---
esco_uri: http://data.europa.eu/esco/skill/da930e2f-6047-4616-a598-bba8ecef3039
esco_label: "manage open publications"
relation: essential
onet_soc: 15-2051.00
source: model-knowledge
confidence: high
qa_count: 0
generator: gemma3:27b (prompt-designed and spot-checked by Claude)
generated: 2026-07-10
---

# manage open publications — Data Scientist

For a Data Scientist, 'managing open publications' isn’t about traditional academic publishing *per se*, but ensuring the reproducibility and impact of your data science work. This means more than just writing papers; it's about packaging code (think Jupyter Notebooks, R scripts), datasets (appropriately anonymized if needed!), and documentation in a way that others can readily use and verify your findings. Tools like GitHub/GitLab are central – version control *is* open publication for code.  You’ll also be increasingly expected to publish models via platforms like Hugging Face Model Hub or Zenodo, alongside clear licensing (e.g., MIT, Apache 2.0) indicating usage rights. Think of it as 'open science' applied to data-driven insights.

## Weitere Anreicherung

Stage-2 source for future practitioner grounding: arXiv cs.LG/stat.ML (ML preprints).
