ODK Data Collection Analysis and Mapping Training Course

Duration 10 days 20 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends Monitoring and Evaluation Officers, Programme Managers and others
Fee from USD 2,200 KSh 190,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 9 Nov 2026 Course code SD-ME-073

Before you join: Participants should understand basic monitoring concepts such as indicators, disaggregation, data collection methods and data confidentiality.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Development and humanitarian programmes depend on timely, credible field data to monitor outputs, assess service quality, identify geographic gaps and support decisions. Paper forms, poorly structured mobile questionnaires and weak data-quality controls can delay reporting, create duplicate records and make it difficult to connect results with locations. Staff responsible for monitoring, assessments and field operations need a practical way to design, deploy, analyse and map mobile data collection workflows.

This course teaches participants to build and manage ODK-based data collection systems using ODK Collect, ODK Central and XLSForm. Participants design monitoring questions, configure validation rules, skips, calculations, repeat groups, media capture and GPS fields. They learn to prepare enumerator workflows, manage submissions, clean exported datasets, calculate monitoring indicators and assess data quality. The course also introduces QGIS for mapping point data, joining programme datasets to administrative boundaries, producing thematic maps and conducting basic spatial analysis.

Instruction combines short technical briefings with guided form-building, realistic humanitarian and development cases, peer review and structured analysis tasks. Cases may include household surveys, health-facility supervision, cash-assistance monitoring, water-point inspections and post-distribution monitoring. Participants progressively build a working ODK form and associated analysis and mapping outputs throughout the course. They leave with a tested mobile form, data-management procedures, a cleaned analysis dataset, indicator calculations and a map-based reporting product.

The course is suited to monitoring and evaluation practitioners, programme staff, assessment teams, GIS officers and data managers who already work with structured programme data and need to establish or improve mobile field-data systems.

What you will be able to do

  • Design an ODK data collection workflow aligned to a monitoring framework and field protocol
  • Build XLSForms with relevant question types, constraints, skips, calculations and repeat groups
  • Configure ODK Collect and ODK Central for controlled form distribution and submission management
  • Apply field-data quality controls using validation rules, enumerator checks and submission review
  • Clean and document ODK exports using a reproducible data preparation workflow
  • Calculate monitoring indicators from disaggregated mobile data using defined numerator and denominator rules
  • Produce QGIS maps from ODK GPS data, administrative boundaries and programme indicators
  • Present a complete mobile data collection, analysis and mapping package for a programme case

Benefits of attending

For you

  • Build deployable mobile forms without relying solely on external developers
  • Diagnose common questionnaire logic and field-submission errors before deployment
  • Produce evidence maps that identify geographic variation in programme results
  • Strengthen credibility when discussing data quality with programme teams and donors
  • Create reusable form and analysis assets for future assessments and monitoring rounds

For your organisation

  • Reduce transcription delays and data-entry errors associated with paper questionnaires
  • Improve field-data completeness through controlled validation, skip logic and submission review
  • Provide programme managers with faster indicator summaries and geographic evidence
  • Standardise forms, codebooks and data-cleaning procedures across projects and field teams
  • Strengthen auditability through documented data flows, user roles and quality-control records

Course modules

20 modules over 10 days

Participants can translate a monitoring requirement into a structured mobile data collection design.

  • Results frameworks linked to data collection questions and reporting decisions
  • Indicator reference sheets defining numerators, denominators, disaggregation and frequencies
  • Unit of analysis selected for households, facilities, individuals or sites
  • Sampling implications for mobile questionnaires and fieldwork scheduling decisions
  • Question wording tested against recall periods, response options and sensitivity
  • Data flow mapped from enumerator device through review, analysis and reporting

Participants can configure the main components of an ODK project and assign appropriate user access.

