Digital Science is proud to be sponsoring this year’s conference.

The post Bibliometrics and Research Impact Community (BRIC) 2025 Conference appeared first on Digital Science.

Traditionally, September and October have always been one of the busiest – and most interesting – times to be in the publishing industry. Back in the day, September would be the deadline for the first of the following year’s issues to be collated by editors, while in more recent times big events like the ALPSP Conference, the Frankfurt Book Fair and Open Access Week have set the agenda for the remainder of the year and beyond.

In 2024, this period has perhaps more intrigue than most given a number of deadlines and political events occurring in the next 12 months or so, many of them revolving around open access (OA) and its further adoption. But will things pan out the way people anticipate, and are there solutions that can be used to help forge a path through so many uncertainties about the future?

Conference season

At the recent ALPSP Conference in Manchester in September, there was a good deal of discussion about how open access had developed this year, and its potential progress in 2025 and beyond. Perhaps unsurprisingly at a conference full of publishers, the mood was a little downbeat when it came to the theme of OA, but not for the reasons one might think. Reading between the lines, there was a frustration at the shifting sands many felt they had to constantly navigate, in the shape of changing or newly introduced policies, and a sense that innovation was being stymied as a result.

For example, the tone for OA seemed to have been set by the JISC report on transformative agreements (TAs) which was published in the UK earlier in 2024. This made for somber reading, with the headline prediction that while the UK’s transitioning to OA was faster than most countries, based on the journal flipping rates observed between 2018–2022 it would take at least 70 years for the big five publishers to flip their TA titles to OA. 

With this in mind, the fact that there were deadlines for Plan S set for 2025 around transition that seemed unlikely to be met, and with the OSTP memo in the US mired in committees and a potential change on the cards in the White House, the belief among many publishers was that the move to OA was not happening at the pace or in the direction that many thought it would.

Geopolitical calculations

In addition to what is happening in the UK, Europe and in the US, events further afield are also causing publishers to take stock of their medium-to-long-term strategies. The publication of authors based in Russia has declined sharply since the invasion of Ukraine in early 2022, and collaboration between US authors and those based in China have also decreased, possibly due to policy changes by the Chinese government favoring publication in China-based journals, but also potentially due to fears about research security issues in the US and in other countries. 

China’s move to OA is also happening at a much lower level than many countries, which is significant as it takes up such a high percentage of published articles, passing the US a few years ago as the world’s most prolific publisher of research articles. As a result, despite the increase in the number of TAs being agreed with universities, publishers are still seeing a high degree of uncertainty in the transition to OA.

Forward motion

This uncertainty will be in the back of publishers’ minds when celebrating OA Week this year, coming as it does every year on the back of major conferences such as ALPSP and Frankfurt, and in the midst of fine tuning budgets for the following year. At Digital Science, we understand this predicament given how closely we work with publishers as customers, and also because many of us have worked in the publishing industry ourselves. As such, we have been analyzing how Digital Science solutions can help publishers steer a path forward on OA and transformative agreements, and have created this use case for Dimensions in support of our community.

This resource has been designed to reflect the period of change that the publishing industry is undergoing, supporting the need for publishers to create, evaluate and negotiate TAs by delivering a strong range of historical and predictive data through Dimensions. Using the Dimensions database – which now holds data on almost 150m publications as well as details on funding, grants and patents – publishers can easily find and analyze data surrounding authorship across categories such as country, geography, institution and funder. Understanding a given discipline’s current or future state of play can complement publishers’ own data and inform their strategies accordingly.

Solid state

The theme of this year’s OA Week – ‘Community over Commercialization’ – is a deliberately provocative one, and should engender a good deal of debate during the week and beyond. It should also broaden the conversation to adjacent areas such as open research and open science, as here we have policy and geopolitics making waves for everyone involved in the research ecosystem. 

The origin of some of these ripples can be seen in two upcoming reports from Digital Science. At the end of October, a new report on Research Transformation includes substantial input from those involved in academia on how OA is impacting on their work, while November sees the ninth annual State of Open Data report, tracking how researchers see open data issues developing as part of their work. Without giving too much away, both of these reports call for greater awareness of – and support using – the myriad of fast-developing technologies that are starting to impact academics and their institutions. As such, the community of interest that supports OA Week every year needs to work together in the ecosystem they all inhabit if those OA deadlines are to be met.

About the Author

Simon Linacre, Head of Content, Brand & Press | Digital Science

Simon has 20 years’ experience in scholarly communications. He has lectured and published on the topics of bibliometrics, publication ethics and research impact, and has recently authored a book on predatory publishing. Simon is an ALPSP tutor and has also served as a COPE Trustee.

The post Will 2025 be a turning point for Open Access? appeared first on Digital Science.

At this year’s World Conference on Research Integrity, a team of researchers from Digital Science led by Pritha Sarkar presented a poster with findings from their deep dive on conflict of interest (COI) statements. Entitled Conflict of Interest: A data driven approach to categorisation of COI statements, the initial goal was to look at COI statements with a view to creating a binary model that determines whether a Conflict of Interest statement is present or not in an article. 

However, all was not as it seemed. While some articles had no COI and some had one present, those present covered a number of different areas, which led the team to think COIs might represent a spectrum rather than binary options.

Gold standard

Conflict of interest is a crucial aspect of academic integrity. Properly declaring a COI statement is essential for other researchers to assess any potential bias in scholarly articles. However, those same researchers often encounter COI statements that are either inadequate or misleading in some way even if they are present. 

The Digital Science team – all working on research integrity with Dimensions – soon realized the data could be leveraged further to better explore the richness inherent in the nuanced COI statements. After further research and analysis, it became clear that COI statements could be categorized into six distinct types:

1. None Declared
2. Membership or Employment
3. Funds Received
4. Shareholder, Stakeholder or Ownership
5. Personal Relationship
6. Donation

This analysis involved manually annotating hundreds of COI statements with Natural Language Processing (NLP) tools. The aim was to create a gold standard that could be used to categorize all other COI statements, however despite the team’s diligence a significant challenge persisted in the shape of ‘data skewness’ – which can be defined as an imbalance in the distribution of data within a dataset that can impact data processing and analytics.

Fatal flaw

One irresistible conclusion to the data skewness was a simple one – that authors weren’t truthfully reporting their conflicts of interest. But could this really be true?

The gold standard approach came from manually and expertly annotating COI statements to develop an auto-annotation process. However, despite the algorithm’s ability to auto-annotate 33,812 papers in just 15 minutes, the skewness that had been initially identified persisted, leading to the false reporting theory for authors (see Figure 1 of COI Poster). 

To firm up this hypothesis, when the Retraction Watch database was analyzed, the troubling trend, including the discrepancy between reported COI category and retraction reason, became even more apparent (see Figure 2 of the COI Poster). 

