For various reasons, this kind of free and unrestricted online availability, which we will call open access, has so far been limited to small portions of the journal literature. But even in these limited collections, many different initiatives have shown that open access is economically feasible, that it gives readers extraordinary power to find and make use of relevant literature, and that it gives authors and their works vast and measurable new visibility, readership, and impact. To secure these benefits for all, we call on all interested institutions and individuals to help open up access to the rest of this literature and remove the barriers, especially the price barriers, that stand in the way. The more who join the effort to advance this cause, the sooner we will all enjoy the benefits of open access.

The literature that should be freely accessible online is that which scholars give to the world without expectation of payment. Primarily, this category encompasses their peer-reviewed journal articles, but it also includes any unreviewed preprints that they might wish to put online for comment or to alert colleagues to important research findings. There are many degrees and kinds of wider and easier access to this literature. By "open access" to this literature, we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited.

While the peer-reviewed journal literature should be accessible online without cost to readers, it is not costless to produce. However, experiments show that the overall costs of providing open access to this literature are far lower than the costs of traditional forms of dissemination. With such an opportunity to save money and expand the scope of dissemination at the same time, there is today a strong incentive for professional associations, universities, libraries, foundations, and others to embrace open access as a means of advancing their missions. Achieving open access will require new cost recovery models and financing mechanisms, but the significantly lower overall cost of dissemination is a reason to be confident that the goal is attainable and not merely preferable or utopian.

To achieve open access to scholarly journal literature, we recommend two complementary strategies.

I. Self-Archiving: First, scholars need the tools and assistance to deposit their refereed journal articles in open electronic archives, a practice commonly called, self-archiving. When these archives conform to standards created by the Open Archives Initiative, then search engines and other tools can treat the separate archives as one. Users then need not know which archives exist or where they are located in order to find and make use of their contents.

II. Open-access Journals: Second, scholars need the means to launch a new generation of journals committed to open access, and to help existing journals that elect to make the transition to open access. Because journal articles should be disseminated as widely as possible, these new journals will no longer invoke copyright to restrict access to and use of the material they publish. Instead they will use copyright and other tools to ensure permanent open access to all the articles they publish. Because price is a barrier to access, these new journals will not charge subscription or access fees, and will turn to other methods for covering their expenses. There are many alternative sources of funds for this purpose, including the foundations and governments that fund research, the universities and laboratories that employ researchers, endowments set up by discipline or institution, friends of the cause of open access, profits from the sale of add-ons to the basic texts, funds freed up by the demise or cancellation of journals charging traditional subscription or access fees, or even contributions from the researchers themselves. There is no need to favor one of these solutions over the others for all disciplines or nations, and no need to stop looking for other, creative alternatives.

Open access to peer-reviewed journal literature is the goal. Self-archiving (I.) and a new generation of open-access journals (II.) are the ways to attain this goal. They are not only direct and effective means to this end, they are within the reach of scholars themselves, immediately, and need not wait on changes brought about by markets or legislation. While we endorse the two strategies just outlined, we also encourage experimentation with further ways to make the transition from the present methods of dissemination to open access. Flexibility, experimentation, and adaptation to local circumstances are the best ways to assure that progress in diverse settings will be rapid, secure, and long-lived.

The Open Society Institute, the foundation network founded by philanthropist George Soros, is committed to providing initial help and funding to realize this goal. It will use its resources and influence to extend and promote institutional self-archiving, to launch new open-access journals, and to help an open-access journal system become economically self-sustaining. While the Open Society Institute's commitment and resources are substantial, this initiative is very much in need of other organizations to lend their effort and resources.

We invite governments, universities, libraries, journal editors, publishers, foundations, learned societies, professional associations, and individual scholars who share our vision to join us in the task of removing the barriers to open access and building a future in which research and education in every part of the world are that much more free to flourish.

