Lin, Eddie Tzu-Yun

English

ScholarlyCommons@Penn

University of PennsylvaniaScholarlyCommons2017 ADRF Network Research ConferencePresentations ADRF Network Research Conference Presentations11-2017Better Together: Three Models for CombiningPublic and Private Data to Create New ResearchData SetsEddie Tzu-Yun LinUniversity of ChicagoFollow this and additional works at: https://repository.upenn.edu/admindata_conferences_presentations_2017This paper is posted at ScholarlyCommons. https://repository.upenn.edu/admindata_conferences_presentations_2017/9For more information, please contact repository@pobox.upenn.edu.Lin, Eddie Tzu-Yun, "Better Together: Three Models for Combining Public and Private Data to Create New Research Data Sets"(2017). 2017 ADRF Network Research Conference Presentations. 9.https://repository.upenn.edu/admindata_conferences_presentations_2017/9Better Together: Three Models for Combining Public and Private Data toCreate New Research Data SetsThis presentation is available at ScholarlyCommons: https://repository.upenn.edu/admindata_conferences_presentations_2017/9  Workforce Data InitiativeBetter Together: Three Models for Combining Public and Private Data to Create New Research Data SetsEddie Tzu-Yun Lintlin2@uchicago.edu  Workforce Data InitiativeOutline• WDI Overview• Challenges of Labor Market Data• Open-Skills Project• Combining Private and Public Sector Data• Use Public Sector Data for Validating Private Sector Data• Use Public Sector Data to Extract New Data from Private Sector Data• Use Private Sector Data for Creating New Public Sector Data• What can you do today?2  Workforce Data Initiative 3The Workforce Data InitiativeWhat We’re DoingOpen Data on Skills and JobsOpening Training Outcomes DataSupporting New Developer Resources and Third Party Tools  Workforce Data InitiativeChallenges of Labor Market Data● Lack of geographic and and temporal granularity of survey-based labor market data sources● Lack of intra-occupational specificity of national labor market taxonomies/ontologies● High frictions to data access for more granular administrative data sources● Lack of technical capacity among social science researchers for working with large, unstructured data sources● Lack of transparency in methods for generated datasets from most Real-time Labor Market Information data vendors4Open Skills Cooperative• Pooling public and private data into a private data store• 9 months of negotiating unique legal and governance structureOpen Skills Research and Development Group• Data scientists, machine learning and AI researchers• Economists• Taxonomists, and other subject matter expertsOpen Skills API• Open aggregate data resource of raw and normalized skills & jobs, and how they relate to each other in time and placeOpen Skills Developer Partners• Building applications on top of the Open Skills API• Supporting veterans’ spouses, career one-stop-shops, & industry use casesOpen Skills DatabaseData@Work Research HubOpen-Skills Project  Workforce Data InitiativeThree Models for Using Private and Public Sector Data6O*NETBLS: JOLTS, OESCensus BureauData@Work Research HubOpen-Skill APIEMSI DataPublic Sector Private Sector   Workforce Data InitiativeData@Work Research Hub Dataset7  Workforce Data InitiativeUse Public Sector Data for Validating Private Sector DataRepresentativeness AnalysisSingle Year Representativeness Summary Data Overview (2013) 8OES JOLTS Data@WorkType Employment Job opening Job postingCounts 169M 90M 2.4MGeographic Granularities586 MSAs 4 Regions 1004 CBSAsMajor Groups 22 (ONET) 26 (NAICS) 23 (ONET)  Workforce Data InitiativeJob Distribution by State: Data@Work vs. OES9Correlation: 0.8738NOTE: Based on 2013 data. Does not include AK and HI.  Workforce Data InitiativePercent Change in Data@Work Job Postings (contributed by CareerBuilder) vs. JOLTS Job Openings10NOTE: Based on 2011-2014 data.  Workforce Data InitiativeUse Public Sector Data to Extract New Data from Private Sector Data 11Occupation NormalizationSkill NormalizationOccupation ClassifierSkill Classifier Public Sector Data Private Sector DataData@Work Research HubOpen-Skill API  Workforce Data InitiativeUse Private Sector Data for Creating New Public Data12Public SectorPrivate Sector DSaPP Resume DataJob Title NormalizerOccupation Classifier Open Data RSI Form  Workforce Data InitiativeWhat can you do today?• Sign up to be part of the Data@Work researcher community on Slack • Explore the data on the Data@Work Research Hub• Ask questions and provide suggestions for additional datasets to the Data@Work on Slack 13  Workforce Data InitiativeOccupation Distribution Correlation by State14NOTE: Based on 2013 data. Does not include AK and HI.  Workforce Data InitiativeUse Public Sector Data to Extract New Data from Private Sector Data 15

Better Together: Three Models for Combining Public and Private Data to Create New Research Data Sets

