Study: Researchers are engaging with open research not merely due to mandates but because of intrinsic motivations—such as transparency, collaboration, visibility, and reuse.

Moving the Needle on Open Data—Strategic Implications for Scholarly Publishers

by ChatGPT-4o

The recent Taylor & Francis and DataSeer study, “Moving the Needle on Open Data”, marks a pivotal moment in the scholarly publishing sector’s transition toward open science. Drawing on a dataset of over 8,000 articles and using AI tools to assess open research indicators—including data sharing, code availability, preprints, and ORCID usage—the study offers critical insights into how deeply open science practices have permeated author behavior. Surprisingly, the findings show that researchers often exceed publishers’ minimum compliance requirements, suggesting that cultural shifts toward openness are taking hold. For scholarly publishers, these findings are both a validation of recent efforts and a wake-up call to accelerate and strategically align with this momentum.

Why This Study Is Relevant for Scholarly Publishers

1. Empirical Evidence of Open Science Engagement

The study reveals that:

• 52% of articles included Data Availability Statements (DAS), surpassing policy mandates.

• 18% of articles generated code/software, with 8% of authors openly sharing it.

• 8% of authors had published preprints.

• ORCID usage was near universal, with 98% of articles including at least one identifier.

These figures demonstrate that researchers are engaging with open research not merely due to mandates but because of intrinsic motivations—such as transparency, collaboration, visibility, and reuse. Scholarly publishers must recognize that open science is no longer peripheral; it’s rapidly becoming the norm.

2. Authors Want Support, Not Just Policy

The study highlights that disciplines differ in uptake, and authors often exceed expectations in the absence of mandates. This reinforces the idea that publishers should shift from merely enforcing open science policies to enabling open science ecosystems. That means providing infrastructure, tools, guidance, and recognition for these behaviors.

3. AI as a Strategic Enabler

By using DataSeer’s AI-driven analysis, Taylor & Francis was able to gather granular insights on a large scale. This signals a wider opportunity for scholarly publishers to adopt AI and metadata analytics not just for internal dashboards or editorial efficiencies, but to map evolving research behaviors and tailor services accordingly.

Strategic Goals for Scholarly Publishers

Based on the findings of this study, publishers should consider adopting the following strategic goals:

🎯 1. Normalize and Incentivize Open Practices

Move beyond compliance frameworks. Normalize open research practices through:

• Enhanced metadata capture (DAS, ORCID, CRediT, funder info).

• Optional but encouraged fields for code, software, and preprints.

• Rewards programs or visibility boosts for open-compliant submissions.

Why it matters: Authors are already motivated—build on this rather than policing behavior.

🎯 2. Develop Discipline-Specific Open Science Strategies

Taylor & Francis observed open engagement skewed by field (e.g., preprints dominated in medicine, life sciences, and physical sciences). Publishers should:

• Create tailored open science support resources per discipline.

• Co-design practices with communities where open norms are lagging (e.g., humanities).

• Embed open science goals into editorial board metrics and development.

Why it matters: A one-size-fits-all approach won’t meet community needs or drive adoption where it’s lacking.

🎯 3. Invest in Open Infrastructure and Cross-platform Interoperability

The study found figshare to be more used than GitHub for code sharing, possibly due to better publication alignment. Publishers should:

• Integrate with trusted repositories (figshare, Zenodo, Dryad, etc.).

• Ensure smooth workflows between submission platforms and open data/code storage.

• Support machine-readable metadata and persistent identifiers (e.g., ORCID, DOIs, RRIDs).

Why it matters: Seamless infrastructure empowers authors to share more and increases discoverability.

🎯 4. Leverage AI and Data Analytics for Continuous Monitoring

Taylor & Francis used AI (DataSeer) to track behavior patterns across thousands of articles. Other publishers can follow suit by:

• Partnering with AI companies or building internal tools to map open science adoption.

• Creating dashboards for internal and external reporting on open research KPIs.

• Using insights to refine submission workflows and community engagement.

Why it matters: Without data, strategic pivots are blind. AI turns qualitative shifts into actionable intelligence.

🎯 5. Align with Funding and Policy Mandates—But Lead, Don’t Follow

While policy compliance is still a driver, this study shows researchers often go beyond what’s required. Publishers should:

• Be proactive about aligning with Plan S, Horizon Europe, NIH, and other funder mandates.

• Lead initiatives on metadata standardization, reproducibility standards, and open research benchmarks.

• Advocate for balanced IP and licensing frameworks that support openness and sustainability.

Why it matters: Funders and institutions are pushing for openness—publishers must demonstrate value by being collaborators, not gatekeepers.

Conclusion: From Compliance to Culture

The Taylor & Francis study is a signal that open research is transitioning from a regulated requirement to a cultural expectation. Researchers are not just complying with mandates—they are actively embracing transparency, reuse, and visibility. This creates a unique inflection point for scholarly publishers. The question is no longer whether to support open research, but how fast and how well publishers can embed it into their business models, editorial workflows, and researcher services.

By aligning strategic goals with emerging author behavior, scholarly publishers can remain not just relevant, but essential in a research ecosystem defined by openness, collaboration, and innovation.

Suggested Next Steps for Leadership Teams

✅ Conduct an internal audit of open science indicators across the portfolio
✅ Launch a cross-functional open research task force (editorial, legal, tech, product)
✅ Develop dashboards to track DAS, ORCID, preprints, and code usage
✅ Pilot incentives for datasets and software deposited in FAIR-aligned repositories
✅ Share your roadmap publicly to attract authors who value transparency and reuse