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SUMMARY:More accessible data science - Joseph Barbier
DTSTART;TZID=Europe/Paris:20261126T151500
DTEND;TZID=Europe/Paris:20261126T154500
DTSTAMP:20260930T112545Z
UID:pretalx-compute-paris-2026-SGAKNW@pretalx.com
DESCRIPTION:Data science work often ends in charts\, dashboards\, PDFs\, s
 lides\, or web reports. These outputs may be reproducible\, beautiful\, an
 d technically correct\, while still being hard or impossible for many peop
 le to use.\n\nThis talk looks at the accessibility gap between analysis an
 d publication: color choices\, typography\, chart structure\, document sem
 antics\, and generated PDFs. We will see why and how accessibility can bec
 ome part of the data workflow itself\, instead of a manual cleanup step at
  the end\, or even not a step at all.
LOCATION:Room 106
URL:https://pretalx.com/compute-paris-2026/talk/SGAKNW/
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