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.

You can see a demo of Dimensions and its latest features and meet some of the Digital Science team at Charleston in November. To organize a meeting, send us an email.

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

Authors either have a conflict of interest or not, right? Wrong. Research from Digital Science has uncovered a tangled web of missing statements, errors, and subterfuge, which highlights the need for a more careful appraisal of published research.

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.

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

What are universities for? With pressures on funding, academic freedoms under scrutiny and volatile global demographic changes, the need to prove new knowledge can have tangible outputs has never been greater. Simon Linacre looks at one university in the UK which is leading the way in research transformation.

When Digital Science launched its Research Transformation campaign in early April, one of the key aspects the team behind the initiative wanted to explore was not just the ‘what’ of how research enabled change, but the nature of the connection itself between the two sides. For many of us involved in academic research or in industry, we only see one side of this transformation, but don’t stop to think about what has enabled it in the first place. 

A key element of research transformation is the ability to understand research from different perspectives, and this is often described in policy documents and commentaries in general terms without spelling out the practicalities of what is going on. And yet to fully understand how to make the shift from working within research institutions to achieving worthwhile impact in industry, it’s the practicalities that in the end really matter. 

Knowledge transfer partnerships

To help us better understand both the nature of the connection between research and industry and the practicalities involved, what better way than to talk to one of the UK’s leading exponents of knowledge transfer partnerships – or KTPs – in the shape of Leeds Beckett University. LBU has one of the largest student populations in the UK at around 28,000, and ever since it started life back in the early 19th century as Leeds Mechanics Institute, it has had strong links with industry. In the UK, there has been a tradition of KTPs which celebrate their 50th anniversary in 2025. They are partly funded by the government and aim to facilitate the transfer of knowledge and technical skills from universities into industry, as well as improve the skills and business awareness of new graduates.

LBU has been particularly active in this area, with a number of successful partnerships set up with local businesses. Interestingly, these partnerships are not a straightforward transfer of knowledge or expertise from one party to another just for commercial gain, but acknowledge a need on the part of the business for a shift or change in their development, aligned to the business’ wider strategic objectives. We spoke to Jo Griffiths, Head of Knowledge Transfer Partnerships at LBU, to learn more about the connection with businesses and what this shift looks like.

I am hugely heartened by the sense that businesses see themselves as part of a wider ecosystem and force for good.

Jo Griffiths

Head of Knowledge Transfer Partnerships, Leeds Beckett University

“I’ve noticed an increase in the number of organizations we’re working with that describe doing something positive and different for the wider community as a key part of their strategic aims. Whether that’s addressing a big global challenge like sustainability – or making changes at a local level to support the growth of the wider business community – I am hugely heartened by the sense that businesses see themselves as part of a wider ecosystem and force for good,” says Ms Griffiths. 

“One recent example is that of NuGreen and sister company QMedical. They are small SMEs based on the border of Yorkshire and Lancashire in the UK. Their aspiration is to turn healthcare waste (all that bagged waste you see in hospitals and clinics) into substitute aggregates, principally sand, for use in the construction sector. Working in partnership with material scientists and engineers from the university via the KTP funding, they’re testing and bringing to market new products by converting the waste into something useful.

“There are many other discussions and projects like this being developed – we’re working on projects with third sector, not-for-profit and charities too. And yes, there is a positive commercial impact to the organization from the proposed partnerships (they wouldn’t get the funding without that) but absolutely key to all of them is how they support others – whether at an individual level, at a community level or as part of a wider shift in societal attitudes and insight.”

Benefits

The advantages of such relationships are clear, and are neatly summarized in the graphic below, where there is a symbiotic relationship between a qualified graduate (known as an ‘associate’) who leads the change, the university which creates the teaching or research, and the organization which sees improved performance as a result of the arrangement. Add in to that environmental benefits as seen in the example shared by Jo Griffiths above, it’s clear why such programs have been embraced by so many organizations and universities in the UK.

But is there also a deeper transformation at play, where the implementation itself can inform further research down the line? One high profile academic at LBU has been involved in a number of KTPs, some of which have yielded significant results for the research he conducts. Dr Jim Morgan is Principal Lecturer at LBU, specializing in Human Factors and Occupational (Health) Psychology, and he has been involved in a number of successful KTPs while working at LBU.

