Global Ocean Accounts Partnership Secretariat · GOAP Technical Guidance on Ocean Accounting · circular
TG-4.3 sits within Section 4 (Data Methods). It owns the administrative source: custodian identification and legal access basis, extraction, deduplication across agencies, cleaning, classification mapping, coverage assessment, and the quality statement that accompanies each variable delivered — catch, licence receipts, customs quantities and values, and vessel register attributes. It does not own the accounts those variables populate. Placing them in the supply and use table, and choosing the price basis for a monetary cell, is TG-3.3 Economic Activity Relevant to the Ocean; fleet capital stock and resource rent are TG-3.1 Asset Accounts Sections 3.3 and 3.6.
This Circular provides guidance on the use of administrative data sources for the compilation of Ocean Accounts. Administrative data (records collected by government agencies and other organisations in the course of their regular operations) are a cost-effective and often wide-ranging source of information for ocean accounting, particularly for maritime activities subject to regulatory oversight. Such data sources include permits and licences for fishing and aquaculture, customs and trade records, vessel registration systems, and vessel tracking data from Automatic Identification Systems (AIS) and Vessel Monitoring Systems (VMS).
Administrative data offer several advantages for ocean accounting programmes: they reduce respondent burden compared to purpose-designed surveys, provide near-complete population coverage for regulated activities, and support temporal and spatial granularity that would be prohibitively expensive to collect through primary data collection. Whilst these advantages are substantial, administrative data also present challenges of coverage, concepts, and quality that must be addressed through systematic quality assurance procedures.
Administrative data and purpose-designed surveys are complementary approaches, not substitutes. Administrative sources perform best where regulatory frameworks produce consistent records (licensed commercial fishing, international trade, and vessel movements). Surveys remain necessary where administrative coverage is incomplete: subsistence and recreational fisheries, informal-sector maritime activities, and emerging ocean economy sectors not yet subject to licensing requirements. A well-designed ocean accounting programme identifies which activities are best captured through administrative sources and where targeted surveys are needed to fill gaps, using the accounting framework itself to detect coverage deficiencies through supply-use confrontation. The methodology for designing such complementary surveys is addressed in TG-4.2 Survey Methods.
Readers of this Circular will gain an understanding of the main types of administrative data relevant to ocean accounting, the institutional arrangements necessary to access such data, methods for integrating administrative records with statistical frameworks, quality assurance procedures to ensure fitness for purpose, and practical workflows for transforming regulatory records into accounting entries. The guidance serves national statistical offices, fisheries management agencies, maritime authorities, and customs administrations seeking to contribute to or compile Ocean Accounts. The foundational concepts of Ocean Accounts are established in TG-0.1 General Introduction to Ocean Accounts, and the governance structures required for multi-agency data collaboration are set out in TG-0.7 Institutional Arrangements.
This Circular requires familiarity with:
TG-0.1 General Introduction to Ocean Accounts — provides foundational understanding of Ocean Accounts components and the relationship between environmental and economic accounting frameworks, including the conceptual distinctions between physical and monetary accounts that administrative data must support.
TG-0.7 Institutional Arrangements — establishes the governance structures, data sharing agreements, and inter-agency coordination mechanisms that are prerequisites for accessing administrative data held by regulatory authorities.
Related Circulars:
Permit and licence data provide basic information on the population of economic units authorised to undertake ocean-related activities. Such administrative systems are maintained by government agencies responsible for regulating access to marine resources and maritime space. The data captured through these systems support the compilation of economic accounts by identifying the universe of producers, and enable physical flow accounts by providing authorised extraction or emission levels.
In practice, the terms “permit” and “licence” are used with varying specificity across jurisdictions. Some countries use “licence” for the general authorisation to engage in an activity (such as commercial fishing) and “permit” for specific conditions attached to that authorisation (such as access to a particular zone or species). Other jurisdictions use the terms interchangeably. For ocean accounting purposes, both instruments serve the same function: they generate administrative records that identify economic units, authorised activities, and regulatory conditions. Compilers should document the national terminology and map permit and licence categories to the relevant accounting classifications, so that the scope of administrative data is clearly understood regardless of local naming conventions. This mapping matters in the Pacific Islands context, where regional organisations such as the Pacific Community (SPC) and the Forum Fisheries Agency (FFA) coordinate data across jurisdictions with differing regulatory terminology.
An administrative data custodian is the agency with statutory authority to issue, amend, or revoke the regulatory instrument in question. Most ocean-related activities are subject to oversight by more than one custodian, and compilers must establish a clear record-authority hierarchy before integrating data across registers.
