Research Data Sharing & Data Availability Statements: A Complete Guide for Authors and Publishers

Introduction

In the era of open science and transparent research, data sharing has become as important as publishing the research paper itself. Journals, funders, and institutions increasingly require authors to share datasets or clearly explain why data cannot be shared. This shift has given rise to Data Availability Statements (DAS)—a critical but often misunderstood component of modern academic publishing.

This comprehensive guide explains what data sharing means, why it matters, how to write effective data availability statements, and how publishers and authors can implement best practices without compromising ethics, privacy, or intellectual property.

What Is Research Data Sharing?

Research data sharing refers to the practice of making raw or processed research data accessible to other researchers, reviewers, and the public. Data may include:

Quantitative datasets

Qualitative interview transcripts

Images, videos, or audio files

Code and software scripts

Survey instruments and experimental protocols

Data sharing can occur via disciplinary repositories, institutional repositories, general-purpose platforms, or journal-hosted archives.

Why Data Sharing Is Becoming Mandatory

1. Transparency and Reproducibility

Shared data allows other researchers to verify findings, replicate studies, and build upon existing work—strengthening scientific credibility.

2. Compliance with Journal and Funder Policies

Major publishers and funding agencies increasingly mandate data sharing or a formal justification for restricted access.

3. Increased Citations and Visibility

Studies show that articles with accessible datasets often receive higher citations and broader academic engagement