For example, he was involved in a project between major infrastructure services and engineering firm Amey, which partnered with LBU on the Target Zero SafetySmart Project. This came about as Amey was facing a challenge regarding one of its employee commitments, which was to create zero harm for them in what were often safety-critical environments. The senior management team at Amey worked with LBU’s Psychology Applied to Safety and Health (PASH) research group on the KTP, filling the recognized need for formal psychological and behavioral knowledge and skills among Amey colleagues to implement and embed behavioral safety strategies and solutions.

The result after a three-year project with Amey’s Consulting and Rail division and LBU was an agreed approach that included both quantitative and qualitative psychological research methods that created a flexible, long-term framework. This, alongside a more detailed understanding of accident risk saw a decrease in incidents, and also led to some cost reductions linked to accidents and incidents.

Case study

LBU has had not one but two successful KTP case studies working with the well-established rail infrastructure companies, Amey and VolkerRail. The following details are drawn from LBU’s REF Impact Case Study in 2021.

Background: Human safety is understandably critical to the railway maintenance industry. The UK Network Rail workforce safety statistics for the five years up to 2013/2014 show that major injuries rose by a quarter, and lost time to injuries more than doubled in that time. In addition to personal suffering, the financial cost of workplace injuries was estimated to be nearly £5bn at this time.

At LBU, the Psychology Applied to Safety and Health (PASH) research group – led by Dr Jim Morgan and Dr Matteo Curcuruto – are involved in a research program focused on “helping safety-critical organizations to translate Organizational Psychology, Human Factors, and Health Psychology research knowledge into enhanced behavioral safety management practices”. This research has been funded by, among other sources, two Knowledge Transfer Partnerships (KTPs) in collaboration with industry partners, namely Amey and VolkerRail.

Research: The research employed in the programs used a ‘bottom-up approach’ to directly involve workers from the start. This approach aimed to generate improved communication, trust and a better culture of safety, with research conducted with workers at the two rail companies, as well as other workers from similar industries.

Impact: The result of the SafetySmart project (with Amey) has been clear, with rail operations reduced by a third in lost time injuries and a quarter in non-lost time injuries. Overall, the company estimates as a result of SafetySmart turnover will increase by over £1.3m in the three years after the project finished.

The programs have also achieved industry recognition, with the Amey KTP awarded the highest rating of “Outstanding” by Innovate UK assessors based on impact for the firm, and second highest rating of “Very Good” for the VolkerRail YourAIM project. 

Additionally, VolkerRail estimates that as a result of the YourAIM project turnover increased by a quarter of a million pounds, with a further £1m in the three years following the project being completed.

Summary: Research by PASH has undoubtedly developed the safety culture at both Amey and VolkerRail, with demonstrable improvements in hours worked and turnover. Moreover, both companies have now implemented robust behavioral safety protocols to keep an eye on safety-critical workflows, further improving safety. The KTP program therefore not only improves human working conditions and business outcomes, but is also part of a symbiotic relationship with research, providing rich data for further research at universities like LBU.

See Jim and Matteo’s KTP-funded research articles in Dimensions.

Future REFerence

The ability for universities to show impactful work outside labs and field studies is particularly important in the UK due to its system of research funding, known as the Research Excellence Framework or REF. Billions of pounds of research funding from the government is determined by how universities and their departments perform in their research programs, and KTPs are a key plank in an institution’s strategy to show how their research can have a positive impact on lives and social wellbeing. In Dr Morgan’s words, KTPs are “simply brilliant for the REF”, as they show the impact research programs at universities can have, as well as helping with the recruitment and work experience of postgraduate students, many of whom find employment with KTP partners when their studies have been completed.

There’s no one-size-fits-all when it comes to the REF, and different institutions take a different approach to gathering and collating information for submission.

REF Framework

As experts in the research assessment ecosystem, Symplectic collaborates closely with the academic community to navigate the changing requirements of the REF.

Learn more about how we’re supporting REF 2029

So, there are numerous reasons why a university such as LBU should pursue KTPs, and rightly be proud of what they have achieved with the numerous projects they have supported and delivered. What is interesting from a research perspective is the importance of the role people play in the projects, both in terms of the interactions between the university and external organizations, as well as the outcomes and how they positively impact individuals’ lives. In addition, it is also clear that the individual researchers themselves gain a huge amount of wider knowledge from their work over and above the project focus. All in all, given the right structure and opportunities to make a difference through research, researchers can do just that.

The post What a difference making a difference makes appeared first on Digital Science.

