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datzin

Datzin is a term used to describe a data-centered approach that emphasizes ethical, transparent, and interpretable data practices alongside the pursuit of actionable insights. The concept is not tied to a single technology or protocol, but rather to a philosophy of how data should be collected, analyzed, and shared.

Origins of the term are informal. It appeared in early 2010s online discussions among data scientists, ethicists,

Core principles commonly associated with datzin include privacy-by-design, informed consent for data subjects, data minimization, and

In practice, organizations applying datzin integrate it into project lifecycles through data governance frameworks, impact assessments,

See also: data ethics, data governance, responsible AI, explainable AI, privacy-by-design.

and
product
researchers,
where
practitioners
sought
a
shorthand
for
balancing
analytical
ambition
with
social
responsibility.
As
usage
spread,
datzin
came
to
denote
a
set
of
practices
rather
than
a
fixed
method,
varying
by
organization
but
commonly
anchored
in
governance,
accountability,
and
clarity
about
limitations.
transparent
documentation
of
data
sources
and
model
decisions.
Reproducibility
and
auditability
are
emphasized
to
enable
independent
verification
of
results,
while
interpretability
aims
to
make
findings
accessible
to
stakeholders
without
specialized
training.
and
responsible
AI
guidelines.
It
is
used
in
product
development,
academic
research,
and
public
policy
to
ensure
that
data-driven
insights
respect
user
rights
and
societal
values.