Moreover, when the team continued with the investigation, they found there were 24,289 overlapping papers in Dimensions GBQ and Retraction Watch, and among those papers, 393 were retracted due to conflict of interest. Out of those 393 papers, 134 had a COI statement, however 119 declared there was no conflict to declare.

Conclusion

Underreporting and misreporting conflict of interest statements or types can undermine the integrity of scholarly work. Other research integrity issues around paper mills, plagiarism and predatory journals have already damaged the trust the public has with published research, so further problems with COIs can only worsen the situation. With the evidence of these findings, it is clear that all stakeholders in the research publication process must adopt standard practices on reporting critical trust markers such as COI to uphold the transparency and honesty in scholarly endeavors. 

To finish on a positive note, this research poster was awarded second-place at the 2024 World Conference on Research Integrity, showing that the team’s research has already attracted considerable attention among those who seek to safeguard research integrity and trust in science.

You can find the poster on Figshare: https://doi.org/10.6084/m9.figshare.25901707.v2

Partial data and the code for this project are also available on Figshare.

For more on the topic of research integrity, see details of Digital Science’s Catalyst Grant award for 2024, which focuses on digital solutions around this topic.

About the Author

Simon Linacre, Head of Content, Brand & Press | Digital Science

Simon has 20 years’ experience in scholarly communications. He has lectured and published on the topics of bibliometrics, publication ethics and research impact, and has recently authored a book on predatory publishing. Simon is an ALPSP tutor and has also served as a COPE Trustee.

The post Shining a light on conflict of interest statements appeared first on Digital Science.

To AI or not AI?

The use of AI technologies has always been susceptible to charges of potential bias due to skewed datasets large language models have been trained on. But surely firms are making sure those biases have been ironed out, right? Sadly, when it comes to AI and recruitment, not all applications of the technology are the same so firms need to tread carefully. In other words – if you don’t understand it, don’t use it.

Since the launch of ChatGPT at the end of 2022, it has been difficult to read a newspaper, blog or magazine without some reference to the strange magic of AI. It has enthused and concerned people in equal measure, with recruiters being no different. From every gain in being able to understand and work with huge amounts of information, there appears to be negatives around data bias and inappropriate uses. 

Scismic is part of the larger company Digital Science, and both have been developing AI-focused solutions for many years. From that experience comes an understanding that responsible development and implementation of AI is crucial not just because it is ‘the right thing to do’, but because it simply ensures better solutions are created for customers. Customers who in turn can trust Digital Science and Scismic as partners during a period of such rapid change and uncertainty.

AI in focus

The potential benefits of using AI in recruitment are quite clear. By using Generative AI such as ChatGPT, large amounts of data can be scanned and interpreted quickly and easily, potentially saving time and money during screening. In turn, the screening process may also be improved by easily picking up key words and phrases in applications, while communications about the hiring process can be improved by using AI-powered automated tools.

But, of course, there is a downside. Using AI too much seems to take the ‘human’ out of Human Resources, and AI itself is only as good as the data it has been trained on. A major issue with AI in recruitment has been highlighted by the recent brief issued by the US Equal Employment Opportunities Commission (EEOC), which supported an individual who has claimed that one vendor’s AI-based hiring tool discriminated against them and others. The EEOC has recently brought cases against the use of the technology, suggesting that vendors in addition to employers can be held responsible for the misuse of AI-based technology. 

When should we use AI?

In general, if you don’t understand it, do not use it. Problems arise for both vendors and recruiters alike when it comes to the adoption of AI tools at scale. While huge data sets offer the advantages set out above, they also introduce biases over and above human biases that employers and employees have been dealing with for years. Indeed, rather than extol the virtues of using AI, it is perhaps more instructive to explain how NOT to use this powerful new technology.

As a responsible and ethical developer of AI-based recruitment solutions, colleagues at Scismic were surprised to see a slide like the one below at a recent event.  While it was designed to show the advantages of AI-based recruitment technology to employers it actually highlights the dangers of ‘layering’ AI systems on top of each other. This means the client company will lose even more visibility on who and how the system is selecting – increasing the risk of bias, missing good candidates and, ultimately, the risk of legal challenge. 

In this scenario, with so many technologies layered onto each other throughout the workflow, it is almost impossible to understand how the candidate pipeline was developed, where candidates were excluded, and at which points bias has caused further bias in the selection process!

While the list of AI tools used in the process is impressive, which is less so from a recruitment perspective is the layer upon layer of potential biases these tools might introduce to the recruitment process.

At Scismic, they offer a different approach. AI is used to REMOVE biases in datasets, so that all of the advantages of using automated processes are protected by introducing mitigating processes, thus ensuring a fairer and more ethical recruitment program for employers. 

Positive Discrimination?

Scismic’s technology focuses on objective units of qualifications – skills. We use AI to reduce the bias of terminology usage associated with describing skills. Now we have two ways in which we reduce evaluation bias:

1. Blinded candidate matching technology that relies on objective units of qualifications – skills
2. Removing bias of candidates terminology to describe their skill sets.

What type of AI is being used?

To help explain how Scismic does this, we can split AI into subjective (or Generative) AI like ChatGPT, and objective AI. Subjective AI is, broadly, a contextual system that makes assumptions on what to provide the user based on the user’s past interactions and its own ability to use context. This system can work well for human interactions (such as ChatBots) which is what it was designed for. 

However, when applied to decision making about people and hiring (which is already an area fraught with difficulty) subjective and contextual systems can simply reinforce existing bias or generate new bias. For example, if a company integrates a GenAI product into its Applicant Tracking System (ATS) and the system identifies that most of the people in the system share a particular characteristic then the system will assume that’s what the company wants. Clearly if the company is actually trying to broaden its hiring pool this can have a very negative effect, which can also be challenged in court. 

Objective AI works differently as it does not look at the context around the instruction given but only for the core components it was asked for. This means it doesn’t make assumptions while accumulating the initial core results (data) but can provide further objective details on the data set.  In many ways it is a ‘cleaner’ system but because it is focused and transparent it is the better choice for removing unintended bias.

AI is a tool and, as with so many jobs that require tools the question is often; what is the best tool to use? In short, we recommend that a tool that produces better results with less bias is the answer in a hiring process.