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

The post Scismic and objective, skills-focused, AI-driven recruitment in STEM appeared first on Digital Science.

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.

The post Healthy increase in access to medical research appeared first on Digital Science.

With the launch of Dimensions Research GPT and Dimensions Research GPT Enterprise, researchers the world over now have access to a solution far more powerful than could have been believed just a few years ago. Simon Linacre takes a look at a new solution that combines the scientific evidence base of Dimensions with the pre-eminent Generative AI from ChatGPT.

For many researchers, the ongoing hype around recent developments with Generative AI (GAI) has left them feeling nonplussed, with so many new, unknown solutions for them to use. Added to well-reported questions over hallucinations and responsibly-developed AI, the advantages that GAI could offer have been offset by some of these concerns.

In response, Digital Science has developed its first custom GPT solution, which combines powerful data from Dimensions with ChatGPT’s advanced AI platform; introducing Dimensions Research GPT and Dimensions Research GPT Enterprise. 

Dimensions Research GPT’s answers to research queries make use of data from tens of millions of Open Access publications, and access is free to anyone via OpenAI’s GPT Store; Dimensions Research GPT Enterprise provides results underpinned by all publications, grants, clinical trials and patents found within Dimensions and is available to anyone with an organization-wide Dimensions subscription that has ChatGPT enterprise account. Organizations keen to tailor Dimensions Research GPT Enterprise to better meet the needs of specific use cases are also invited to work with our team of experts to define and implement these.

These innovative new research solutions from Dimensions enable users of ChatGPT to discover more precise answers and generative summaries by grounding the GAI response in scientific data – data that comes from millions of publications in Dimensions – through to the increasingly familiar ChatGPT’s conversational interface. 

These new solutions have been launched to enable researchers – indeed anyone with an interest in scientific research – to find trusted answers to their questions quickly and easily through a combination of ChatGPT’s infrastructure and Dimensions’ well-regarded research specific capabilities. These new innovations accelerate information discovery, and represent the first of many use cases grounded in AI to come from Digital Science in 2024.

How do they work?

Dimensions Research GPT and Dimensions Research GPT Enterprise are based on Dimensions, the world’s largest collection of linked research data, and supply answers to queries entered by users in OpenAI’s ChatGPT interface. Users can prompt ChatGPT with natural language questions and see AI-generated responses, with notifications each time any content is based on Dimensions data as a result of their queries on the ChatGPT platform, with references shown to the source. These are in the shape of clickable links, which take users directly to the Dimensions platform where they can see pages with further details on the source records to continue their discovery journey. 

Key features of Dimensions Research GPT Enterprise include: 

• Answers to research queries with publication data, clinical trials, patents and grant information
• Set up in the client’s private environment and only available to client’s end users
• Notifications each time content generated is based on Dimensions data, with references and citation details.

What are the benefits to researchers?

The main benefit for users is that they can find scientifically grounded, inherently improved information on research topics of interest with little time and effort due to the combination of ChatGPT’s interface and Dimensions’ highly regarded research specific capabilities. This will save researchers significant time while also giving them peace of mind by providing easy access to source materials. However, there are a number of additional key benefits for all users in this new innovation:

• Dimensions AI solutions makes ChatGPT research-specific – grounding the answers in facts and providing the user with references to the relevant documents
• It calls on millions of publications to provide information specific and relevant to the query, reducing the risk of hallucination of the generative AI answer while providing an easy route to information validation
• It can help overcome challenges of sheer volume of content available, time-consuming tasks required in research workflows and need for trustworthy AI products.

What’s next with AI and research?

The launch of Dimensions Research GPT and Dimensions Research GPT Enterprise represents Digital Science’s broader commitment to open science and responsible development of AI tools. 

These new products are just the latest developments from Digital Science companies that harness the power of AI. In 2023, Dimensions launched a beta version of an AI Assistant, while ReadCube also released a beta version of its AI Assistant last year. Digital Science finished 2023 by completing its acquisition of AI-based academic language service Writefull. And 2024 is likely to see many more AI developments – with some arriving very soon! Dimensions Research GPT and Dimensions Research GPT Enterprise, alongside all Digital Science’s current and future developments with AI, exemplify our commitment to responsible innovation and bringing powerful research solutions to as large an audience as possible. If you haven’t tested ChatGPT yet as part of your research activities, why not give it a go today?

The post Fast forward: A new approach for AI and research appeared first on Digital Science.

