Longitudinal dataset of journal data sharing policies across 22 disciplines for 2014 2019 and 2023

TL;DR

This paper presents a dataset tracking data sharing policies of 220 high-impact journals across 22 disciplines from 2014 to 2023.

Contribution

The study introduces a longitudinal dataset capturing changes in journal data sharing policies over time.

Findings

The dataset includes 220 journals and classifies policies into four categories: require, recommend, accept, or no policy.

It enables comparative analysis of data sharing trends across disciplines and time periods.

The dataset supports research on open science practices and publishing standards evolution.

Abstract

This dataset documents journal data sharing policies across 22 disciplines for 2014 2019 and 2023. A total of 220 high-impact journals were surveyed, representing the top ten journals (by Impact Factor) from each discipline listed in the Essential Science Indicators. For each journal, policies concerning two types of data sharing were reviewed: repository-based data sharing and supplementary materials. Policy requirements were classified into four categories based on their strength: require, recommend, accept, or no policy. Data were collected at three time points through systematic reviews of journal websites and submission guidelines. The dataset includes journal metadata—such as publishers, ISSN, and Impact Factor—along with detailed policy descriptions and classifications. This longitudinal dataset provides evidence of changes in data sharing requirements over time and enables comparative studies of journal policies. These data may be useful for research on open science practices, the development of science policy, and the evolution of scholarly publishing standards.

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