  • ODK Collect, ODK Central and XLSForm roles within collection workflows
  • Project workspaces created with clear naming, ownership and retention conventions
  • User roles assigned for administrators, enumerators, reviewers and analysts
  • Central project settings configured for secure form and submission management
  • Server addresses and authentication configured on Android collection devices
  • Form versions planned to protect historical submissions during questionnaire updates

Participants can create a valid XLSForm structure for a field monitoring questionnaire.

  • Survey, choices and settings worksheets structured using XLSForm conventions
  • Question names designed as stable variables for exports and analysis
  • Labels written for enumerators, respondents and multilingual questionnaire delivery
  • Choice lists coded with analysis-ready values and readable labels
  • Form metadata configured for title, identifier, version and default language
  • XLSForm syntax checked before upload using structured error messages

Participants can select suitable ODK question types and prevent common entry errors.

  • Select-one and select-multiple questions matched to indicator measurement requirements
  • Integer, decimal and date fields constrained with realistic acceptance ranges
  • Required responses applied only where nonresponse prevents valid analysis
  • Constraint messages written to explain corrections clearly to enumerators
  • Text inputs limited through string length, format and regular-expression checks
  • Appearance settings selected for radios, dropdowns, numbers and date widgets

Participants can build conditional form paths and calculated fields that reduce enumerator burden.

  • Relevant expressions control questions shown to eligible respondents only
  • Required logic adjusted for conditional paths and legitimate missing values
  • Calculate fields derive ages, totals, ratios and interview durations
  • Boolean expressions combine equality, logical operators and selected response values
  • Cascading selects filter geographic lists from province through community
  • Logic paths tested using positive, negative and boundary-case respondent scenarios

Participants can model repeated records and grouped questionnaire sections for analysis-ready exports.

  • Field-list groups organise related questions into usable mobile screens
  • Repeat groups capture household members, distributions, visits or observations
  • Repeat counts controlled through prior responses and roster-derived values
  • Parent-child relationships interpreted in repeat exports and relational datasets
  • Household identifiers designed to prevent duplicate and ambiguous records
  • Nested repeat structures avoided where simpler data models meet requirements

Participants can configure geographic, media and timestamp fields with appropriate safeguards.

  • Geopoint fields capture latitude, longitude, altitude and GPS accuracy
  • Location accuracy thresholds set according to programme mapping requirements
  • Photo, audio and signature fields assessed against consent and protection needs
  • Start, end and audit timestamps used for fieldwork monitoring
  • Device metadata reviewed for troubleshooting, supervision and duplicate detection
  • Sensitive location fields protected through minimisation and access controls

Participants can test, revise and publish ODK forms through a controlled release process.

  • Desk testing checks labels, choices, relevance, constraints and calculations
  • Android device testing identifies display, connectivity and usability problems
  • User acceptance testing records field-team feedback before production release
  • Test submissions reviewed in Central before forms reach enumerators
  • Version numbers documented with changes, dates and approval decisions
  • Published forms updated without disrupting active fieldwork or historical records

Participants can prepare enumerators and field supervisors for consistent mobile data collection.

  • Enumerator briefing covers consent, neutrality, privacy and respondent safeguarding
  • Standard operating procedures define device custody, charging and offline collection
  • Interview introductions aligned with approved consent and information statements
  • Daily field plans assign clusters, targets, supervisors and submission deadlines
  • Escalation procedures address refusals, protection concerns and technical failures
  • Pilot feedback translated into revised forms, instructions and training materials

Participants can review incoming submissions and act on data-quality issues during fieldwork.

  • Central submission tables filtered by date, enumerator, status and location
  • Completeness checks identify missing required values and unfinished submissions
  • Range and consistency checks detect implausible values and contradictory answers
  • Duplicate detection compares identifiers, timestamps, coordinates and respondent attributes
  • GPS accuracy and interview duration reviewed for supervision follow-up
  • Daily quality dashboards guide feedback to enumerators and field supervisors

Participants can manage ODK projects using documented access, retention and protection controls.