 In this week’s fourth Spotlight on the value of social science research, we assess the final ingredient to improve UK research and innovation: why social sciences are essential to international collaboration and tackling shared global challenges.

The focus of the Academy of Social Sciences (AcSS) report Reimagining the Recipe for Research & Innovation has understandably been parochial in nature, based as it is in the UK and tackling some of the unique challenges faced by researchers operating in the UK. However, the final piece in the AcSS jigsaw in its argument for using social sciences to support STEM research looks further afield, and analyzes how social science research in general can improve collaboration and societal problems on a global scale.

There are a couple of sound contextual reasons why this argument has a strong base. Firstly, as the UK is home to some of the most highly regarded research institutions, it is well placed to offer some guidance on this aspect of research. And perhaps most importantly, with the UK having benefited from some of the more progressive higher education policies in the shape of its Research Excellence Framework (REF) and early adoption of Open Access mandates, it can offer some leadership in making recommendations for future research strategy.

Covid insights

In the AcSS report, its authors – which include Dr Juergen Wastl and Kathryn Weber-Boer from Digital Science – identify the fourth and final ingredient specifically as the ability of social sciences to enable progress through international collaboration and meeting global challenges. No global challenge has been greater in recent times than the Covid-19 pandemic, and using this example, the authors show how insights from both STEM and social science research were necessary to successfully fight the spread and control of the disease. 

We see some specific examples of this in the case study below, but to further illustrate the important role social sciences have played, the report looks at how research in all areas has supported the United Nations Sustainable Development Goals (SDGs). Looking at how both UK researchers and those internationally have focused on these global challenges, the authors used Dimensions to identify some interesting trends (see Figure 1). For example: 

• The volume of publications is greater – and the average number of citations lower – for ‘social’ SDGs when compared with the ‘economic’ and ‘environmental’ SDGs, across all of the datasets
• For UK-authored papers, about a quarter of SDG-related publications are in the social sciences – either uniquely or in collaboration with STEM colleagues – and some three-quarters are in the STEM area
• Within each of the three main subdivisions – STEM, social science and STEM/social science – UK-authored publications have much greater citation rates than the average globally
• The biggest increase in citation rates – compared with the global average – for UK-authored papers is around double in many cases
• Collaborative studies across social science and STEM account for a minority of publications however they are among the most cited research.

Impact of impact

Perhaps one of the more remarkable findings in the AcSS study is that, when analyzing the impact studies that form part of the UK’s REF program in 2021 – where universities present the wider impacts their research has had – the social sciences show a greater contribution in most of the eight categories they are broken down into. While STEM leads in Health and Technology as one might expect, social sciences lead in Societal and Economic impacts.

No global challenge has been greater in recent times than the Covid-19 pandemic… insights from both STEM and social science research were necessary to successfully fight the spread and control of the disease.

Case study

The case study used to illustrate the influence of the social sciences in the AcSS report concerns the Covid-19 pandemic and how social sciences – not on their own and in collaboration with STEM research – helped the government and health services navigate through one of the world’s most challenging episodes.

One article they cite, published in Nature Human Behaviour in April 2020, was an early attempt by a large group of scholars to share not only their collective insights in order to enable a more effective response to the pandemic, but the gaps that were evident and needed to be filled. This collaborative response to the pandemic included advice on influencing credible community sources of information and advice on how to frame public health messaging. 

The pioneering work on drug discovery obviously played a huge part in overcoming Covid-19, but much of that great work might have been wasted had social science research not played its part in how vaccines were deployed. When we look back on this and the other three ingredients – enabling whole systems thinking, critical for good policy development and underpinning smart and responsible innovation – the Covid example is emblematic of the value that social sciences can bring. Important on their own, but vital when plugged into STEM research, collaboration and solving some of the world’s most pressing problems.

It is this collaborative approach between the social sciences and STEM research that has been one of the key aspects of the Spotlight series. From the first Spotlight on seeing a more complete picture from whole systems thinking, through to effective policy making and responsible innovation, it has been notable not so much what value can be brought through collaboration between social sciences and STEM, but what can also be lost when they don’t work in harmony. Hopefully this series and the AcSS report it has highlighted can ensure fewer wasted opportunities to make a difference in the future.

Next time

We will continue our Spotlight series next month, so please watch out for more details on Digital Science’s LinkedIn and Twitter/X accounts – as well as right here on TL;DR.

