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An Interactive Visual Analytics Dashboard for the Employment Situation Report

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The Employment Situation Report is a monthly news release by the Bureau of Labor Statistics which describes the results of the Current Population Survey. Its release is widely anticipated by economists, journalists, and politicians as it is used to forecast the economic condition of the United States by describing ongoing trends and has a broad impact on public and corporate economic confidence leading directly to investment decisions. The report itself is in a PDF format that is comprised primarily of text and tabular information. Quickly and correctly interpreting the results of the jobs report is vital for quality reporting and decision making, but the report is more suited for longer study than deriving insights. In this project we explore the use of an interactive dashboard for visual analytics upon the released BLS data. Using an application demonstration and a usability study we will show that visually interacting with the most current employment data, users are able to rapidly achieve rich insights similar to those reported on in the text of the Employment Situation Report.

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An Interactive Visual Analytics Dashboard for the Employment Situation Report

  1. 1. An Interactive Visual Analytics Dashboard for the Employment Situation Report Benjamin Bengfort1 , Xintong Han2 , Assaf Magen3 , and Hao Zhou4 Department of Computer Science, University of Maryland {bengfort1 , hzhou4 }@cs.umd.edu, {xintong2 ,amagen3 }@umd.edu May 12, 2015
  2. 2. The Employment Situation Report
  3. 3. “Its information is widely anticipated, forecasted and used by Wall Street firms, their economists and many business decision-makers. It may even impact broader public and corporate confidence, and therefore future business and hiring decisions.” What You Need To Know About the Employment Report
  4. 4. New York Times Reporting on the Jobs Report
  5. 5. The visual analytics process combines automatic and visual analysis methods with a tight coupling through human interaction in order to gain knowledge from data. Visual Analytics D. A. Keim, J. Kohlhammer, G. Ellis, and F. Mansmann, Mastering The Information Age-Solving Problems with Visual Analytics. Florian Mansmann, 2010. Visualization Knowledge Models Data User Interaction Model Viz Model Building Mapping Transformation Data Mining Feedback Loop
  6. 6. The Sensemaking Process J. Heer and B. Shneiderman, “Interactive dynamics for visual analysis,” Queue, vol. 10, no. 2, p. 30, 2012. High Level Overview Zoom & Filter Details on Demand
  7. 7. Requirements for BLS Analysis - Interactive, hypothesis-driven exploration of multiple data sets that can be verified and exported. - General accessibility without prerequisite domain knowledge. - Rapid and correct at-a-glance insights.
  8. 8. Requirements for BLS Analysis - Interactive, hypothesis-driven exploration of multiple data sets that can be verified and exported. - General accessibility without prerequisite domain knowledge. - Rapid and correct at-a-glance insights.
  9. 9. Requirements for BLS Analysis - Interactive, hypothesis-driven exploration of multiple data sets that can be verified and exported. - General accessibility without prerequisite domain knowledge. - Rapid and correct at-a-glance insights.
  10. 10. The Jobs Report is based on the following, national surveys: - Current Population Survey (CPS): surveys households and relates demographic trends to employment and labor force characteristics. - Current Employment Statistics (CES): surveys employers for industry-specific details concerning employment. Additionally, for Census region specific information: - Local Area Unemployment (LAU): household survey that relates state and metro regions with demographic and labor force dimensions. Available Data Sets
  11. 11. The Jobs Report is based on the following, national surveys: - Current Population Survey (CPS): surveys households and relates demographic trends to employment and labor force characteristics. - Current Employment Statistics (CES): surveys employers for industry-specific details concerning employment. Additionally, for Census region specific information: - Local Area Unemployment (LAU): household survey that relates state and metro regions with demographic and labor force dimensions. Available Data Sets
  12. 12. The Jobs Report is based on the following, national surveys: - Current Population Survey (CPS): surveys households and relates demographic trends to employment and labor force characteristics. - Current Employment Statistics (CES): surveys employers for industry-specific details concerning employment. Additionally, for Census region specific information: - Local Area Unemployment (LAU): household survey that relates state and metro regions with demographic and labor force dimensions. Available Data Sets
  13. 13. The BLS Pipeline T. Ojeda, S. P. Murphy, B. Bengfort, and A. Dasgupta, Practical Data Science Cookbook. Packt Publishing Ltd, 2014. Data Ingestion Data Wrangling Data Storage API Front-End Application Overview Zoom & Filter Details on Demand
  14. 14. Data Ingestion - Data challenge I: management of - 1,684 time series ids to fetch from BLS - 305,445 records from Jan 2000 - Feb 2015 - Data challenge II: monthly refresh of data - Solution: lightweight Python wrapper using the BLS API version 2.0 (with API key authentication).
  15. 15. Data Ingestion - Data challenge I: management of - 1,684 time series ids to fetch from BLS - 305,445 records from Jan 2000 - Feb 2015 - Data challenge II: monthly refresh of data - Solution: lightweight Python wrapper using the BLS API version 2.0 (with API key authentication).
  16. 16. Data Ingestion - Data challenge I: management of - 1,684 time series ids to fetch from BLS - 305,445 records from Jan 2000 - Feb 2015 - Data challenge II: monthly refresh of data - Solution: lightweight Python wrapper using the BLS API version 2.0 (with API key authentication).
  17. 17. import blsapi import prettytable if __name__ == '__main__': ## Demo Series series = ['LNS12000000', 'LNS13000000', 'LNS10000000'] result = blsapi.bls_series(series, startyear='2010', endyear='2015') ## Fields fields = ["series id", "year", "period", "value", "footnotes"] ## Pretty print a table of the results for s in result['Results']['series']: table = prettytable.PrettyTable() for item in s['data']: table.add_row([item[k] for k in fields]) print table.get_string()
  18. 18. Data Wrangling - Data challenge 0: Initial BLS IDs? - Data challenge III: BLS APIs come with no meta data associated with them. Data must be parsed directly from the description text. - Data challenge IV: Integration of other data sources and general computation.
  19. 19. Data Wrangling - Data challenge 0: Initial BLS IDs? - Data challenge III: BLS APIs come with no meta data associated with them. Data must be parsed directly from the description text. - Data challenge IV: Integration of other data sources and general computation.
  20. 20. Data Wrangling - Data challenge 0: Initial BLS IDs? - Data challenge III: BLS APIs come with no meta data associated with them. Data must be parsed directly from the description text. - Data challenge IV: Integration of other data sources and general computation.
  21. 21. Web Application and API Application Architecture BLS API PostgreSQL Datastore Ingestion & Wrangling
  22. 22. Multiple Dashboard Interface
  23. 23. On to the Song & Dance (Demonstration)
  24. 24. Usability Testing - 8 participants over 2 studies: 5 research driven tasks and 8 questions. - Users were asked to interact with the application and “think aloud” while researching their tasks. They completed a usability questionnaire on completion. - Results from the study and feedback were incorporated into a prioritized change list.
  25. 25. Future Work - Automatic headline generation to match the time series that are added to the explorer. - Better rate of change handling (specify deltas) or compute differentials across wider ranges of time. - Enhance the choropleth with more details on demand for local data. - Automated ingestion mechanism.
  26. 26. Questions?
  27. 27. http://bit.ly/elmr-video http://bit.ly/elmr-repohttp://elmr.herokuapp.com/ http://bit.ly/elmr-slides

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