A Bring Your Own Data Lab on Historical Network Analysis
Exploring Connections
Datum:
17.10.2024 bis 18.10.2024Ort:
Leibniz Institute of European History (IEG)
Alte Universitätsstraße 19
D – 55116 Mainz
Germany
Contact and Registration:
Dr Judit Garzón Rodríguez
hermes [at] ieg-mainz.de (hermes[at]ieg-mainz[dot]de)
Note: maximum number of participants is 15.
Kategorie(n):
Weitere Infos:
Bring Your Own Data LabProgramme (in work)
Day 1: 17.10.2024
08:45: Registration
09:30: Welcome | Dr Judit Garzón Rodríguez
09:40: Impuls 1: Epistemology of network research + Case Study | Dr Cindarella Petz (Leibniz-Institute of European History, Digital Historical Research | DH Lab)
10:30: Impuls 2
11:30: Coffee break
11:45: Impuls 3: (Dis)entangling the Past through Multilayer Networks | Sebastian Borkowski, M.A (University of Bern, Data Science Lab)
12:45: Lunch break
14:00: Instruction + Creating Poster | Dr Cindarella Petz + Sebastian Borkowski, M.A
15:00: Coffee break
15:20: Instruction + Creating Poster | Dr Cindarella Petz + Sebastian Borkowski, M.A
16:00: Rotating Poster Session with Peer-2-Peer feedback and mentoring | Dr Cindarella Petz + Sebastian Borkowski, M.A
17:00: Plenary session and collaborative planning of the work sessions for the second day | Dr Cindarella Petz + Sebastian Borkowski, M.A
17:45: Conclusion | Dr Judit Garzón Rodríguez
18:30: Workshop dinner (At Own Expense) | all participants
Day 2: 18.10.2024
09:30: Welcome | Dr Judit Garzón Rodríguez
09:40: Impuls: Showing Code examples of yesterday | Dr Cindarella Petz + Sebastian Borkowski, M.A
10:30: Hands-on | all participants
11:30: Coffee break
11:45: Hands-on | all participants
13:00: Lunch break
14:00: Hands-on + Mentoring | all participants
15:15: Coffee break
15:30: Hands-on + Mentoring | all participants
16:20: Closing remarks | Dr Judit Garzón Rodríguez
Preparation and Prerequisites:
- Basic programming knowledge (R, Python, …). Note that the course will be in Python. On the Leibniz-Institute of European History GitHub repository you can access some preparing material (Python programming, Data Analysis with Python): There are 2 Jupyter Notebooks: Introduction_Jupyter_Python.ipynb and Intro_Data_Analysis_with_Python.ipynb. There is also a Jupyter Notebook assignment.ipynb if you want to check your understanding (the document is not long, you may need < 1h).
- Willingness to learn new technical skills
- Important: install and get comfortable with Anaconda3. It contains all packages we will need (Jupyter notebooks included)
- Installing Anaconda
- Setting up a new environment, e.g. “HNR”
- Installing networkX-package, pandas, matplotlib