The Evolving Nonprofit Sector Data Infrastructure

A demonstration of reproducible workflows with nonprofit data for the ARNOVA Conference 2024.

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SLIDES

Nonprofit Data Packages

Packages used in the demo script:

# install.packages( "devtools" )
devtools::install_github( "Nonprofit-Open-Data-Collective/peopleparser" )
devtools::install_github( 'nonprofit-open-data-collective/titleclassifier' )
devtools::install_github( 'nonprofit-open-data-collective/fiscal')
devtools::install_github( 'nonprofit-open-data-collective/irs990efile')

If you are having problems downloading packages try:

# options( download.file.method = "wininet" )    # for windows
# options( download.file.method = "libcurl" )    # for all op systems

Some Useful Nonprofit Packages • Nonprofit Open Data Collective on GitHub

We also use the following R packages in the demo script:

package.list <- 
  c( "tidyverse",
     "knitr", "pander",
     "ggrepel", "RecordLinkage",
     "data.table", "reshape2",
     "utils" )

install.packages( package.list )

Workflow Demo

WORKFLOW EXAMPLE

1. Build tables using the irs990efile package.
2. Standardize names of the leadership team present in Part VII (the compensation tables) using the peopleparser package.
3. Standardize titles in Part VII using the titleclassifier package.
4. Identify CEO transition years within the data.
5. Build a financial dataset by combining the following 990 Parts: revenues, expenses, and assets.
6. Generate common financial operating ratios using the fiscal package.
7. Add NTEE codes and standardized address fields from the Unified BMF.
8. Merge financial tables and compensation tables into a single table for the analysis.

# REPRODUCIBLE WORKFLOWS
library( dplyr )
library( data.table )

nodc <- "https://raw.githubusercontent.com/Nonprofit-Open-Data-Collective/"
repo <- "arnova-2024/refs/heads/main/"
file <- "functions.R"
source( paste0( nodc, repo, file ) )

hd.2016 <- get_table( "F9-P00-T00-HEADER", year=2016 )
p1.2016 <- get_table( "F9-P01-T00-SUMMARY", year=2016 )
bmf <- get_bmf()

df <- merge( hd.2016, p1.2016, by="URL", all=TRUE )
df <- merge( df, bmf, by="EIN2", all.x=TRUE )

NCCS CORE Panel

Sector in Brief Dashboard

The Nonprofit Sector in Brief Dashboard aggregates more than three decades of NCCS data to illuminate trends in the nonprofit sector. The dashboard currently provides data up to 2021 and will be continuously updated with the most recent available data. View data and trends by organization type, subsector, asset size, geography, and time period to see a snapshot of the nonprofit sector as seen through IRS data.

NCCS data catalog:

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