Problem: how do teams collaborate on data?

Pro:

• need is apparent, and can be intertwined with Netcheck work
• can work with Netlify + RKI data team on it

con:

• not necessarily hot topic for Renard / academia in general (SWE research problems ...)

Topics that Renard / Ferdous / Athar are publishing on:

• local hierarchical classification (publishes a Python Library!)
• Deep learning with Pathogens
• detecting viruses in genome sequencing

The Python Library one could be a good point to convince BYR.

Idea: Create a tool / workflow that statisticians can use to verify + document their data.

Topic Draft: tooling to document and verify assumptions on evolving data

Statistical Tests for Verification + Explanation

Goal: easily keep track of knowledge about data

DACS Fit:

• DACS entwickelt statistische und informatische Methoden, um automatisiert große Datenmengen auszuwerten, relevante Signale herauszufiltern und Vorwissen passend einzubinden. [...] Wichtig ist dabei das zielgerichtete Maßschneidern von Verfahren auf spezifische, praktische Probleme.

How will I work?

• survey different teams (across different companies + industries) to find how they keep track of their data knowledge
• identify problems