Evidence map›Paper›PMID 33717315›Full record

ArticleAsian bioethics review2019

Openness in Big Data and Data Repositories: The Application of an Ethics Framework for Big Data in Health and Research.

Vicki Xafis, Markus K Labude

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Asian bioethics review, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Article
  3. A call for open science in forensics.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  4. Article
  5. Review
  6. Clinical Data Warehousing: A Scoping Review.Journal of the Society for Clinical Data Management · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
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.

Vicki XafisCentre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.ORCID https://orcid.org/0000-0002-5104-9686
Markus K LabudeCentre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.ORCID https://orcid.org/0000-0002-5352-3986

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a growing expectation, or even requirement, for researchers to deposit a variety of research data in data repositories as a condition of funding or publication. This expectation recognizes the enormous benefits of data collected and created for research purposes being made available for secondary uses, as open science gains increasing support. This is particularly so in the context of big data, especially where health data is involved. There are, however, also challenges relating to the collection, storage, and re-use of research data. This paper gives a brief overview of the landscape of data sharing via data repositories and discusses some of the key ethical issues raised by the sharing of health-related research data, including expectations of privacy and confidentiality, the transparency of repository governance structures, access restrictions, as well as data ownership and the fair attribution of credit. To consider these issues and the values that are pertinent, the paper applies the deliberative balancing approach articulated in the

Indexed as

Big dataData repositoryDecision-making frameworkHealth dataOpen dataOpen science

Identifiers

PMID33717315
PMCPMC7747413

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.