Record authority hierarchy by data type:
For multi-agency situations (for example, aquaculture operations holding a production license from the fisheries ministry, a discharge permit from the environment ministry, and a site lease from the coastal zone management authority), the issuing agency for the primary licensed activity takes precedence for record authority, and secondary agencies supply supplementary fields (discharge limits, site coordinates) into the integrated record.
Deduplication decision tree: records describing the same operator across multiple registers are linked using a shared operator identifier (the tax registration number or national business identifier as the primary link key). Where the same activity appears in more than one register, the most recently updated record from the primary custodian takes precedence, with secondary-custodian fields appended where they extend rather than contradict the primary record. The formal multi-agency data-sharing agreement template is set out in TG-0.7 Institutional Arrangements.
National fisheries authorities typically maintain registers of fishing vessels and operators authorised to harvest aquatic resources within territorial waters and the exclusive economic zone (EEZ). Under the United Nations Convention on the Law of the Sea (UNCLOS), coastal States have sovereign rights to manage living resources within their EEZ, which extends up to 200 nautical miles from baselines. This jurisdictional framework underpins the licensing systems that regulate access to fisheries.
The treatment of fish and aquatic resources within the SEEA framework is detailed in TG-6.7 Fisheries Accounting, which explains how licence data feed into asset accounts for natural aquatic resources. The distinction between capture fisheries (ISIC group 031) and aquaculture (ISIC group 032) is fundamental to both regulatory frameworks and accounting treatment.
Key data elements captured in fishing license systems typically include:
Live-weight conversion of quota data. Quota volumes must be converted to live-weight equivalent using the source hierarchy described in Section 3.2.1. For Pacific tuna quotas issued under FFA Vessel Day Scheme (VDS) arrangements (recorded as fishing days rather than tonnage), apply the FFA-published species-specific catch-per-vessel-day coefficients (updated annually by FFA/SPC) to convert vessel-day quotas to live-weight equivalent tonnes.
For countries with quota-based fisheries management, license data include allocated catch limits that can be compared against reported landings to assess compliance and sustainable yield. Where individual transferable quotas (ITQs) exist, records of quota trades provide additional information on the economic value of access rights. This valuation information is relevant to the compilation of monetary asset accounts as discussed in TG-3.1 Asset Accounts.
A common challenge in using licence databases for accounting purposes is the presence of inactive records (vessels that remain on the register but are no longer operational). Licence registers may include vessels that have been decommissioned, sold outside the jurisdiction, or have simply ceased fishing activity without formally surrendering their licence. For accounting purposes, compilers should distinguish between the ‘registered’ fleet (all current licence holders) and the ‘active’ fleet (vessels that reported activity during the accounting period). That distinction can be established by cross-referencing licence registers with landing declarations, vessel tracking data, or annual renewal records.
Materiality threshold for inactive vessels. An inactive-vessel share exceeding 10% of the registered fleet triggers a register audit conducted jointly with the fisheries management agency, with results documented in the source register maintained under Section 3.7. Inactive vessels are retained in capital stock accounts as idle capacity, flagged with an “inactive” status attribute in the vessel register extract, consistent with SNA 2025 para. 20.14 on the treatment of idle fixed assets. They are not excluded from the fleet capital stock but are reported separately in a memorandum row to enable over-capacity assessment. See TG-3.1 Asset Accounts for the capital stock recording conventions.
Decision use cases for fishing license data:
Stock assessment calibration — Licence records establish the upper bound of fishing capacity. Fisheries scientists use that bound to calibrate effort estimates and to detect unreported fishing where observed catches exceed licensed capacity.
Economic activity measurement — Licence fee revenues and vessel characteristics feed directly into supply-use tables for the fishing industry, supporting measurement of government revenue from natural resource access and the capital stock of fishing enterprises.
Spatial attribution — Authorised fishing areas in licence records enable attribution of catches to specific marine zones for spatially disaggregated asset accounts. Such attribution matters for countries with large EEZs where different zones support different fisheries.
Aquaculture operations (the farming of aquatic organisms including fish, molluscs, crustaceans and aquatic plants) are typically subject to environmental permits that authorise the location, scale, and species cultivated. These permits capture information essential for compiling asset accounts for cultivated biological resources.
Administrative records for aquaculture commonly include:
Aquaculture licensing data support both physical and monetary accounts. Production capacity figures provide the basis for estimating potential output, whilst environmental discharge limits enable recording of flows from economy to environment, including nutrient loads and organic wastes. The methodology for recording such flows is addressed in TG-3.4 Flows from Economy to Environment.