The post In the Spotlight: Social sciences’ fourth key ingredient for research success appeared first on Digital Science.

Last week’s Spotlight on social science research looked at its potential contribution to UK policy making. This week we identify the third key ingredient to improve UK research and innovation: how social sciences can underpin smart and responsible innovation.

The third ingredient in our Spotlight series on social science contribution is arguably the most easily recognizable one: that social sciences are essential to research and innovation in the area of governance, and how it should be an enabler rather than an obstacle to technological progress. 

The report on which these Spotlight pieces have been based – Reimagining the Recipe for Research & Innovation by the Academy of Social Sciences (AcSS) – identifies that the social sciences occupy a strategically vital place in their ability to enhance our understanding of human behavior, public opinion, legal systems, markets and policy. Without this understanding, the underpinning of any research and innovation program becomes much less stable.

Three’s a charm

The authors of the AcSS report – which include Dr Juergen Wastl and Kathryn Weber-Boer from Digital Science – identify the third ingredient specifically as the ability of social sciences to take on board different perspectives. For example, historical, geographical/cultural and legal perspectives all lend themselves to a wider understanding of the import and impact of technological innovation. The authors use the case of biotechnology governance to illustrate their point – some countries will regulate keenly, while others will have a more laissez faire approach, depending on contextual factors relevant to each dominant culture or nation state.

Sometimes these factors can be encapsulated in a single paper – the authors identify such an article that looks at legal implications of EU law and AI, which can spread across different areas in a way that STEM papers would struggle to achieve, and in doing so build bridges between those areas.

Active ingredient

Perhaps more than any other ingredient in this four-part series, the role social sciences play in underpinning smart and responsible innovation is perhaps the most dynamic and visible.

The authors show this by using Dimensions data: according to Dimensions, most UK research in law relating to digital health had been funded through the UK’s engineering and physical sciences public funding body. Research that had been funded in this way related to specific areas such as governance of AI and smart home security – in other words, social science research influencing and informing innovation.

More than any other ingredient… the role social sciences play in underpinning smart and responsible innovation is perhaps the most dynamic and visible.

Case study

The specific case study drawn out by the AcSS report authors concerns the hot topic of AI and how it relates to the field of robotics. Where does social science fit in here? The authors identify a specific paper which they see as emblematic of the influence social sciences can have on research and innovation.

The article in question identified an apparent incompatibility between European notions of discrimination and existing work on algorithmic and automated fairness. The article made three key arguments: EU non-discrimination law doesn’t provide a ‘static’ framework aligned with testing for discrimination in AI systems; discrimination is essentially a human behavior, and as such is difficult to identify in AI systems; setting standards of evidence might help make processes consistent, but not necessarily where judicial decisions are involved related to AI. 

More broadly, interdisciplinary research at one university has been shown to influence understanding of the impact of AI technologies on human rights, in turn helping to define human rights standards. Such impacts, where knowledge and experience embedded in social science research can support innovation and its responsible adoption, are likely to be critical as AI and other new technologies emerge.

Next time

The fourth and final ingredient is… Social sciences are essential to international collaboration and tackling shared global challenges.

The post In the Spotlight: Social sciences’ third key ingredient for research success appeared first on Digital Science.

The report on which these Spotlight pieces have been based – Reimagining the Recipe for Research & Innovation by the Academy of Social Sciences (AcSS) – has received huge coverage since its publication in January, with the “Secret Sauce” report featured in the Financial Times, Nature, Times Higher Education, WonkHE and Research Professional among others, and further news outlet coverage (see Altmetric). Interestingly, what we can see here is the embodiment of the second ingredient identified in the report’s ‘secret sauce’, namely how social science research itself can have an impact on UK policy making. One way this can happen is through coverage of social science research in national, international and industry media.

Cooking up a storm

The AcSS report seeks to elucidate how the UK’s research and innovation (R&I) can improve, which the report argues is through targeted investment in social sciences as a complement to STEM research. The authors – which include Dr Juergen Wastl and Kathryn Weber-Boer from Digital Science – recognize the role social sciences can play to see that the UK’s competencies are maximized when it comes to overall R&I investment.

So what is really meant for the second ingredient to be “critical for good policy development”? Using Dimensions data, the report’s authors can see not only how many publications in different research areas receive funding, but how influential they are by being cited in policy documents in the UK. While many more STEM research projects are funded, around 3% of these end up being cited in policy documents, but for social sciences this rate doubles to 6%. Furthermore, when both STEM and social sciences are included in a funded research project, the rate increases by another 50% again to 7.5%.

