Join our webinar - Data available on request: exploring a challenge in research data sharing

Join us for a discussion of one of the more pervasive challenges in research data sharing; data ‘available on request’. A panel of data specialists, researchers and editors will explore this issue as part of Love Data Week 2023, on 16th February at 09:00 EST / 14:00 UTC / 15:00 CET.
Published in Research Data
Join our webinar - Data available on request:  exploring a challenge in research data sharing

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The 2022 State of Open Data report shows a growing consensus that data produced by research should be made openly available. Alongside the research article, outputs such as data, code and protocols are vital to reproducibility and form building blocks of further research. Data sharing is becoming a standard requirement of funders and governments (for example the 2022 White House OSTP Nelson memo), whereas journals increasingly require transparency around how and where data will be available. 

But clear challenges still remain. Last year, a paper looking at over 3,000 open access articles reported only 6.8% of authors declaring data as ‘available on request’ actually shared data when requested. 

Publisher policies often express a preference for data sharing in repositories, but ‘available on request’ remains a common statement in research publications. With the background of a growing drive toward open and transparent data sharing, there is a pressing question of how best to achieve the goals laid out in high level policies.

To address this issue we are convening a panel discussion with editors, researchers and data specialists to explore:

  • Should ‘data available on request’ continue to be a valid data statement? If not, what’s the best approach to move away from this quite common statement?
  • How can publishers, funders, research institutes, peer reviewers and authors work together to ensure data are available
  • How should research data factor into credit and researcher assessment criteria?

Register for event here

This event is relevant to researchers, information and data specialists, librarians, funders and anyone working on the challenges of open research and data sharing. 

Attendees will have the chance to ask questions of the panel, and the event will be recorded and distributed to all registrants.


Moderator: Dr Maria Hodges has a PhD in Biochemistry from Cancer Research UK. She has been an Editor for Nature Structural and Molecular Biology, the Scientific Publications Manager for Cancer Research UK, managing the British Journal of Cancer, and an Editor of Genome Medicine. Dr Hodges is the Executive Editor for the BMC Series journals and for the Springer Nature Research Data Team. She is passionate about open access publishing and open science.

Dr Livia Puljak is a full professor at the Catholic University of Croatia, where she is also the Head of the Center for evidence-based medicine and healthcare. She was trained in the United States, Italy and Canada. Her research interests include research methodology, evidence-based medicine and clinical epidemiology. She has published more than 200 articles in international peer-reviewed journals and mentored more than 60 defended diploma, Master and PhD theses. She was the inaugural director of Cochrane Croatia.

Dr Rajarshi Guha is a co-Editor-in-Chief of the Journal of Cheminformatics, where sharing of data underlying researcher articles is mandatory. He is also involved in software and algorithm development in the areas of cheminformatics methods and large scale infrastructure projects including Pharos, BARD and open source projects such as the CDK.

Graham Smith is Open Data Programme Manager at Springer Nature. He works to develop and promote data sharing tools, partnerships and initiatives across the organisation’s publishing activities. Throughout his career he has worked with a wide range of disciplines and researchers to develop a data specialist viewpoint, implementing data curation and metadata services in public sector and commercial settings, including at the Natural History Museum in London.

Nicholas Bailey is Technical Product Manager at Dimensions Research Integrity. He is an expert in the way machines interpret natural languages (the languages humans use to talk to one another) and is passionate about keeping science objective, honest and reproducible. He spent 7 years developing AI in the legal and scholarly publishing sectors before becoming a product manager at Digital Science. A gifted scientific communicator, Nicholas regularly speaks at conferences and provides mentoring for early-career data scientists and developers. Alongside his work with Digital Science, Nicholas researches deep reinforcement learning and emergent languages at City University of London. He lives with his wife and two children in Cambridge, UK.

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