---
esco_uri: http://data.europa.eu/esco/skill/833289fa-3646-4010-9d9e-93ba8c9ef2d8
esco_label: "apply research ethics and scientific integrity principles in research activities"
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
---

# apply research ethics and scientific integrity principles in research activities — Data Scientist

As a Data Scientist, 'applying research ethics & scientific integrity' isn’t just about avoiding blatant plagiarism; it permeates *every* stage of your work. Think beyond academic papers – you're constantly building models that impact real people. This means careful consideration of data sourcing: is the data collected legally and with informed consent? Are there biases in the data reflecting societal inequalities, and if so, how do you mitigate them or transparently acknowledge their presence? Tools like data lineage trackers become crucial for demonstrating responsible data handling. A 'good' Data Scientist proactively documents data origins, transformations, and potential limitations.

## Weitere Anreicherung

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