Case by case

To show how well some cases can turn out when using ‘objective AI’ responsibly and astutely, here are three case studies that illustrate how to arrive at some genuinely positive outcomes:

1. The right AI: With one customer, Scismic was hired to introduce a more diverse pool of talent as the company was 80% white males, and those white males were hiring more white males to join them. After introducing Scismic’s recruitment solution, the percentage of diverse applicants across the first five roles they advertised rose from 48% to 76%
2. The right approach: One individual who had been unlucky in finding a new role in life sciences for a very long time finally found a job through Scismic. The reason? He was 60 years old. With an AI-based hiring process, his profile may well have been ignored as an outlier due to his age if a firm typically hired younger people. However, by removing this bias he finally overcame ageism – whether it had been AI- or human-induced – and found a fulfilling role with a very grateful employer
3. The right interview: Another potential hire being helped by Scismic is neurodivergent, and as a result appears to struggle to be successful in interviews. An AI-based scan of this person’s track record might see a string of failed interviews and therefore point them to different roles or levels of responsibility. But the lack of success is not necessarily down to this, and human intervention is much more likely to facilitate positive outcomes than using AI as a shortcut and misdiagnose the issue.

When not to use AI?

One aspect highlighted in these case studies is that while AI can be important, what can be equally as important is when NOT to use it, and understand it is not a panacea for all recruitment problems. For instance, it is not appropriate to use AI when you or your team don’t understand what the AI intervention is doing to your applicant pipeline and selection process. 

Help in understanding when and when not to use AI can be found in a good deal of new research, which shows how AI is perhaps best used as a partner in recruitment rather than something in charge of the whole or even part of the process. This idea – known by some as ‘co-intelligence’ – requires a good deal of work and development on the human side, and key to this is having the right structures in place for AI and people to work in harmony. 

For example, market data shows that in the life sciences and medical services, employee turnover is over 20%, and in part this is due to not having some of the right structure and processes in place during recruitment. Using AI in the wrong way can increase bias and lead to hiring the wrong people, thus increasing this churn. However, using AI in a structured and fair way can perhaps start to reverse this trend.

In addition, reducing bias in the recruitment process is not all about whether to use or not use AI – sometimes it is about ensuring the human element is optimized. For instance, recent research shows that properly structured interviews can reduce bias in recruitment and lead to much more positive outcomes. 

With recruitment comes responsibility

It is clear that AI offers huge opportunities in the recruitment space for employees and employers alike, but this comes with significant caveats. Both for recruiters and vendors, the focus on developing new solutions has to be how they can be produced and implemented responsibly, ethically and fairly. This should be the minimum demand of employers, and is certainly the minimal expectation of employees. The vision of workplaces becoming fairer due to the adoption of ethically developed AI solutions is not only a tempting one, it is one that is within everyone’s grasp. But it can only be achieved if the progress of recent decades in the implementation of fairer HR practices are not lost in the gold rush of chasing AI. As a general rule, recruiters and talent partners should understand these components of the technologies they are using:

1. What is the nature of the dataset the AI model has learnt from? 
2. Where are the potential biases and how has the vendor mitigated these risks?
3. How is the model making the decision to exclude a candidate from the pipeline? And do you agree with that premise?

Understanding the steps involved in creating this structure can be instructive – and will be the focus of our next article, ‘Implementing Structured Talent Acquisition Processes to Reduce Bias in your Candidate Evaluation’. In the meantime, you can contact Peter Craig-Cooper at Peter@scismic.com to learn more about our solutions.

See also our announcement: STEM skills-based economy focus for Scismic’s new Chief Commercial Officer

About the Author

Simon Linacre, Head of Content, Brand & Press | Digital Science

Simon has 20 years’ experience in scholarly communications. He has lectured and published on the topics of bibliometrics, publication ethics and research impact, and has recently authored a book on predatory publishing. Simon is an ALPSP tutor and has also served as a COPE Trustee.

The post Scismic and Objective, Skills-focused, AI-driven Recruitment in STEM appeared first on Digital Science.

Research strategy

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As the demand to showcase the value of academic research intensifies, our data and solutions enable you to objectively measure and demonstrate academic, societal, and economic impact.

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Elements helps you to build collection of structured, reusable impact records, ready to be curated into case studies, developed into news stories or included in reports to funders.

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Impact doesn’t happen overnight, so our dedicated built-in Impact Module allows researchers (or their proxies) to build up their impact records over time, adding narrative fields to capture events as they happen as well as adding associated files, links and references.

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Carnegie Mellon University: Tracking Sustainable Development Goals using Symplectic Elements

How can I measure the real-world impact of our research?

Track and showcase the full scope of your research impact using Dimensions. With real-time, interconnected data across the entire research lifecycle, Dimensions helps you:

• Measure research influence through publications, grants, patents, clinical trials, and policy documents.
• Benchmark your institution’s performance with customizable dashboards and gain insights into strengths and successes.
• Demonstrate real-world impact to stakeholders and funders, helping to attract top talent and secure future funding.

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Make your researchers and their expertise as discoverable as possible by repurposing research information data to populate fully-rounded profiles including biographical information as well as publications, grants and professional & teaching activities.  To help your research go even further, you can also provide profile visitors with direct links to open access copies of your publications.

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The Higher Education Technology Agenda (THETA) 2025

25th May 2025 | Australia

Conference

Join us in Perth for THETA 2025.

Find out more

Bibliometrics and Research Impact Community (BRIC) 2025 Conference

3rd June 2025 | Canada

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3rd June 2025 | Ireland

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10th September 2025 | Australia

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Latest insights

Women’s first publications in decline

Deep dive into data that shows that the proportion of women authors publishing their first article is in decline

Read now

Introducing… Research Transformation

A new campaign from Digital Science looks at how research can transform society at large

Read now

What is ‘initial transformation’?

What’s in a name – what we can learn from the evolution of the use of author’s initials in their publishing names

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Forensic Scientometrics

A new field has emerged where academic ‘sleuths’ use publication data to unearth breaches of ethics

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Come meet us

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25th May 2025 | Australia

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Join us in Perth for THETA 2025.

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Bibliometrics and Research Impact Community (BRIC) 2025 Conference

3rd June 2025 | Canada

Conference

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Sponsor

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10th September 2025 | Australia

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Making data a priority

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A new approach for AI

Introducing an integration between Dimensions and ChatGPT for a new way to research data

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Digital Science welcomes the Barcelona Declaration as a force to continue pushing forward not only openness and transparency but also innovation in and around the scholarly record. Following the launch of this important initiative, we reflect on Digital Science’s path and historical contributions, the economics of maintaining the scholarly record, and its future.

Dimensions is built around open data

In many senses, Dimensions is a demonstration of what can be done when data are made freely and openly available. It would not have been possible to build and maintain Dimensions without the work of initiatives such as I4OC, and the data made available by CrossRef, DataCite, PubMed, ORCID, arXiv and many others. Many pieces of the Dimensions data system leverage use of public sources, and we believe that it is only right and proper to have a version of our product that is available to the community for research purposes at no cost – hence, the free version of Dimensions that we have maintained since 2018, and which we will continue to maintain into the future.

