Evidence map›Paper›PMID 26739310›Full record

ArticleInternational journal of health geographics2016

Anonymisation of geographical distance matrices via Lipschitz embedding.

Martin Kroll, Rainer Schnell

Abstract read
In one paragraph

Article in International journal of health geographics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Using mobile location data in biomedical research while preserving privacy.Journal of the American Medical Informatics Association : JAMIA · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Martin KrollResearch Methodology Group, University of Duisburg-Essen, Lotharstraße 65, 47057, Duisburg, Germany. martin.kroll@uni-due.de.
Rainer SchnellResearch Methodology Group, University of Duisburg-Essen, Lotharstraße 65, 47057, Duisburg, Germany. rainer.schnell@city.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnonymisation of spatially referenced data has received increasing attention in recent years. Whereas the research focus has been on the anonymisation of point locations, the disclosure risk arising from the publishing of inter-point distances and corresponding anonymisation methods have not been studied systematically.

methodsWe propose a new anonymisation method for the release of geographical distances between records of a microdata file--for example patients in a medical database. We discuss a data release scheme in which microdata without coordinates and an additional distance matrix between the corresponding rows of the microdata set are released. In contrast to most other approaches this method preserves small distances better than larger distances. The distances are modified by a variant of Lipschitz embedding.

resultsThe effects of the embedding parameters on the risk of data disclosure are evaluated by linkage experiments using simulated data. The results indicate small disclosure risks for appropriate embedding parameters.

conclusionThe proposed method is useful if published distance information might be misused for the re-identification of records. The method can be used for publishing scientific-use-files and as an additional tool for record-linkage studies.

Indexed as

Position-Specific Scoring MatricesData AnonymizationDatabases, FactualHumansPersonally Identifiable Information

Identifiers

PMID26739310
PMCPMC4704375

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.