Organiser: Uta Priss
Notebooks, in particular Jupyter Notebooks, are becoming increasingly popular as a means for documenting procedures, data, calculations, and findings for data science applications and teaching. It has been speculated that computational notebooks might replace traditional scientific papers, as they present data and results in an interactive manner which readers can execute while they are reading. As a method for data analysis, FCA could utilise notebooks for directly publishing and sharing data exploration workflows, algorithms and interactive teaching materials. Notebooks even present a uniform interface for a variety of programming languages potentially allowing for code integration across languages. This workshop intends to provide a space for FCA researchers who are already using notebooks to share their experiences and for others to learn about them.
Researchers who would like to present their FCA experiences with notebooks at the workshop are asked to prepare a notebook which can be executed and presented (instead of slides) and send the link to it to by the submission deadline. The length of the notebook should correspond to a 20 minute presentation. Ideally the linked notebook should be directly executable without requiring further installation (i.e. through one of the cloud hosting sites for notebooks). Alternatively, a link to a static, downloadable version of the notebook is also acceptable. The proceedings of the workshop will not be printed but instead consist of a website with links to the notebooks. The main criterion for acceptance is that the notebook must demonstrate an application of FCA.
16:30 - 16:50 | Egor Dudyrev | FCApy Tutorial | download Run on Colab |
16:50 - 17:10 | Robert Jäschke | FCA & DraCor | download slides |
17:10 - 17:30 | Angel Mora | FCA Tutorial | download |
17:30 - 17:50 | Thomas Georges, Marianne Huchard | From user stories to feature models | download Run on MyBinder slides |
17:50 - 18:00 | Discussion |
Dmitry Ignatov | Maximal antichains in the partition lattice | download |
Dmitry Ignatov | Maximal antichains in the Boolean lattice | download |
Dmitry Ignatov | Interpretable ML with FCA and JSM | download |
Uta Priss | Learning FCA with Python | download Run on Mybinder |