Integrated multi-trophic aquaculture (IMTA) systems present a specific accounting consideration. In IMTA operations, waste outputs from one cultured species (for example, nutrient-rich effluent from finfish cages) serve as inputs for another species (such as seaweed or filter-feeding shellfish). The net discharge to the marine environment is reduced by the amount absorbed by the co-cultured species, and permits for IMTA operations may specify both gross discharge limits and expected uptake by extractive species.
Recording IMTA flows — net entry with mandatory gross memorandum. The net recording approach for IMTA internal nutrient transfers is a practical approximation permissible where permit data explicitly cover internal recycling flows. Whilst that approximation is accepted, SEEA CF physical flow accounts are gross by design to preserve the supply-use identity, and gross flows must therefore also be recorded as a memorandum item alongside the net entry. The following two-row recording convention applies:
IMTA recording is flagged as a known area where national practice may deviate from the SEEA CF gross-recording standard, and the deviation must be documented in account metadata. See TG-3.4 Flows from Economy to Environment for the authoritative SEEA CF residual flow recording convention.
Decision use cases for aquaculture license data:
Nutrient loading estimates — Permit discharge limits combined with production data enable estimation of nutrient contributions to coastal eutrophication. Those estimates populate water quality accounts and SDG indicator 14.1.1 on coastal eutrophication.
Production monitoring — Licensed production capacity provides a benchmark against which reported output can be assessed. Systematic under-reporting indicates either data quality issues or informal sector activity requiring supplementary surveys.
Coastal zone planning — Spatial distribution of aquaculture licenses informs marine spatial planning by identifying areas of intensive use and potential conflicts with other activities.
Maritime jurisdictions regulate offshore activities beyond fishing. Table 3.1.3 below summarises the main permit categories and their accounting relevance.
Deep-sea mineral permits — two-category treatment. Deep-sea mining of polymetallic nodules, seafloor massive sulphides, and cobalt-rich crusts is an emerging category requiring a clear accounting-boundary rule:
Decision use cases for offshore permits:
Residual flow accounting — Dumping permits specify authorised disposal volumes, and those volumes give a direct measurement of waste flows to the marine environment that populate residual flow accounts under SEEA CF.
Capital formation — Offshore energy permits track investment in marine renewable energy infrastructure. That investment feeds capital formation accounts for the ocean economy.
Environmental pressure indicators — Aggregation of permit data across offshore activities enables compilation of spatial pressure maps showing cumulative impacts on marine ecosystems.
Customs administrations generate detailed data on international trade in goods, including seafood products, maritime equipment, and other ocean-related commodities. These data are essential for compiling supply and use tables, physical flow accounts for traded products, and balance of payments statistics.
Customs records for fish and fishery products provide detailed information on:
The SEEA AFF recommends that physical flow accounts for fish products record imports and exports in live weight equivalent to ensure consistency with domestic production statistics. Conversion factors must be applied to transform processed product weights (fillets, frozen, canned) to the comparable live weight measure.
Live-weight conversion factor source hierarchy. The choice of conversion factor materially affects total live-weight equivalent trade volumes and the supply-use balance, particularly for seafood-exporting countries. Compilers should apply the following three-step adaptation protocol:
Worked example. A national customs system records 1,000 tonnes (net product weight) of canned skipjack tuna exports. Applying the FAO factor of 1.9 for canned tuna (drained-weight basis), the live-weight equivalent for the physical export account is 1,000 × 1.9 = 1,900 tonnes.
This conversion workflow is consistent with the parallel live-weight conversion of quota data described in Section 3.1.1. Both pathways must apply the same factor source for a given species and processing form to preserve supply-use consistency.
For island nations and coastal States where fisheries are economically significant, customs data serve multiple accounting purposes:
Supply-use balancing — Exports and imports provide the external trade components necessary to balance domestic production against consumption and intermediate use. The integration of trade data with production data is discussed in TG-6.7 Fisheries Accounting.
Trade in fish caught by foreign vessels — When foreign-flagged vessels harvest fish in a country’s EEZ under access agreements, the transhipment or landing of catches may be recorded in customs statistics, supporting the distinction between catches from national waters and catches by national fishing vessels. This distinction matters for Pacific Island Countries where distant-water fishing nations operate under access agreements.
For Pacific Island Countries, reconciliation between national customs records and regional databases maintained by the Forum Fisheries Agency (FFA) requires systematic attention. FFA compiles catch and effort data reported under regional fisheries management arrangements, which may differ from national customs records through differences in timing (landing date versus export date), valuation (access fees versus market price), and coverage (transhipments at sea versus port landings). Compilers should establish regular data confrontation between customs and FFA sources, and should document the reconciliation procedures and any systematic differences. The FFA’s Regional Fisheries Surveillance Centre also maintains vessel day scheme data that can cross-validate customs records for purse seine fisheries. Institutional arrangements for accessing FFA data are facilitated through national fisheries agencies and should be formalised under the frameworks described in TG-0.7 Institutional Arrangements.
