Open Science
Bubble
Ideological
Professional
Open Science is a global movement advocating for transparency, accessibility, and collaboration in scientific research by promoting ope...Show more
Open Science
Bubble
IdeologicalProfessional
Open Science is a global movement advocating for transparency, accessibility, and collaboration in scientific research by promoting open data, open-access publishing, and the use of open-source tools.
Statistics
Estimated Global Reach
15K
Popularity
Medium
Regional Hotspot
Worldwide
General Q&A
Open Science champions transparency, accessibility, and collaborative practices in research, making scientific knowledge freely available and reusable for all.
Community Q&A
Open Science champions transparency, accessibility, and collaborative practices in research, making scientific knowledge freely available and reusable for all.
The community thrives on online platforms, open repositories, collaborative events, and global conferences dedicated to fostering open standards.
Community Q&A
Summary
Key Findings
Openness Rituals
Community DynamicsOpen Science insiders engage in preprint posting, hackathons, and open conferences as key rituals reinforcing transparency and collaboration norms.
Transparency Debate
Opinion ShiftsDebates over open peer review and F.A.I.R. data standards shape insider views, reflecting tensions between openness ideals and scientific rigor.
Anti Paywall Identity
Identity MarkersMembers self-identify strongly against paywalled publishing as a core social boundary, often causing friction with traditional academia.
Collaborative Code Share
Social NormsSharing open code and datasets publicly is an insider expectation, not just preference, signaling trust and collective ownership of knowledge.
Sub Groups
Open Data Advocates
Focus on promoting and implementing open data standards and repositories.
Open-Access Publishing Supporters
Advocate for and participate in open-access journals and publishing models.
Open-Source Scientific Software Developers
Develop and maintain open-source tools and platforms for scientific research.
Policy & Advocacy Groups
Work on policy change, institutional adoption, and public awareness for Open Science.
Student & Early Career Researcher Groups
University-based groups focused on training and grassroots Open Science initiatives.
Statistics and Demographics
Platform Distribution
1 / 3
Universities & Colleges
25%Universities and colleges are central to the Open Science movement, hosting research groups, seminars, and student-led initiatives that drive open science practices.
Educational Settingsoffline
Conferences & Trade Shows
20%Academic conferences and trade shows are key venues for Open Science advocacy, networking, and sharing of open research practices.
Professional Settingsoffline
Reddit
12%Reddit hosts active subreddits (e.g., r/openscience, r/academia) where researchers and advocates discuss open science issues, tools, and news.
Gender & Age Distribution
Ideological & Social Divides
Community Development
Discover Similar Bubbles
Insider Knowledge
Terminology
Greeting Salutations
Example Conversation
Insider
Have you posted your latest preprint?
Outsider
Huh? Why ask that specifically as a greeting?
Insider
In Open Science, sharing early through preprints signals engagement and transparency; it's almost like asking 'How's your research progress?'
Outsider
Oh, that’s a neat way to connect!
Cultural Context
This greeting reflects Open Science's emphasis on early sharing and openness as social norms.
Inside Jokes
"Did you actually post a preprint or are you just hiding behind paywalls?"
This joke pokes fun at researchers who claim openness but don’t share their preprints, hinting at perceived hypocrisy within the community.
"FAIR enough"
A pun on 'fair enough,' used ironically when data or practices partially meet but do not fully comply with FAIR principles.
Facts & Sayings
„Preprint it!“
An encouragement to share research findings publicly before formal peer review to accelerate knowledge dissemination.
„F.A.I.R. or bust“
A motto emphasizing the importance of data being Findable, Accessible, Interoperable, and Reusable in Open Science practices.
„Open by default“
A guiding principle that scientific outputs should be openly shared unless there is a strong reason not to.
„Share your code, share your science“
Highlighting the belief that reproducibility requires transparency in software and data as well as results.
Unwritten Rules
Always share your data and code unless you have a sensitive privacy or ethical reason.
This maintains trustworthiness and reproducibility; failure to share can lead to exclusion from collaborative projects.
Engage constructively in open peer review; criticism should be constructive, not dismissive.