In other words, funded research in social science is more likely to influence policy than STEM research in relative terms, and both combined even more so. Furthermore, the ‘translation rate’ from grants into publications and then into policy documents is higher for social science research than for STEM.

An additional impact can be seen in the chart below, which shows the number of policy documents per grant category (on the left of the chart) and the per publication category (in the middle), but with the fields of health sciences and biomedical and clinical sciences removed. What we can see is that policy documents in every category cite grants and publications produced in the others. Perhaps most importantly, nearly half of UK policy documents from 2012–2022 cited on social science-related or joint combined social science grants.

Funded research in social science is more likely to influence policy than STEM research in relative terms, and both combined even more so.

Case study

An example of how this has worked in practice is from the pressing issue of climate change, where the UK-based Centre for Climate Change & Social Transformations (CAST) investigates systemic and society-wide transformations that are required to address climate change. By researching and understanding the social transformations that are necessary to develop a low-carbon society, CAST can have a huge impact on affecting the behaviors of citizens, perhaps even more than science-based solutions whose impact might be minimized if not adopted by the population at large.

Next Time

The next ingredient is… Social science underpins smart and responsible innovation.

The post In the spotlight: Social sciences’ second key ingredient for research success appeared first on Digital Science.

But is there more to the report than just a clever metaphor? Below and over the next three weeks, we take a quick look at the report’s findings and, perhaps more importantly, the methodology behind the study, which used Dimensions data to understand the research landscape. Because Dimensions is the world’s largest collection of linked research data with over 140 million publications, it is a rich source of information on the impact of social science research.

Enabling whole-systems thinking

The AcSS report aimed to better understand the UK’s research and innovation (R&I) position, which is currently in a state of transition. Overall, the report argues that investment in R&I in the UK lags behind its competitors, despite the regard its higher education sector enjoys. The authors – which include Dr Juergen Wastl and Dr Kathryn Weber-Boer from Digital Science – seek to identify the role social sciences can play to ensure the UK’s position is optimized when it comes to R&I investment.

The first ingredient in the mix is for the social sciences to enable ‘whole-systems thinking’. What does this mean? The focus here is on innovation and entrepreneurship, and how social science can enable a better understanding of system capabilities such as economies, institutions, skills or culture. These contexts shape how enterprises in the UK can develop; being able to read them and make the right investment decisions on the back of it is a key part of a successful and dynamic economy.

The authors feel this point needs emphasizing as too often the social sciences are seen as a handbrake by contributing to ‘ELSIfication’, ie. stressing ethical, legal or societal implications (ELSI) in a given situation. However, that perception is questioned by the report which points to some key advances made in STEM research – such as in artificial intelligence (AI) and trustworthy autonomous systems (TAS) – where the level of expertise in these and related areas in social sciences in the UK far outpaces that of STEM. There is a huge untapped, advanced resource for STEM that would benefit R&I development if the two areas collaborated.

“…not only can social sciences improve STEM research and technological innovation by understanding the contexts they exist within, but they can also offer significant ‘value add’ when it comes to taking scientific breakthroughs into the society we live in.”

Case study

An example of the type of collaboration envisaged by the authors is given with the story of Professor Lucie Cluver in South Africa (University of Oxford and University of Cape Town), whose work on the impacts of AIDS showed that offering welfare payments to young orphaned girls meant they were less likely to seek older boyfriends who might, in turn, infect them. Understanding the complex social, environmental and psychological impacts of the disease has therefore provided an effective way to reduce infections above and beyond any STEM research into AIDS itself.

What we can see here is that not only can social sciences improve STEM research and technological innovation by understanding the contexts they exist within, but they can also offer significant ‘value add’ when it comes to taking scientific breakthroughs into the society we live in – above and beyond the checks and balances of ensuring ethical and legal parameters are maintained. The report is also keen to stress the relative superiority UK research enjoys in the social sciences, and how this can benefit STEM research as a whole when it comes to its impact on society.

Next time

The next ingredient is… Social sciences are critical for good policy development.

The post In the spotlight: Social sciences’ first key ingredient for research success appeared first on Digital Science.

