2026/27 Taught Postgraduate Module Catalogue

ODLC5103M Environmental Data Analytics

15 Credits Class Size: 50

Module manager: Dr Arjan Gosal
Email: a.gosal@leeds.ac.uk

Taught: 1 Jan to 28 Feb, 1 Jan to 28 Feb (adv year) View Timetable

Year running 2026/27

Pre-requisite qualifications

Students are required to meet the programme entry requirements prior to studying the module. OLDA5101M or equivalent knowledge to the Trainee Data Scientist descriptor (https://ddat-capability-framework.service.gov.uk/role/data-scientist#trainee-data-scientist) in the Government Digital and Data Profession Capability Framework.

Module replaces

N/A

This module is not approved as an Elective

Module summary

This module introduces professionals to the critical role of environmental data in addressing global sustainability challenges. Designed to be accessible to those without prior analytics experience, it demystifies the diverse datasets used in climate science, ecology, and geospatial analysis. Rather than focusing on complex technical processing, the module empowers students to critically interpret environmental data, understand its inherent limitations, and use it to confidently inform sustainable decision-making in various organisational contexts.

Objectives

The objective of this module is to equip participants with the conceptual understanding necessary to meaningfully engage with environmental data analytics. The module aims to provide:

- An understanding of the heterogeneity, scale, and sources of environmental data (e.g. spatial, climate, earth observation).
- The ability to critically evaluate environmental data for biases, uncertainties, and limitations.
- An appreciation of how data drives sustainability initiatives and policy decisions.
- Knowledge of the ethical and governance issues surrounding environmental data collection and open data frameworks.

Learning outcomes

On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:

1. Explain the characteristics, sources, and real-world applications of diverse environmental datasets.
2. Evaluate the strengths, limitations, and uncertainties inherent in measuring and modelling environmental data.
3. Demonstrate a critical understanding of how environmental data is used to address global challenges and inform sustainability policy.
4. Describe and critically evaluate the ethical, governance, and open-data frameworks applicable to environmental data science.

Skills outcomes

On successful completion of the module students will have demonstrated the following skills learning outcomes:

1. Critically appraise sources of environmental information and methodological approaches to assess their suitability for informing sustainability decisions. (Work Ready, Sustainability)
2. Summarise and communicate complex environmental data insights clearly and concisely to non-technical stakeholders to drive organisational change. (Work Ready, Academic)
3. Use appropriate digital tools and platforms to explore, extract, and interpret relevant information from existing environmental dashboards. (Digital, Enterprise)

Syllabus

Indicative content for this module includes:

- Introduction to environmental data and global challenges
- Key environmental datasets (e.g. geospatial, climate, earth observation)
- Understanding uncertainty, variability, and scale in environmental data
- Interpreting environmental models, dashboards, and forecasts
- Data-driven decision making for sustainability and policy
- Ethics, governance, and open data in environmental science

Teaching Methods

Delivery type Number Length hours Student hours
Discussion forum 6 1 6
WEBINAR 6 1 6
Independent online learning hours 42
Private study hours 96
Total Contact hours 12
Total hours (100hr per 10 credits) 150

Opportunities for Formative Feedback

For the 20% coursework assessment: There will be practice activities in a similar format in week 2 and 3. Formative feedback for these activities will be provided in the webinars and on the discussion forum prior to the assessment.

For the 80% coursework assessment: Progress towards assessment 2 will be scaffolded throughout the taught units of this module including self-assessment checkpoints. Students will have weekly formative activities for each taught unit of this module that directly relate to components of the coursework task. Feedback on these will be provided in the webinars and on the discussion forum.

Methods of Assessment

Coursework
Assessment type Notes % of formal assessment
Coursework Students will be required to produce a written description (300 words) evaluating the suitability of a specific environmental dataset for a given sustainability scenario. 20
Coursework Students will produce a Report (1,500 words) on one of the environmental case studies examined in this module. The report will take the form of a briefing or user-guide, requiring students to evaluate the data used, assess limitations, and provide evidence-based recommendations for decision-makers. 80
Total percentage (Assessment Coursework) 100

This module will be reassessed by a 100% individual assessment covering all learning outcomes.

Reading List

Check the module area in Minerva for your reading list

Last updated: 22/07/2026

Errors, omissions, failed links etc should be notified to the Catalogue Team