Illegal, unreported and unregulated (IUU) fishing indicators — Comparison of import volumes with reported exports from origin countries can reveal discrepancies indicative of unreported catches or trade in IUU-sourced products. SDG indicator 14.6.1 tracks progress in combating IUU fishing, which can be supported by trade data analysis.
Decision use cases for customs trade data:
Supply-use balancing — Customs data provide the import and export components of seafood supply-use tables. Discrepancies that emerge in balancing may indicate unreported production or consumption.
IUU fishing detection — Trade flow analysis comparing bilateral import-export data identifies anomalies consistent with illegal fishing, which supports SDG 14.6.1 monitoring.
Value chain analysis — Product-level trade data reveal the structure of seafood value chains, including which species are exported fresh and which are processed domestically. That structure informs industrial development policy.
Customs data also capture trade in goods used as inputs to ocean industries:
These data support the compilation of intermediate consumption and capital formation components of ocean economy supply-use accounts.
Port authorities and customs administrations generate data on vessel movements and cargo throughput that are central to measuring maritime transport activity:
These data feed into both national accounts (transport sector output) and physical flow accounts (material throughput through maritime logistics). Detailed guidance on compiling maritime transport accounts is provided in TG-6.10 Maritime Transport and Ports.
Vessel tracking systems provide spatially explicit data on maritime activity that improve the attribution of economic activity and environmental pressures to specific marine locations. Two primary systems are relevant. All inter-agency data sharing agreements required by this section should be established under the framework in TG-0.7 Institutional Arrangements.
The Automatic Identification System is an automatic tracking system mandated by the International Maritime Organization (IMO) for vessels engaged in international voyages and for all passenger vessels, cargo vessels of 300 gross tonnage and above, and fishing vessels above certain size thresholds (varying by jurisdiction). AIS transponders broadcast vessel identity, position, course, and speed at regular intervals.
Key data elements from AIS include:
AIS data are now widely available through satellite reception and coastal base stations, and they enable:
Fishing effort estimation — Analysis of vessel tracks can identify fishing behaviour from speed and movement patterns, which yields estimates of fishing effort by area that complement or substitute for vessel logbook data. This spatial effort data supports the compilation of catch accounts by marine zone.
Spatial attribution — Catches can be attributed to specific marine zones (territorial sea, EEZ zones, high seas) based on vessel positions during fishing activity, supporting spatially explicit asset accounts. This aligns with the spatial framework described in TG-2.2 Macro-economic Dependencies on Ocean Ecosystems.
Fleet characterisation — Analysis of active vessel populations, activity levels, and spatial patterns provides information on the structure of fishing industries beyond what license registers capture.
Environmental pressure mapping — Combining vessel activity data with emission factors enables spatial mapping of pressures from shipping emissions, underwater noise, and collision risk with marine mammals. These pressure indicators feed into TG-3.4 Flows from Economy to Environment.
A material limitation of AIS data is gaps caused by vessels that disable their transponders (so-called ‘dark’ vessels) or operate in areas with limited satellite or terrestrial receiver coverage. AIS gaps may be intentional (vessels seeking to conceal unauthorised fishing activity) or unintentional (equipment failure, signal interference, or gaps in satellite coverage in remote ocean areas).
Tiered AIS gap decision framework. Compilers should apply the following tiered method, choosing the tier based on the duration and pattern of the observed gap:
Materiality threshold. Where gap-adjusted fishing effort exceeds 3% of unadjusted total effort, a mandatory quality note must accompany the published account.
Worked example. A purse-seiner experiences a 5-day AIS gap in a zone with documented 70% expected satellite coverage. Tier (b) statistical estimation yields:
where “AIS-observed vessel-days” is the count of days with valid AIS position fixes received within the reference zone during the gap-adjusted period.
A ±15% uncertainty range is documented in metadata to reflect typical variance in satellite-AIS coverage models.
Independent validation of vessel presence in areas with suspected AIS gaps can be obtained from remote sensing data. See TG-4.1 Remote Sensing and Geospatial Data for earth observation methods supporting AIS validation.
Vessel Monitoring Systems are fisheries-specific tracking systems required by many fisheries management authorities for licensed fishing vessels. Unlike AIS, VMS data are typically transmitted only to fisheries management agencies and are not publicly available. VMS systems often require more frequent position reporting than AIS (commonly every 1-2 hours, or more frequently during fishing activity).