  • Project roles reviewed against least-privilege access and staff responsibilities
  • Submission editing policies defined for corrections, accountability and audit trails
  • Data retention schedules distinguish operational files from archived research records
  • Personally identifiable information classified before export, sharing or mapping
  • Consent records linked to permitted uses, disclosure limits and retention periods
  • Incident response steps document lost devices, compromised accounts and accidental disclosure

Participants can prepare clean, documented analysis datasets from ODK submissions.

  • CSV exports selected for flat analysis tables and spreadsheet workflows
  • Repeat tables joined using parent identifiers and documented relationship keys
  • Variable names, labels and value codes verified against the XLSForm
  • Missing values distinguished from skips, refusals, unknowns and not-applicable responses
  • Cleaning logs record transformations, exclusions, corrections and responsible reviewers
  • Data dictionaries document variables, formats, values, sources and derivations

Participants can calculate and interpret programme monitoring indicators from cleaned ODK data.

  • Indicator calculations apply approved numerator, denominator and eligibility definitions
  • Disaggregation tables compare sex, age, disability, location and programme group
  • Frequency distributions identify common responses, missingness and unusual patterns
  • Cross-tabulations test differences between population groups and service locations
  • Weighted and unweighted results distinguished when survey sampling requires weights
  • Analysis notes state assumptions, exclusions, limitations and interpretation boundaries

Participants can assess data quality and communicate limitations before reporting results.

  • Data Quality Assessment dimensions examine validity, reliability, precision and integrity
  • Completeness rates calculated for records, variables and reporting periods
  • Source-document verification traces reported values back to original submissions
  • Consistency checks compare current results with prior periods and related indicators
  • Outlier review distinguishes genuine programme variation from data-entry error
  • Corrective action registers assign owners, deadlines and verification evidence

Participants can prepare ODK geographic data for accurate mapping in QGIS.

  • Coordinate reference systems distinguish geographic coordinates from projected map coordinates
  • WGS 84 GPS coordinates imported from ODK exports into QGIS
  • Point layers inspected for null coordinates, swaps and improbable locations
  • Administrative boundary datasets selected at suitable geographic reporting levels
  • Attribute joins connect indicator tables with district and community boundaries
  • Geographic identifiers standardised before joining field data to reference layers

Participants can create readable maps that communicate programme results without misrepresentation.

  • Choropleth maps classify district indicators using appropriate class-break methods
  • Graduated symbols display counts, caseloads and facility-level service volumes
  • Colour schemes selected for ordered data, categories and accessibility needs
  • Map layouts include title, legend, scale bar, north arrow and sources
  • Classification methods compared using equal interval, quantile and natural breaks
  • Sensitive locations masked, aggregated or omitted before external map circulation

Participants can use basic spatial analysis to identify coverage patterns and priority areas.

  • Spatial joins summarise household observations within administrative boundaries
  • Buffer analysis estimates populations or facilities near programme service points
  • Distance measurements identify communities far from clinics, water points or markets
  • Hotspot screening compares clustered reports with expected geographic distribution
  • Coverage maps combine beneficiary data, target populations and service locations
  • Priority areas ranked using agreed vulnerability, access and coverage criteria

Participants can prepare concise reporting products that connect findings with programme decisions.

  • Results tables present indicator values, denominators, disaggregation and reporting periods
  • Map captions explain geographic units, classification methods and key limitations
  • Data stories connect findings to operational questions and recommended actions
  • Visual checks prevent misleading scales, truncated axes and unsupported comparisons
  • Reporting packs distinguish internal operational products from donor-facing outputs
  • Decision logs record actions, owners, deadlines and evidence used

Participants can plan practical integration and improvement steps for an operational ODK workflow.