However, service to the community was not the only reason to create a free version of Dimensions back in 2018; it was also about ensuring that researchers had access to search the scholarly record for free and about ensuring that, in an era of increasing research evaluation and increasing research on research, there would be a platform where anyone could go to check results from an analysis or evaluation exercise. At that time, we wrote a paper stating our rationale and principles behind the development of Dimensions and wrote a follow-up piece announcing and committing to continued access for academic research.

In summary, and relevant to current developments, we believe that:

• Researchers have a fundamental right to access research metadata to further their research;
• Research into bibliometrics and scientometrics, and related fields, needs to have a basis for reproducibility and we seek to participate in that ecosystem to ensure that any analysis carried out using Dimensions data is reproducible;
• Data that are used to evaluate academics or institutions should be made available in a way that allows those being evaluated to have an insight into the data on which they are being evaluated.

There is, however, an important additional component that goes beyond these principles – innovation.

A more complex picture

Before we talk about innovation, it is important to acknowledge that Dimensions is not solely built on open data. Indeed, it is a mixed environment with data of different types describing different research objects using different sources.  This leads to significant complexity in the data pipeline and in the work that needs to be done to provide “analytics-ready” data. However, for the purposes of the current discussion, it is helpful to understand a bit about the different nature of the sources of data used in our data products. These include open data from open sources. When data are published under a CC0 licence (as Digital Science did with its GRID dataset in 2017) then it is unambiguous that these data may be used in any context, commercial or noncommercial, and that they may be merged with other datasets for the purposes of creating new and better things. It is an interesting question as to whether a Digital Science “mirror” of these helps to make the research infrastructure more robust and easier to access. 

Our products also make use of licensed data. These are data for which we have an agreement that restricts its use. Examples can range from research articles; grant data from funders; and, patent documents. They can also include data licensed into products such as Altmetric, which includes data from news providers and social media platforms such as Twitter (X). These data can be expensive to acquire and can only be used and made available in our products within certain limits, even where they are already in the public domain.

All these data and data that are derived from them, even if already freely and openly available, can require substantial resources to compile and process. Examples of such derived data could include funder details, details of ethics statements, conflict of interests, data availability statements, and so on, that Digital Science has transformed, enriched and contextualised. All are activities that take significant investment and add significant value to those who use it. We expect that these types of data will increasingly become part of the Open dataset as the research ecosystem matures. Yet, as we innovate, these are also the data that cost Digital Science the largest investment to produce and maintain, including where this may be done in an automated manner. The infrastructure behind Dimensions is not simply a platform that takes data from open sources and then reserves it for users to consume; rather, it is a complex and expensive mechanism for compiling, refining and improving data so that it can be discoverable, useful and analytics ready.

Taking author contribution statements as an example, the Dimensions team has invested in the creation and curation of AIs that identify author contribution statements across the research literature. These AIs operate at a level of accuracy that still needs improvement, and hence further investment. Neither the scholarly community, nor publishers, nor standards organisations have defined or accepted a standardised data format that makes author contribution statements widely available. As such there is a significant cost to data processing. On top of this, innovations such as the CReDIT taxonomy are neither universally or evenly applied. The use of CReDIT would be of significant value to sociologists who study the research community, as well as to the evaluation community and anyone involved in tenure and promotion processes. And yet, there is no accepted structured data format that makes these data easily available. As such, the Dimensions team is working on the development of a CReDIT data structure and the creation of these data at a level of quality where they can be trusted and used in these important use cases.

As the research ecosystem matures, what should the path from algorithmically generated information back to openly available data with a defined provenance be? One option is to provide enhanced metadata back to publishers to enhance the scholarly record where gaps exist. Arguably, it is not enough for data only to be open – it should be owned by the community that created it, which includes ensuring the context and provenance of the data are maintained. This process has happened many times before, most notably during the application of DOIs to the historical scholarly record.

A model for thinking about innovation

To make sense of this complex landscape we have a mental model that we use to think about the developing world of open research metadata.

The area outside the outer circle (or horizon) can be thought of as all unpublished articles and all articles as yet unprocessed. With time the outer circle expands encompassing both more detail about the existing published literature (new fields, greater accuracy) and the detail about newly published work. At the horizon of the circle the data are mined and fall inside the circle. The fact that the circle expands is important in this model as the effort to derive the data does not expand proportionally to the volume of data refined, but it does increase. The horizon is representative of the ongoing investment in innovation that is required to derive and improve data from raw, unstructured formats. In practical terms, some cases require humans to identify data from texts; in other cases humans write and train AIs to create annotations and make them available.

The inner circle (or the “beautiful” horizon) can be thought of as open data or data that has become so inexpensive to make available as part of increases in efficiency of the production process that it is completely commoditised. These are data that either cost little to provide or are already refined to the point where little or no innovation is required to make them available. Examples include article title, journal name, page number, DOI and, most recently as a result of I4OC and I4OA, citations and abstracts.

The area between these two circles is where the friction at the heart of the Barcelona Declaration exists. A few years ago, it might be argued that there was no inner circle and yet, over the last 20 years, projects including PubMed, Crossref, I4OC, I4OA and pre-print servers such as RePEc and arXiv have slowly created a space for open data, either through community action or technological progress. Among the contributors to this effort there are some notable players including the Microsoft Academic Search project, 1science from the team at ScienceMetrix, and others.

Such a model is not unusual in other contexts, nor is it surprising that it is the natural point of friction. Determining the time for which an innovation should be profitable and the level of profit is not a trivial problem – it is sometimes left to market forces or sometimes is the result of legislation. In the context of copyright law, which was originally developed to protect creativity, the distance between the circles is determined by law to be 70 years after the death of the author in many geographies, although there are variances. Perhaps closer to home, and less legal (but nonetheless social-contract-style) agreements include humanities PhD theses, which often have an agreed two-year embargo period during which the student has the opportunity to develop and publish a book or otherwise build on top of their work.

There are other non-legislative mechanisms that also determine the distance between analogous horizons in other contexts. One might argue that the creation of a new patented invention is like the innovation horizon of the outer circle, whereas the beautiful horizon of the inner circle is the creation of parallel developments that seek to achieve the same ends as the original invention via different mechanisms. Typically, the time taken for competitors to duplicate an approach, might take several years. At some point the patent will expire, but it may already be rendered useless by the innovations of others.