‘Have you done your due diligence?’ These six words induce fear and dread in anyone involved in finance, with the underlying threat that huge peril may be about to engulf you if the necessary homework hasn’t been done. Due diligence in the commercial sphere is a hygiene factor – a basic, if detailed, audit of risk to ensure that all possible outcomes have been assessed so nothing comes out of the woodwork once an investment has been made.

The question, however, is just as important for academic institutions looking to check the data on their research programs: have you done your due diligence on that? If not, then a linked database such as Dimensions can help you.

Strategic objectives

At a recent panel discussion hosted by Times Higher Education (THE) in partnership with Digital Science on optimizing research strategy, the question of due diligence was framed by looking at the academic research lifecycle and the challenges emanating from the increased amount of data now accessible to universities. More specifically, how universities could extract and utilize verified data from the ever–increasing number of sources they had at their disposal. 

Speaking on the panel, Digital Science’s Technical Product Solutions Manager Ann Campbell believes there are numerous benefits to using new modes of data to overcome problems associated with data overload. “It’s important to think holistically, of not only the different systems that are involved here but also the different departments and stakeholders,” she said. “It’s better to have an overarching data model or a perspective from looking at the research life cycle instead of separate research silos or different silos of data that you find within these systems.”

The panel recognized that self–reporting for academics could lead to gaps in the data, while different impact data could also be missed due to a lack of knowledge or understanding on behalf of faculty members. 

Digital Science seeks to address these problems by adding some power to its Dimensions linked database in the shape of Google BigQuery. By marrying this computing power to the size and scope of Dimensions, academics and research managers are empowered to identify specific data from all stages of the research lifecycle. This allows researchers to seamlessly combine external data with their own internal datasets, giving them the holistic view of research identified by Ann Campbell in the discussion. 

Data savant

The theme of improving the capabilities of higher education institutions when it comes to data utilization has been most vividly described by Ann Campbell in her November presentation to the Times Higher Education Digital Universities conference in Barcelona in October. Memorably, she compared universities’ use of data to the plot of popular TV drama Game of Thrones. Professors as dragons? Rival departments as warring families? Well not quite, but what Ann did observe was that there are many competing elements within HEIs – research management, research information, academic culture, the library – and above them are senior management who have key questions that can only be answered using data and insights across all of them:

• Which faculties have a high impact? Should we invest more in them?
• Which faculties have high potential but are under–resourced?
• How can we promote our areas of excellence?
• How can we identify departments with strong links to industry?
• What real–world research impact can we feed back into our curriculum?
• Are we mitigating potential reputational risk through openness and transparency? 

Bringing these disparate challenges together requires a narrative, which is another reason why the Game of Thrones analogy works so well as we see that for all the moving parts of the story to work, a coherent story is required. This can be how an institution’s research culture strategy is working with a rise in early career international collaborations, how an increase in new funding opportunities followed a drive to increase interdisciplinary collaborations, or how the global reputation of a university could be seen to have improved its impact rankings position due to increased SDG–related research. 

Any good story needs to have the right ingredients, and where Digital Science can really help an institution is to bring together those ingredients from across an organization into viewable and manageable narratives. 

Telling stories

But the big picture is not the whole story, of course. There are other, smaller narratives swirling through HEIs at any given time that reflect the different specialisms, hot topics or focus areas of the university. Three of these focus areas most commonly found in modern universities are research integrity, industry partnerships and research impact, and these were discussed recently at another collaborative webinar between THE and Digital Science: Utilising data to deliver research integrity, industry partnerships and impact. 

This panel discussion was a little more granular, and teased out some specific challenges for institutions when it came to data utilization. For research integrity, certain data relating to authorship can be used as ‘trust markers’, based around authorship, reproducibility and transparency. Representing Digital Science, Technical Product Solutions Manager Kathryn Weber–Boer went through the trust markers that form the basis of the Dimensions Research Integrity solution for universities. 

But why are these trust markers important? The panel discussion also detailed that outside universities’ realm of interest, both funders and publishers were increasingly interested in research integrity and the provenance of research emanating from universities. As such, products like Dimensions Research Integrity were forming a key part of the data management arsenal that universities needed in the modern research funding environment.  

In addition, utilization and scrutiny of such data can help move the dial in other important areas, such as changing research culture and integrity. Stakeholders want to trust in the research that’s being done, know it can be reproduced, and also see there is a level of transparency. All of these factors then influence the promotion and implementation of more open research activities.

