Evidence map›Paper›PMID 39076822›Full record

ArticleRoyal Society open science2024

Expanding the data Ark: an attempt to make the data from highly cited social science papers publicly available.

Coby Dulitzki, Steven Michael Crane, Tom E Hardwicke, John P A Ioannidis

Abstract read
In one paragraph

Article in Royal Society open science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Coby DulitzkiDepartment of Biology, Stanford University, Stanford, CA, USA.ORCID 0000-0002-7455-5397
Steven Michael CraneStanford Prevention Research Center, Stanford School of Medicine, Stanford, CA, USA.ORCID https://orcid.org/0000-0001-5385-2926
Tom E HardwickeSchool of Psychological Sciences, University of Melbourne, Melbourne, Australia.ORCID 0000-0001-9485-4952
John P A IoannidisMeta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA.ORCID 0000-0003-3118-6859

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Access to scientific data can enable independent reuse and verification; however, most data are not available and become increasingly irrecoverable over time. This study aimed to retrieve and preserve important datasets from 160 of the most highly-cited social science articles published between 2008-2013 and 2015-2018. We asked authors if they would share data in a public repository-the Data Ark-or provide reasons if data could not be shared. Of the 160 articles, data for 117 (73%, 95% CI [67%-80%]) were not available and data for 7 (4%, 95% CI [0%-12%]) were available with restrictions. Data for 36 (22%, 95% CI [16%-30%]) articles were available in unrestricted form: 29 of these datasets were already available and 7 datasets were made available in the Data Ark. Most authors did not respond to our data requests and a minority shared reasons for not sharing, such as legal or ethical constraints. These findings highlight an unresolved need to preserve important scientific datasets and increase their accessibility to the scientific community.

Indexed as

data transparencymetaresearchopen dataopen sciencereproducibilitysocial science

Identifiers

PMID39076822
PMCPMC11285638

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.