Since reviews are often public, respectful dialogue preserves community spirit and collective improvement.
Cite preprints and data repositories properly to acknowledge open contributions.
Proper citation rewards early sharing and discourages scooping or idea theft.
Use persistent identifiers like DOIs when sharing outputs.
These enable findability and tracking credit in the scholarly ecosystem.
Fictional Portraits
1 / 3
Sofia, 29
ResearcherfemaleA molecular biologist in Spain who publishes her work openly and actively shares data to accelerate discoveries.
TransparencyCollaborationAccessibility
Motivations
- To increase collaboration across borders
- To ensure research is accessible to all without paywalls
- To improve reproducibility and transparency in science
Challenges
- Funding restrictions limiting open access publishing
- Resistance from traditional journals and some colleagues
- Time and resources required to prepare open data and code
Platforms
ResearchGateTwitter academic chatsOpen Science conferences
preprintsFAIR dataopen peer review
Insights & Background
Historical Timeline
Main Subjects
Concepts
1 / 3
1 / 3
Concepts
First Steps & Resources
Get-Started Steps
Time to basics: 2-3 weeks
1
Explore Open Science Principles
2-3 hoursBasic
Summary: Read foundational materials outlining open science values, goals, and practices.
Details: Begin by immersing yourself in the core principles of Open Science. Seek out manifestos, introductory articles, and position papers from reputable organizations and advocates. Focus on understanding the motivations behind open data, open access, and open-source tools. Take notes on key terms and concepts such as FAIR data, preprints, and reproducibility. Beginners often struggle with jargon or the breadth of the movement; to overcome this, create a glossary as you go. This foundational knowledge is crucial for meaningful participation and will help you communicate effectively with others in the community. Evaluate your progress by being able to summarize the main goals of Open Science and explain why transparency and accessibility matter.
2
Join Open Science Communities
1-2 hoursBasic
Summary: Register and introduce yourself in online forums or local open science groups.
Details: Engagement with the Open Science bubble is highly social. Find online communities, mailing lists, or local meetups dedicated to open science topics. Register, read the community guidelines, and introduce yourself—mention your background and interest in open science. Lurking (reading without posting) is common at first, but try to participate by asking questions or commenting on discussions. Beginners may feel intimidated by experts; remember that most communities value curiosity and respectful engagement. This step is important for networking, staying updated, and finding mentors. Progress is measured by your comfort in participating and the connections you make.
3
Access and Review Open Data
2-4 hoursIntermediate
Summary: Locate and download datasets from open repositories; explore their structure and documentation.
Details: Practical engagement starts with finding and examining open datasets. Use open data repositories to download datasets relevant to your interests. Carefully review the accompanying documentation (metadata, data dictionaries) to understand how the data is structured and what it represents. Beginners often overlook the importance of metadata or struggle with unfamiliar formats—take your time to read any README files and try opening the data in a spreadsheet or analysis tool. This step builds familiarity with the types of resources available and the expectations for sharing and using open data. Evaluate your progress by being able to describe the contents and potential uses of a dataset.
1
Explore Open Science Principles
2-3 hoursBasic
Summary: Read foundational materials outlining open science values, goals, and practices.
Details: Begin by immersing yourself in the core principles of Open Science. Seek out manifestos, introductory articles, and position papers from reputable organizations and advocates. Focus on understanding the motivations behind open data, open access, and open-source tools. Take notes on key terms and concepts such as FAIR data, preprints, and reproducibility. Beginners often struggle with jargon or the breadth of the movement; to overcome this, create a glossary as you go. This foundational knowledge is crucial for meaningful participation and will help you communicate effectively with others in the community. Evaluate your progress by being able to summarize the main goals of Open Science and explain why transparency and accessibility matter.
2
Join Open Science Communities
1-2 hoursBasic
Summary: Register and introduce yourself in online forums or local open science groups.
Details: Engagement with the Open Science bubble is highly social. Find online communities, mailing lists, or local meetups dedicated to open science topics. Register, read the community guidelines, and introduce yourself—mention your background and interest in open science. Lurking (reading without posting) is common at first, but try to participate by asking questions or commenting on discussions. Beginners may feel intimidated by experts; remember that most communities value curiosity and respectful engagement. This step is important for networking, staying updated, and finding mentors. Progress is measured by your comfort in participating and the connections you make.
