical measurement of ecosystem services and ecosystem assets.

Sources in ocean accounts:

• Sampling variability in fish stock surveys
• Remote sensing classification errors
• Spatial interpolation between monitoring stations
• Temporal variability between observations

Approaches to address:

• Report confidence intervals where available
• Document sampling design and coverage
• Use ensemble methods or multiple data sources
• Distinguish between measurement precision and accuracy

3.4.2 Valuation Uncertainty

Uncertainty in the valuation of ecosystem services and ecosystem assets.

Sources in ocean accounts:

• Choice of valuation method (market prices, replacement cost, stated preference)
• Benefit transfer from other contexts
• Discount rate selection for asset values
• Treatment of non-marginal changes

Approaches to address:

• Report physical accounts alongside monetary values
• Use sensitivity analysis for key assumptions
• Document valuation method selection rationale
• Present ranges rather than point estimates for contested values

3.4.3 Ecosystem Dynamics Uncertainty

Uncertainty related to the dynamics of ecosystems and changes in flows.

Sources in ocean accounts:

• Non-linear ecosystem responses to pressures
• Threshold effects and regime shifts
• Cumulative and synergistic impacts
• Climate change effects on baselines

Approaches to address:

• Use scenario analysis where trends are uncertain
• Document known ecological thresholds
• Update reference conditions as understanding improves
• Link accounts to ecosystem monitoring programs

3.4.4 Future Prices and Values Uncertainty

Uncertainty regarding future prices and values.

Sources in ocean accounts:

• Future market conditions for ocean products
• Changing social preferences for ecosystem services
• Policy changes affecting resource access or use
• Technological change affecting substitution possibilities

Approaches to address:

• Use current prices for flow accounts
• Apply sensitivity analysis for asset valuations
• Document assumptions about future conditions
• Update valuations periodically

3.5 Documentation Requirements

The SEEA EA emphasizes that all accounting work should document (para 2.95):

3.5.1 Scope of Measurement

• Geographic coverage (EEZ, coastal zone, specific regions)
• Temporal coverage (accounting period, time series extent)
• Thematic coverage (ecosystem types, economic sectors, asset categories)
• What is included and excluded, with rationale

3.5.2 Definitions Applied

• Ecosystem type definitions and classification used
• Industry and product classifications
• Asset boundary definitions (e.g., treatment of aquaculture)
• Alignment with international standards (or departures with justification)

3.5.3 Methods Used

• Data sources and collection methods
• Compilation procedures and algorithms
• Valuation approaches (for monetary accounts)
• Spatial analysis methods
• Gap-filling and estimation procedures

3.5.4 Assumptions Made

• Key assumptions underlying estimates
• Sensitivity of results to assumption changes
• Known biases and their direction
• Expert judgment employed and its basis

3.6 Quality Flags for Accounts Tables

Ocean accounts tables should include quality indicators to help users understand reliability. A recommended flagging system:

3.7 Quality Improvement Strategies

Ocean accounts should be viewed as evolving systems that improve over time. Key strategies:

3.7.1 Prioritized Development

• Focus initial efforts on highest-priority policy questions
• Accept provisional estimates where data are limited
• Build comprehensive accounts progressively

3.7.2 User Feedback

• Engage data users in identifying quality priorities
• Track how accounts are used in decision-making
• Respond to user-identified gaps and issues

3.7.3 Data Source Development

• Work with data providers to improve underlying data
• Coordinate timing of surveys and monitoring
• Invest in new data collection where gaps are critical

3.7.4 Method Enhancement

• Adopt improved methods as they become available
• Participate in international methodological development
• Share innovations with other countries

3.8 Circular-Specific QA Guidance

Each circular in Sections 3 and 4 of this Technical Guidance includes a section on quality assurance specific to that topic. These sections:

• Identify common data quality issues for the topic
• Recommend specific QA procedures
• Provide worked examples of uncertainty documentation
• Reference this circular for general principles

Cross-references:

• 3.1 Asset accounts – QA for stock measurements
• 3.2 Flows from environment to economy – QA for ecosystem service flows
• 3.3 Economic activity – QA for ocean economy statistics
• 3.4 Flows from economy to environment – QA for pressure data
• 3.5 Social accounts – QA for social indicators
• 4.1 Remote sensing – QA for geospatial data
• 4.2 Survey methods – QA for survey-based data
• 4.3 Administrative data – QA for administrative sources

4. Acknowledgements

Authors: GOAP Secretariat

Reviewers: GOAP Technical Expert Panel

This circular draws on quality assurance frameworks from the SEEA EA (Chapter 2), the UN Fundamental Principles of Official Statistics, and the Generic Statistical Business Process Model (GSBPM).

5. References

1. United Nations. (2021). System of Environmental-Economic Accounting—Ecosystem Accounting, Chapter 2: Principles of ecosystem accounting. Paragraphs 2.86-2.95.

2. United Nations Economic and Social Council. (2013). Resolution 2013/21: Fundamental Principles of Official Statistics.

3. UNECE. (2019). Generic Statistical Business Process Model (GSBPM), Version 5.1.

4. SEEA. (2022). SEEA Ecosystem Accounting Glossary.