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CourseCivil, Rail & Smart Cities Enrolment open

Urban Data Auditing Course

300-hour online course in Urban Data Auditing. 6 modules covering ISO/IEC 25012:2008, ISO 8000-8:2015 and Great Expectations. Assigned tutor and open enrolment.

Duration300 h
ModeOnline
Start datesOctober / March
LocationEurope (Madrid)
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Understand the data ecosystem of a municipal administration.

02

Apply the data quality models of the ISO standards.

03

Plan and carry out data audits with evidence.

04

Verify compliance with data protection rules and the ENS.

05

Detect bias in data used for analytics and AI.

06

Write audit reports with classified findings.

07

Design corrective action plans and follow-up.

Profile

Who it's for

  • Data auditor looking to specialise in Urban Data Auditing.
  • Data governance manager looking to specialise in Urban Data Auditing.
  • Data quality analyst looking to specialise in Urban Data Auditing.
  • Data Protection Officer looking to specialise in Urban Data Auditing.
  • Information systems auditor looking to specialise in Urban Data Auditing.
  • Cybersecurity consultant looking to specialise in Urban Data Auditing.
  • Engineering or science graduates seeking to enter local government.
Standards & tools

What you'll work with

  • ISO/IEC 25012:2008
  • ISO 8000-8:2015
  • Regulation (EU) 2016/679 (GDPR)
  • Royal Decree 311/2022, National Security Scheme (ENS)
  • ISO/IEC 27001:2022
  • ISO 19157-1:2023
  • Regulation (EU) 2024/1689 on Artificial Intelligence
  • Organic Law 3/2018, on the Protection of Personal Data and Guarantee of Digital Rights
Syllabus

6 modules · 300 h

  1. 1.1Types of municipal data
  2. 1.2Master and reference data
  3. 1.3Sensor data and time series
  4. 1.4Urban geospatial data
  5. 1.5Personal and sensitive data
  6. 1.6Data lifecycle
  7. 1.7Owner and custodian roles
  8. 1.8Data-related risks
  9. 1.9Data governance framework
  10. 1.10Workshop: data asset inventory
  1. 2.1Quality dimensions under ISO 25012
  2. 2.2Accuracy, completeness and consistency
  3. 2.3Currency and traceability
  4. 2.4Measurement with ISO 8000
  5. 2.5Data profiling
  6. 2.6Validation rules
  7. 2.7Deduplication and normalisation
  8. 2.8Geographic data quality under ISO 19157
  9. 2.9Continuous improvement plans
  10. 2.10Lab: profiling a dataset with Python
  1. 3.1Audit planning and scope
  2. 3.2Criteria and reference frameworks
  3. 3.3Statistical sampling of records
  4. 3.4Substantive and controls testing
  5. 3.5ETL process auditing
  6. 3.6Evidence and working papers
  7. 3.7Classification of findings
  8. 3.8Audit report
  9. 3.9Follow-up of recommendations
  10. 3.10Practical: quality audit of a municipal census register
  1. 4.1Data protection auditing
  2. 4.2Record of processing activities
  3. 4.3National Security Scheme (ENS) and biennial audit
  4. 4.4Access controls and logging
  5. 4.5Encryption and pseudonymisation
  6. 4.6Data retention and erasure
  7. 4.7Data processing agreements
  8. 4.8Cloud provider auditing
  9. 4.9Data breaches and notification
  10. 4.10Case study: ENS audit of a city platform
  1. 5.1Bias in training datasets
  2. 5.2Representativeness of sensor data
  3. 5.3Dataset documentation
  4. 5.4Data requirements of the AI Regulation
  5. 5.5Data lineage and reproducibility
  6. 5.6Validation of urban predictive models
  7. 5.7Data drift and monitoring
  8. 5.8Algorithmic auditing
  9. 5.9Transparency of results
  10. 5.10Workshop: bias analysis in mobility data
  1. 6.1Selection of the system under audit
  2. 6.2Audit plan and scope
  3. 6.3Quality and compliance testing
  4. 6.4Findings log
  5. 6.5Audit report
  6. 6.6Corrective action plan
  7. 6.7Sampling and substantive testing
  8. 6.8Classification of findings by severity
  9. 6.9Dissertation and presentation
  10. 6.10Final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM Institute campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: students progress at their own pace within the intake period, which makes it possible to combine the programme with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Great Expectations, OpenRefine, Python (pandas), Talend Data Quality, QGIS, in free, academic or evaluation versions. Practical exercises are based on real procedures: data profiling and quality auditing of a municipal register, GDPR compliance auditing, and bias assessment in analytics data. Assessment is continuous across modules, plus a final integrative project.

Accredited laboratories(EN ISO/IEC 17025) with rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-led Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:lecturers with experience in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:safety-by-design approach, ciber-OT, DIH and compliance as core pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Selection of the system under audit

Understand the data ecosystem of a municipal administration.

Audit plan and scope

Apply the data quality models of the ISO standards.

Quality and compliance testing

Plan and carry out data audits with evidence.

Findings log

Verify compliance with data protection rules and the ENS.

Audit report

Detect bias in data used for analytics and AI.

Career opportunities

Where this takes you

Data auditorData governance managerData quality analystData Protection OfficerInformation systems auditorCybersecurity consultant
Admissions & scholarships

Requirements

  • No prior qualification is required.
  • Internet connection and a computer capable of running the programme's software.
  • Sufficient level of Spanish to follow technical regulatory texts.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 300 hours, spread over 3 to 5 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.

The programme uses Great Expectations, OpenRefine, Python (pandas), Talend Data Quality and QGIS. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

A SEIUM Institute own diploma upon passing the continuous assessment and the integrative project. This is in-house training, not an official qualification from the Ministry.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised towards the advanced programme. Consult the recognition policy when enrolling.

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