Biodiversity Informatics BIOL5132
- Academic Session: 2024-25
- School: School of Biodiversity One Health Vet Med
- Credits: 10
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 2
- Available to Visiting Students: Yes
- Collaborative Online International Learning: No
Short Description
This course will provide evidence-based advanced practical training in using databases, software, and web services to analyse data, create mashups and visualisations of biodiversity data.
Timetable
The course will be an intensive 3 day training session, combining morning lectures (5 hours in total) with afternoon computer laboratory sessions (10 hours in total).
Requirements of Entry
None
Excluded Courses
None
Co-requisites
None
Assessment
Students will submit practical exercises to gauge their depth of understanding and engagement with the skills learned in each of the practical sessions. The work will be assessed not only on completion of the assigned tasks but on interpretation and self-reflection of the theories learned (25%). The remaining 75% will be based on a set exercise that tests the practical skills and theories learned.
Course Aims
To provide evidence-based advanced practical training in using web services to aggregate and visualise biodiversity data, using an interactive and open-access based approach.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
■ demonstrate advanced competence in querying biodiversity databases and be able to critically discuss with respect to the primary literature their most appropriate uses
■ critically discuss with respect to the literature the strengths and limitations of existing biodiversity databases
■ consider a biological question related to biodiversity informatics and take an evidence-based approach to determine which current databases and services are relevant to answering that question
Minimum Requirement for Award of Credits
Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.