These data extracts were obtained by CISER from the National Center for Charitable Statistics in December 2008. They contain only public charities located in New York State for the years 2004, 2005, and 2006.

The data produced by NCCS are intended for use by researchers and policy-makers in their quantitative analyses, and as a springboard for more in-depth survey or case study research.

The NCCS Core files are based on the Internal Revenue Service's annual Return Transaction Files (RTF). They contain data on all 501(c)(3) organizations that were required to file a Form 990 or Form 990-EZ and complied. The IRS does not keypunch financial data for approximately 80,000 organizations that filed Form 990 but that were not required to do so because they had less than $25,000 in gross receipts or are congregations. NCCS also excludes a small number of other organizations, such as foreign organizations or those that are generally considered part of government.

Comprehensive dataset containing 74 verified NCCS Drop Box Only locations in United States with complete contact information, ratings, reviews, and location data.

Recent years have seen a dramatic rise in donor-advised funds (DAFs). Though housed in public charities, DAFs are often characterized as de facto private foundations due to the deference sponsors typically give to donors’ wishes. The consequence has been frequent calls to institute DAF grant disbursement requirements and other restrictions akin to those on foundations. Despite their growing importance, we know little about what distinguishes different DAF sponsoring organizations beyond a commonly used three-type split between community foundations, national sponsors, and single-issue sponsors. To better understand variation in behavior across DAF sponsoring organizations – which may, in turn, be driven by the donors they attract – we develop a proxy measure of the priorities they display in the language they use on their websites. The measure seeks to identify the extent to which a sponsor emphasizes achieving charitable objectives versus providing extrinsic benefits to donors. In addi..., Data collected consists of elements from: IRS Nonprofit 990 Database; NCCS Exempt Organizations Business Master File; website search Data processing and analysis described in the README file, , # Charitable Objectives or Donor Benefits? What Sponsor Language Reveals about Donor-Advised Fund Priorities and Resource Flows

https://doi.org/10.5061/dryad.6wwpzgn8r

Description of the data and file structure

Each file uploaded to Dryad has a corresponding Data Description file which lists and describes the variables.

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DATA FILE PRODUCTION

Files in bold text represent the publicly provided final data files and Stata code.

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1. DOWNLOAD RAW NONPROFIT RETURNS FROM IRS

Process: Manual process

URL: Â Â Â Â https://www.irs.gov/charities-non-profits/form-990-series-downloads

Outputs: Individual XML files of nonprofit annual 990 returns

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**2. DOWNLOAD EXEMPT ORGANIZATIONS BUSINESS MA...,

These quarterly reports show the number of receipts, dispositions and pending New Court Cases (NCCs) during the defined period. The data shown is by month with quarterly and fiscal year (FY) summaries through the most recently completed quarter.

As of 2019, about ** percent of households across India were segmented as belonging to the NCCS C category of consumers. Contrariwise only **** percent of the country's population fell under the NCCS E category that year. Between 2014 and 2019, the share of population classified as category A, B, and C consumers has grown tremendously, reflecting the trajectory of the booming middle class within the Indian economy.

The Global Landslide Catalog (GLC) was developed with the goal of identifying rainfall-triggered landslide events around the world, regardless of size, impacts or location. The GLC considers all types of mass movements triggered by rainfall, which have been reported in the media, disaster databases, scientific reports, or other sources. The GLC has been compiled since 2007 at NASA Goddard Space Flight Center. This is a unique data set with the ID tag “GLC” in the landslide editor. This dataset on data.nasa.gov was a one-time export from the Global Landslide Catalog maintained separately. It is current as of March 7, 2016. The original catalog is available here: http://www.arcgis.com/home/webmap/viewer.html?url=https%3A%2F%2Fmaps.nccs.nasa.gov%2Fserver%2Frest%2Fservices%2Fglobal_landslide_catalog%2Fglc_viewer_service%2FFeatureServer&source=sd To export GLC data, you must agree to the “Terms and Conditions”. We request that anyone using the GLC cite the two sources of this database: Kirschbaum, D. B., Adler, R., Hong, Y., Hill, S., & Lerner-Lam, A. (2010). A global landslide catalog for hazard applications: method, results, and limitations. Natural Hazards, 52(3), 561–575. doi:10.1007/s11069-009-9401-4. [1] Kirschbaum, D.B., T. Stanley, Y. Zhou (In press, 2015). Spatial and Temporal Analysis of a Global Landslide Catalog. Geomorphology. doi:10.1016/j.geomorph.2015.03.016. [2]

Rscript for figure generation and data analysis:

GenerateFigures.R

Seurat objects containing processed data after quality control:

NCCS_For_Zenodo.RDS - NCCS discovery cohort.

Pavia_For_Zenodo.RDS - Pavia validation cohort.

