FCSM Research and Policy Conference

Modernizing Data Dissemination

Clayton Waring

Senior Economist

BLS Office of Productivity and Technology

November 4, 2021

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Data Dissemination

Make it as easy as possible for people to find and use data that is of interest to them.

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Data Repository

Technology

Structure for Storing and Organizing Data

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Stuff

Easy and Intuitive

Bedroom Dresser

Kitchen Cabinet

Bookshelves

Garden Shed

Parking Garage

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Stuff

Bedroom Dresser

All clothes share certain common characteristics that define them as clothes

Kitchen Cabinet

All dishes share certain common characteristics that define them as dishes

Parking Garage

All vehicles share certain common characteristics that define them as vehicles

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Stuff

The method by which items are stored and organized depends on the common characteristics and attributes found in the items being stored.

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Stuff

Items are grouped together based on shared commonalities, and items are separated based on their differences.

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Statistical Data

At some basic, fundamental level storing and organizing statistical data shouldn’t be any different than storing and organizing  clothes in a dresser, dishes in a cabinet, or cars in a garage.

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Statistical Data

What are the common characteristics and attributes found in all statistical data?

What is the definition of statistical data?

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Statistical Data

Time Series: A set of numbers that represents the change over time in some measurable aspect of people, places, and things.

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Statistical Data

Time Series Elements

Measures

People, Places, and Things

Time

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Statistical Data

Measures

Represented by numeric value

Employment, wages, prices, productivity, injuries, expenditures, value of shipments, etc.

May increase and decrease over time

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Statistical Data

People, Places and Things

Establishments (labor, capital, materials, output, etc.)

Households (people, property, belongings, etc.)

Occupation, Demographic, Industry, Geography, Goods and Services, etc.

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Storing and Organizing Statistical Data

Time

Past, present, and future

Frequency of observation

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Statistical Data

Time Series

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Measure

People, Places, and Things

Statistical Data

Time

Pattern of Information
|                            |            |                  |
|----------------------------|------------|------------------|
| People, Places, and Things | State      | North Carolina   |
|                            | Industry   | Hospitals        |
|                            | Occupation | Nurses           |
| Measure                    | Measure    | Employment Level |
|                            | Unit       | Thousands        |
| Time                       | Year       | 2021             |
|                            | Month      | November         |

How many thousands of nurses are currently employed at hospitals in North Carolina?

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Data Query

Three Independent Pathways Can be Used to Locate All Data

Measures

Commonalities and differences across data

People, places, and things

Commonalities and differences across data

Time

Commonalities and differences across data

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Old Versus New

Statistical Data

Data

Metadata

Statistical Data

Measures

People, places, and things

Time

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Assign Values to People, Places, and Things

Dave

Weight

Car

Speed

Beach

Temperature

House

Size

Doctors in Virginia

Average salary

Men in U.S. over age 50

Employment rate

Shirts in Pittsburg, PA

Consumer prices

U.S. Manufacturing Sector

Productivity

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Advantages

Easy and intuitive to understand

Highly scalable and flexible

Integrate data from multiple sources

‹#› — U.S. Bureau of Labor Statistics • bls.gov

Clayton Waring

Senior Economist

www.bls.gov/lpc

202-691-5644

waring.clayton@bls.gov

Contact Information

‹#› — U.S. Bureau of Labor Statistics • bls.gov

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