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Public Use Data Decription Facility Type Variable typeCur_Name address1 address2 City State zip cty_code A10 A11 A12 B1 B2 B3 B4 B5 B6 B7 B8 C1 C2 C3 C4 q1bm q1by q1b q1a1date q1a2date q2 q2a q2b1Label
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How to fill out public use data decription

01
Gather the required data set that you want to describe.
02
Identify the key variables in your data set and their definitions.
03
Determine the format of the data (e.g., CSV, Excel, etc.).
04
Include information about the source of the data and the date it was collected.
05
Specify any restrictions on data usage or sharing, if applicable.
06
Provide example entries for key variables to illustrate how they should be interpreted.
07
Add any relevant documentation links or references that may assist users.
08
Review the description for clarity and completeness before finalizing.

Who needs public use data decription?

01
Researchers who require data for studies and analyses.
02
Organizations looking for data to inform policy-making.
03
Students and educators using data for teaching and learning purposes.
04
Data analysts who need to understand the context of data sets.
05
Any stakeholder interested in using public data for innovative projects and evaluations.
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Public use data description is a document that provides detailed information about datasets that are made available to the public, including their structure, content, and any relevant usage guidelines.
Organizations and individuals who create and distribute datasets intended for public use are typically required to file a public use data description.
To fill out a public use data description, you should provide comprehensive information about the dataset, including title, descriptions, data elements, format, access methods, and any limitations on data use.
The purpose of public use data description is to ensure transparency, facilitate data sharing, and provide users with the necessary context and understanding to appropriately utilize the dataset.
Information that must be reported includes dataset title, description, contact information, data collection methods, variable descriptions, any restrictions on use, and metadata relevant to the dataset.
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