---
title: "Open science"
chunk: 1/8
source: "https://en.wikipedia.org/wiki/Open_science"
category: "reference"
tags: "science, encyclopedia"
date_saved: "2026-05-05T03:48:21.258734+00:00"
instance: "kb-cron"
---

Open science (also known as open research) is the movement to make scientific research, including publications, data, physical samples, software, and models, transparent and accessible to all levels of society through collaborative networks. This encompasses practices such as publishing open research, campaigning for open access, encouraging scientists to practice open-notebook science (such as openly sharing data and code), broader dissemination and public engagement in science, and generally making it easier to publish, access, and communicate scientific knowledge.
Usage of the term varies substantially across disciplines, with a notable prevalence in the STEM disciplines. The term 'open research' has gained currency as a broader alternative to 'open science,' encompassing the humanities and arts alongside traditional scientific disciplines. The primary focus connecting all disciplines is the widespread uptake of new technologies and tools, and the underlying ecology of the production, dissemination and reception of knowledge from a research-based point-of-view. The term 'open scholarship' has also been proposed to include research from the arts and humanities as well as the different roles and practices that researchers perform as educators and communicators. 
Open science can be seen as continuing, rather than revolutionizing, practices that began in the 17th century with the academic journal, which enabled scientists to share resources in response to growing societal demand for scientific knowledge. The Open Science movement emerged primarily from tensions within science between professional ethical codes prescribing transparency and collaborativeness on the one hand and competitive pressures leading to a focus on research article output and the exclusive handling of research on the other. Institutional interests to protect proprietary information for profit added to the latter.

== Principles ==

The six principles of open science are:

Open methodology
Open source
Open data
Open access
Open peer review
Open educational resources

== Background ==
The scientific research process is characterized by a series of activities, including the collection, analysis, publication, re-analysis, critique, and reuse of data. A number of barriers have been identified by proponents of open science that impede or dissuade the broad dissemination of scientific data.
These include financial paywalls of for-profit research publishers, restrictions on usage applied by publishers of data, poor formatting of data or use of proprietary software that makes it difficult to re-purpose, and cultural reluctance to publish data for fears of losing control of how the information is used.
According to the FOSTER taxonomy, open science can often include aspects of open access, open data, and the open-source movement. However, modern scientific research requires software for data and information processing.
 Additionally, open research computation addresses the problem of reproducibility of scientific results.

=== Types ===
The term 'open science' lacks a single standardized definition or measurement framework. On the one hand, it has been referred to as a "puzzling phenomenon". On the other hand, the term has been used to encapsulate a series of principles that aim to foster scientific growth and its complementary access to the public. Sociologists Benedikt Fecher and Sascha Friesike have categorized Open Science into five schools of thought, each emphasizing different aspects of the movement.
According to Fecher and Friesike 'Open Science' encompasses diverse perspectives on how knowledge is created and shared. Fecher and Friesike identify five distinct schools of Open Science, each reflecting different priorities and approaches to the movement:

==== Infrastructure School ====
The infrastructure school views efficient research as dependent on openly available platforms, tools, and applications. It regards open science primarily as a technological challenge, focusing on internet-based infrastructure including software, applications, and computing networks. The infrastructure school is tied closely with the notion of "cyberscience", which describes the trend of applying information and communication technologies to scientific research, which has led to an amicable development of the infrastructure school. Specific elements of this prosperity include increasing collaboration and interaction between scientists, as well as the development of "open-source science" practices. The sociologists discuss two central trends in the infrastructure school:
1. Distributed computing: This trend encapsulates practices that outsource complex, process-heavy scientific computing to a network of volunteer computers around the world.  The examples that the sociologists cite in their paper is that of the Open Science Grid, which enables the development of large-scale projects that require high-volume data management and processing, which is accomplished through a distributed computer network. Moreover, the grid provides the necessary tools that the scientists can use to facilitate this process.
2. Social and Collaboration Networks of Scientists: This trend encapsulates the development of software that makes interaction with other researchers and scientific collaborations much easier than traditional, non-digital practices. This trend emphasizes social media platforms and collaborative digital tools to enable research communication and coordination. De Roure and colleagues (2008) identify four key SVRE capabilities:

Managing and sharing research objects (reusable digital commodities)
Built-in incentives for making research objects available
Openness and extensibility for integrating diverse digital artifacts
Actionable functionality enabling active research use, not just storage.

==== Measurement school ====

The measurement school focuses on developing alternative methods to determine scientific impact, recognizing its crucial role in researchers' reputations, funding, and careers. The authors then discuss other research indicating support for the measurement school. The three key currents of previous literature discussed by the authors are: