ISO 19157 Geographic Data Quality Assessment Training Course

Course overview

Geographic datasets are routinely accepted, merged, published and used for planning without a defensible statement of whether they are fit for purpose. Positional error, incomplete road attributes, duplicate features, invalid topology and outdated imagery-derived classifications can lead to poor routing, inaccurate asset inventories, unreliable environmental reporting and disputed supplier acceptance. This course gives GIS professionals a repeatable ISO 19157-based framework for specifying, measuring, reporting and communicating geographic data quality rather than relying on informal visual checks or generic “clean data” claims.

Participants work through the ISO 19157 quality model, including data quality scope, measures, evaluation methods, conformance quality levels and metadata reporting. They learn to define quality requirements against an intended use; select elements such as completeness, logical consistency, positional accuracy, temporal quality, thematic accuracy and usability; design sampling plans; calculate quality measures; and distinguish direct inspection, indirect evaluation and declared quality. Practical work uses QGIS and ArcGIS Pro to identify errors, inspect topology, compare datasets against authoritative reference sources and prepare structured quality results.

Instructor-led sessions combine worked calculations, standards interpretation, GIS quality-control exercises and a running case involving the acceptance of a municipal infrastructure dataset. Each participant produces an ISO 19157-aligned data quality evaluation plan, measurement register, sample inspection record and quality report for a supplied dataset or an appropriate workplace dataset. The completed pack can be adapted for supplier acceptance, data publication, migration assurance or internal GIS governance. The course is suited to professionals who need to assess data credibly and managers who need quality evidence that supports operational, regulatory or procurement decisions.

Course objectives

By the end of this course, participants will be able to:

• Define ISO 19157 data quality requirements against a stated geographic data use case
• Select applicable quality elements, sub-elements and measures for vector and raster datasets
• Construct a data quality evaluation plan with scope, reference data, methods and acceptance thresholds
• Design a statistically defensible sampling approach using population, sample size and confidence concepts
• Measure completeness, logical consistency, positional accuracy, temporal quality and thematic accuracy
• Apply QGIS and ArcGIS Pro validation tools to detect attribute, topology and spatial-reference errors
• Calculate and interpret quality results, including error rates, positional discrepancies and conformance outcomes
• Produce an ISO 19157-aligned data quality report and supplier acceptance recommendation

Benefits of attending

Target competencies

Who should attend

• GIS Analysts — who validate operational datasets before analysis, publication or system loading
• Geospatial Data Managers — who need consistent quality controls, specifications and reporting across data holdings
• Remote Sensing Analysts — who must quantify classification, positional and temporal quality in derived products
• Survey and Mapping Professionals — who need to demonstrate positional and attribute quality against client specifications
• Data Governance and Quality Leads — who establish evidence-based controls for spatial data within enterprise governance
• GIS Procurement and Contract Managers — who must define acceptance criteria and assess supplier data deliveries

Requirements and prerequisites

Participants should be comfortable opening, viewing and editing vector GIS data such as points, lines and polygons, and should understand basic attribute tables, coordinate reference systems and common file formats such as GeoPackage, shapefile or GeoJSON. Familiarity with either QGIS or ArcGIS Pro is helpful because exercises use both interfaces, but advanced geoprocessing, programming and statistics are not required. A complete beginner can attend if they first understand basic GIS concepts and are prepared for guided software practice. No prior knowledge of ISO standards, formal sampling theory or metadata schemas is assumed.

Training methodology

The programme uses short instructor-led standard interpretation sessions followed by guided GIS labs and calculation workshops. Participants inspect supplied vector, raster and tabular datasets in QGIS and ArcGIS Pro, identify quality defects, compare features with reference data and record results in an ISO 19157 evaluation template. Small groups critique quality requirements for different intended uses, including asset management and land-cover mapping. Each day adds to a running quality-assurance case, culminating in an individual application plan and a reviewed quality report on day 10.

Course outline

Day 1: ISO 19157 foundations and fitness for purpose

• Geographic data quality as evidence for fitness for purpose
• ISO 19157-1:2023 quality management principles
• ISO 19157-2:2023 evaluation procedure concepts
• Data product specifications and quality requirements
• Intended use, user needs and quality scope
• Quality assurance versus quality control in GIS workflows
• Reading quality statements in geospatial metadata

Workshop: Participants analyse a municipal asset-data scenario and draft a fitness-for-purpose statement identifying the decisions the dataset must support.