Perhaps uniquely in the research information sector, Digital Science has pushed both horizons – pushing the innovation horizon:

• Connecting patent data, grant data, clinical trials and datasets in an analytics-ready dataset;
• Pioneering the creation of article level metrics with Altmetric;
• Pioneering the open sharing of research data at scale with Figshare;
• Improving the timeliness of data;
• Innovating to democratise the application of computational power to bibliographic data;
• Showing how to connect bibliographic data to wider contexts to leverage investments in open identifiers;
• Developing the first SDG categorisation;
• Developing transparent categorisation approaches using AI;
• Measuring the progress toward the adoption of OCRID against algorithmically identified research identifiers;
• Making a free ChatGPT experience available that leverages the content in Dimensions;
• Contributing to the ongoing discussions to protect the scholarly record by the open documentation of approaches to identify paper-mill activity;

as well as pushing the open data horizon:

• Making grant data freely available to funders who award less than $1m in funding per year;
• Making Dimensions available for free to Research4Life;
• Making GRID institution data available CC0;
• Making dataset searching and citations freely available in Dimensions and Figshare;
• Making ANZSRC and SDG classification freely available in Dimensions;
• Making grants data available to ORCID profiles through the UberWizard.

Taking a pragmatic position suggests that the annulus needs to be determined dynamically rather than systematically. If an individual or a company invests in pushing the innovation horizon then they are taking a chance on improving the data that researchers and other stakeholders have to make better decisions, gain deeper insights or be more efficient, and there should be an incentive to continue to invest in innovation. If the innovation is incremental or easy to replicate then the returns will be small as others should easily duplicate it. If the innovation is significant then it will be harder for others to reproduce and hence it will take a longer period before competitive forces come to bear.

A step change in technology can upset the equilibrium and change both the current competitive dynamics as well as the future focus of innovation. Machine learning was one of the key technologies that has allowed the Dimensions team to push resources into innovation over the last few years, and enhancements in the AI landscape with large language models (LLMs) will continue to fuel these developments.

At Digital Science, our belief is that by taking risks, being innovative and pushing boundaries, so that clients gain real value and significant benefit from our offerings, there should be an opportunity for an appropriate return on investment. We believe that the chance to profit is naturally kept in check by competition, which typically pushes the outer circle, by initiatives such as the Barcelona Declaration, which often advance the inner circle, and by our own mission as Digital Science to support and serve research and the community around it, where we have clearly demonstrated the ability and the will to move both circles.

The Future

Using the model above, it made sense in the past that scholarly information would be closed. In the 1950s, when Eugene Garfield started the Institute for Scientific Information, the investment required to construct the science citation index was significant. Indeed, it was Garfield’s realisation that 80% of the citations related to 20% of the literature which turned the problem of citation tracking into one that was tractable with technology contemporary to the era.

The investment that needed to be made to “mine” the publication and citation information, given the level and nature of scholarly information infrastructure at this time, was vast. Hence, it is unsurprising that the Science Citation Index was, in essence, the only such index for almost 50 years. With the digitisation of the scholarly record towards the end of the 20th Century, the bar to entry was lowered and PubMed, Crossref, Google Scholar and Scopus were all innovators, introducing competition and, ultimately, creating the Open Data Horizon.

In 2018, Dimensions made use of successive innovations from the community, such as I4OC, together with machine learning to lessen the distance between the two circles.

In the next 10 years, with technological advances in how we write and publish scholarly output, we see a world in which much of the metadata is simply available at the point of production as open data – a true realisation of the Barcelona Declaration. At this point, the distance between the two circles will be zero, with the innovation horizon and the open data horizon coinciding. The effective cost of production of the data will be zero.

So, what will be beyond Barcelona? There are still many challenges regarding research information – there will probably be a further period beyond the Barcelona Declaration’s aims in which, as we already are, we start to invest more heavily in information provenance, the integrity of research information, and in understanding sentiment and bias in the research literature. Our field of focus will shift to ensuring that we can trust the information that will be increasingly important not only in decision making but in forming the basis of AI curricula in the future.

I have confidence that in an innovative field such as research, innovation will continue to be expected of those who seek to serve the space. While Barcelona defines a beautiful horizon, that is still compatible with an endless frontier.

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Last week, one of the world’s largest charitable organizations, the Bill & Melinda Gates Foundation, changed its policy on open access. In a major shift, it decreed that from 2025 it would no longer fund authors’ article processing charges (APCs) to be published in open access journals. Instead, it will mandate authors to make their articles available as ‘preprints’, which are available to read by everyone but require no fee to post online in a repository. 

Quite clearly, this move is designed to build on the advantages of making medical research openly accessible, as well as capturing the frustration that many share of not being able to discover key information about potentially life or death medical issues – whether that is due to paywalls on articles, or the sometimes hefty APCs that are charged. It was these advantages and frustrations that resulted in the open access (OA) movement forming in the 1990s, and as we detailed here last year fuelled the growth in OA over the last quarter of a century. 

But as we celebrate National Public Health Week and World Health Day on 7th April, what has been the impact of OA in opening up research to the public at large?

Research Transformed

Articles supported by the Bill & Melinda Gates Foundation (BMGF) make up a sizeable corpus of texts in the medical literature – according to Dimensions, in 2023 there were 4,494 publications that acknowledged funding from the Foundation,  appearing in journals published by major publishers such as Elsevier (855 articles funded by BMGF), Springer Nature (780) and Wiley (347). While there are already substantial numbers of articles published in major journals funded by BMGF – and the new mandate does not appear to stop them being published in such journals subsequent to posting as preprints – we may see some changes as a result of the ‘preprint first’ policy.

Changing our focus to looking back at how health research such as that funded by BGMF has been made available to all as open access articles, we can see from the chart below that there has been a marked increase in the amount of medical research that is now openly accessible over the last 20 years or so. And significantly, we can also see this using the free web app of Dimensions.

In 2003 there were 1.66 million article publications, according to Dimensions, with just a quarter of them available as open access articles. We can see in the chart that some of the main health categories made up a sizable number of these OA articles in 2003, which was just three years after the Bill & Melinda Gates Foundation was first formed. 

Fast forward 10 years, and medical research had started to transform in terms of its accessibility to the public. In 2013 there were 3.1 million articles published, of which 1.3 million, or 42%, were now OA. Looking at health research specifically, the percentages were much bigger as adoption in these fields outpaced others: In Biomedical and Clinical Sciences 48% of articles were OA, in Clinical Sciences it was 45% and in Biological Sciences it was already over half at 57%.

Further acceleration in the adoption of open access in the last decade has seen the accessibility of health research grow even further. Not only has the total number of articles published increased by well over 50%, but the proportion of articles in medical research that are open access are well over 60%, and nearly 70% in the case of Biological Sciences. 

New perspectives

Since its inception, the Bill & Melinda Gates Foundation has made grant payments totalling over $71 billion to support gender equality, global development and global health programs. Its aim has been to create a world where each individual has the opportunity to lead a healthy, productive life, and you can see from its commitment to OA that it views access to the most current research as being part of that mission. As we reflect on and celebrate National Public Health Week and World Health Day, it is clear how important access to data is in supporting underserved communities to take advantage of the benefits that access to health research brings. To learn more about how research impacts society, see our latest TL;DR campaign on Research Transformation.

