Evidence map›Paper›PMID 38419824›Full record

ArticleInternational journal of population data science2023

Four questions to guide decision-making for data sharing and integration.

Amy Hawn Nelson, Sharon Zanti

Abstract read
In one paragraph

Article in International journal of population data science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Amy Hawn NelsonUniversity of Pennsylvania, Actionable Intelligence for Social Policy.
Sharon ZantiUniversity of Pennsylvania, Actionable Intelligence for Social Policy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This paper presents a Four Question Framework to guide data integration partners in building a strong governance and legal foundation to support ethical data use. Objectives: While this framework was developed based on work in the United States that routinely integrates public data, it is meant to be a simple, digestible tool that can be adapted to any context. Methods: The framework was developed through a series of public deliberation workgroups and 15 years of field experience working with a diversity of data integration efforts across the United States. Results: The Four Questions- Conclusions: A robust governance process is essential for determining whether data sharing and integration is legal, ethical, and a good idea within the local context. This process is iterative and as relational as it is technical, which means authentic collaboration across partners should be prioritized at each stage of a data use project. The Four Questions serve as a guide for determining whether to undertake data sharing and integration and should be regularly revisited throughout the life of a project. Highlights: Strong data governance has five qualities: it is purpose-, value-, and principle-driven; strategically located; collaborative; iterative; and transparent.Through a series of public deliberation workgroups and 15 years of field experience, we developed a Four Question Framework to determine whether and how to move forward with building an IDS and at each stage of a data sharing and integration project.The Four Questions-

Indexed as

Information DisseminationDecision MakingUnited Statesdata governanceethical data sharinglegal frameworks for data integration

Identifiers

PMID38419824
PMCPMC10900076

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.