Unique ID: 2015114

Division: Office of Information and Regulatory Affairs
Issue Date: February 13th 2019
Last modified: March 13th 2019
Collaborative

A Pilot Study To Establish Data Use and Quality Standards for Using New Sources of Structured and Unstructured Data

Case Studies to establish Quality Standards for using new sources of structured and unstructured data

Two case studies

  1. Assess data quality for alternative sources of data for measuring housing quality and other characteristics about housing units.
  2. Methodological challenges in using state level data to examine education success and education to career trajectories

Project Objective:

Exploration, Scientific / research

Project Outcomes:

Feasibility assessment to determine if Big Data could be used to potentially reduce survey cost and respondent burden.

Statistical Area

Education, Urban statistics

Project Sources
Project Sources
Type Of Institution: National statistical office
Big Data Source: Other
Region: North America
Country Area: United States
Id Country Regional: country
Partnerships
Partnerships
Data Providers: Intermediary Big Data provider
Other Partners: Government institute, Research or academic institute
Accessing Data
Accessing Data
Data Access Rights: Only for this project
Intermediary Comments: A university is acting as our intermediary and is contracted to do the work.
Data Coverage
Data Coverage
Data Coverage: Only a portion of all data
Coverage Geo Pop: Part of country / low % of market
Cost Implication: Commercial
Cost Comments: We also are including free administrative information from state and local governments.
Coverage Period: 2008 - 2013
Project Details
Project Details
Frequency Comments: The case studies involve data from specific states and localities.
Data Quality
Data Quality
Quality Framework: Quality of output statistics
Quality Aspects Evaluated: Privacy and Security, Accessibility, Relevance, Institutional/Business Environment, Validity, Accuracy, including selectivity, Coherence, including linkability to other sources
Validation Comments: We are comparing commercial and administrative data against our survey measures. Also, in the housing case study researchers will measure ground truth via a "windshield" survey at specific sites.
Quality Framework Comments: Compare to published survey estimates. On the input side we are also developing a scorecard to assess quality and coverage.
Data Quality Concerns Comments: We are concerned about coverage and representativeness of big data that is why we are conducting this pilot work and comparing the results to our survey measures.
Methodology
Methodology
Methods Used: Traditional statistical methods, Data visualization methods
Technologies
Technologies
Technologies: GIS, Relational database, Data mining tools, Data visualization tools, Other
Technologies Comments: SAS
Other
Other
Income Level: High-income
Iso: US
Timeframe To Produce Indicator: NA
Frequency Comments: The case studies involve data from specific states and localities.
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