About the Author

Simon Linacre, Head of Content, Brand & Press | Digital Science

Simon has 20 years’ experience in scholarly communications. He has lectured and published on the topics of bibliometrics, publication ethics and research impact, and has recently authored a book on predatory publishing. Simon is an ALPSP tutor and has also served as a COPE Trustee.

The post Healthy increase in access to Medical Research appeared first on Digital Science.

On Monday night our five amazing Lightning Talk speakers set the scene for what this means for research. From how the research profession has been shaped around persistent biases that work against 51% of the population, to why we should all care about the underrepresentation of women and other groups within research and in the topics we choose to allocate funding for, and from specific examples of what this means for all of society, to why we must have better representation within the teams that build solutions to overcome the challenges we face as a society, #FuturePub gave our audience lots to think about over the pizza, drinks, and table tennis tournaments that followed.

It feels awfully frivolous to wish anyone a “happy” International Women’s Day. That such a day needs to exist is saddening, but it is necessary. The day is a powerful reminder of the ongoing struggle for gender equality, but also an opportunity to celebrate the achievements of women across all sectors of society. For those of us working within and adjacent to research, this day holds particular significance as it provides an opportunity to acknowledge the accomplishments of women scientists, engineers, scholars, and innovators who have made valuable contributions to human knowledge and progress, and highlight their groundbreaking discoveries, innovative solutions, and significant impact in their respective fields, so it felt like the perfect theme for our first community engagement event of 2024.

Historically, women have faced numerous barriers and obstacles in pursuing careers in science, technology, engineering, and mathematics (STEM). From discriminatory hiring practices to implicit biases and systemic barriers, women have often been marginalised and underrepresented in research fields. International Women’s Day helps to raise awareness about the challenges and inequalities that women continue to face in the research profession. Despite progress in recent decades, gender disparities persist in areas such as funding, publication rates, leadership positions, and recognition for research achievements. By shining a spotlight on these issues, International Women’s Day sparks important conversations and mobilises efforts to address gender inequality and promote inclusivity in research, which our five speakers certainly did.

Subhadra Das – The History We Deserve

We kicked off the evening by hearing about some of the history that has shaped today’s research culture from Subhadra Das, a writer, historian, broadcaster and comedian who looks at the relationship between science and society. She specialises in the history and philosophy of science, particularly the history of scientific racism and eugenics. For nine years she was Curator of the Science Collections at University College London. She has written and presented podcasts and stand-up comedy shows, curated museum exhibitions, and has appeared on radio and TV. Her first book Uncivilised: Ten Lies That Made The West is out now.

Beginning her talk with a reminder of the full title of Darwin’s Origin of the Species, Subhadra told the story of some of the lesser-known characters of centuries past including Edward Drinker Cope, a nineteenth-century American scientist whose research ran the gamut from dinosaur hunting to false notions of the sex binary and what it means to be “civilised”. Cope believed that people of European ancestry were evolutionarily superior to other races. Cope’s legacy continues today, with evidence of the persistent mistreatment and dismissal of the medical symptoms of non-European people and women in particular. For example, Subhadra shared the statistic that black women and birthing people die at 3 to 4 times the rate of white people from childbirth-related causes. Subhadra’s talk, and indeed her book, are evidence-based reminders that we should be mindful of our history today and always in order to serve all of society through research, and mitigate for the biases built into the system. You can pick up a copy of Subhadra’s book here.

Even though we have come a long way since Cope’s time, gender discrimination is still rife, in research and in society. A quick look at some of the comments under Professor Dame Athene Donald’s Digital Science-sponsored Speaker Series talk on the Royal Institution’s YouTube channel shows that there is real disengagement around equity for all in research. However, we hope that, by presenting data-supported evidence of the impact that a lack of inclusion in science will have on ALL of us, we will be able to create more dialogue and discourse around the topic and generate a greater appetite for everyone to play their part to change things, one small step at a time.

Dr Hélène Draux – Digital Science – What The Decline in Women’s First Publications Means For Research

Data and the demographics of research are topics that our next speaker lives and breathes. Dr Hélène Draux is a Senior Data Scientist at Digital Science. She creates bespoke bibliometrics analyses and visualisations for clients in the research sector with data, using platforms such as Dimensions, Altmetric, Figshare, Elements, IFI Claims, and GRID, often also incorporating clients’ data and external data. Her specialties include gender analyses, geographic analyses, topic modelling, network analyses, and interactive visualisations. She has published a book chapter on Visualisation of Research Metrics, and her work was featured in Nature. During the pandemic she also published a peer reviewed article about the speed of publishing and gender differences in publication, and it is this work that Hélène built on in her Lightning Talk.

Despite past progress, including women in the US surpassing men in doctoral degree attainment, the COVID-19 pandemic has disproportionately affected women, potentially halting or reversing their academic advancements. Based on data from dimensions.ai and Gender API, Hélène explored the trend from the year 2000 onwards, and observed a significant drop in women’s first publications in recent years. Her talk highlighted the importance of recognising and addressing the systemic challenges faced by women in academia, with a call to action for institutions and funders to support and retain women in research, thus ensuring their contributions continue to enrich and diversify the field.

As Hélène discussed, we need to recruit and retain women in research because, when it comes to research, diversity is not just a buzzword but a cornerstone for progress and innovation. Historically, women and other under-represented groups have been marginalised in the research profession, leading to significant gaps in knowledge, perspectives, and solutions. Recognizing the critical importance of inclusivity in research is not merely a matter of social justice but also a fundamental necessity for advancing science and fostering a more equitable society, for everyone.

At its core, the research profession thrives on collaboration, creativity, and critical thinking. When women and other under-represented groups are excluded from this domain, we miss out on a wealth of diverse lived experiences, insights, and talents that could drive groundbreaking discoveries and transformative advancements. The inclusion of diverse voices not only enhances the quality and relevance of research, but also ensures that the solutions generated are more comprehensive, effective, realistic, and sustainable.

Professor Jennifer Rohn – UCL – Outsmarting urinary tract infection

This brings us nicely to our third talk of the evening, this time from Professor Jennifer Rohn. Jennifer is a research group leader in the Division of Medicine at University College London, and the Head of the Centre for Urological Biology. Her team studies the biology of urinary tract infections, or UTIs, and seeks to develop new cures for treatment-resistant and chronic UTIs. She works in cross-disciplinary collaborations with clinicians, engineers and materials scientists, and her research interests include cell biology, microbiology, antimicrobial resistance, immunology, tissue engineering, and the development of novel therapies and human cell-based model platforms. She is also a novelist, journalist, public speaker, science communicator and pundit.

