A Privacy Preserving Approach to Feasibility Analyses on Distributed Data Sources in Biomedical Research.

Clicks: 285
ID: 36159
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #56 of 170 articles by views in Studies in health technology and informatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 170 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Funding agencies and field experts promote reuse of scientific data and biomaterial beyond the scope of the original project. The availability of research data, however, is limited by the interest of original authors as well as the privacy rights of the study participants, especially in the biomedical sciences. On the other hand, for an available data set to be a useful contribution to the scientific community, it has to be findable and accessible with reasonable effort. Therefore, using the R Shiny library, we designed and implemented a software for data discovery and feasibility analyses with compliance to regulatory and contractual regulations. Due to its genericity, it was successfully tested with heterogeneous data sets and ultimately applied to the data and biomaterial of the German Center for Cardiovascular Research (DZHK). The resulting tool - named the Feasibility Explorer - is publicly available and can be used by researchers to get an overview of data and biomaterial available in the DZHK and to select collectives in the process of submitting a usage application. To implement the rights of participants and original authors, data is integrated by querying the informed consent and not persistently stored. All calculations on the data are performed server-sided and only aggregated information is send to a client, whereas the extent of information was strictly limited to a necessary minimum that allows an applicant to assess whether an application is worthwhile.
Reference Key
scheel2019astudies Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Scheel, Heiko;Dathe, Henning;Franke, Thomas;Scharfe, Tabea;Rottmann, Thorsten;
Journal Studies in health technology and informatics
Year 2019
DOI
10.3233/SHTI190835
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.