3
Access and Review Open Data
2-4 hoursIntermediate
Summary: Locate and download datasets from open repositories; explore their structure and documentation.
Details: Practical engagement starts with finding and examining open datasets. Use open data repositories to download datasets relevant to your interests. Carefully review the accompanying documentation (metadata, data dictionaries) to understand how the data is structured and what it represents. Beginners often overlook the importance of metadata or struggle with unfamiliar formats—take your time to read any README files and try opening the data in a spreadsheet or analysis tool. This step builds familiarity with the types of resources available and the expectations for sharing and using open data. Evaluate your progress by being able to describe the contents and potential uses of a dataset.
4
Experiment with Open-Source Tools
3-5 hoursIntermediate
Summary: Install and try open-source software commonly used in open science workflows.
Details: Open Science relies heavily on open-source tools for data analysis, collaboration, and publishing. Identify a widely used tool (such as a data analysis platform or reference manager) and install it on your computer. Follow beginner tutorials to perform basic tasks, such as importing data or organizing references. Beginners may face technical challenges with installation or unfamiliar interfaces—seek help from community forums or documentation. This hands-on experience is essential for understanding the practical side of open science and prepares you for more advanced participation. Progress is demonstrated by successfully completing a simple workflow using the tool.
5
Share and Discuss Open Resources
2-3 hoursIntermediate
Summary: Share an open-access article or dataset and discuss its significance in a community setting.
Details: Contribute to the open science ecosystem by sharing a resource you found valuable—such as an open-access paper, dataset, or tool—on a community platform. Write a brief summary explaining why you think it's important or interesting, and invite discussion or feedback. Beginners sometimes hesitate to share, fearing their contributions are too basic; remember that sharing is a core value in open science, and your perspective as a newcomer is valuable. This step helps you practice open communication, builds confidence, and fosters engagement. Progress is measured by the responses you receive and your ability to articulate the resource's relevance.
Welcoming Practices
„Inviting newcomers to collaborative hackathons“
Allows novices to contribute hands-on, experience communal problem-solving, and quickly become part of the community.
„Encouraging new members to share preprints and data openly“
This practice fosters a culture of transparency and helps newcomers integrate by participating in fundamental Open Science rituals.
Beginner Mistakes
Not licensing shared data or code properly
Always apply a clear open license (like Creative Commons or MIT) to specify reuse terms, enabling others to legally use your work.
Posting sensitive data without considering privacy
Understand ethical and legal considerations before sharing, and use anonymization or controlled access where necessary.
Pathway to Credibility
Tap a pathway step to view details
Consistently sharing preprints and datasets
Demonstrates commitment to openness and invites community trust through transparency.
Participating in open peer review and giving constructive feedback
Shows active engagement and helps build a reputation as a thoughtful contributor to communal quality control.
Contributing tools or software through collaborative projects or hackathons
Builds tangible contributions that support the community’s infrastructure and showcase technical expertise.
Facts
Regional Differences
Europe
European Open Science initiatives often emphasize policy mandates and infrastructure funding, such as Plan S, shaping researcher incentives.
North America
In North America, there is strong advocacy from libraries and funding agencies, but less coordinated mandates compared to Europe, leading to diverse adoption.
Misconceptions
Misconception #1
Open Science is just about making papers free to read.
Reality
It encompasses open data, open code, transparent methodologies, reproducibility, equitable access, and cultural change beyond just publication access.
Misconception #2
Anyone can just upload poor-quality work as a 'preprint'.
Reality
While preprints bypass traditional peer review, communities encourage self-policing, community commenting, and rapid feedback to maintain quality.
Misconception #3
Open Science means abandoning peer review entirely.
Reality
Most open science advocates promote open and transparent peer review, not its elimination; they seek to improve and make it accountable rather than remove it.
Clothing & Styles
Conference badges with stickers
Open Science community members often personalize their conference badges with stickers representing open repositories, funders, or tools, signaling affiliation and achievements.
