Functional data analysis and applications in digital and augmented humanities
Target audience
All members of Doctoral School and external PhD students.
Conference talks are open to the public.
Organizing and scientific committee
Ana Mª Aguilera (University of Granada)
Marc Leman (Ghent University)
Pieter-Jan Maes (Ghent University)
Marc Vidal (Ghent University; University of Granada; Max-Planck-Institut für Kognitions- und Neurowissenschaften)
Alexandra Michalko (Ghent University)
Adriaan Campo (Ghent University)
Bart Moens (Ghent University)
Contact information
De Krook (4rth floor), Miriam Makebaplein 1, 9000 Ghent, Belgium
Abstract
This course aims at introducing students to the analysis of data in the form of curves. The course will last 3 days, comprising lectures connected to practical hands-on sessions, and (the last day) more advanced talks by experts. After having had an introduction to theory and tools, students will collect curve data in the ASIL lab (De Krook) and learn how to analyze them. Emphasis is on functional data analysis. Materials (text and tools, such as R and RStudio) will be distributed so that students can prepare themselves before they attend the course.
Objectives
The overall objective of the course is to the develop data-analysis skills of PhD-students working in the domain of digital and/or augmented humanities. The learning outcome in PhD-students will be an increase in insight, knowledge, and skill of how to deal with curve data. To reach that learning outcome, the course will introduce examples and datasets where curve data occur, and then focus on theory and tools needed to analyze these data, followed by practical training (hands-on work with R/RStudio, data-acquisition in ASIL at De Krook). Learning how to handle curve data is relevant to get high impact research outcomes and this course will offer them the insight from which further data-analysis study and/or data-analysis collaborations with experts in the field can be started.
Dates and Venue
28 - 30 November 2023 from 9:00 to 17:00 (including several breaks)
zaal De Blauwe Vogel, De Krook, Miriam Makebaplein 1, 9000 Ghent, Belgium
Programme
Course lectures
- Data gathering
- Computational tools (R Studio)
- Probability principles
- Curve approximation
- Functional principal components analysis
- Inference with functional data
- Advanced techniques
Keynote speakers & talks
- Ana Mª Aguilera (University of Granada): “An introduction to functional data analysis”
- Jan Beran (Universität Konstanz): “On Fourier based functional data analysis, with applications”
- Alessia Caponera (University of Milano-Bicocca): “Sparse functional data: mean and covariance estimation with an application to climate data”
- Ingrid Dauchebies (Duke University; Vrije Universiteit Brussel): “Surfing with wavelets”
- Marc Leman (Ghent University): “New challenges in augmented humanities: complex data and challenging analyses”
- Alessandra Menafoglio (Politecnico di Milano): “The Bayes space approach to functional data analysis for probability density functions”
- Marc Vidal (Ghent University; University of Granada; Max-Planck-Institut für Kognitions- und Neurowissenschaften): “The near-perfect classification phenomenon: an overview of functional classification techniques applied to data coming from digital humanities”
More information can be found through this link.
Registration
Follow this link for the registration and waiting list.
Registration fee
Free of charge for Doctoral School members.
The no show policy applies.
Number of participants
Maximum 20 participants. Priority will be given to members of the Doctoral School of Arts, Humanities and Law, Social and Behavioural Sciences (10 applicants maximum). Participants from abroad are also welcome.
Talks will be open to the general public.
Language
English
Teaching material
Access to an online platform for all digital documents (handouts of theoretical lectures, additional documentation, data sets) will be provided.
Evaluation method
The evaluation criteria is 75 % of attendance and active participation.
After successful participation, the Doctoral Schools will add this course to your curriculum of the Doctoral Training Programme in Oasis. Please note that this can take up to one to two months after completion of the course.