The Open Science Landscape

Are you curious about sovereign research and open science? We have answers and links to frameworks, tools, and news you can use!

Open science is an ethic, a movement, an approach, and a passion for scholars across the globe. It is not an established set of standards and practices, and its meaning encompasses different things to different communities. The following selection represents the ways that those communities view and value open science.

These examples are meant to be informative, not comprehensive. We welcome your submissions! Please reach out by clicking on the Contact button.

Open Science Frameworks

The Center for Open Science provides training, registries, and tutorials for its Open Science Framework registry.

GO FAIR manages the implementation of FAIR data systems at the institutional level, provides technical guidance on FAIR data management, and hosts activities for the global community of data stewards.

ResearchGate provides simple registries and supports communications, with a focus on social connections and research metrics.

OpenAIRE is CERN's comprehensive open science platform, capable of hosting the full range of research artifacts with tools, like Zenodo.

Open Science Services

At this time, most services are free to use and consist of platforms that help investigators understand the disjointed array of OS options and obligations in a few ways:

hosting open access materials (data, publications, tutorials);
supporting communities of practice (events, membership organizations, think tanks); and
providing trustworthy tools (pre-print, pre-registration, blockchain validation, etc.).

The most popular free services for the American OS community include:

DMP Tool: this data management planning service walks investigators through the technical details of long-term data stewardship, which is now a common requirement on proposals.
GitHub: this code sharing service remains popular with technical researchers.
Open Science 101: this free training and certification module was developed by NASA for the Year of Open Science.
Open Science Chain: this NSF-supported program of the San Diego Supercomputer Center allows OS investigators to register their data on the blockchain.
ORCiD: this service is a free, unique, persistent identifier for research artifacts, scholarship, and activities; it is integrated with SciENcv and SAM.gov.
OSF Registries: this pre-registration service allows investigators to submit pertinent details of their project at the beginning of the study, which increases trust and prevents fraud through transparency.
protocols.io: this service allows registration of methodology and increases trustworthiness for projects that have closed and/or sensitive components (e.g., classified research, human subject research, etc.).
Zotero: this citation service facilitates reference and knowledge sharing.

Open Science Principles

The principles that underpin the OS movement can be quite comprehensive and represent an aspirational view of research culture at best, and a bit of an overreach at worst. In any case, OS principles provide a context for the community of practice that works outside the mainstream.

In general, the core principles aim to reduce fraud, improve trust, and increase access to the process and artifacts of science. As the movement matured, sociocultural considerations broadened the impact and relevance of open science as a viable research practice and driver of innovation.

Technical Principles

FAIR (data stewardship): Findability, Accessibility, Interoperability, and Reuse
TRUST (data repository management): Transparency, Responsibility, User focus, Sustainability and Technology
CARE (data governance): Collective Benefit, Authority to Control, Responsibility, and Ethics

Innovation Principles

Open Access: This principle promotes unrestricted access to scholarly literature and outputs, often enabled through open licenses, such as Creative Commons. OA ensures that knowledge is not locked behind paywalls so that it can be freely used, shared, and built upon.
Transparency: This principle involves openly sharing research methods, data, code, and decision-making processes. It reduces questions about research practices and enhances accountability.
Replicability: This principle encourages the investigation of consistent results across independent studies.
Reproducibility: This principle supports recomputing results using the same data and methods to test the soundness of methodologies and the integrity of research data.
Reusability: This principle ensures that research outputs, including datasets, protocols, and software, can be adapted for new purposes, maximizing the value of scientific investments.
Inclusion: This principle removes barriers to participation in science, ensuring that researchers across geographies, career stages, and institutional backgrounds can access, contribute to, and benefit from research.
Equitability: This principle ensures fairness in how opportunities, resources, and benefits are distributed. It addresses structural imbalances, such as funding gaps or publishing costs, so that participation in open science does not disadvantage under-resourced researchers.
Diversity: This principle promotes the inclusion of varied perspectives, disciplines, and knowledge systems in research. It strengthens scientific quality and advances broader impact goals by incorporating different lived experiences and epistemologies.