The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
The privacy challenge in the race for digital vaccination certificates
Open accessAbstract
https://doi.org/10.1016/j.medj.2021.04.018 In the wake of COVID vaccination campaigns, companies and governments make haste in launching digital vaccination certificates. These digital certificates often differ in design and structure but are typically stored in mobile apps. However, using these apps comes with two significant challenges: interoperability and privacy. Interoperability is important for broad and easy usability of digital vaccination certificates. Yet, it is difficult to establish because poor coordination and a rat race for innovation have complicated the adoption of common technical standards. Data privacy is important for user trust and legal compliance. It is, in fact, an even bigger challenge than interoperability.
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“The storage of vaccination-related digital information in a centralized database enables faster and more convenient verification, yet it also raises ethical, security, and privacy concerns.”
From Digital Identities and Verifiable Credentials (2021) · cites this paper as Rieger et al. 2021
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In the citing paper
“The storage of vaccination-related digital information in a centralized database enables faster and more convenient verification, yet it also raises ethical, security, and privacy concerns.”
From Digital Identities and Verifiable Credentials (2021) · cites this paper as Rieger et al. 2021
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Although this development is notable, EU Digital COVID Certificates cannot yet be stored in a standardized wallet alongside a broad array of documents, certificates, and credentials that can be used to prove a subject’s identity (Rieger et al. 2021).”
From Digital Identities and Verifiable Credentials (2021) · cites this paper as Rieger et al. 2021
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In the citing paper
“Such databases can facilitate unintended profiling, they are appealing targets for hackers, and they typically limit individuals’ control over the processing of their personal data (Rieger et al. 2021).”
From Digital Identities and Verifiable Credentials (2021) · cites this paper as Rieger et al. 2021
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“Such databases can facilitate unintended profiling, they are appealing targets for hackers, and they typically limit individuals’ control over the processing of their personal data (Rieger et al. 2021).”
From Digital Identities and Verifiable Credentials (2021) · cites this paper as Rieger et al. 2021
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Citations
Cites
Forgetting personal data and revoking consent under the GDPR: Challenges and proposed solutions
Politou, E., Alepis, E., & Patsakis, C. (2018) · Journal of Cybersecurity · doi:10.1093/cybsec/tyy001 · Cited by 313
Building a Blockchain Application that Complies with the EU General Data Protection Regulation
Rieger, A., Guggenmos, F., Lockl, J., Fridgen, G., & Urbach, N. (2019) · MIS Quarterly Executive · doi:10.17705/2msqe.00020 · Cited by 109
Self-citationElectronic vaccination certificates: avoiding a repeat of the contact-tracing ‘format wars’
Marhold, K., & Fell, J. (2021) · Nature Medicine · doi:10.1038/s41591-021-01286-w · Cited by 17
Vaccination: keep records secure with blockchain
Cheung, J. C.-S. (2021) · Nature · doi:10.1038/d41586-021-00411-6 · Cited by 4
Vaccination certificates could entrench inequality
Baylis, F. E., & Kofler, N. M. (2021) · Nature · doi:10.1038/d41586-021-00757-x · Cited by 4
Cited by
Digital Identities and Verifiable Credentials
Sedlmeir, J., Smethurst, R., Rieger, A., & Fridgen, G. (2021) · Business & Information Systems Engineering · doi:10.1007/s12599-021-00722-y · Cited by 206
Self-citation
Metadata
- Authors
- Rieger, A., Roth, T., Sedlmeir, J., & Fridgen, G.
- Affiliations
- University of Luxembourg (LU)
- Fraunhofer Institute for Applied Information Technology (DE)
- Corresponding author
- Rieger, Alexander
- Venue
- Med
- Publisher
- Elsevier BV
- Published
- 2021-06
- Volume
- 2
- Issue
- 6
- Pages
- 633-634
- ISSN
- 2666-6340 (ISSN-L)
- OpenAlex
- W3157518002
- Cited by
- 13
- References
- 5
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 3 · 2022: 6 · 2021: 2
- FWCI
- 2.71
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 375 d)
- Locations
- Med (publishedVersion)
- PubMed (publishedVersion)
- Open Repository and Bibliography (University of Luxembourg) (submittedVersion, cc-by-nc-sa)
- ERef Bayreuth (University of Bayreuth) (submittedVersion)
- Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) (submittedVersion)
- Fraunhofer-Publica (Fraunhofer-Gesellschaft) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › COVID-19 Digital Contact Tracing
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- COVID-19 vaccination, privacy, interoperability, mobile application, technical standards, data protection
- MeSH terms
- Vaccination, Privacy
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