In Jennifer’s talk we learned that UTIs affect a staggering 400 million people each year, and the gold-standard treatment, oral antibiotics, often fail. This is because the bacteria which cause UTI have clever ways of evading antibiotics, often hiding below the surface of the bladder that is treated with antibiotics. Therapy innovations in this “mostly women’s” disease space have been hampered by lack of interest, urgency and research funding. Jennifer shared her work on one possible solution to get around bacteria’s ability to hide from drug attack and the impact this work is having on 51% of the population that are more prone to developing UTIs.

Representation in the research profession is essential for addressing pressing societal challenges. Issues such as healthcare disparities, environmental degradation, and social inequality require multifaceted approaches that can only be developed through inclusive research practices. Without diverse representation, research outcomes may inadvertently perpetuate biases, deepen inequalities, and fail to address the needs of marginalised communities adequately. This is also something that must be considered when developing policy around societal groups as our next speaker demonstrated.

Joe Twyman – Deltapoll – Sex with Strangers: Why Data Context Matters

One of Britain’s best known political pollsters, Joe Twyman is Co-Founder and Director of the global public opinion consultancy Deltapoll and is a pioneer of using the internet for conducting opinion research. Previously he was a director at the founding of YouGov back in 2000, holding a variety of senior positions within that company and was responsible for building their online research operations. He also spent two and a half years in Baghdad as a director of YouGov’s Iraq operation from 2007 to 2010. He has published a number of academic research papers, worked as project director for five British Election Studies and frequently provides expert analysis for TV, radio and newspapers both at home and abroad.

Joe’s talk was all about how we must understand the context of data collection to be able to appropriately act on its results. Joe used the example of a research study from the 1970s that became a definitive work on the differences in sexual behaviour between men and women. The study was so significant it inspired a dance hit in the 1990s that made the top ten across Europe. But all was not as it seemed as the results of the study showed a huge difference in the fairly positive responses of men and the outright refusal of all women. It didn’t take much of a deep dive into the methodology for Joe to reveal to us that the study was conducted on fewer than 50 men and 50 women, at one university campus, using those three famous lines as the sum total of the entire experimental interaction, with data collected during a small time period – oh, and the study also happened to be carried out when prolific serial killer Ted Bundy was targeting women on campus. Nevertheless, this study has gone on to inform a range of policy decisions, when its results are likely to be lacking in accuracy or true representation of society more broadly.

If we neglect to prioritise diversity and inclusion in the research profession, the consequences for both science and society can be profound. Scientific progress may stagnate as innovative ideas are overlooked, and potential breakthroughs remain undiscovered. Furthermore, the lack of representation can erode public trust in science, leading to scepticism, disengagement, and missed opportunities for collaboration between researchers and the communities they serve. Ultimately, a homogenous research profession limits our collective ability to confront complex challenges and shape a more equitable future. So, at a time when we are creating so many tech tools to help achieve this goal, we need to be mindful of who is building the solutions and whose lived experiences are being represented –  topics our final speaker addressed brilliantly.

Dr Kate Devlin – King’s College London – Navigating the AI ‘Sea of Dudes’

Dr Kate Devlin is Reader in AI & Society at King’s College London, and is a co-investigator on the Responsible AI UK programme – a network that conducts and funds research into AI to benefit people, communities and society and that unites the responsible AI ecosystem in the UK and beyond. She also does work on sex robots but this time she wasn’t talking about that. Instead, Kate wanted to address the gender imbalance in AI and why we need to be concerned.

In 2016, computer scientist Margaret Mitchell described AI as a “sea of dudes”. What has the discipline done in that time to improve things and make it fairer and more representative of the world? Well, somewhat frustratingly, not a lot yet. Kate’s talk focused on the lack of – and need for – women in AI. In her own words, “Yes, we know and celebrate Ada Lovelace. No, that doesn’t fix things.” Kate shared the net worth of eight of the top tech CEOs who all happened to be men, and highlighted the challenges that this poses in terms of building technological solutions that should help all of society.

Inclusive representation in the research profession is not just morally important but also strategically necessary for advancing science and addressing the complex challenges facing our world. By embracing diversity and challenging the status quo, we can unlock the full potential of research to drive positive change and create a more equitable and sustainable future for all. Through its innovative solutions and commitment to inclusivity, Digital Science is contributing to reshaping the research landscape and ensuring that everyone can be “in the room where it happens”. But we can only achieve this through engagement with stakeholders from across the research community, which is why it was great to see such broad representation from academia, industry, government, funder, and publisher at FuturePub, with conversations and competitions going on late into the night.

Once again, our friends at Bounce looked after us brilliantly, and we’d like to thank Khai, Paddy, Laura, Anna, Dave and the rest of the team for keeping the pizza cooking, the drinks flowing, and the ping pong balls flying everywhere. We were thrilled that Oxford University Press were able to donate five copies of Athene’s book to give away as prizes to the winners of the table tennis competitions that were expertly run by Bounce’s Games Gurus. Champions also walked away with a bottle of fizz.

Among our winners on the night were Michelle Boismenu from Oxford Nanopore Technologies and Sam Conneely from Mimecast, seen posing with their medals and books. Congratulations to them and our other winners, including Digital Science’s own Luke George, seen basking in the glory of his victory across a ping pong table while catching up on the latest from Athene’s book. If you didn’t make it into our top five, you can grab a copy of Athene’s book here.

You can check out the video from the night here and the photo gallery from the event here. Find out more about how we are contributing to greater equity and representation in research here, discover what else we are talking about in our TL;DR space here, and sign up to our newsletter to find out more wherever you see the big yellow button – scroll up, and you should see it on the right-hand side. You can also subscribe to the FuturePub Series on Cassyni to watch these talks and previous Lightning Talks too. In addition, friend of Digital Science and brilliant research community legend Frank Norman has also shared his thoughts on the night.

We’ve been running FuturePub for a while now, and are excited to continue our community engagement events, but audience feedback consistently reveals that the name doesn’t really convey the vibe or value of attending one of our events, and because of that we might be missing out on engaging with some parts of our industry – so, like all good researchers, we’re taking that feedback on board and shaking things up! FuturePub will be back in London in the Autumn, but with a brand new name. Do you have any suggestions as to what we can rename our informal networking nights out? Let us know using the contact form on our website! We’d love to hear from you. And if you would like to speak at a future event, fill in this short proposal form as soon as possible. It will help us spot the emerging themes and trends from the community and find the best partners to run our next event with.

Our events wouldn’t be what they are without our amazing audience, so thank you for joining us at FuturePub! Thanks also to our Digital Science helpers, Bex, Antonio and James. We’d also like to thank the team at Bounce once more. Huge thanks to Vinny Whiteman and Issy Oakes for their videography and photography skills, and thanks to Huw James from Science StoryLab who will be working his magic to bring us another highlights video of the night – watch this space! See you in the Autumn.