  • Unique identifiers support matching across ODK, programme databases and beneficiary registers
  • Import and export schedules align data refreshes with reporting deadlines
  • API concepts explain controlled exchange between ODK Central and other systems
  • Workflow bottlenecks assessed across design, collection, review, analysis and reporting
  • Change-control procedures govern form revisions, indicator changes and data corrections
  • Implementation plans define resources, responsibilities, milestones and risk controls

Participants can build, review and present a complete ODK monitoring form, analysis dataset and decision map for a programme case.

  • Monitoring question translated into an indicator-led ODK data collection design
  • XLSForm built with validation, relevance, calculations, repeats and geopoint capture
  • Test submissions reviewed against predefined completeness and consistency checks
  • Clean analysis dataset produced with documented variables, exclusions and derivations
  • QGIS map prepared showing programme findings, geographic variation and priority areas
  • Peer review assesses usability, data protection, analysis logic and reporting clarity

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. XLSForm questionnaire template
  2. ODK deployment checklist
  3. Enumerator fieldwork protocol
  4. Data cleaning and codebook template
  5. Indicator calculation workbook
  6. QGIS monitoring map layout

Who should attend

  • Monitoring and Evaluation Officers — need reliable mobile workflows for indicator reporting and learning
  • Programme Managers — need timely field evidence for operational decisions and donor reporting
  • Assessment Officers — need structured surveys for needs assessments and post-distribution monitoring
  • Data Managers — need controlled exports, cleaning procedures and submission-quality checks
  • GIS Officers — need to connect field coordinates with programme indicators and administrative maps
  • Field Coordinators — need practical oversight of enumerators, devices and daily submissions

Skills and tools covered

XLSForm designODK Central administrationMobile data qualityIndicator analysisQGIS thematic mappingSpatial data analysis

Tools and standards

ODK Central, ODK Collect, XLSForm, QGIS

How the course runs

Training methodology

The course uses short instructor briefings followed by guided technical build sessions, case-based group work and individual application tasks. Participants construct forms in XLSForm, test them on mobile devices, review submissions in ODK Central and prepare analysis outputs from realistic programme datasets. Facilitated peer review is used to inspect question wording, logic, validation rules and map design. Simulations address enumerator error, missing coordinates, duplicate submissions and urgent reporting requests. Each participant prepares an application plan for a current or planned field-data collection assignment.

Requirements and prerequisites

Participants should understand basic monitoring concepts such as indicators, disaggregation, data collection methods and data confidentiality. They should be comfortable using spreadsheets to enter, filter and review tabular data, and should have experience working with programme, survey or assessment data. Familiarity with GPS coordinates or GIS is useful but not assumed. No prior ODK, XLSForm, programming, database administration or QGIS experience is required. Participants should bring a laptop capable of running a modern web browser and QGIS; an Android device is useful for mobile collection testing but is not mandatory.

A typical training day

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

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

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

Participants should understand basic monitoring indicators and be comfortable working with spreadsheets. Prior experience with ODK, XLSForm, QGIS, programming or database management is not required.

Participants should bring a laptop with a current web browser and permission to install or use QGIS. An Android phone or tablet is useful for testing ODK Collect, although shared devices can be used where available.

It is designed for M&E officers, assessment staff, programme managers, data managers, GIS staff and field coordinators. It is particularly relevant to teams collecting household, facility, distribution, protection, education, health or water and sanitation data.

This course focuses on the full operational chain from ODK form design through field submission, data cleaning, indicator analysis and mapping. General M&E courses usually focus more on programme theory and indicator design, while GIS courses may not address mobile survey logic or field-data quality controls.

Participants can adapt the form, protocol, codebook and map layouts developed during the course for a live programme assignment. The course also provides practical controls for reviewing submissions, correcting recurring field errors and documenting analysis decisions.

The first part of the course concentrates on monitoring design, XLSForm construction, ODK deployment and fieldwork controls. The later part focuses on data management, indicator analysis, QGIS mapping, spatial analysis and a capstone presentation; each training day runs from 08:30 to 16:30 with about 6.5 contact hours.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

Related courses in Monitoring & Evaluation