Undergraduate

modules

Modules

BIO8068 : Management and Visualisation of Data in Ecology and Conservation

Semesters
Semester 2 Credit Value: 10
ECTS Credits: 5.0

Aims

Modern ecological surveys can produce large datasets, e.g. from GPS tags on animals, camera traps, genetics data etc. These large datasets require environmental scientists trained in data analytics, in other words capable of managing the entire pipeline from raw data, data cleaning and management, modelling, visualisation, and communication to other scientists and non-specialists. Students will learn different methods of storing and handling large datasets, the theory and practice of reproducible research, robust software coding with version control, data visualisation, both static and interactive (web-based) graphical display and communication of results. The module will focus primarily on data from ecology and environmental science, but will also include examples of data processing skills needed to understand complex bioinformatics or similar data.

Outline Of Syllabus

• Why are large datasets a challenge? Problems of understanding large ecological datasets, assessing data quality and visualisation.
• The challenge of data collected by other ecologists: spreadsheets, messy data, missing meta-data. The need for standardised methods of cleaning and checking data
• Concept of data processing pipelines from raw data to published report; advantages for reproducible research
• Relational databases: storing linked tables of data to allow advanced selection of variables, query, and processing. Commercial and open-source options.
• Data visualisation – good and bad practice in graphics for environmental data.
• Interactive visualisation – embedding data and model outputs in interactive websites. Maps, graphs and tabular data
• Version control – why it is essential to have a fully annotated history of all updates to software code. Collaborative and individual version control. Web-hosted version control.
• Producing word-processed reports or presentations from directly from data without the need for copy-and-paste

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion130:0030:00Practical lab report
Scheduled Learning And Teaching ActivitiesLecture61:006:00N/A
Scheduled Learning And Teaching ActivitiesPractical102:0020:00PC-based classes to provide relevant skills
Guided Independent StudyDirected research and reading14:004:00Lectures follow up
Guided Independent StudyIndependent study140:0040:00Preparation for continuous assessment
Total100:00
Teaching Rationale And Relationship

There will be an emphasis on PC-based practical classes, rather than lectures, to ensure a high-level of practical skills are developed through hands-on use of relevant datasets and software.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Practical/lab report2M100Students will be provided with typical raw ecological datasets to clean, analyse and interpret and visualise. Approx. 2000 words
Assessment Rationale And Relationship

This is very much a skills-based module, and so the assessment will test students’ abilities to process complex environmental data, using typical ‘messy’ datasets often encountered. They will have to demonstrate that they can analyse and interpret their data in a reproducible manner, know how to select appropriate graphical/tabular displays.

Reading Lists

Timetable