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PSI Data Use and Authorship Proposal

The purpose of the PSI Data Use and Authorship Proposal is:

1. To make PSI's data accessible to external users while protecting PSI's proprietary intellectual property; and
2. To ensure appropriate acknowledgment of programmatic and research contributions to written materials based on PSI data.
Individuals wishing to analyze PSI data and compose written materials based on PSI data are required to complete this online application form. Upon submission of this form, an email request will be sent to the Evidence department at PSI to process the request. If you do not receive a reply within one week (5 business days) of submitting the form, please contact Lee-Ann Gallarano at

For purposes of this application form, "PSI data" shall include, but not be limited to, recorded data and supporting documentation, regardless of form or the media on which it may be recorded, which PSI has the authority to make available to the applicant for the research or other purposes identified in this application form. All PSI data is proprietary to PSI and confidential.  [Note: All data transmitted by Strategic Research and Evaluation to external parties will be de-identified; that is, no direct or indirect identifiers of research participants are included in the data sets. These include names and addresses.]

Proposals will be reviewed by Strategic Research and Evaluation. Before the application will be considered, the applicant must agree, on his/her behalf and on behalf of the Collaborators and/or Co-authors listed in the Proposal(s), to the Stipulations for Use of PSI Data, Pledge of Confidentiality, and PSI Authorship Guidelines. The director of the local PSI office or PSI Global Network member that collected the data must approve the PSI Data Use and Authorship Proposal. Only proposals for specific, well-defined research projects with finite time frames will be considered.

Although PSI strives to make its research accessible, please note that older studies (published in 2012 or earlier) may be missing raw datasets. We apologize for any inconvenience and can help you find related resources that may be useful.