↓ Skip to main content

A RESTful interface to pseudonymization services in modern web applications

Overview of attention for article published in BMC Medical Informatics and Decision Making, February 2015
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users
patent
1 patent

Citations

dimensions_citation
62 Dimensions

Readers on

mendeley
60 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A RESTful interface to pseudonymization services in modern web applications
Published in
BMC Medical Informatics and Decision Making, February 2015
DOI 10.1186/s12911-014-0123-5
Pubmed ID
Authors

Martin Lablans, Andreas Borg, Frank Ückert

Abstract

BackgroundMedical research networks rely on record linkage and pseudonymization to determine which records from different sources relate to the same patient. To establish informational separation of powers, the required identifying data are redirected to a trusted third party that has, in turn, no access to medical data. This pseudonymization service receives identifying data, compares them with a list of already reported patient records and replies with a (new or existing) pseudonym. We found existing solutions to be technically outdated, complex to implement or not suitable for internet-based research infrastructures. In this article, we propose a new RESTful pseudonymization interface tailored for use in web applications accessed by modern web browsers.MethodsThe interface is modelled as a resource-oriented architecture, which is based on the representational state transfer (REST) architectural style. We translated typical use-cases into resources to be manipulated with well-known HTTP verbs. Patients can be re-identified in real-time by authorized users¿ web browsers using temporary identifiers. We encourage the use of PID strings for pseudonyms and the EpiLink algorithm for record linkage. As a proof of concept, we developed a Java Servlet as reference implementation.ResultsThe following resources have been identified: Sessions allow data associated with a client to be stored beyond a single request while still maintaining statelessness. Tokens authorize for a specified action and thus allow the delegation of authentication. Patients are identified by one or more pseudonyms and carry identifying fields. Relying on HTTP calls alone, the interface is firewall-friendly. The reference implementation has proven to be production stable.ConclusionThe RESTful pseudonymization interface fits the requirements of web-based scenarios and allows building applications that make pseudonymization transparent to the user using ordinary web technology. The open-source reference implementation implements the web interface as well as a scientifically grounded algorithm to generate non-speaking pseudonyms.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
Unknown 58 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 17%
Researcher 9 15%
Student > Master 7 12%
Student > Doctoral Student 5 8%
Student > Bachelor 4 7%
Other 11 18%
Unknown 14 23%
Readers by discipline Count As %
Computer Science 20 33%
Medicine and Dentistry 5 8%
Pharmacology, Toxicology and Pharmaceutical Science 4 7%
Engineering 3 5%
Nursing and Health Professions 2 3%
Other 11 18%
Unknown 15 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 March 2022.
All research outputs
#6,553,692
of 23,221,875 outputs
Outputs from BMC Medical Informatics and Decision Making
#631
of 2,019 outputs
Outputs of similar age
#89,998
of 354,527 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#12
of 24 outputs
Altmetric has tracked 23,221,875 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 2,019 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 354,527 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.