Understanding Open Access (OA)

Open Access (OA) is transforming academic publishing by providing digital, online, free-to-reader access to scholarly content, removing most copyright and licensing restrictions. The drive towards OA is fuelled by the demand for greater accessibility and dissemination of – often publicly funded – research. The “Gold” OA model holds the final published version of an article (or Version of Record) permanently and freely available online for anyone, anywhere to read. An article publishing charge (APC) is usually applicable to publish Gold OA. “Green” OA – also known as self-archiving – refers to making an article published within a journal under a publisher’s traditional subscription also available to the public in an institutional or disciplinary open access repository. Green OA is sometimes understood to refer to making such a work available on the author’s personal website. 

There is no difference between format, quality or method of production between comparable OA and traditional subscription-based articles. For example, OA articles are also peer reviewed. Instead, the distinction lies in the business model and the copyright and access rights of each model. Whilst traditional subscription models will remain highly relevant for authors and publishers for the foreseeable future, many are responding by adopting OA models as an alternative to respond to demands from authors and funders and to remain competitive and relevant in a rapidly evolving market. Importantly, OA also provides additional opportunities for authors, funders and publishers through secondary dissemination, access and commercial models.

OA is important to

• Authors: OA increases the visibility and impact of their work, potentially leading to more citations and career advancement.
  Whilst some authors are motivated to choose OA for ethical reasons, others will make judgements about “impact” and, perhaps, career progression, both of which may be better served with a wider readership. In some cases this is a personal choice, in others it is mandated by their institution. 
• Publishers: OA opens new revenue opportunities and ensures relevance in the rapidly evolving academic landscape
  New OA journals from university presses, societies and digital platforms can compete effectively in a market previously dominated by commercial publishers. Indeed, the digital-first approach of newer entrants makes them cheaper, faster, and with a potentially wide reach. To maintain their position, traditional academic publishers are having to move quickly to compete.
• Funders: OA ensures that publicly funded research is accessible to all, maximising the return on investment
  Funders are pushing authors to produce a single high-impact OA paper for a piece of research, rather than paying for multiple (OA or other) papers. 
• Researchers: OA facilitates broader and faster access to research, accelerating scientific progress
  Knowledge often spans different silos of knowledge or journals. With OA, researchers are no longer constrained by which journals their institutions subscribe to and can extend ideas or insights from an adjacent body of literature to their own area of interest.

OA Pillars for Success

OA articles have the same fundamental success criteria as subscription articles, although the importance given to each of the following pillars may vary:

Strategies for Monetizing OA articles 

1. Article Processing Charges (APCs):

• Authors or their institutions pay a fee for the article to be made openly accessible. This is the most prevalent model for monetizing OA journals.

2. Institutional Agreements and Memberships:

• Establish agreements with institutions or consortia for bulk publishing deals, where institutions pay a lump sum to cover APCs for their researchers.

3. Sponsorship and Grants:

• Secure funding from governmental or non-governmental organisations that support open access publishing as part of their mission to promote scientific dissemination.

4. Advertising:

• Incorporate advertisements in the journal website or in the articles themselves, targeting audiences relevant to the journal’s focus area.

5. Enhanced Services:

• Offer premium services to authors such as expedited peer review, advanced editorial support, or extensive promotional activities for a fee.

6. Data Hosting and Supplementary Material Fees:

• Charge for hosting large datasets, multimedia files, or other supplementary materials that accompany the published articles.

7. Commercial Partnerships:

• Form partnerships with companies that benefit from the exposure and alignment with the journal’s content, such as software tools for researchers or laboratory equipment suppliers.

8. Institutional Repositories:

• Provide OA journal content to institutional repositories for a fee, ensuring that research is accessible through multiple platforms.

9. Freemium Model:

• Offer basic access for free while charging for enhanced access or additional features like deep analytics, article metrics, or downloadable content.

10. Crowdfunding:

• Engage the academic community and the public in crowdfunding campaigns to support open access publishing, leveraging platforms designed for collective financing.

11. Secondary Rights and Licensing:

• Licence the content for reuse in educational materials, professional training courses, or other commercial products, generating revenue through these secondary uses.

12. Conference Partnerships:

• Partner with academic conferences to publish proceedings or special issues, with the costs covered by the conference organisers or included in the registration fees.

Technology Implications 

Rapid advance in new technologies

AI is changing the way we manage data and consume information. The current buzz around generative AI (to generate ideas, suggest improvements, or even draft portions of text) can distract from its wider impacts. For example, AI can streamline the publication process, including proof-reading, editing and formatting. It can give us a better understanding of reader behaviour. We are also applying AI to data pipelines to read, interpret and link historical content with new publications to present a corpus of knowledge and generate new insights. All this is possible through both tooling (such as Apache Spark and Databricks) coupled with cloud computing. Done well, this gives a huge competitive advantage, both for OA and traditional publishing models.

Versioning.