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#FuturePub is back in London for our first event of 2024 and, by popular demand, we are thrilled to be hosting this at the awesome ping ping club Bounce in Farringdon once again!

The focus of this FuturePub is to create a platform for conversation around inclusion, from gender imbalance in research and tech to intersectional challenges faced by people across the world, and how a more diverse research workforce and tech designed with everyone in mind will ultimately lead us through some of the challenges we face as a global society and towards a better quality of life for all.

See the speakers for this event (details below):

What is FuturePub and how does it work?

We’ve hosted over a dozen #FuturePub events, since our first back in January 2014, and quickly became known as “a staple of the London science tech/publishing scene” (thanks Eva!).

The evenings are designed to be fun and informal – we aim to give opportunities to those working on new ideas and innovations a chance to present and get feedback on their ideas. And did we mention the free food and drink?

In case this is your first time, here’s how it works:

1. Five or six quick-fire talks cover a range of new and exciting developments in science and publishing technology
2. These all fit into a one-hour slot (from around 7 pm to 8 pm) to keep the evening fast-paced and fun. Arrive from 6 pm for pre-talk food and drinks and to play a few games of ping pong or shuffleboard
3. The rest of the evening is open for discussions and conversations over the remainder of the drinks and food. We get a great mixture of attendees from the research, tech, publishing and start-up communities, so there will be plenty of people to meet and chat with, especially around such an exciting topic.

Timings for the evening

Here’s the confirmed schedule for 4th March:

• 6 pm – doors open, drinks available, and opportunities to play ping pong or shuffleboard
• 6:30 pm – food served (a selection of bite-sized starters and heaps of pizza, with vegetarian, vegan and gluten-free options available)
• 7 pm – Lightning Talks start
• 8 pm – Lightning Talks end, remaining food to be consumed, ping ping duels to be thrown down
• 8:30 pm – food cleared, drinks still available for the continuing conversations
• 11 pm – that’s a wrap! Though if you would like to continue conversations, you are welcome to find a nearby pub. Just let us know which one you’re going to. Suze will have a whisky-ginger-generous squeeze of lime please.

Speakers & Talks

Subhadra Das – The History We Deserve

I’ll be telling the story of Edward Drinker Cope, a nineteenth-century American scientist whose research ran the gamut from dinosaur hunting to false notions of the sex binary and what it means to be civilised. I’ll be considering how this highly influential but relatively lesser-known figure in the history of science left a legacy we need to be mindful of today in the interests of greater social justice.

Subhadra Das is a writer, historian, broadcaster and comedian who looks at the relationship between science and society. She specialises in the history and philosophy of science, particularly the history of scientific racism and eugenics. For nine years she was Curator of the Science Collections at University College London. She has written and presented podcasts and stand-up comedy shows, curated museum exhibitions, and has appeared on radio and TV. Her first book Uncivilised: Ten Lies That Made The West is out now.

Dr Hélène Draux – Digital Science – What The Decline in Women’s First Publications Means For Research

Despite past progress, including women in the US surpassing men in doctoral degree attainment, the COVID-19 pandemic has disproportionately affected women, potentially halting or reversing their academic advancements. Based on data from dimensions.ai and Gender API, we explore the trend from 2000 onwards, noting a significant drop in women’s first publications in recent years. This presentation highlights the importance of recognising and addressing the systemic challenges faced by women in academia, emphasising a call to action for institutions and funders to support and retain women in research, ensuring their contributions continue to enrich and diversify the field.

Dr Hélène Draux is a Senior Data Scientist at Digital Science. She creates bespoke bibliometrics analyses and visualisations for clients in the research sector, using data from the Digital Science portfolio (e.g. Dimensions, Altmetric, Figshare, Elements, IFI Claims, and GRID), clients’ data and external data. Her specialties include gender analyses, geographic analyses, topic modelling, network analyses, and interactive visualisations. She has published a book chapter on Visualisation of Research Metrics, her work was featured in Nature, and during the pandemic she has published a peer reviewed article about the speed of publishing and gender differences in publication.

Professor Jennifer Rohn – UCL – Outsmarting urinary tract infection

Urinary tract infections (UTI) affect a staggering 400 million people each year, and the gold-standard treatment, oral antibiotics, often fails. This is because the bacteria which cause UTI have clever ways of evading antibiotics, but therapy innovations in this “mostly women” disease space have been hampered by lack of interest, urgency and research funding. In this talk, you’ll learn more about how bacteria hide from drug attack, and one possible solution to get around it.

Professor Jennifer Rohn is a research group leader in the Division of Medicine at University College London, and the Head of the Centre for Urological Biology. Her team studies the biology of urinary tract infections (UTI) and seeks to develop new cures for treatment-resistant and chronic UTIs. She works in cross-disciplinary collaborations with clinicians, engineers and materials scientists, and her research interests include cell biology, microbiology, antimicrobial resistance, immunology, tissue engineering, and the development of novel therapies and human cell-based model platforms. She is also a novelist, journalist, public speaker, science communicator and pundit.

Joe Twyman – Deltapoll – Sex with Strangers: Why Data Context Matters

A research study from the 1970s became a definitive work on the differences in sexual behaviour between men and women. The study was so significant it inspired a dance hit in the 1990s that made the top ten across Europe. But all was not as it seems…

One of Britain’s best known political pollsters, Joe Twyman is Co-Founder and Director of the global public opinion consultancy Deltapoll and is a pioneer of using the internet for conducting opinion research. Previously he was a director at the founding of YouGov back in 2000, holding a variety of senior positions within that company and was responsible for building their online research operations. He also spent two and a half years in Baghdad as a director of YouGov’s Iraq operation from 2007 to 2010. He has published a number of academic research papers, worked as project director for five British Election Studies and frequently provides expert analysis for TV, radio and newspapers both at home and abroad. You can find him on twitter @joetwyman.

Dr Kate Devlin – King’s College London – Navigating the AI ‘Sea of Dudes’

In 2016, computer scientist Margaret Mitchell described AI as a “sea of dudes”. What has the discipline done in that time to improve things and make it fairer and more representative of the world? Hahaha. Nothing. This is 5 minutes on the lack of – and need for – women in AI. (Yes, we know and celebrate Ada Lovelace. No, that doesn’t fix things.)

Dr Kate Devlin is Reader in AI & Society at King’s College London, and is a co-investigator on the Responsible AI UK programme – a network that conducts and funds research into AI to benefit people, communities and society and that unites the responsible AI ecosystem in the UK and beyond. She also does work on sex robots but for once she’s not talking about that.

Don’t forget to register!

Tickets are limited, so please don’t forget to sign up, and feel free to share this event with your friends that would like to attend and possibly even speak at this or future events.

See you on 4th March at Bounce in Farringdon!

The post #FuturePub London – International Women’s Day 2024 appeared first on Digital Science.