VMS data provide fisheries managers with:
For ocean accounting purposes, VMS data (where accessible under data sharing arrangements) provide higher-quality information on fishing vessel activity than AIS, particularly for smaller vessels not subject to AIS carriage requirements.
VMS access fallback hierarchy. In many jurisdictions VMS data are classified as law-enforcement sensitive and fisheries agencies are legally constrained in sharing them with statistical offices. Compilers should pursue the following access hierarchy:
Model confidentiality clause for VMS data sharing agreements. The following clause is recommended for insertion into inter-agency agreements:
VMS data transferred to the [national statistical office] shall be: used exclusively for statistical compilation purposes; stored in a secure, access-controlled environment; not disclosed at the individual vessel level in any published account output; and subject to the same statistical confidentiality provisions as individual tax records.
The value of vessel tracking data for ocean accounting is maximised when integrated with other administrative and statistical sources:
Such integration requires unique vessel identifiers (IMO number, national registration number, MMSI) that are consistently applied across data sources. The development of a unified vessel identifier system is recommended as part of the institutional arrangements for ocean accounting.
Small vessel identification (sub-IMO fleet). The IMO ship identification number scheme covers vessels of 100 gross tonnage and above in international service, and the voluntary IMO fishing vessel numbering scheme covers vessels above certain thresholds. The bulk of artisanal and small-scale fishing vessels (typically under 12 m length overall or under 100 GT) fall outside both schemes. For these vessels:
· Figure 4.3.1
Source TG-4.3, Sections 3.3.3 (linkage keys), 3.4 (compilation workflow), 3.5 (worked example, Steps 5--6), 3.6.3 (data confrontation); UN GSBPM v5.1 Phases 4--5 (Process and Analyse); OECD Quality Framework for Statistical Activities (data integration principles).
Figure 4.3.1 traces the full integration pathway. Each of the six administrative sources carries a different linkage key. AIS broadcasts an MMSI, vessel registers record the IMO or national registration number, and customs and business registers are keyed to the operator’s tax or business identifier rather than to the vessel itself (Section 3.1.0), so a common-identifier match is required before records can be combined. The matched records resolve into a single integrated vessel-linked record, which is then cleaned, classified, and integrated through the compilation workflow set out in Section 3.4.
That enriched record carries catch, capacity, ownership, and price fields alongside the identifiers used to build it, and it yields the four variable sets set out in the worked example in Section 3.5: catch by species and zone (Step 5), ex-vessel prices and licence fee receipts (Steps 6(a)—(b)), vessel register attributes (Step 6(c)), and trade quantities and values, the last of these when combined with customs export data (Section 3.2). Each is delivered to the account that uses it rather than tabulated here. The dashed return flow denotes the data confrontation step (Section 3.6.3), in which source records such as landing declarations are reconciled against the integrated outputs. The broader set of account components that administrative data support beyond this vessel-identifier pathway is mapped in Section 3.7.
Decision use cases for vessel tracking data:
Effort-based catch estimation — For data-poor stocks lacking complete landing records, AIS/VMS-derived fishing effort by zone can be combined with catch-per-unit-effort estimates to produce spatially disaggregated catch estimates.
MPA compliance monitoring — Vessel tracking data enable detection of incursions into marine protected areas. These incursion records feed ecosystem condition accounts that quantify fishing pressure in protected zones.
Emissions attribution — Combining vessel tracks with engine characteristics and speed-dependent emission factors enables spatial attribution of shipping emissions to coastal zones and high-traffic areas.
Transforming administrative records from their source format into account-ready data requires systematic procedures. This section presents a general compilation workflow applicable across different administrative sources.
Before initiating compilation, compilers should assess:
Data availability — Which administrative systems exist, which agencies hold the data, and under what legal authority can the data be accessed. A systematic inventory of administrative sources relevant to ocean accounting should be prepared as part of the institutional arrangements described in TG-0.7 Institutional Arrangements.
Data scope and coverage — What population of economic units or activities is covered by the administrative system, and what known gaps exist. For example, a fishing license register covers commercial fishing but typically excludes subsistence fishing and recreational fishing.
Update frequency and timeliness — How often are administrative records updated, and what lag exists between the reference period and data availability. Port statistics may be available monthly with a 2-month lag, whilst annual fishing license renewals provide data only once per year.
Data format and structure — Whether data are available in machine-readable formats (databases, spreadsheets) or only as paper records or PDFs requiring manual extraction.
