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Updated: Sep 24, 2025

Paw-Print Analysis of Contrast-Enhanced Recordings PrAnCER: A Low-Cost, Open-Access Automated Gait Analysis System for Assessing Motor Deficits
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Privacy-preserving local analysis of digital trace data: A proof-of-concept.

Laura Boeschoten1,2, Adriënne Mendrik3, Emiel van der Veen3

  • 1Department of Methodology and Statistics, Utrecht University, Padualaan 14, 3584 CH Utrecht, the Netherlands.

Patterns (New York, N.Y.)
|May 5, 2022
PubMed
Summary

We developed PORT, a software platform for local data extraction and analysis of digital trace data. PORT enables social scientists to access and analyze sensitive user data securely, overcoming privacy barriers.

Keywords:
data donationdata extractiondigital trace datalocal processingprivacyproof-of-conceptsoftware

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Area of Science:

  • Social Sciences
  • Data Science
  • Computer Science

Background:

  • Digital trace data offers significant potential for social-scientific research.
  • Privacy concerns and limited API access have restricted scientists' use of this data.
  • A recent workflow allows citizens to donate processed digital traces to researchers.

Purpose of the Study:

  • To introduce PORT, a software platform for local data extraction and analysis.
  • To enable secure processing of digital trace data, protecting user privacy.
  • To facilitate researchers' access to previously unobtainable social data.

Main Methods:

  • PORT implements the local processing component of a digital trace data donation workflow.
  • The software processes data locally on users' machines, shielding sensitive information.
  • Researchers can customize data processing based on data packages and research questions.

Main Results:

  • PORT successfully enables local extraction and analysis of digital trace data.
  • The platform ensures data privacy by shielding sensitive information from researchers.
  • PORT facilitates the use of social data science for previously inaccessible datasets.

Conclusions:

  • PORT overcomes privacy and access barriers in digital trace data research.
  • The platform empowers social scientists to conduct research on sensitive data securely.
  • PORT opens new avenues for social data science discovery.