Big Data Management in Ecology and Evolution

Faculteit Science and Engineering
Jaar 2020/21
Vakcode WBBY028-05
Vaknaam Big Data Management in Ecology and Evolution
Niveau(s) bachelor
Voertaal Engels
Periode semester II a
ECTS 5
Rooster rooster.rug.nl

Uitgebreide vaknaam Big Data Management in Ecology and Evolution
Leerdoelen At the end of the course, the student is able to:
1) describe big data applications in ecological and evolutionary research
2) design a big data strategy for an ecological or evolutionary research question, taking into account the strengths and
limitations of big data approaches
3) apply big data analysis techniques on ecological and evolutionary datasets, and interpret the outcome of these
analyses from a biological perspective
4) present results using big data visualization techniques
Omschrijving Recent developments in automatic data recording and genetic sequencing techniques, and the increased availability of long-term
datasets, are rapidly advancing ecological and evolutionary research. Massive amounts of data are generated, both by researchers
and by the general public in citizen science projects, and accessible to ecologists and evolutionary biologists. These large datasets
also pose significant challenges to researchers in terms of managing and processing big data sets, conducting analyses, and
visualizing and interpreting results. For the next generation of ecologists and evolutionary biologists, big data techniques and
analysis skills have become critically important. Using examples of big data applications in ecology and evolution, students will learn
big data techniques and develop big data analyses skills.
Uren per week
Onderwijsvorm Hoorcollege (LC), Opdracht (ASM), Practisch werk (PRC), Werkcollege (T)
(Lectures 16 hrs, tutorials 23 hrs, assignments 31 hrs, practicals 38 hrs, self study 32 hrs.)
Toetsvorm Opdracht (AST), Presentatie (P)
(Presentation 15%, assignment 1 60%, assignment 2 25%. All partial grades (1st grade: 3 assignments during course; 2nd grade: assignment & presentation) should be equal or higher than 5. The final grade should be higher than 5.5.)
Vaksoort bachelor
Coördinator dr. M. Hammers
Docent(en) dr. M. Hammers
Verplichte literatuur
Titel Auteur ISBN Prijs
R 2021 R Development Core Team
Entreevoorwaarden The course assumes prior knowledge of data analysis using the program R and knowledge of statistical analysis techniques. It is
recommended to have followed the course 'Biostatistics II' before the start of the course.

PLEASE NOTE
Biology and Life Science & Technology (old curriculum) course units are only accessible for students of those degree programmes. Students from other degree programmes who would like to participate in Biology course units are obliged to contact one of the academic advisors before registration. After this contact, students have to request admission from the Board of Examiners Biology/Life Science & Technology. Failing to follow this procedure results in immediate unenrollment without prior notification.
Opmerkingen Participation in all tutorials and practicals is mandatory. Not attending will result in not awarding the final grade.

Capacity: max. 30 students.

Dit vak had vorig jaar vakcode WBLS19016
Opgenomen in
Opleiding Jaar Periode Type
BSc Biology: major Ecology and Evolution 2 semester II a keuze
BSc Biology: major Integrative Biology  (Option A: students who follow Res. Project 1 within the majors BMS, MLS, or BN) 3 semester II a keuze