February 14, 2002
Budapest, Hungary

Leslie Chan: Bioline International
Darius Cuplinskas: Director, Information Program, Open Society Institute
Michael Eisen: Public Library of Science
Fred Friend: Director Scholarly Communication, University College London
Yana Genova: Next Page Foundation
Jean-Claude Gu don: University of Montreal
Melissa Hagemann: Program Officer, Information Program, Open Society Institute
Stevan Harnad: Professor of Cognitive Science, University of Southampton, Universite du Quebec a Montreal
Rick Johnson: Director, Scholarly Publishing and Academic Resources Coalition (SPARC)
Rima Kupryte: Open Society Institute
Manfredi La Manna: Electronic Society for Social Scientists 
Istv n R v: Open Society Institute, Open Society Archives
Monika Segbert: eIFL Project consultant 
Sidnei de Souza: Informatics Director at CRIA, Bioline International
Peter Suber: Professor of Philosophy, Earlham College & The Free Online Scholarship Newsletter
Jan Velterop: Publisher, BioMed Central

Gen AI Policy

Biosfer: Jurnal Pendidikan Biologi is referring to Elsevier's Generative AI policies for journals. These policies aim to provide greater transparency and guidance to authors, reviewers, editors, readers, and contributors.

For authors

The use of generative AI and AI-assisted technologies in manuscript preparation - an overview

SLRev recognizes the potential of generative AI and AI-assisted technologies (“AI Tools”), when used responsibly, to help researchers work efficiently, gain critical insights fast and achieve better outcomes. Increasingly, these tools, including AI agents and deep research tools, are helping researchers to synthesize complex literature, provide an overview of a field or research question, identify research gaps, generate ideas and provide tailored support for tasks such as content organization and improving language and readability. Authors preparing a manuscript for an SLRev journal can use AI Tools to support them. However, these tools must never be used as a substitute for human critical thinking, expertise and evaluation. AI Tools should always be applied with human oversight and control. Ultimately, authors are responsible and accountable for the contents of their work. This includes accountability for:

• Carefully reviewing and verifying the accuracy, comprehensiveness, and impartiality of all AI-generated output (including checking the sources, as AI-generated references can be incorrect or fabricated).

• Editing and adapting all material thoroughly to ensure the manuscript represents the author’s authentic and original contribution and reflects their own analysis, interpretation, insights and ideas.

• Ensuring the use of any tools or sources, AI-based or otherwise, is made clear and transparent to readers — for the use of AI Tools we require a disclosure statement upon submission.

• Ensuring the manuscript is developed in a way that safeguards data privacy, intellectual property and other rights, by checking the terms and conditions of any AI Tool that is used.

Responsible use of AI Tools Authors must check the terms and conditions of any AI Tool that they use to ensure that the privacy and confidentiality of their data and inputs, including their unpublished manuscripts, is maintained. Particular care should be taken with any personally identifiable data. Images that duplicate or refer to existing copyrighted images, real people, or others’ identifiable products or brands must not be generated, nor any likeness of an individual’s voice. Authors should check for factual errors and for any potential bias.

Authors should also check the terms and conditions of any AI Tool they wish to use to ensure that, they only grant to the AI Tool the right to use their materials to provide the service to them and that they do not grant to the AI Tool any other rights to the materials that they input into the AI Tool (including without limitation the right to train the AI Tool on those materials). They must also ensure that the AI Tool does not impose constraints on the use of outputs from the AI Tool in a way that could restrict the subsequent publication of the relevant article. Disclosure Authors should disclose the use of AI Tools for manuscript preparation in a separate AI declaration statement in their manuscript upon submission and a statement will appear in the published work. Authors should document their use of AI, including the name of the AI Tool used, the purpose of the use, and the extent of their oversight. Declaring the use of AI Tools supports transparency and trust between authors, readers, reviewers, editors and contributors and facilitates compliance with the terms of use of the relevant AI Tool. Basic checks of grammar, spelling and punctuation need no declaration. AI use in the research process should be declared and described in detail in the methods section. Authorship Authors should not list AI Tools as an author or co-author, nor cite AI Tools as an author. Authorship implies responsibilities and tasks that can only be attributed to and performed by humans. Each (co-) author is accountable for ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved and authorship requires the ability to approve the final version of the work and agree to its submission. Authors are also responsible for ensuring that the work is original and has not been previously published, that the stated authors qualify for authorship, and the work does not infringe third party rights, and should familiarize themselves with SLRev’s Ethics in Publishing policy before they submit.

