Course in Urban Data Observatories
Online 300-hour course in Urban Data Observatories. 6 modules covering Directive (EU) 2019/1024 on open data, Implementing Regulation (EU) 2023/138 on high-value datasets and QGIS. Assigned tutor and open enrolment.
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What you will be able to do
Understand international models of urban observatories.
Identify and evaluate urban data sources.
Design the data architecture of an observatory.
Apply metadata and interoperability standards.
Analyse urban data using spatial and statistical techniques.
Disseminate information through visualisations and open portals.
Plan the institutional sustainability of an observatory.
Who it's for
- Urban data analyst wishing to specialise in Urban Data Observatories.
- Observatory coordinator wishing to specialise in Urban Data Observatories.
- Data engineer wishing to specialise in Urban Data Observatories.
- Municipal statistics technician wishing to specialise in Urban Data Observatories.
- GIS specialist wishing to specialise in Urban Data Observatories.
- Urban researcher wishing to specialise in Urban Data Observatories.
- Graduates in engineering or sciences seeking to enter local government.
What you'll work with
- Directive (EU) 2019/1024 on open data
- Implementing Regulation (EU) 2023/138 on high-value datasets
- Directive 2007/2/EC (INSPIRE)
- Law 37/2007 on the reuse of public sector information
- Regulation (EU) 2016/679 (GDPR)
- Law 12/1989 on the Public Statistical Function
- Technical Interoperability Standard for the Reuse of information resources
- ISO 37120:2018
6 modules · 300 h
1.1Origins of Urban Observatories 1.2 UN-Habitat's Global Urban Observatories Network 1.3 Municipal and Metropolitan Observatories 1.4 Thematic Observatories on Housing and Mobility 1.5 Institutional Models and Funding 1.6 Mission, Users and Products 1.7 Relationship with Official Statistics 1.8 University Observatories 1.9 Cases of Barcelona, Bogotá and New York 1.10 Practical Case: Benchmarking three observatories
2.1Censuses and continuous population register2.2Municipal administrative records2.3Land registry and property data2.4Remote sensing and Copernicus2.5IoT sensors and urban platforms2.6Mobile phone data2.7Surveys and citizen perception2.8Platform data and web scraping2.9INE experimental statistics2.10Workshop: inventory of a city's sources
3.1Data modelling and data dictionaries3.2Data warehouses and data lakes3.3ETL processes and automation3.4Geospatial data and georeferencing3.5DCAT-AP standards and metadata3.6Smart Data Models3.7APIs and OGC services3.8Data quality and validation3.9Security and access control3.10Laboratory: Python ETL pipeline
4.1Indicators and time series4.2Spatial analysis and autocorrelation4.3Neighbourhood segmentation4.4Urban predictive models4.5Inequality analysis4.6Periodic thematic reports4.7Technical notes and factsheets4.8Peer review and validation4.9Management of user requests4.10Practice: vulnerability report by census tracts
5.1Open data portals5.2Interactive visualisation and dashboards5.3Urban atlases and geoportals5.4Data storytelling5.5Communication to policymakers5.6Accessibility of visualisations5.7Reuse licences5.8Measuring the observatory's impact5.9User community and collaboration5.10Workshop: urban dashboard in Power BI
6.1Defining mission and scope6.2User map and needs6.3Selection of sources and themes6.4Proposed technical architecture6.5Initial product catalogue6.6Institutional sustainability plan6.7Data model and metadata6.8Dashboard prototype6.9Report and presentation6.10Final review with tutor
How you'll learn
Training is 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: students progress at their own pace within the enrolment period, which makes it possible to combine the course with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is QGIS, PostgreSQL with PostGIS, CKAN, Power BI, Python, in free, academic or evaluation versions. The tests are studied through real procedures for designing an observatory's architecture, preparing reports with geospatial data and publishing open datasets. Assessment is continuous per module, plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Understand international models of urban observatories.
Identify and evaluate urban data sources.
Design the data architecture of an observatory.
Apply metadata and interoperability standards.
Analyse urban data using spatial and statistical techniques.
Where this takes you
Requirements
- No prior degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient 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.
Frequently asked questions
The programme comprises 300 hours in total, spread over 3 to 5 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
The course uses QGIS, PostgreSQL with PostGIS, CKAN, Power BI and Python. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An SEIUM own diploma upon passing the continuous assessment and the integrating project. It 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 in the higher programme. Check the recognition policy when you enrol.
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