Using ICPSR's New Deposit Form

Use a clear, specific title that includes:

• What the study is about (topic, population, or method). Capitalize major words and avoid vague titles like “Survey Data” or “Research Project.”
• Where the study covers (city, state, country, or Global if truly worldwide).
• What time period the study covers (e.g., 1999; 2001-2003; 1999, 2010, 2015; include months only to distinguish repeated releases). Match the time period to what the data describe (not necessarily when they were collected).

Enter an alternate title for the data collection if users might search for it using an acronym or shortened version of the name.

When the PI is a person:

• Use “Search for a Person” to enter the name, affiliation, and ORCID ID that appear in the person’s ORCID profile.
• If you can’t find an ORCID ID for a PI, enter their full name the way it appears in publications or their curriculum vitae. Enter middle names and initials in the Given Name field and suffixes (e.g. Jr., III) in the Family Name field.
• Enter the PI’s affiliation as it appears in the Research Organization Registry (ROR). If the organization doesn’t have a ROR ID, use its full name, avoid acronyms, and do not include departments or colleges.
• Enter a PI’s affiliation at the time the research was conducted.

When the PI is an organization:

• Enter the organization as it appears in the Research Organization Registry (ROR). If the organization doesn’t have a ROR ID, use its full name and avoid acronyms.

ICPSR encourages using ORCID and ROR whenever possible and may revise Principal Investigator fields to add these values.

• Whenever possible, enter the organization’s name as it appears in the Research Organization Registry (ROR).
• Enter the name without any organization hierarchy, for example, “National Institute on Aging” instead of “United States Department of Health and Human Services. National Institutes of Health. National Institute on Aging”.
• If the organization doesn’t have a ROR, use its full name and avoid acronyms.
• Whenever possible, include a unique identifier for the funding award. This can be a grant number; a URL, preferably a persistent one like a digital object identifier (DOI); or both.

• Clearly describe what the study is about – even if this information is already in your study documentation.
• Write in the third person.
• Use past tense to describe how the data were collected. Use present tense to describe the data themselves.
• Avoid discussing potential uses, target audiences, or the value of the data.

• Choose subject terms from the ICPSR Subject Thesaurus that describe the topic of your data. 
• Considerations for choosing subject terms:
  • What is the study about?
  • What would an ICPSR user interested in these data search for?
  • What subject terms are used for similar studies in ICPSR’s catalog?
• You might need to combine terms to describe your topic, for example, “mothers” and “health” for “maternal health.”
• You can also add subject terms in two other fields: JEL Classification Codes (for economics topics) and MeSH Terms (for health and biomedical topics).
• Do not add terms for concepts that are described in other fields, like geography and methodology.
• If existing terms do not adequately describe the study’s topic, email suggested new terms to icpsr-help@umich.edu for possible addition to the ICPSR thesaurus. Most new terms come from the Library of Congress Subject Terms or other social science controlled vocabularies.

• Add JEL classification codes if you are depositing your data with the Western Economic Alliance International (WEAI) Data and Code Repository or the American Economic Association (AEA) Data and Code Repository.
• You may also add JEL classification codes to data related to economic research deposited in any archive.

• Add MeSH terms if your data are related to health or health care, including clinical care, mental and behavioral health, and public health.
• Health conditions, medicines, health care occupations, or disciplines related to your data are good candidates for MeSH terms.

• Specify the time periods covered by the data, rather than the dates of data collection.
• Use the Start Date and End Date fields to specify the years and, optionally, months and days, covered by the data.
• If the study title contains years, they should match the years in the Time Periods dialog box.
• Use the Time Frame field only if needed to add context or when the date cannot be expressed exclusively in numbers.

• Select a value only for studies that use a probabilistic study sample designed to represent an entire nation.
• Describe the sampling strategy in more detail in the Sampling Note and Sampling Procedures fields.
• If your data do not use a sample or you are unsure, leave this blank.

• Select the country, state, city, county, region, or continent covered by the study.
• Spell out place names completely instead of using acronyms. For example, enter “United States” instead of “USA.”
• Type at least four characters to see matches.
• Choose only the narrowest level of geographic coverage. For example, if you select “Los Angeles, California, United States,” do not also add “California, United States” and “United States.”
• For studies with participants from around the world or that are applicable everywhere, select “Earth.”

