OnTheMap: It can do WHAT?

That’s usually the reaction I get when I go full-datageek while telling people about OnTheMap (OTM). The Census Bureau’s  OntheMap application is an interactive web-based tool that visualizes Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) data. LODES provides counts of jobs and workers and information about commuting patterns for areas as small as a census block.

I’ve been using OntheMap since around 2011 and it is by far my favorite labor market data tool. With LODES, you won’t be able to get the level of industry detail or currency of other labor market data sets like the Quarterly Census of Employment and Wages (QCEW) or Quarterly Workforce Indicators (QWI). But for those interested in labor market information at the neighborhood-level and using maps to show patterns of employment, the data source rivals all other public data sources. In fact, it inspired the name of this data blog and influenced its central theme –identifying where the jobs are.

The most novice of OTM users can do some really interesting analyses using the geographies and analysis options available in the application.

Figure 1. OntheMap Application Destination Analysis


Users with some GIS experience can extract shapefile output from OTM to create and format their own maps (Figure 2).

Figure 2. Destination Analysis by City

OTM becomes an even more powerful resource when intersecting LODES with other labor market information. As an example, Figure 3 is a map illustrating unemployment rates by census tract for Baltimore City and surrounding counties available through the American Community Survey (ACS). This unemployment data is overlaid with shapefiles extracted from OntheMap depicting job density and the top 25 work destinations for Baltimore City residents. Alone, these two datasets are robust but their power lies in visualizing the data and interpreting relevant intersections between them.The map allows us to confirm trends that might come as no surprise to us and also observe specific patterns that might have implications for policy. For instance:

  1. There are high concentrations of unemployed residents in inner-city Baltimore compared to other areas,
  2. Jobs in the region are concentrated in Downtown Baltimore and along public transportation lines and the beltway, and
  3. Many Baltimore City workers commute to areas in the surrounding counties for work.

Figure 3. Unemployment Rates, Job Flows and Access to Employment in Baltimore City

Destination Analysis by Census Tract

I’ve recently presented my OTM/LODES maps and analyses at the 2013 LED Partnership Workshop as well as webinars and conferences for the American Evaluation Association, ESRI’s 2013 Mid-Atlantic Users Conference, the Federal Reserve’s 2013 Resilience and Rebuilding for Low-Income Communities Conference, and the Baltimore Neighborhood Indicators Alliance’s (BNIA) Data Day in 2012. I really enjoy exposing newbies to the data and encouraging its use.

However I’m most intrigued with discovering new ways to present the data and using LODES for more complex analyses and advanced methodologies like spatial regression discontinuity and for purposes like evaluating economic development projects and strategies.This can be accomplished by downloading and manipulating the raw LODES from OTM  and/or importing shapefiles for specific areas or neighborhoods for analysis. As an example LODES is the primary data set I’m using in my dissertation to study employment outcomes of tax increment financing (TIF) districts in Baltimore. Figure 4 is a snapshot of how I visualized the raw LODES data and TIF districts to think through my methodology (more on this to come).

Figure 4. Spatial Analysis of TIF Districts in Baltimore City

Tips and Techniques

The possibilities can be endless for posing and answering complex questions using LODES and OntheMap. Check back for other posts about this data set and visualization tool.

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