Module 1: Introduction to open and responsible science

Photo by Ylanite Koppens, Pexels.

After completing this module, you can…

  • Explain basic concepts and aspects of open science.
  • See open science as an integral part of the research lifecycle.
  • Apply key open science policies and recommendations to your research practices.
  • Choose some of the open science digital tools and practices suitable for your research.

What and why? – Open science as a part of research life cycle

  • Why should we change the way we do research?
  • Why should we embrace open science as a normal way of doing research?
  • What are the challenges and opportunities to make this openness happen?
  • Should we change the way we consider the merits in science?

These are just a few examples of the questions that open science as a part of scientific practices may arise.

Open science is not a new concept. Its widespread use became more frequent in the 2010s. The tradition of openness itself is at the roots of science, but the developments in digital technologies have transformed scientific practices to a level that requires a different approach to research that must be understood by all the agents involved: researchers, institutions, policy makers, publishers, businesses and society in general.

Publishing and sharing knowledge (including open educational resources) are fundamental principles of scientific research. They promote transparency, enable peer review, and support scientific dialogue. Open sharing of information increases the impact of research, fosters collaboration, enhances researchers’ visibility, and ensures that scientific knowledge is accessible to everyone.

To start with, watch a short video Open access: democratising knowledge (7:15) leading to the world of open science.

1. Plan and design: defining the research problem, planning research, research environment specification, funding and resourcing research, organising research; 2. Collect and capture: choosing research methods, choosing and collating research data, documenting research events; 3. Collaborate and analyse: processing research data, discovering and identifying research findings; 4. Manage, store and preserve: generating research outputs and describing research findings, the storage and preservation of research outputs and methods, evaluating preservation needs; 5. Share and publish: evaluating and publishing research outputs, assessing findings, e.g. peer reviews, distributing and communicating research findings, ensuring long-term accessibility; 6. Discover, reuse and cite: finding and utilising research findings and outputs, curating research outputs.
Fig. 1. A typical research cycle could look like this.

Open science has traditionally been defined as a movement to make the primary outputs of publicly funded research results – particularly publications and research data – publicly accessible in digital format with no or minimal restriction. However, it is more than that. Open science is about extending the principles of openness to the whole research cycle (Fig. 1, 2), fostering sharing and collaboration as early as possible, thus resulting in a change in the way in which science and research is done.

1. Plan and design: transparency of funding, open science requirements for funding, open sharing of ideas and invitation to collaborate; 2. Collect and capture: preparing data for sharing, sharing raw data; 3. Collaborate and analyse: open code software, open notebook, managing confidentiality/privacy, making use of open-source software and open interfaces; 4. Manage, store and preserve: creating descriptive metadata, FAIR principles, managing privacy/confidentiality; 5. Share and publish: sharing data in open repositories, clarifying usage rights with suitable licenses, open access journals and self-archiving, sharing in social media, creating persistent digital identifiers, open peer review, evaluating accessibility of results, publishing metadata with an open license, ensuring links between publications, data and methods; 6. Discover, reuse and cite: utilising open data/findings, creating new knowledge, giving merit to the original data producer.
Fig. 2. Open science as a part of the research cycle.

Open science applies to all research disciplines: It extends across the life and physical sciences, engineering, mathematics, social sciences, and humanities. It is important to remember that actually, if you think profoundly, open science is not that different to “traditional” science. It just means that you carry out your research in a more transparent and collaborative way.

Opening the research process supports validation, reproducibility and reduces cases of academic misconduct. Open science aims at improving the quality and reliability of research through principles like inclusion, fairness, equity, and sharing. It helps to maximize the impact of your research and provides the foundations for others to build upon. In short, applying open science in your daily workflows is just part of good research practice!

Open science is an umbrella term. It can mean different things at different stages of the research life cycle. It is based on the principles of accessibility, transparency, re-use and collaboration. Open access to publications, open research data, open research methods, open source code, software and infrastructure, open collaboration, open peer review, open notebooks, open educational resources and citizen science can be regarded as components of open science (Fig. 3). Eventually, open science is about putting more science in society and more society in science.

Open data, open access, open source, open notebooks, open peer review, scientific social networks, citizen science and open educational resources are parts of open science.
Fig. 3. Open science facets as a beehive. CC BY FOSTER consortium.

Key dimensions of open science

There are multiple approaches to the term and definition of open science. The Five Open Science Schools of Thought (Fecher & Friesike, 2014; see pp. 24-47) synthesizes these approaches. The most important aspects of these different viewpoints are simplified in Fig. 4.

Five Open Science Schools of Thought (Fecher & Friesike 2014). 1) Infrastructure school. Assumption: Efficient research depends on the available tools and applications. Goal: Creating openly available platforms, tools and services for scientists. Keywords: Collaboration platforms and tools. 2) Public school. Assumption: Science needs to be made accessible to the public. Goal: Making science accessible for citizens. Keywords: Citizen science, science PR, science blogging. 3) Measurement school. Assumption: Scientific contributions today need alternative impact measurements. Goal: Developing an alternative metric system for scientific impact. Keywords: Altmetrics, peer review, citation, impact factors. 4) Democratic school. Assumption: The access to knowledge is unequally distributed. Goal: The access to knowledge freely available for everyone. Keywords: Open access, intellectual property rights, open data, open code. 5) Pragmatic school. Assumption: Knowledge-creation could be more efficient if scientists worked together. Goal: Making the process of knowledge creation more efficient and goal orientated. Keywords: Wisdom of the crowds, network effects, open data, open code.
Fig. 4. The five open science schools of thought by Fecher and Friesike, 2014.

One of the main arguments of open science states that scientific knowledge is a product of social collaboration and its ownership belongs to the community. Many funders around the world now require researchers to share outputs arising from the research they fund with as few restrictions as possible. From an economic point of view, scientific outputs, particularly that of publicly funded research, are a public good that everyone should be able to use at no cost. Everyone should have an equal opportunity to access research outputs in a digital format and free of charge or other restrictions. Publicly funded research should be made available to increase public trust in research, to support scrutiny and validation, to enable reuse, and to drive innovation.

Remember, open science aims at:

  • Distributing knowledge openly and equally.
  • Increasing collaboration and driving innovations.
  • Utilising new digital technologies and collaborative tools when practicing science.

Updated: 8/2025

< References and further reading
Module 1: Guiding principles of open science >