AISP Toolkit Feb25 2025 - Flipbook - Page 34
CENTERING RACIAL EQUITY THROUGHOUT THE DATA LIFE CYCLE
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Involving community members in primary data
collection activities where possible and appropriate,
and compensating them for their time.
Failing to support and learn alongside community
members so that they are empowered to inform data
collection and research activities to their full extent.
Prioritizing data minimization.
Collecting data for the sake of having more data,
or collecting data that is not su昀케ciently granular
to meet community and project needs (see RELD &
SOGIE Data Standards Framework).
Coordinating across institutions and programs
to prevent duplicative data collection and use
existing data sources where possible.
Being extractive by collecting data in ways that
bene昀椀t the institution or research team without
demonstrated bene昀椀t to the community (e.g.,
surveilling populations for punitive purposes).
Documenting key dimensions of metadata (data
about data) so that data can be used legally and
ethically:
Failing to assess, document, and mitigate data
integrity issues (e.g., inaccuracies, missing
data, values out of range, duplicate rows) that
compromise the data’s trustworthiness and
usefulness for decision-making.
•
Description of the dataset, its purpose, who
created it, etc.
•
Provenance, or the history of the data, where
it came from, why it was collected, and
timeline of changes.
•
Technical speci昀椀cations that may be needed
to use the data, such as 昀椀le type, format, or
software requirements.
•
Rights related to data ownership, how data
may be used, copyright and licenses, and
restrictions on sharing and access.
•
Preservation, or the steps to protect, store,
maintain, and back up the data.
•
Citation information that allows others to
properly reference the original source.
Ensuring that the people whose data are collected
understand the purpose, bene昀椀ts, and risks.
Not providing clear opportunities to opt out of
sharing data before, during, and after data collection.
Finding out why people “opt out” of providing data
for surveys and other data collection efforts, and
using their feedback to minimize harm in future
data collection processes.
Failing to consider which data carry elevated risk
of harm (e.g., resident HIV status collected by a
housing program) and overlooking ways to mitigate
risks.
Seeking new data, new measures, and new ways of
understanding to drive action toward equity, even
when there are signi昀椀cant barriers.
Being complacent, not seeking to improve data
collection practices, especially when there are
concerns of bias, data quality, and missingness.
Co-creating with community members a
framework for the collection and use of RELD/
SOGIE data that re昀氀ects the overarching mission
of the integrated data system and speci昀椀c
community context
Defaulting to national data RELD standards
without validating against community needs or
avoiding use of RELD/SOGIE data at all because
they don’t exist or aren’t complete.