Kosmopolis

University of Pennsylvania
ScholarlyCommons
2017 ADRF Network Research Conference
Presentations ADRF Network Research Conference Presentations
11-2017
Better Together: Three Models for Combining
Public and Private Data to Create New Research
Data Sets
Eddie Tzu-Yun Lin
University of Chicago
Follow this and additional works at: https://repository.upenn.edu/
admindata_conferences_presentations_2017
This paper is posted at ScholarlyCommons. https://repository.upenn.edu/admindata_conferences_presentations_2017/9
For more information, please contact repository@pobox.upenn.edu.
Lin, Eddie Tzu-Yun, "Better Together: Three Models for Combining Public and Private Data to Create New Research Data Sets"
(2017). 2017 ADRF Network Research Conference Presentations. 9.
https://repository.upenn.edu/admindata_conferences_presentations_2017/9
Better Together: Three Models for Combining Public and Private Data to
Create New Research Data Sets
This presentation is available at ScholarlyCommons: https://repository.upenn.edu/admindata_conferences_presentations_2017/9
  Workforce Data Initiative
Better Together: Three Models for Combining Public and 
Private Data to Create New Research Data Sets
Eddie Tzu-Yun Lin
tlin2@uchicago.edu
  Workforce Data Initiative
Outline
• WDI Overview
• Challenges of Labor Market Data
• Open-Skills Project
• Combining Private and Public Sector Data
• Use Public Sector Data for Validating Private Sector Data
• Use Public Sector Data to Extract New Data from Private Sector Data
• Use Private Sector Data for Creating New Public Sector Data
• What can you do today?
2
  Workforce Data Initiative 3
The Workforce Data Initiative
What We’re Doing
Open Data on 
Skills and Jobs
Opening 
Training 
Outcomes Data
Supporting 
New Developer 
Resources and 
Third Party 
Tools
  Workforce Data Initiative
Challenges of Labor Market Data
● Lack of geographic and and temporal granularity of survey-based labor 
market data sources
● Lack of intra-occupational specificity of national labor market 
taxonomies/ontologies
● High frictions to data access for more granular administrative data sources
● Lack of technical capacity among social science researchers for working with 
large, unstructured data sources
● Lack of transparency in methods for generated datasets from most Real-time 
Labor Market Information data vendors
4
Open Skills 
Cooperative
• Pooling public and 
private data into a 
private data store
• 9 months of 
negotiating unique 
legal and 
governance 
structure
Open Skills Research 
and Development 
Group
• Data scientists, 
machine learning 
and AI researchers
• Economists
• Taxonomists, and 
other subject 
matter experts
Open Skills API
• Open aggregate 
data resource of 
raw and normalized 
skills & jobs, and 
how they relate to 
each other in time 
and place
Open Skills 
Developer Partners
• Building applications 
on top of the Open 
Skills API
• Supporting veterans’ 
spouses, career 
one-stop-shops, & 
industry use cases
Open Skills 
Database
Data@Work 
Research HubOpen-Skills Project
  Workforce Data Initiative
Three Models for Using Private and Public Sector Data
6
O*NET
BLS: JOLTS, OES
Census Bureau
Data@Work Research 
Hub
Open-Skill API
EMSI Data
Public Sector Private Sector 
  Workforce Data Initiative
Data@Work Research Hub Dataset
7
  Workforce Data Initiative
Use Public Sector Data for Validating Private Sector Data
Representativeness Analysis
Single Year Representativeness Summary Data Overview (2013) 
8
OES JOLTS Data@Work
Type Employment Job opening Job posting
Counts 169M 90M 2.4M
Geographic 
Granularities
586 MSAs 4 Regions 1004 CBSAs
Major Groups 22 (ONET) 26 (NAICS) 23 (ONET)
  Workforce Data Initiative
Job Distribution by State: Data@Work vs. OES
9
Correlation: 0.8738
NOTE: Based on 2013 data. Does not include AK and HI.
  Workforce Data Initiative
Percent Change in Data@Work Job Postings (contributed by 
CareerBuilder) vs. JOLTS Job Openings
10
NOTE: Based on 2011-2014 data.
  Workforce Data Initiative
Use Public Sector Data to Extract New Data from Private Sector Data 
11
Occupation 
Normalization
Skill Normalization
Occupation 
Classifier
Skill Classifier 
Public Sector Data Private Sector Data
Data@Work 
Research Hub
Open-Skill API
  Workforce Data Initiative
Use Private Sector Data for Creating New Public Data
12
Public SectorPrivate Sector DSaPP 
Resume Data
Job Title Normalizer
Occupation Classifier 
Open Data 
RSI Form
  Workforce Data Initiative
What can you do today?
• Sign up to be part of the Data@Work researcher community on Slack 
• Explore the data on the Data@Work Research Hub
• Ask questions and provide suggestions for additional datasets to the 
Data@Work on Slack 
13
  Workforce Data Initiative
Occupation Distribution Correlation by State
14
NOTE: Based on 2013 data. Does not include AK and HI.
  Workforce Data Initiative
Use Public Sector Data to Extract New Data from Private Sector Data 
15


https://repository.upenn.edu/cgi/viewcontent.cgi?article=1008&amp;context=admindata_conferences_presentations_2017

Better Together: Three Models for Combining Public and Private Data to Create New Research Data Sets

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