The framework for formal data sharing agreements is set out in TG-4.7 National Data Coordination Architectures Section 3.2, covering scope, frequency, quality standards, confidentiality regimes (statistical confidentiality, commercial sensitivity, and personal data protection), exchange formats, and dispute resolution. That guidance applies directly to agreements with fisheries departments, customs administrations, and port authorities.
Once data sharing arrangements are established, extraction procedures should be documented: database queries or API calls used to extract records, file naming and versioning conventions, storage locations and backup procedures, and any manual interventions required.
General data cleaning and validation procedures follow the classify-map-validate-integrate workflow in TG-4.6 Data Harmonisation and Interoperability Section 3.5 (Phase 3: Validate), covering missing values, inconsistent formats, duplicate records, out-of-scope records, and implausible values. The documentation requirements for quality assurance procedures (automated rules, manual review protocols, imputation decisions, and adjustments) are set out in TG-0.7 Quality Assurance Principles.
Critical fields and imputation rules — administrative data. For ocean accounting, “critical fields” are defined as: vessel identifier, catch volume (tonnes), catch species (FAO ASFIS alpha-3 code), fishing zone code, and reporting period (year or quarter). Imputation is acceptable for critical fields only where record-level missingness does not exceed 5% of records within a species-zone-period cell. Above this threshold the data source is rated as not fit for direct compilation, and supplementary estimation methods (e.g., sample survey expansion) must be applied instead. The default imputation method is nearest-neighbour hot-deck imputation, with donor pools defined by matching on vessel class, season, and fishing zone, the three variables most predictive of catch composition. All imputed values in account output tables must carry an OBS_STATUS attribute of “E” (estimated), consistent with the SDMX OBS_STATUS codelist and the conventions of TG-4.6.
The concordance development process (structural comparison, conceptual alignment, mapping relationships, documentation, and validation) and the management of temporal concordances across ISIC and CPC revisions are covered in TG-4.6 Data Harmonisation and Interoperability Section 3.4. The following example illustrates the application of that concordance process to fisheries administrative categories.
Example: Fishing license type to ISIC mapping
Once administrative data are cleaned and classified, they are prepared for delivery to the compiling circular. Preparation procedures include:
Business register matching — Linking licence holders or permit applicants to business register entries using business identifiers (tax numbers, registration numbers). Matching on a shared business identifier enables consistent industry classification and aggregation with other business statistics.
Temporal alignment — Aligning administrative reference periods (license validity periods, customs clearance dates) with accounting periods (typically calendar years).
Unit conversion — Converting administrative units (license counts, permit capacities) to accounting units (number of enterprises, production volumes, capital stock values).
Aggregation and tabulation — Aggregating individual administrative records to the reporting level the account requires (industry totals, product categories, geographic zones), so that the variable is delivered at the granularity the account table expects. Placing the aggregates into account rows, and any balancing that follows, is done in the compiling circular — TG-3.3 Economic Activity Relevant to the Ocean for ocean industry flows, TG-3.1 Asset Accounts for asset entries.
Compilation documentation requirements follow the general quality documentation framework in TG-0.7 Quality Assurance Principles and the metadata standards in TG-4.6 Data Harmonisation and Interoperability Section 3.6, covering data sources, cleaning procedures, classification mappings, assumptions, known limitations, and comparisons with previous rounds. The source register template in Section 3.7.1 below provides the administrative-data-specific documentation format for recording custodian details, legal access basis, and quality ratings for each administrative source.
This section presents a synthetic worked example illustrating how fishing license data can be integrated with catch reporting data to populate physical flow accounts for capture fisheries, and how the same administrative data are extended to populate monetary production accounts. The example demonstrates the complete workflow from administrative records to account entries.
The national fisheries authority maintains a database of commercial fishing licenses. Each license record includes vessel identification, authorised fishing areas, target species, and gear types. Vessel operators are required to submit monthly catch reports specifying species caught, volumes, and fishing locations. The national statistical office seeks to compile annual physical flow accounts for capture fisheries showing catch by species and marine zone, and to extend these into monetary supply-use entries.
A formal data sharing agreement is established between the statistical office and fisheries authority, specifying quarterly transfer of:
Data are transferred as CSV files via secure file transfer protocol.
License register extract (sample records):
Catch reports database (sample records):
Check 1: Coverage completeness
Interpretation: 12 vessels licensed but not reporting catches may be inactive or non-compliant. Flag for follow-up with fisheries authority.
Check 2: Spatial compliance
Interpretation: Small number of zone violations detected. These catches are included in accounts but flagged for enforcement follow-up.
Check 3: Temporal alignment
Interpretation: Most reports submitted on time. Late reports are included in annual accounts but noted for quality documentation.
