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* initial checkin * gitignore and docker-compose update * readme update and error on hud * encoding issue * one more small README change * data roadmap re-strcuture * pyproject sort * small update to score output folders * checkpoint * couple of last fixes
39 lines
2.4 KiB
YAML
39 lines
2.4 KiB
YAML
# There is no method for adding field descriptions to `yamale` schemas.
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# Therefore, we've created a dictionary here of fields and their descriptions.
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name: A short name of the data set.
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source: The URL pointing towards the data set itself or more information about the
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data set.
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relevance_to_environmental_justice: It's useful to spell out why this data is
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relevant to EJ issues and/or can be used to identify EJ communities.
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spatial_resolution: Dev team needs to know if the resolution is granular enough to be useful
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public_status: Whether a dataset has already gone through public release process
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(like Census data) or may need a lengthy review process (like Medicaid data).
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sponsor: Whether there's a federal agency or non-governmental agency that is working
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to provide and maintain this data.
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subjective_rating_of_data_quality: Sometimes we don't have statistics on data
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quality, but we know it is likely to be accurate or not. How much has it been
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vetted by an agency; is this the de facto data set for the topic?
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estimated_margin_of_error: Estimated margin of error on measurement, if known. Often
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more narrow geographic measures have a higher margin of error due to a smaller sample
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for each measurement.
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known_data_quality_issues: It can be helpful to write out known problems.
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geographic_coverage_percent: We want to think about data that is comprehensive across
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America.
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geographic_coverage_description: A verbal description of geographic coverage.
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data_formats: Developers need to know what formats the data is available in
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last_updated_date: When was the data last updated / refreshed? (In format YYYY-MM-DD.
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If exact date is not known, use YYYY-01-01.)
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frequency_of_updates: How often is this data updated? Is it updated on a reliable
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cadence?
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documentation: Link to docs. Also, is the documentation good enough? Can we get the
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info we need?
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data_can_go_in_cloud: Some datasets can not legally go in the cloud
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discussion: Review of other topics, such as
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peer review (Overview or links out to peer review done on this dataset),
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where and how data is available (e.g., Geoplatform.gov? Is it available from multiple
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sources?),
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risk assessment of the data (e.g. a vendor-processed version of the dataset might not
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be open or good enough),
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legal considerations (Legal disclaimers, assumption of risk, proprietary?),
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accreditation (Is this source accredited?)
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