5c03e07ded
Simpler story (slide decks unread -> three-bullet status email), proper Claude-chat look with avatars and bubbles on both sides. Canonical trigger prompt switched to English everywhere (homepage, architecture, both adapter generators rebuilt) - V7 consistency green, all checks pass. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PDKeXvpT6tENSvyQGLV1Uq
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esco_uri, esco_label, relation, onet_soc, source, confidence, qa_count, generator, generated
| esco_uri | esco_label | relation | onet_soc | source | confidence | qa_count | generator | generated |
|---|---|---|---|---|---|---|---|---|
| http://data.europa.eu/esco/skill/8f6ed69b-29d0-4c01-81ba-f05920a185f3 | digital curation | optional | 15-2051.00 | model-knowledge | high | 0 | gemma3:27b (prompt-designed and spot-checked by Claude) | 2026-07-10 |
digital curation — Data Scientist
For a Data Scientist, 'digital curation' isn’t about archiving old websites; it's about ensuring the reliability and reproducibility of your entire analytical pipeline. Daily tasks involve meticulously documenting data provenance – where did the data come from? What transformations were applied (cleaning, feature engineering)? Which versions of libraries/code were used? Think beyond just storing raw files; you’re building a traceable history. This means using version control (Git is essential), employing metadata standards to describe datasets and models, and potentially leveraging data catalogs like Amundsen or Marquez to make this information searchable for yourself and collaborators.
Weitere Anreicherung
Stage-2 source for future practitioner grounding: arXiv cs.LG/stat.ML (ML preprints).