Check 4: Plausibility
Interpretation: 7 reports flagged for manual review. After consultation with fisheries authority, 5 corrected, 2 excluded as data errors.
Species code to ISSCAAP mapping (International Standard Statistical Classification of Aquatic Animals and Plants):
Zone code to marine spatial unit mapping:
Aggregation of catch reports to annual totals:
Link to business register for industry classification:
Using Vessel_ID → Operator_Name → Business_Register_ID matching:
Variable delivered:
Catch is delivered by industry, product and spatial unit, with the coverage and quality statement from Step 7. Entering it in the physical supply and use table is done in TG-3.3 Economic Activity Relevant to the Ocean; the corresponding stock entries are in TG-3.1 Asset Accounts Section 3.4.1.
The same administrative records yield three further variables. This Circular is responsible for extracting them, documenting their coverage and stating their basis; the valuation conventions that turn them into monetary account entries are applied in the compiling circular.
(a) Ex-vessel prices. Fish market transaction records (or, where unavailable, fisheries agency price surveys) give an observed ex-vessel price per species-zone cell — for the worked example, USD 3,400 per tonne for tuna. Deliver the price with its source, reference period, and whether it is inclusive or exclusive of taxes on products, so that the account can place it on the required price basis. Valuing output is TG-3.3 Economic Activity Relevant to the Ocean, which applies the SNA basic-price convention.
(b) Licence fee receipts. Annual licence fee receipts are read directly from the fisheries agency revenue system and delivered as a government receipt series, identified by the access right they are charged for. Whether they are recorded as rent on a natural asset or as a tax on production is an accounting classification, taken in TG-3.3 for the transaction and in TG-3.1 Asset Accounts Section 3.3 where they inform resource rent.
(c) Vessel register attributes. Gross registered tonnage, vessel age and service status are extracted per vessel. Inactive vessels identified under the 10% threshold in Section 3.1.1 are flagged rather than removed, so the account can decide their treatment. Applying a depreciation profile to derive written-down capital stock is TG-3.1 Asset Accounts Section 3.6.
Coverage estimate:
Known gaps:
Data quality flags:
Comparability with previous years:
Integration with other accounts:
This physical catch account feeds into:
Integration requires unique identifiers — Vessel_ID enabled linking across the licence register, catch reports, and business register. Consistent identifiers are a prerequisite.
Coverage gaps and data confrontation — Some licensed vessels will not report. Cross-checking against licensed zones and vessel capacities identifies implausible records. Document known gaps for users.
Mappings and documentation must be maintained — Species and zone codes require translation to standard classifications, and full source documentation is essential for fitness-for-use assessment and future revision.
The generic data-quality framework (UN NQAF dimensions: assessment, documentation, uncertainty) is in TG-0.7 Quality Assurance Principles. The subsections below address quality issues specific to administrative-data reuse: coverage gaps from regulatory scope, IUU adjustment, conceptual alignment with SNA, and data confrontation against survey benchmarks.
Administrative coverage depends on regulatory scope. Under-coverage arises for subsistence and recreational fishing without licensing, small vessels exempt from AIS, and informal-sector activities outside business registers. Over-coverage from inactive licence holders is handled via the materiality threshold and register audit in Section 3.1.1. SEEA AFF requires IUU fishing to be reflected in catch statistics where feasible, often via model-based estimation.
Tiered IUU estimation approach. Compilers should apply the following tiered methodology to produce IUU adjustment estimates:
Regardless of tier, IUU estimates must be: (a) labelled as “modelled — IUU adjustment” in account tables; (b) published with explicit uncertainty intervals; (c) recorded in a separate account row from directly observed catch data, not merged into reported totals. SDG indicator 14.6.1 addresses the complementary trade-based dimension of IUU detection discussed in Section 3.2.1.
For small-scale and artisanal fisheries that are often under-represented in administrative data, complementary survey methods may be required, as discussed in TG-4.2 Survey Methods. Specific methods for estimating the contribution of the informal sector to fisheries output include:
Compilers should document the methods used to estimate informal sector contributions and the associated uncertainty, and flag the resulting estimates as modelled rather than directly observed.
Administrative concepts may not align with statistical definitions:
Timing differences — Administrative records may be dated by registration rather than occurrence (e.g., landing date versus catch date)
Valuation differences — Customs values (CIF/FOB) may differ from the transaction prices required for national accounts
Classification differences — Administrative product codes may not correspond to statistical classifications (CPC, HS)
Geographic scope — Jurisdictional boundaries for regulation may differ from accounting territories
Conceptual alignment requires documentation of differences and systematic bridging procedures that transform administrative data to statistical frameworks.