Another important aspect of research integrity and data utilization is not just having information on where data is being shared in what way, it is also whether it is being shared as it has been recorded as, and where it is actually located. As pointed out in the discussion, Dimensions is a ‘dataset of datasets’ and allows the cross–referencing of these pieces of information to understand if research integrity data points are aligned. 

Positive outlook

Discussions around research integrity and data management can often be gloomy affairs, but there is some degree of optimism now there are increasing numbers of products on the markets to help HEIs meet their goals and objectives in these spheres of activity. Effective data utilization will undoubtedly be one of THE critical success factors for universities in the future, and it won’t just be for the effective management of issues like research integrity or reputations. With the lightning fast development, adoption of Generative AI in the research space and increasing interest in issues like research security and international collaboration, data utilization – and who universities partner with to optimize it – has never been higher up the agenda. 

You can view the webinars here on utilizing new modes of data and delivering research integrity.

The post Putting data at the heart of your organizational strategy appeared first on Digital Science.

The phrase ‘patently obvious’ is used in many contexts, from political exchanges to newspaper op-ed columns. Curiously, it is rarely used in the realm of actual patents, but in the case of General Electric’s (GE) HealthCare division, its use seems entirely appropriate.

In early 2023, GE made the decision to spin off GE HealthCare, and immediately following the move the new entity started its M&A strategy by acquiring two companies of its own – Caption Health and IMACTIS. At this early stage, is it possible to infer whether these were sound investments? Six months later, there is still a way to go before full year financial results are posted along with other financial data. However, Digital Science company IFI CLAIMS Patent Services – a global patent database provider for application developers, data scientists, and product managers – can gain insights by looking into the patents the newly enlarged GE HealthCare now holds.

Patents = strategic insights

It should be ‘patently obvious’, but checking companies’ patents can be a part of any due diligence process before an investment decision is made. Not only does this help understand risk and technology overlaps, it can also be used to determine where R&D efforts are currently focused in the target acquisition, and in turn set the strategy for the newly merged entity. Analyzing a company’s patent holdings in the midst of M&A dealings provides insights, such as: 

• Strategic direction of companies (i.e., such as the extent to which they are making strides in AI)
• Unique takes on M&A transactions as it is possible to determine – based on companies’ technologies – if core competencies overlap or not with the acquiring company
• Ascertaining if a company’s core competencies are enhanced or not by the acquisitions it’s made

IFI’s latest acquisition report takes a look at GE HealthCare’s acquisitions of IMACTIS and Caption Health’s patented technologies to determine the innovative direction of the company.

‘A good fit’

So what insights can be gleaned from patent data about GE HealthCare and its nascent M&A strategy? According to the report, the acquisition of Caption Health and IMACTIS were a ‘good fit’ for GE HealthCare. Both the acquisitions point towards GE HealthCare’s continued growth in terms of both AI and the application of AI to its existing core technologies. Specifically:

• IMACTIS is a tech healthcare company that offers, among other things, the provision of 3D virtual imaging to surgical navigation
• Caption Health focuses on providing AI capabilities and image data generation to ultrasound technologies

You can see from the chart below that GE HealthCare competes with a number of major companies in establishing AI-related patents, which surged in 2019-2020 before dipping in 2021. As such, the acquisitions in the early part of 2023 of companies that are focused on technology and AI in particular seem to be a good strategic move, especially given the furore around AI technology since late 2022.

What the data says

The report concludes that both Caption Health and IMACTIS make sense for GE HealthCare for several reasons. In the current competitive climate, Caption Health adds necessary AI capabilities while IMACTIS adds new dimensions to the suite of patents it has with 3D virtual images. So overall, it’s a gold star for GE HealthCare when it comes to enhancing its patent – and future commercial – strategy. Isn’t that obvious?

Three key takeaways

1. Digital Science’s IFI CLAIMS Patent Services – a global patent database provider for application developers, data scientists, and product managers – can help customers gain insights by looking into the patents held by firms, such as newly enlarged GE HealthCare.

2. IFI’s latest acquisition report takes a look at GE HealthCare’s acquisitions of IMACTIS and Caption Health’s patented technologies to determine the innovative direction of the company – the report concludes that both Caption Health and IMACTIS make sense for GE HealthCare for a number of reasons.

3. Checking companies’ patents should be a part of any due diligence process before any corporate investment decision is made, especially in pharmaceuticals sector.

The post AI: To buy or not to buy appeared first on Digital Science.