• Choose a value only if the data contain a geographic variable that can be used for analysis, for example, the state or county where participants live.
• Do not select a value if the data are all from the same place and not further divided up by geography. For example, if the study took place in New York City, but there are no other geographical variables in the data, leave this field blank. Do not select “City.”
• You can enter geographic units that do not appear in the drop-down list. Do this only when the data contain a specific geographic variable that does not appear in the list, such as local court districts or school catchment areas.

• Use this field, if needed, to provide more information about the study design than the summary.
• Possible topics include survey design, interview methods, how data were obtained, and follow-ups to respondents.

• Describe the study’s target population in a short phrase or sentence.
• Identify the characteristics that determine inclusion in the study. For studies about people, this might be age, nationality, residence, or demographic characteristics.
• The universe can also consist of things other than people, such as households, organizations, or geographic units.

• Use this field to indicate if and how the data collection repeated over time.
• You can enter time methods that do not appear in the drop-down list. Do this only when the data contain a specific time method that does not appear in the list.

• In quantitative data, units of analysis often correspond to rows or observations in a dataset.
• You can enter units of analysis that do not appear in the drop-down list. Do this only when no applicable option is available. For example, if the unit of analysis in your data collection is college students, choose “Individual”; do not enter “college students.”
• You can choose more than one unit of analysis. For example, if data about individuals contain multiple observations over time, choose both “Individual” and “Time Unit.”

• Use this field to describe how the units of analysis in your data were selected from the universe or population of interest.
• You can describe the sampling strategy in more detail in the optional Sampling Note field.
• You can enter sampling procedures that do not appear in the drop-down list. Do this only when the data collection uses a specific, known sampling strategy that does not appear in the list.
• If the sampling procedure resulted in a nationally representative sample, indicate this in the Nationally Representative Sample field.

• Briefly describe the methodology used to select participants from the universe or population of interest.
• In addition to completing the Sampling Note, use the Sampling Procedures field to describe the sampling strategy using standardized language.
• A detailed discussion of such things as sampling error or other limitations of the sampling methodology is not required here.

• Give the name of any weighting variables in the data and explain when they should be used.
• If weights are described in documentation provided with the data, indicate where that information can be found.

• Fill out this field only if the data were collected with a survey instrument and the response rates are provided.
• For longitudinal data, describe the response rate across waves of data collection.

• Use this field to describe what the data are derived from, not their current form.
• People, things, and other data can all be data source types.
• You can enter data source types that do not appear in the drop-down list. Do this only when no applicable option is available; select from the list whenever possible. For example, if the data are derived from birth certificates, choose “Registers/Records/Accounts: Administrative”; do not enter “birth certificates.”
• You can provide more information about the data sources in the External Data Sources field.

• Cite any websites, datasets, books, journal articles, or other sources used to compile the data.
• At minimum, include the title, author, publication year, and journal (if applicable) of each external data source. Optionally, describe how each data source was used to create or compile the data.
• For online sources, include the URL to access the data. A persistent identifier such as a digital object identifier (DOI) is preferable whenever possible.
• Any citation format is accepted.

• Use this field to indicate how data were collected using standardized terminology.
• Select the most specific value that applies to the data. For example, if data were collected via computer-assisted telephone interview, select “Telephone interview: Computer-assisted (CATI)” rather than “Telephone interview” or “Interview.”
• You can enter collection modes that do not appear in the drop-down list. Do this only when no applicable option is available.
• For studies that collected data in more than one way, select all collection modes that apply.

• Collection Dates refer to when data collection occurred, while Time Periods describe when the data refer for. For example, for data about population growth between 1950 and 2000 collected in 2020, the collection date would be 2020.
• Enter dates in YYYY-MM-DD, YYYY-MM, or YYYY format.
• Use the Collection Time Frame for non-numeric dates (e.g., Fall 2018) or to provide context on the collection date (e.g. “Wave 3” in a longitudinal data collection). Do not restate the date in words.

• Use this field to provide more detailed information than the Summary, including a review of variables that are important for users to know about.
• List the key topics or groups of variables covered in the data collection.