Day 2: Quality model, elements and measures

• Data quality elements and sub-elements
• Completeness commission and omission measures
• Logical consistency conceptual consistency measures
• Domain consistency and format consistency checks
• Topological consistency for vector feature relationships
• Positional, temporal and thematic quality measures
• Usability as a quality element

Workshop: Participants map operational requirements for a roads dataset to an ISO 19157 quality-element selection matrix.

Day 3: Defining quality requirements and conformance

• Writing measurable spatial data quality requirements
• Quality measure identification and measure descriptions
• Evaluation method selection criteria
• Conformance quality levels and acceptance thresholds
• Pass-fail rules and tolerance specification
• Quality scope by feature type, attribute and geographic extent
• Data quality evaluation plan structure

Workshop: Participants create an evaluation plan for a supplier-delivered utility network dataset, including quality measures and acceptance thresholds.

Day 4: Sampling and inspection design

• Full inspection versus sample-based inspection
• Population definition and sampling unit selection
• Simple random, systematic and stratified sampling
• Sample size, confidence level and margin of error
• Reference datasets and ground-truth sources
• Independent versus dependent quality evaluation
• Recording inspection decisions and defect classifications

Workshop: Participants design a stratified sample for land-parcel attributes and produce a documented sample-selection rationale.

Day 5: Completeness and logical consistency assessment

• Detecting missing and excess features
• Attribute completeness assessment methods
• QGIS Select by Expression for null and domain checks
• ArcGIS Pro Data Reviewer validation workflows
• Topology rules for gaps, overlaps and dangles
• Duplicate feature detection and geometry comparison
• Defect logging and error-rate calculation

Workshop: Participants run completeness and topology checks on a utility dataset and produce a defect log with calculated omission and commission rates.

Day 6: Positional and temporal quality assessment

• Absolute and relative positional accuracy
• Horizontal positional discrepancy measurement
• Reference-point selection and coordinate comparison
• Root mean square error and percentile reporting
• Coordinate reference system transformation risks
• Temporal validity, temporal consistency and currency
• Assessing timestamp and update-cycle evidence

Workshop: Participants compare road-centreline positions against authoritative reference features and calculate positional quality statistics.

Day 7: Thematic accuracy and remote sensing quality

• Thematic classification accuracy concepts
• Confusion matrices and reference sample labels
• Producer accuracy, user accuracy and overall accuracy
• Kappa limitations and alternative interpretation considerations
• Raster resolution and mixed-pixel effects
• Ground truth, reference imagery and validation independence
• Documenting land-cover classification quality

Workshop: Participants assess a land-cover classification using a confusion matrix and write an interpretation for a planning-data user.

Day 8: Quality results, metadata and reporting

• Data quality result types and result recording
• Quantitative results, descriptive results and conformance results
• Quality measure names, identifiers and evaluation dates
• Lineage statements and process-history evidence
• ISO 19115 metadata links to data quality information
• Communicating limitations without overstating reliability
• Quality report structure for internal and external audiences

Workshop: Participants convert inspection results into a structured data quality report section with scope, method, result and conformance statement.

Day 9: Supplier acceptance and quality improvement

• Translating ISO 19157 requirements into procurement specifications
• Data delivery acceptance-test procedures
• Nonconformance classification and remediation requests
• Corrective action tracking for spatial data defects
• Quality dashboards and recurring control metrics
• Risk-based prioritisation of data quality issues
• Roles, responsibilities and quality governance checkpoints

Workshop: Participants conduct a mock supplier acceptance review and issue a justified accept, conditional accept or reject recommendation.

Day 10: Integrated quality assessment project

• Scoping an end-to-end quality evaluation
• Selecting elements, measures and evaluation methods
• Executing GIS checks and sample inspections
• Interpreting results against acceptance thresholds
• Preparing an ISO 19157-aligned quality statement
• Presenting quality findings to decision-makers
• Workplace implementation planning

Workshop: Participants complete and present an ISO 19157-aligned evaluation pack containing their plan, evidence register, results, quality report and implementation actions.

Tools & standards covered

ISO 19157-1:2023, ISO 19157-2:2023, QGIS, ArcGIS Pro

A typical training day

08:30 – 10:30	First session
10:30 – 10:45	Refreshment break
10:45 – 12:30	Second session
12:30 – 13:30	Lunch and networking
13:30 – 15:00	Third session
15:00 – 15:15	Refreshment break
15:15 – 16:30	Workshop and daily review

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions