application/vnd.openxmlformats-officedocument.spreadsheetml.sheet

cb_nscg2019_frcgc.xlsx

cb_nscg2019_frcgn.xlsx

cb_nscg2019_i_icg.xlsx

cb_nscg2019_frscg.xlsx

cb_nscg2019_icg.xlsx

The National Survey of College Graduates (NSCG) began in 1993 and has been conducted biennially to provide individuals, educational institutions, businesses and the Federal Government with the information they need to make important decisions. The survey provides data on the number and characteristics of individuals with a bachelor's or higher degree, with a special focus on individuals with education and/or employment in science or engineering. The survey includes age, educational history, citizenship, disability status, occupational/employment information, race and ethnicity, salary sex, student loan debt, job satisfaction and work-related training. It samples individuals who are living in the United States during the survey reference week, have at least a bachelor's degree, and are younger than 76.

National Survey of College Graduates

Includes educational institution identifiers for degrees earned and state-level identifiers for residency and employer location, which are not available on the PUF. Values of salary and income are rounded and top-coded on the PUF.

Designates the primary owning agency for these data/this metadata record.

ID assigned by agency, unique within agency's catalog (note, if no ID exists, you can choose to number consecutively).

Acronym or other title by which the dataset/data file is commonly known.

Is data part of a larger "grouping" of datasets/data files (separate inventory entries that should be related together under one umbrella)?

Title for larger grouping to which this asset belongs.

Descriptive summary of what is contained in the data.

Agency’s preferred citation for data asset.

Agency(ies) responsible for making the data available.

Website that describes the data collection generally.

All agencies/organizations that need to approve applications for these data.

Agency(ies) responsible for funding data collection -- may be the same or different than source.

Website that describes these restricted data more thoroughly.

Earliest to most recent data collection dates requestable for this data asset. If data collection goes back to 1900 but digital data are available beginning in 1998, use 1998. This should be the entire time span available, even if data were not collected for all years in the span. Data collected in 1998, 2000, 2002, and 2003 would be recorded as 1998-2003.

What is the smallest geographical unit about which descriptions can be made? The data may be able to be aggregated up to higher levels, this is just the lowest level a user would be able to describe. This field does not apply for data without geographical information.

Group to whom the data can be generalized. Can be described inclusively or exclusively.

Largest geographic area to which the data can be generalized. Can be described inclusively or exclusively (e.g., national, the state of Michigan, not generalizable).

What does a "case" (row) represent? If a college/university is reporting on its faculty/staff/students, for example, the unit of observation is the institution (school) because everything is a characteristic of that institution. Some data assets might have multiple units of observation.

Best way to classify or describe the predominant subject matter.

Information about the number of units included, how the sample was selected, what sampling frame was used, etc.

How were the data collected/what was the source of the information?

How often does this data collection occur?

Additional information about the methodology that is not captured elsewhere but would be useful for a potential user.

What is the reference period for questions in the survey (e.g., hours worked in the last month or last week…)?

Number of cases/observations in the data. This is to give users a rough idea of the size of the dataset -- it does not have to be exactly precise, but users often want to know some idea of "scale" (e.g., 100 cases or 1 million cases?).

Number of variables (columns) in the dataset to give users a quick sense of whether the dataset contains many variables or just a few.

Describe any fees to access these data -- can be "generic language" (e.g., there might be a fee of up to $xxx for accessing these data) or a range, however the agency typically describes access fees.

URL from which users can apply for the data asset. An email address may be provided if there is no URL.

Information on any limitations to use or file access (e.g., sensitive topics, certain subgroups).

Is there a public use version of these data available?

Website that provides information about and access to the PUF.

Does the lowest level of geography available in the PUF differ from that in the restricted data that are the focus of this metadata record?

Do (any) variables in the PUF contain less detail than is available in the restricted data that are the focus of this metadata record?

Can the public use version of these data be added to an application.

Does the application for these data need to include questions related to federal tax information.

What is the level of restriction for accessing these data?

If user needs to choose state(s) as the provisioning unit, which states are available?

Delimited list of geographic entities from which a user can select if not state.

If user needs to choose month(s) as the provisioning unit, which months are available.

Start and end years of data availability. If availability is not continuous, please use "provisioned by other time unit" field.

Delimited list of time units from which a user can select if not month or consecutive years (e.g., 3- or 5-year groups).

Delimited list of provisionable data the user can select if not time or geography.

Can non-citizens apply to use these data?

Is the user required to provide a list of variables they would need from the data?

Filenames of documentation that should be presented as part of the application for users requesting this asset, likely for users to download, fill out, and reupload. This includes dataset-specific RDUAs and lists of variables for selection.To upload Application Documentation please visit https://sap.researchdatagov.org/rdg/admin

Contextual message to indicate field entry.

The Administrative Data Research Facility (ADRF) is a secure cloud-based computing platform designed to promote collaboration, facilitate documentation, and provide information about data use to the agencies that own the data. The ADRF has provided secure access to over 100 confidential government datasets from 50 different agencies at all levels of government. More information on ADRF is available at https://coleridgeinitiative.org/adrf/.

Remote access to restricted-use data at the authorized licensed location via the the Administrative Data Research Facility (ADRF) by a connected, networked computer.  

Researchers may access restricted-use National Center for Health Statistics (NCHS) data at Research Data Centers (RDCs) located in Hyattsville, MD, Atlanta, GA, Rockville, MD, and Washington DC (government employees only). The NCHS RDCs are open by appointment only during regular business hours. The NCHS RDC computers are not connected to the Internet, and they have standard statistical software. An RDC Analyst will review all materials brought into the RDC and will review any notes, code, or output the researcher may want to take out of the RDC. Electronic devices (e.g., cell phones and laptops) are not permitted in the RDC. Some NCHS projects are authorized to access NCHS data at Federal Statistical RDCs (FSRDC). Non-US Citizens: In general, non-US citizens are not granted access to NCHS RDCs and are encouraged to use Federal Statistical RDCs to access restricted-use NCHS data.

Access via physical data enclaves in Atlanta, GA; Hyattsville, MD; Rockville, MD; or Washington, DC (government employees only).

NCSES Secure Data Access Facility (SDAF) houses NCSES restricted-use data and provides secure remote access to researchers. After researchers have submitted a restricted-use data application, received approval from NCSES, and have been trained on how to use the SDAF, they can login using an approved computer and a private internet connection. Each researcher has access to their own, personal file space and to a suite of software that can be used to store, access, and analyze data. For more information on accessing NCSES restricted-use data, please visit https://ncses.nsf.gov/about/licensing. 

The NCSES Secure Data Access Facility is a virtual data enclave where approved researchers access NCSES restricted-use data.

USDA offers offsite remote access via a secure internet connection using the researcher’s own computer and web browser to approved datasets for data analysis within the Data Enclave. Each researcher has access to their own personal file space and to a suite of software that can be used to store, access, and analyze data.

Remote access through a virtual data enclave.

Access via a physical data enclave at the Social Security Administration in Washington, DC.

The ICPSR physical data enclave is located in the Perry Building on the campus of the University of Michigan.

Access via the physical data enclave at ICPSR in Ann Arbor, MI.

The ICPSR virtual data enclave allows users access to restricted data via their own computers using a virtual desktop. 

Remote access through ICPSR`s virtual data enclave.

Data can be used by the researcher(s) at their institutions via a method and following requirements set by the agency owning the data. These might include a non-networked computer, a secure office, or other provisions deemed necessary to ensure security.

Data can be used at the user`s institution following the license agreement.

Researchers share four secure workstations at BEA’s headquarters at the Suitland Federal Center in Suitland, MD. Workstation use is by appointment only. Due to pandemic-related restrictions that currently prevent access at the physical data enclave, BEA is temporarily providing access at the user`s domicile. A security clearance is required to access the BEA network. 

Access via a physical enclave at BEA`s headquarters in Suitland, MD.

BLS Onsite access is available in a researcher room at the BLS national office in Washington, DC.  Researchers with approved projects can reserve time during normal business hours to use BLS workstations connected to an internal server where all data and project files are stored.  More information is available at www.bls.gov/rda/onsite-at-bls.htm. 

Access via a designated researcher room at the BLS national office in Washington, DC.

BLS offers offsite limited remote access to restricted data through a Virtual Data Enclave for two survey files:  NLSY Geocode and CFOI-Masked data.  More information is available at www.bls.gov/rda/offsite.htm. 

Remote access to limited restricted-use data through a virtual data enclave. 

Federal Statistical Research Data Centers (FSRDCs) are Census Bureau facilities, housed in partner institutions, that meet all physical and information security requirements for access to restricted–use micro data of the agencies whose data are accessed there. Remote access via secure Virtual Desktop Interface (VDI) is permitted for researchers working with selected data, at the discretion of the data-owning agency. All FSRDC researchers must obtain the Census Bureau`s Special Sworn Status and successfully complete a thorough background investigation prior to accessing an RDC.

Federal Statistical Research Data Centers (FSRDCs) are Census Bureau facilities, housed in partner institutions, that meet all physical and information security requirements for access to restricted–use micro data of the agencies whose data are accessed there.

Remote access to the IRS network via a secure VPN line using a government laptop issued and configured by IRS IT.

Remote access to the IRS network via secure VPN line using government laptop issued and configured by IRS IT.

Access at IRS Headquarters, Submission Processing Center, or other satellite (field) offices.

National Survey of College Graduates

Description

Metadata: Identification and Summary