RDS files containing DEGs or differentially abundant surface markers:

TestResults2Groups.rds - Cell type specific LTR vs Non Responder DEG

TestResults2GroupsADT.rds - Cell type specific LTR vs Non Responder differential surface markers

TestResults2GroupsLungOnly.rds - Cell type specific LTR vs Non Responder DEG on lung samples only

TestResults2GroupsLungOnlyADT.rds - Cell type specific LTR vs Non Responder differential surface markers on lung samples only

TestResults3Groups.rds - Cell type specific LTR vs R vs Non Responder differential DEG

TestResults3GroupsGeneralADT.rds - Across cell type LTR vs R vs Non Responder differential surface markers

TestResults2GroupsGeneralRNA.rds - Across cell type LTR vs Non Responder DEG

TestResults2GroupsGeneralADT.rds - Across cell type LTR vs Non Responder differential surface markers

TestResults2GroupsLungOnlyGeneralRNA.rds - Across cell type LTR vs Non Responder DEG on lung samples only

TestResults2GroupsLungOnlyGeneralADT.rds - Across cell type LTR vs Non Responder differential surface markers on lung samples only

TestResults3GroupsGeneralRNA.rds - Across cell type LTR vs R vs Non Responder differential DEG

TestResults3GroupsGeneralADT.rds - Across cell type LTR vs R vs Non Responder differential surface markers

Logistic regression models trained on the NCCS discovery cohort:

PerCellPredictions

PerCellPredictions_2Groups_LungOnly

PerCellPredictions_2Groups_

The Global Landslide Catalog (GLC) was developed with the goal of identifying rainfall-triggered landslide events around the world, regardless of size, impacts or _location. The GLC considers all types of mass movements triggered by rainfall, which have been reported in the media, disaster databases, scientific reports, or other sources. The GLC has been compiled since 2007 at NASA Goddard Space Flight Center. This is a unique data set with the ID tag “GLC” in the landslide editor. This dataset on data.nasa.gov was a one-time export from the Global Landslide Catalog maintained separately. It is current as of March 7, 2016. The original catalog is available here: http://www.arcgis.com/home/webmap/viewer.html?url=https%3A%2F%2Fmaps.nccs.nasa.gov%2Fserver%2Frest%2Fservices%2Fglobal_landslide_catalog%2Fglc_viewer_service%2FFeatureServer&source=sd To export GLC data, you must agree to the “Terms and Conditions”. We request that anyone using the GLC cite the two sources of this database: Kirschbaum, D. B., Adler, R., Hong, Y., Hill, S., & Lerner-Lam, A. (2010). A global landslide catalog for hazard applications: method, results, and limitations. Natural Hazards, 52(3), 561–575. doi:10.1007/s11069-009-9401-4. [1] Kirschbaum, D.B., T. Stanley, Y. Zhou (In press, 2015). Spatial and Temporal Analysis of a Global Landslide Catalog. Geomorphology. doi:10.1016/j.geomorph.2015.03.016. [2]

These quarterly reports show the number of receipts, dispositions and pending New Court Cases (NCCs) during the defined period. The data shown is by month with quarterly and fiscal year (FY) summaries through the most recently completed quarter. Report for FY 2022 (53 weeks).

This data was used to create the Economic Development Department's 2016 Creative Economy Snapshot Report available at http://www.austintexas.gov/page/creative-development. Data was compiled by the CreativeVitality Suite from a variety of sources including Occupations & Demographic: Economic Modeling Specialists International, Industry Sales: Economic Modeling Specialists International, State Arts Agency Grants: National Assembly of State Arts Agencies (Final Descriptive Reports), Nonprofit Revenues: National Center for Charitable Statistics, NCCS. This product has been produced by the Economic development Department of the City of Austin for the sole purpose of informational reference. No warranty is made by the City of Austin regarding specific accuracy or completeness.

Climate and hydrological indices for Norway averaged over the period 1991–2020, derived from SeNorge2018 version 20.05, NORA3, KlimGrid and the HBV model with the atmospheric reference data (“est.obs.”) as input. The dataset is produced by the Norwegian Water Resources and Energy Directorate (NVE) and the Norwegian Meteorological Institute (MET Norway) for the Norwegian Centre for Climate Services (NCCS), as part of the NCCS report “Climate in Norway" version 2025 (Dyrrdal et al., 2025). The data can be used as a “current climate” reference for projected future changes. Data produced by the Norwegian Centre for Climate Services is free of charge and can generally be used without restriction for both commercial and non-commercial purposes. Exceptions to this principle apply in cases of customized deliveries, dissemination of data produced by partners, or when specific delivery guarantees are required. Errors and missing data may occur. The Norwegian Centre for Climate Services provides no guarantees regarding the timeliness of the information and accepts no responsibility for any incorrect or misleading information that the data may produce. If you discover any errors or missing data, please contact the Norwegian Centre for Climate Services.