The book, journal or article is no longer a single instance. Articles may have different versions depending on their stage in the editorial process (including pre-press stored in green OA) but also according to copyright restrictions across many different geographies, different business models, and include regional and market variations. Being able to manage the release and dissemination of multiple versions of a product means you need to automate both workflows and the implementation of policies.

Business Rules 

As mentioned earlier, OA publication often requires the removal of copyright restrictions, but these need to be managed at a number of different levels. For example, an academic book is split into multiple chapters, often with different sets of authors for each chapter, many will want to re-use or reproduce other published content, such as diagrams. Copyright, royalties and access need to be managed at different levels within the hierarchy of the book. As the content is republished, for example as an audiobook or podcast, these need to be traced back to original access agreements and permissions. Technical solutions make this tracing faster and more accurate at scale.

Workflow Management 

One of the reasons authors give for embracing OA is time-to-publish. Whilst self-archiving pre-publication in green repositories has some benefit, we really need to improve the publication workflow. Earlier we suggested how AI covers tasks such as proof-reading and formatting, but we can also streamline the peer-review process, making it easy for reviewers to be assigned, notified, and briefed, whilst making it simple to submit feedback promptly and be paid for their work. Once ready for publication, automated publication and dissemination, using the business rules described above, cuts time-to-publish.

Driving Discoverability and Impact 

All parties (authors, researchers, funders and publishers) want to ensure that newly published articles are quickly disseminated and reach a wide audience. We therefore need to index and link articles so that researchers can find newly published content alongside existing articles. Whilst traditionally, this is done using an author’s chosen keywords, we can now automate the mining, tagging and linking of books and articles to find new relationships, make build relevant recommendations, and so help users to derive new insights. 

Impact measurement 

Funders, institutions and authors themselves are motivated by impact: the frequency and reach of downloads and citations. The example below shows the attention score of a paper by Trish Greenhalgh et al. in the Lancet during the Covid outbreak. Understanding the usage data for publishers to inform publishing and product development decisions. 

How Estafet Can Help

Technologies and Capabilities

We have already built capabilities for other publishers to support end-to-end OA publishing and dissemination processes. This includes:

• Text Mining and NLP: Extract key concepts and data from articles, linking them to other datasets for new insights.
• Knowledge Graphs: Represent relationships between concepts to facilitate discovery and navigation of related research.
• Semantic Enrichment: Add semantic annotations to make content machine-readable and interoperable.
• Data Analytics and Visualization: Analyse and visualise data to uncover trends and correlations.

With extensive experience in academic publishing, Estafet understands the unique challenges and opportunities in this sector. Our expertise ensures tailored solutions that meet the specific needs of publishers, authors, and researchers.

Agile Discovery and Innovation Framework

Estafet’s Agile framework supports continuous innovation. We work closely with clients at every stage of the process to understand business goals and guide you to the most appropriate technology solution based on your ambition, needs and budget. We keep costs low and quality high through our nearshore delivery centre.

Conclusion

Estafet provides the technologies, frameworks, and expertise to help academic publishers successfully navigate the OA landscape. By embracing digital-first strategies and innovative solutions, publishers can maximise revenue, enhance research visibility, and support the broader academic community. 

Contact Us

For tailored solutions and to learn more about our services, please get in touch with Estafet at info@estafet.com. Explore our case studies and discover how we can help you thrive in the OA era.

Case Studies

1.
Breaking silos and creating new insights

Combined interdisciplinary sources, using cloud services to generate new insights through data enrichment, NLP, and Knowledge Graphs.

• Combine interdisciplinary sources such as research data, public data, and free-form text from publications
• Flexible cloud services that could collaborate on many different types of problems
• Generate new insights through data enrichment, harmonisation, Natural Language Processing, Machine Learning and Knowledge Graphs
• Products include Corpora-as-a-Service (all available, relevant information gathered on-demand into a single cloud platform)

Knowledge Graph

Cutting Time-to-Publish:

Implemented Elasticsearch for fast, accurate search across millions of documents, significantly reducing publication time and increasing efficiency.

• Our customer needed to reduce time to publication for journal articles by enabling authors to find the right contract for each article. Search needed to be faster and more accurate. 
• Elasticsearch autocompleted name matches, including alternate names, language support, and interchangeable terms across 100,000,000 documents
• The result was a 30 ms search response on each keystroke across the 60,000 different organisations
• With 2 million API calls per day, the overall time saving was huge with accuracy increased by 80%
• This freed the customer to work on value-generating opportunities and increased operational efficiency.

Smart Search Across Journals and Books:

Developed a unified user experience with a high-quality, canonical data model to improve the discoverability and impact of published works.

• A single user experience across many registers of published works
• A high quality, canonical data model
• Improves the reach and quality of published works, so that customers find information they need and evaluate research impact.
• The Works Registry ensures:
  • Published works are registered in a single location available to all
  • Duplicate works are not stored more than once
  • Best view of works for given search criteria are returned with confidence factor of linked works
  • There is a common identifier for all known works
  • Completeness for any missing works

By Alistair Park, CCO at Estafet in collaboration with Bryan Davies