Big Data Management in Ecology and Evolution

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