Introduction
Data Sharing and Disclosure Limitation Techniques
Bibliographic Data
| ID | 12807331 |
|---|---|
| Editors | Joan E Sieber (corresponding author) |
| Year | 2006 |
| Volume | 1 |
| Issue | 3 |
| Pages | 47-49 |
| Publication date | 2006-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Empirical Research on Human Research Ethics (JOURNAL) |
| Journal identifiers | ISSN: 1556-2646 • E-ISSN: 1556-2654 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1525/jer.2006.1.3.47 |
| PMID | 19385822 |
| OpenAlex | W2007425130 |
| Language | EN |
| Citations received | 3 |
| References cited | 6 |
THIS SPECIAL SECTION OF JERHRE is in response to the needs of institutions to develop advanced data sharing capabilities. On October 1, 2003, the National Institutes of Health (NIH) initiated a requirement that investigator-initiated proposals for grants with direct costs over $500,000 in any year incorporate plans to accommodate sharing research data. The requirement stipulates that such plans describe the procedures through which shared data would be rendered "free of identifiers that would permit linkages to individual research participants and variables that could lead to deductive disclosure of the identity of individual subjects." (http://grants2.nih.gov/grants/policy/data_sharing). We expect that many researchers who deal with human research data are unfamiliar with the procedures presented in the ensuing articles. These sophisticated procedures have been developed to help protect confidentiality of subjects' data in files that are shared, while simultaneously preserving the analytic value of data for secondary users. Among these are procedures developed by government statisticians that include innovative methods to prevent deductive disclosure of identities. More recently, academic researchers and data experts have adapted or extended these methods. Together, these methods aim to achieve both disclosure limitation and retention of key analytic usefulness of the shared data
Computer security · Confidentiality · Data anonymization · Data science · Data sharing · Government (linguistics · Identifier · Information privacy · Internet privacy · Key (lock · Knowledge management · Unique identifier · Computer Science · Ethics in Clinical Research · Medicine · Privacy-Preserving Technologies in Data
Views of Ethical Best Practices in Sharing Individual-Level Data From Medical and Public Health Research
Best Practices for Ethical Sharing of Individual-Level Health Research Data From Low- and Middle-Income Settings
Conducting Digital Intervention Research among Immigrant Survivors of Intimate Partner Violence
Sharing Social Science Data
Essentials of the Disclosure Review Process
Solving Problems of Disclosure Risk While Retaining Key Analytic Uses of Publicly Released Microdata
Solving Problems of Disclosure Risk in an Academic Setting
L'ère du chiffre. Systèmes statistiques et traditions nationales/The Age of Numbers. Statistical Systems and National Traditions
| Unique citing works | 3 |
|---|---|
| Citations per year | 0,27 |
| Citation span | 2015 - 2022 (8) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 3 |