Valuation basis of customs records. Customs records report CIF values for imports and FOB values for exports, whilst SNA supply-use tables require flows valued at basic prices. Compilers should deliver customs-sourced trade variables in their recorded basis, labelled as CIF or FOB, together with the freight, insurance, margin and product-tax fields needed to convert them. Choosing and applying the price basis for the supply-use cell is a valuation decision taken in the account: see TG-3.3 Economic Activity Relevant to the Ocean, and SNA 2025 Chapter 15 paras. 15.36—15.42 with IMTS 2010 Chapter 4 for the underlying conventions. The trade margin coefficients and product-tax rates required for that conversion should be obtained from the national accounts unit responsible for the published supply-use tables rather than estimated within the source-processing step.
The general data confrontation framework, comprising internal consistency checks, cross-source reconciliation, benchmark comparison, and physical plausibility assessment, is covered in TG-4.6 Data Harmonisation and Interoperability Section 3.5 (Phase 3: Validate). For administrative data specifically, confrontation of landing declarations against customs export records and vessel-capacity range checks against catch reports are the most productive cross-source checks. These are illustrated in the worked example in Section 3.5.,
Time series analysis of administrative data should identify:
Where discontinuities exist, back-casting or adjustment procedures may be required to produce consistent time series for accounting purposes.
Access to administrative data for statistical purposes requires legal authority, data sharing agreements, secure transfer infrastructure, and confidentiality protocols. Template agreements and the full governance framework are in TG-0.7 Institutional Arrangements and TG-4.7 National Data Coordination Architectures.
Administrative data flow into multiple components of Ocean Accounts and support several analytical uses. Understanding these upward connections helps compilers prioritize data development efforts and communicate the value of administrative data integration to custodian agencies. Table 3.7.1 maps the main administrative sources to the account components they populate and the policy uses they support.
Table 3.7.1: Administrative data sources, account components, and policy uses
These connections indicate that administrative data serve several account purposes at once. For example, fishing licence data feed into both asset accounts (measuring the capital stock of the fishing fleet) and pressure accounts (measuring fishing effort by zone). Because a single source serves several account domains, investment in improving administrative data quality generates benefits across all of them.
Compilers should maintain a register of administrative sources showing which account components depend on each source, the update frequency required, and the priority for quality improvement. This register supports dialogue with custodian agencies and demonstrates the value of their data systems for national statistical programmes, whilst enabling coordinated improvements in data infrastructure.
To support comparability across countries and regional benchmarking, the source register should capture the following ten minimum fields for each administrative source:
Example completed row — national fishing license register:
The source register should be maintained under the governance framework set out in TG-0.7 Institutional Arrangements and reviewed at each annual inter-agency data-governance meeting.
Administrative data sources provide essential inputs for Ocean Accounts and offer wide coverage of regulated maritime activities at relatively low cost. These three data categories together describe the population, scope, flows, and activity patterns of ocean-related maritime activity. Effective use of these data sources requires attention to quality assurance, conceptual alignment with statistical frameworks, and institutional arrangements for data sharing. The accounting framework itself provides a mechanism for confronting data from multiple sources and identifying inconsistencies that can then be resolved through consultation with data custodians.
National statistical offices and ocean accounting agencies should develop systematic programmes to identify, access, and integrate administrative data sources, working collaboratively with regulatory authorities to improve data quality and expand coverage over time. The compilation workflow presented in Section 3.4 and the worked example in Section 3.5 provide practical guidance for transforming administrative records into account-ready data, including the physical-to-monetary extension, whilst Section 3.7 demonstrates the multiple account uses that administrative data support and provides a minimum-fields template for the source register that anchors inter-agency data governance.
Administrative data are a foundation for ocean accounting, particularly in countries where statistical capacity is limited and survey programmes are costly. By building partnerships with fisheries authorities, maritime agencies, customs administrations, and other custodians of administrative data, statistical offices can compile Ocean Accounts that support evidence-based ocean management and contribute to SDG 14 monitoring and reporting.
Authors: [To be confirmed]
Reviewers: [To be confirmed]
Cite this report
Administrative Data Sources (2026) (GOAP Technical Guidance on Ocean Accounting, TG-4.3, v0.7.1). GOAP Secretariat. https://guidance.oceanaccounts.org/circulars/section-4/4-3-administrative-data/
guidance.oceanaccounts.org/circulars/section-4/4-3-administrative-data
© 2026 Global Ocean Accounts Partnership Secretariat · CC BY-NC 4.0 · The report, its PDF and this deck are built from the same source.
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