---
title: "Research transparency"
chunk: 1/6
source: "https://en.wikipedia.org/wiki/Research_transparency"
category: "reference"
tags: "science, encyclopedia"
date_saved: "2026-05-05T03:50:11.648451+00:00"
instance: "kb-cron"
---

Research transparency is a major aspect of scientific research. It covers a variety of scientific principles and practices: reproducibility, data and code sharing, citation standards or verifiability.
The definitions and norms of research transparency significantly differ depending on the disciplines and fields of research. Due to the lack of consistent terminology, research transparency has frequently been defined negatively by addressing non-transparent usages (which are part of questionable research practices).
After 2010, recurrent issues of research methodology have been increasingly acknowledged as structural crisis, that involve deep changes at all stages of the research process. Transparency has become a key value of the open science movement, which evolved from an initial focus on publishing to encompass a large diversity of research outputs. New common standards for research transparency, like the TOP Guidelines, aims to build and strengthen open research culture across disciplines and epistemic cultures.

== Definitions ==

=== Confused terminologies ===
There is no widespread consensus on the definition of research transparency.
Differences between disciplines and epistemic cultures has largely contributed to different acceptions. The reproduction of past research has been a leading source of dissent. In an experimental setting, reproduction relies on the same set-up and apparatus, while replication only requires the use of the same methodology. Conversely, computational disciplines use reversed definitions of the term replicability and reproducibility. Alternative taxonomies have proposed to make do entirely with the ambiguity of reproducibility/replicability/repeatability. Goodman, Fanelli and Ioannidis recommended instead a distinction between method reproducibility (same experimental/computational setup) and result reproducibility (different setup but same overall principles).
Core institutional actors continue to disagree on the meaning and usage of key concepts. In 2019, the National Academies of Science of the United States retained the experimental definition of replication and reproduction, which remains "at odds with the more flexible way they are used by [other] major organizations". The Association for Computing Machinery opted in 2016, for the computational definition and added also an intermediary notion of repeatability, where a different team of research use exactly the same measurement system and procedure.
Debate over research transparency has also created new convergences between different disciplines and academic circles. In the Problem of science (2021), Rufus Barker Bausell argues that all disciplines, including the social sciences, currently face similar issues to medicine and physical sciences: "The problem, which has come to be known as the reproducibility crisis, affects almost all of science, not one or two individual disciplines."

=== Negative definitions ===
Due to lack of consistent terminology over research transparency, scientists, policy-makers and other major stake-holders have increasingly rely on negative definitions: what are the practices and forms that harm or disrupt any common ideal of research transparency.
The taxonomy of scientific misconducts has been gradually expanded since the 1980s. The concept of questionable research practices (or QRP) was first incepted in a 1992 report of the Committee on Science, Engineering, and Public Policy as a way to address potentially non-intentional research failures (such as inadequacies in the research data management process). Questionable research practices uncover a large grey area of problematic practices, which are frequently associated to deficiencies in research transparency. In 2016, a study identified as much as 34 questionable research practices or "degree of freedom", that can occur at all the steps of the project (the initial hypothesis, the design of the study, collection of the data, the analysis and the reporting).
Surveys of disciplinary practices have shown large differences in the admissibility and spread of questionable research practices. While data fabrication and, to a lesser extent, rounding of statistical indicators like the p value are largely rejected, the non-publication of negative results or the adjonctions of supplementary data are not identified as major issues.
In 2009, a meta-analysis of 18 surveys estimated that less than 2% of scientists "admitted to have fabricated, falsified or modified data or results at least once". Real prevalence may be under-estimated due to self-reporting: regarding "the behaviour of colleagues admission rates were 14.12%". Questionable research practices are more widespread as more than one third of the respondents admit to have done it once. A large 2021 survey of 6,813 respondents in the Netherlands found significantly higher estimate, with 4% of the respondents engaging in data fabrication and more than half of the respondents engaging in questionable research practices. Higher rates can be either attributed to a deterioration of ethic norms or to "the increased awareness of research integrity in recent years".