Community perspectives on open data and data recognition

DOI: 10.60804/pha7-2t30

Photos of Jen Gibson, Hilary Hanahoe, Lautaro Matas (left to right).

In the second of a series of interviews with leaders from SCOSS-funded open infrastructure organizations, we asked about their perspectives on open data. In this post, we present perspectives from Dryad, RDA and La Referencia on milestones for open data, understanding data use, and how to advance recognition for data as an important scholarly output.

Dryad is an open data publishing platform and a community committed to the open availability and routine reuse of all research data. Dryad publishes research data across domains and provides a fully curated data publishing process to ensure data are discoverable and reusable. 

The Research Data Alliance (RDA) is a neutral global forum that brings together researchers, data practitioners, policymakers, and infrastructure providers to develop practical solutions for data sharing and reuse. Through the RDA Working Groups and Interest Groups, community members identify and collaboratively develop solutions to open science challenges, by producing recommendations, standards, technical specifications, and best practices that organisations worldwide can adopt. 

LA Referencia is a federated open science network connecting national open access infrastructures across Latin America (and Spain). LA Referencia builds and sustains shared, community-governed infrastructure; it harvests, normalizes, enriches and exposes metadata from national aggregators and institutional repositories, to make research outputs openly accessible, interoperable, and reusable across borders. 

What would you highlight as key milestones achieved in open data and in understanding data impact over the last few years?

“There’s been an evolution in the conversation around data and its relevance, importance, and impact. There’s been increased adoption of data sharing and stakeholder engagement is also deepening. The GREI program that Dryad participates in shows the NIH’s investment in generalist repositories, and repositories are adopting common standards by virtue of that program; that’s an important foundation for the future.

It is positive to see that funders are engaging with programs focused on rescuing data. Dryad has spoken with diverse stakeholders about the importance of data as a foundation of human knowledge. I see more opportunities to encourage wider reuse of data. Inspiring initiatives like 2i2C and Radiant Earth are modeling what can be done if data of a certain nature and scope is made available in a computationally-friendly environment.”

Jen Gibson, Dryad

“The definition of the FAIR principles is a key milestone. It’s 10 years young this year and it has really helped to advance the understanding of open science challenges. FAIR is not only mandated by many funding organizations, but also very well recognised by researchers and scientists globally. The remaining challenge is that FAIR compliance is not simple, nor does it come without a significant cost. It is a long-term investment that is required by all stakeholders to achieve the open science goals that have been set.

The second amazing achievement to me is the Rewards and Recognition “movement”, if I may call it that. The acknowledgement that all stakeholders in the research lifecycle can and should be recognised is a huge step forward. But like the changes in open access, this will take time and effort to become more mainstream. Pioneers in this field, like some Dutch institutions, are beacons of hope and promise that research assessment can change for the benefit of all. ” 

Hilary Hanahoe, Secretary General Research Data Alliance

Why do you believe that understanding how data is connected to other research objects is important? 

“LA Referencia supports links to datasets when these relationships are provided in the original metadata coming from repositories, journals, or other content providers. This means that connections between articles and datasets are already exposed when institutions describe them explicitly in their systems. Through a new project supported by the IOI Fund, we are now working to go further. One of the project’s objectives is to recover and reconcile links from external, open sources (e.g. OpenAIRE Graph, OpenAlex), and integrate them into LA Referencia’s aggregation and enrichment workflows. This work is part of the project’s technical roadmap and aims to strengthen the completeness, consistency, and reliability of relationships between research outputs across the region. 

Understanding how data is connected to other research objects is essential because research is produced as a process, not as isolated outputs. Making these connections visible supports reproducibility and reuse, allows data creators to receive attribution, and helps optimize the use of public resources by enabling data to be reused rather than recreated. In addition, richer linking between publications, datasets, software, and projects can inform more nuanced and responsible research-evaluation practices, moving beyond publication-centric metrics toward a better understanding of how knowledge is actually generated and reused. “

Lautaro Matas, Technical Manager, LA Referencia 

What information (e.g. metadata) is currently scarce or missing that you think is critical to better understand the use and impact of research data? 

“Despite sustained collective efforts and increasing alignment with metadata guidelines and FAIR principles, the overall quality and completeness of metadata across repositories and journals remains limited when measured against what is needed to properly understand research processes, data reuse, and impact. In many cases, metadata is sufficient for basic discovery, but insufficient for supporting robust evaluation, meaningful metrics, and evidence-based policy that could help shift incentives away from closed, proprietary systems toward an ecosystem of open science and public goods. 

Several types of metadata are particularly scarce or inconsistently available at scale, yet critical: 

• Standardized, machine-readable licenses, clearly expressing reuse conditions for datasets and related outputs. 
• Persistent identifiers for people (such as ORCID), with consistent attribution of roles and contributions.
• Persistent identifiers for institutions (e.g. ROR), enabling reliable affiliation tracking and aggregation. 
• Explicit links between research objects, including relationships between articles, datasets, software, methods, and supplementary materials. 
• Citation information for datasets, including both formal citations and other forms of reuse signals. 
• Journal- and venue-level metadata, such as publishing context, policies, and identifiers, which are often missing or poorly normalized. 
• Versioning and provenance metadata, indicating how datasets evolve over time and which versions were used in specific studies. 
• Usage and access metadata, collected in a comparable and privacy-preserving way. 
• Basic methodological and contextual metadata (temporal, geographic, and disciplinary coverage) that supports interpretation and reuse.

Improving metadata quality, coverage, and interoperability—together with more transparent usage and impact data—is essential to enable better metrics, fairer evaluation practices, and more efficient reuse of research data.”

Lautaro Matas, Technical Manager, LA Referencia 

What do you think are key aspects to advance recognition of data outputs?

“I like the Center for Open Science Strategy for Change, and how they describe components of infrastructure, policy, and community practices. My favorite is community practices, changing behavior among researchers. Until we do that, our experience in open science is that policy will only take us so far. Even when there are policies in place, researchers’ practices are not always aligned with research assessment. Researchers are going to do the things that they are recognized for, rather than things that take them out of their way or additional time. 

A key element of Dryad is that it treats data as a published object, each dataset has its own publication page. The next step is to make the broad-spectrum data we publish even more usable by humans in computational environments. Dryad has made tremendous progress in publishing more data over time, and we have been capturing data in ways that make it easier for the researcher to share it. There’s an interesting conversation around what more we can do to make cross-disciplinary data more attractive and ingestible for the machines, such as uncompressing files and helping people more readily find heterogeneous data. If we get more researchers connected with more data and more familiar with the practice of reusing data, then they will begin to recognize that behavior in others and give one another credit. I’m optimistic about that circle being realized in my lifetime.”

Jen Gibson, Dryad

“I was disappointed to note in the recently published State of Open Data 2025 report, that strong support for national mandates—policies that require researchers to share their data— has shifted both globally and regionally over the last 10 years in a less than positive way. That could be due to a number of factors: reduced budgets, geopolitical events, increased data wrangling burdens on scientists and researchers, slow growth of internal support services and staff to facilitate open data. This, to my mind, makes the research assessment framework and rewards and recognition activities all the more urgent. We need to demonstrate the impact and the value of open science and open data and how it can positively impact career trajectories, and contribute to achieving the open science goals. This means training, awareness raising and advocacy for recognition. It requires updated policies, funding and procedures to reward and recognise those producing open research and data outputs. It requires culture change and effort amongst all actors to accept and implement the necessary changes so all can reap the benefits.”

Hilary Hanahoe, Secretary General Research Data Alliance