• Scales are shared measurement tools that combine multiple variables or data elements into a single score. Common examples include the Minnesota Multiphasic Personality Inventory (MMPI), the Consumer Price Index (CPI), and the Beck Depression Inventory.
• Provide a citation for each scale whenever possible. At minimum, include the title, author, publication year, and journal (if applicable). Include a DOI or URL if one is available.
• Cite scales as a list or describe them in full sentences.
• If the data contain Likert scales, it is allowed but not necessary to note them here.

• Cite any published articles, reports, preprints, presentations, or other works that analyze, critique, or discuss the data and its collection process or methodology.
• Exclude publications that mention, but do not analyze, the data collection.
• For online resources, include the URL to access the publication. A persistent identifier such as a digital object identifier (DOI) is preferable whenever possible.
• If a DOI is available, use the Import via DOI option to enter publication details. If the publication does not have a DOI, select “Manually Enter Citation” to provide the title, author, publication date, and other information manually.

• Some funding agencies require grant recipients to follow a data management plan for sharing data. Sites like DMPTool and DMPonline support creating and publishing data management plans. Use this field to provide a link to a published data management plan.
• Only URLs can be entered in this field. To provide a copy of a data management plan that is not available online, upload it along with the data and documentation.

• Preregistration lets researchers publicly share hypotheses and data analysis plans before data collection begins. Sites like the Open Science Framework and the AEA RCT Registry support preregistering studies and sharing plans publicly.
• Only URLs can be entered in this field. To provide a copy of a preregistration that is not available online, upload it along with the data and documentation.

• Use the fields in this dialog box for data collections that include code or depend on an uncommon or custom application.
• If the data can be analyzed with commonly available statistical software, this field is usually not needed.
• Provide as much information about the software application as is needed to access and run it. Depending on the application, this may include a version, download link, operating system information, and shared libraries.

• Use this field to indicate broadly whether the data contain numeric information, text, images, software code, or some other format.
• Select more than one value for data collections with multiple formats, for example, a mixed methods study that includes survey responses (Numeric) and interview transcripts (Text).

• Use this field to provide any additional information that users need to know about the data collection.
• Linking to a project website in a note is acceptable. However, links break and websites change over time. To ensure that users will be able to understand the data collection long into the future, include key details in the appropriate fields or in the documentation.

• Most archives have collection criteria that determine what type of data collections can be deposited. To learn more about archive collections, see Thematic Data Collections at ICPSR.
• The archive you select determines whether the data collection can be curated or self-published.
• If you are not sure, select “Inter-university Consortium for Political and Social Research.” Our team at ICPSR will review the submission and make sure it gets in the right hands.

• To recognize personally identifiable information, consider: if the data were made public, could someone find individuals through direct or indirect identifiers?
• Currently, ICPSR’s single stream deposit form can be used only for data collections that do not contain personally identifiable information. Data containing personally identifiable information can be deposited with ICPSR’s legacy deposit form.
• For more information about identifying information and how to recognize it, see ICPSR’s Approaches to Confidentiality.

• To recognize sensitive information, consider: if the data were made public, would that create a risk of harm (e.g., psychological distress, social embarrassment, financial loss) greater than the risk that people experience in everyday life?
• Currently, ICPSR’s new single stream deposit form can be used only for data collections that do not contain personally identifiable information. Data containing personally identifiable information can be deposited with ICPSR’s legacy deposit form.

If you would like to delay public release of your data, please enter an embargo release date. The embargo period may be set for up to three years from the date of your submission. After this date, your data will automatically become publicly available.

• Fill out this field only for deposits to archive collections supported by journals, such as the American Economic Association (AEA) Data and Code Repository.
• Include details about the related article in the Data-related Publications field.

For guidance on making your deposit accessible, see Depositor Guidelines for Sharing Accessible Study Materials using ICPSR.

• Depositors select from a variety of licenses to distribute their data, including Creative Commons licenses and a Public Domain Mark.
• Available software licenses include: Apache License 2.0; BSD 2-Clause “Simplified” or “FreeBSD” License; BSD 3-Clause “New” or “Revised” License; GPL 3.0; LGPL 3.0; MIT License; Mozilla Public License 2.0; Common Development and Distribution License; and the Eclipse Public License.
• If depositors would like to use multiple licenses or create a customized license, they may upload a LICENSE file alongside the data and documentation within the project workspace.
• ICPSR requires a license for the distribution of data, but copyright remains with the author.