Preparing Otolith Data for Age Estimation
A process note by Farnaz on how a large otolith dataset was cleaned, matched, and prepared for training.
Offener Kreis
Physical edition released
This section contains notes, essays, and project-related reflections written alongside ongoing work. I use writing as a way to think through research processes, document decisions, and make complex or long-term work more visible - especially the parts that usually remain hidden behind finished results or publications. Many of these texts emerge directly from practical work in marine research, software development, collaboration, and citizen science contexts.
A process note by Farnaz on how a large otolith dataset was cleaned, matched, and prepared for training.
A short process note on how the Offener Kreis reflection card set evolved from a coherent layout into a clearer visual orientation system.
Building the workflow before the system: how I structured the early development of PelAtlas so that the next step is always visible.
Documenting the process behind the reflection card set Offener Kreis. From research and question curation to structure, design exploration, and production considerations.
A week of exchange, alignment, and first architectural decisions for PelAtlas under the EU-CONEXUS DELPHI project.
A practical walkthrough showing how to create depth-corrected echograms from EK80 data using echopype, with a focus on how vessel heave enters the depth calculation.
Reflections on co-productive work between industry and research, and on how shared artifacts can create connection beyond formal collaboration.
A structured introduction to decision trees and ensemble methods, written as accompanying material for a Data Science lecture.
A personal review of 2025, tracing projects, collaborations, and shifts in focus toward citizen science and marine research.
Notes from the partX closing event, including project pitches, discussions, and emerging collaborations around participatory research.
A practical explanation of how Neovim, Jupyter kernels, and multiple Python environments fit together for an interactive, notebook-like workflow.