The core values guiding the Future Science platform
Research should be accessible to everyone. All publications hosted on Future Science must be freely accessible to readers without paywalls or subscription barriers. Research funded by public institutions belongs to the public, and the systems that distribute it should reflect that principle.
Focused on serving the academic community, not generating profit. Future Science operates as a non-commercial initiative. It does not seek profit, does not charge authors for publishing, and does not monetize reader attention. The platform is sustained through institutional support, grants, and community contributions.
Decisions and policies are led by scholars and institutions. Governance of the platform and its supported initiatives rests with the academic community. Scholars, editors, and institutional partners make decisions about policies, standards, and the direction of the project.
Built on transparent, collaborative, and reusable technology. The code powering Future Science is publicly available and open to inspection, reuse, and improvement. Data produced through the platform is made available under open licenses wherever possible.
Affordable solutions supported by universities and research organizations. Future Science is designed to operate with minimal financial overhead. By relying on open-source tools, lean infrastructure, and community-driven academic effort, the platform avoids the cost structures that characterize commercial publishers.
Designed to last and remain stable over time. Architectural choices favour stability, simplicity, and maintainability. Content is archived through partnerships with preservation services such as Zenodo, ensuring that publications and infrastructure remain accessible and functional over the long term.
Standards of scientific quality are not timeless. They emerge from the material and institutional conditions under which knowledge is produced, circulated, and evaluated. Each major shift in how knowledge travels has redefined what counts as good science.
Antiquity – 15th century
Knowledge is rare because texts must be copied by hand. Literacy is limited and copying is expensive. Under these conditions, scientific and religious authority tend to overlap, and the main challenge is determining which texts deserve preservation and transmission.
Scientific criterion
Orthodoxy and doctrinal consistency
Keywords
15th – 18th centuries
Printing dramatically lowers the cost of reproducing knowledge, and books circulate widely across Europe. Many competing systems of thought can now coexist, so the key problem becomes distinguishing genuine science from speculation, superstition, or pseudoscience.
Scientific criterion
Demarcation between science and non-science
Keywords
Key thinkers
19th – 20th centuries
Scientific communication increasingly occurs through specialized journals. Knowledge becomes organized into disciplines and professional communities, and researchers work inside intellectual fields with their own methods, references, and standards.
Scientific criterion
Paradigm coherence and disciplinary validation
Keywords
Key thinkers
Late 20th – early 21st century
Digital communication removes many publication constraints. Data, code, protocols, and negative results can be shared globally, and as scientific claims become easier to verify, attention shifts toward reproducibility and transparency.
Scientific criterion
Reproducibility and openness
“When publication space becomes effectively unlimited, selective reporting becomes harder to justify.”
Keywords
Key thinkers
Present and emerging future
Artificial intelligence, open-access publishing, automated research systems, synthetic data generation, and collaborative digital infrastructures are transforming scientific practice. We do not yet know which criteria will define scientific excellence in this new environment. The next epistemology remains to be invented.
Scientific criterion
?
Keywords
Key thinkers
If scientific criteria evolve with scientific infrastructures, then periods of technological transformation require experimentation with new research environments.
The challenge today is not simply producing more knowledge. It is designing institutions capable of identifying, evaluating, and organizing trustworthy knowledge under radically new conditions.
This is why alternative scientific ecosystems must be explored and tested.