The use of generative AI and AI-assisted tools in figures, images and artwork

We do not permit the use of Generative AI or AI-assisted tools to create or alter images in submitted manuscripts. This may include enhancing, obscuring, moving, removing, or introducing a specific feature within an image or figure. Adjustments of brightness, contrast, or color balance are acceptable if and as long as they do not obscure or eliminate any information present in the original. Image forensics tools or specialized software might be applied to submitted manuscripts to identify suspected image irregularities.

The only exception is if the use of AI or AI-assisted tools is part of the research design or research methods (such as in AI-assisted imaging approaches to generate or interpret the underlying research data, for example in the field of biomedical imaging). If this is done, such use must be described in a reproducible manner in the methods section. This should include an explanation of how the AI or AI-assisted tools were used in the image creation or alteration process, and the name of the model or tool, version and extension numbers, and manufacturer. Authors should adhere to the AI software’s specific usage policies and ensure correct content attribution. Where applicable, authors could be asked to provide pre-AI-adjusted versions of images and/or the composite raw images used to create the final submitted versions, for editorial assessment.

The use of generative AI or AI-assisted tools in the production of artwork such as for graphical abstracts is not permitted. The use of generative AI in the production of cover art may in some cases be allowed, if the author obtains prior permission from the journal editor and publisher, can demonstrate that all necessary rights have been cleared for the use of the relevant material, and ensures that there is correct content attribution.

For reviewers

The use of generative AI and AI-assisted technologies in the journal peer review process

When a researcher is invited to review another researcher’s paper, the manuscript must be treated as a confidential document. Reviewers should not upload a submitted manuscript or any part of it into a generative AI tool as this may violate the authors’ confidentiality and proprietary rights and, where the paper contains personally identifiable information, may breach data privacy rights.

This confidentiality requirement extends to the peer review report, as it may contain confidential information about the manuscript and/or the authors. For this reason, reviewers should not upload their peer review report into an AI tool, even if it is just for the purpose of improving language and readability.

Peer review is at the heart of the scientific ecosystem and SLRev abides by the highest standards of integrity in this process. Reviewing a scientific manuscript implies responsibilities that can only be attributed to humans. Generative AI or AI-assisted technologies should not be used by reviewers to assist in the scientific review of a paper as the critical thinking and original assessment needed for peer review is outside of the scope of this technology and there is a risk that the technology will generate incorrect, incomplete or biased conclusions about the manuscript. The reviewer is responsible and accountable for the content of the review report.

For editors

The use of generative AI and AI-assisted technologies in the journal editorial process

A submitted manuscript must be treated as a confidential document. Editors should not upload a submitted manuscript or any part of it into a generative AI tool, as this may violate the authors’ confidentiality and proprietary rights and, where the paper contains personally identifiable information, may breach data privacy rights.

This confidentiality requirement extends to all communication about the manuscript, including any notification or decision letters, as they may contain confidential information about the manuscript and/or the authors. For this reason, editors should not upload their letters into an AI tool, even if it is just for the purpose of improving language and readability.

Peer review is at the heart of the scientific ecosystem, and SLRev abides by the highest standards of integrity in this process. Managing the editorial evaluation of a scientific manuscript implies responsibilities that can only be attributed to humans. Generative AI or AI-assisted technologies should not be used by editors to assist in the evaluation or decision-making process of a manuscript, as the critical thinking and original assessment needed for this work is outside of the scope of this technology, and there is a risk that the technology will generate incorrect, incomplete, or biased conclusions about the manuscript. The editor is responsible and accountable for the editorial process, the final decision, and the communication thereof to the authors.

SLRev states that authors are allowed to use generative AI and AI-assisted technologies in the manuscript preparation process before submission, but only with appropriate oversight and disclosure, as per our instructions. Editors can find such disclosure at the bottom of the paper in a separate section before the list of references. If an editor suspects that an author or a reviewer has violated our AI policies, they should inform the publisher.