A new open-access platform to bring greater oversight of deforestation risks – SPOTT.org | SPOTT.org

“ZSL [Zoological Society of London], as a sub-grantee alongside Global Canopy, will be launching a revolutionary platform in 2022 bringing together the best data available on corporate exposure to, and reporting on, deforestation and other related environmental, social and governance (ESG) issues.

The project aims to provide market-leading data to help financial institutions identify risks and find opportunities for sustainable investments to meet the growing demand for responsible financial products in light of the biodiversity and climate crises.

The database will be underpinned by the data collected through ZSL’s SPOTT assessments, Global Canopy’s Forest 500 assessments and the Stockholm Environment Institute, Global Canopy and Neural Alpha’s Trase Supply Chains and Trase Finance data, and will be aligned with the Accountability Framework Initiative and its guidance.

Supported by a five-year grant from the Norwegian government, the resulting data and metrics will provide a more comprehensive view of company performance on deforestation, conversion and associated human rights risks. The dataset will also provide broader coverage of the most exposed forest risk supply chains (in particular: palm oil, soy, timber, pulp, rubber and cattle products) and geographies where corporate performance data on these topics is currently missing. By mapping and integrating data from aligned initiatives and external datasets, more complete and in-depth coverage of corporate performance data will be available….”

Public use and public funding of science | Nature Human Behaviour

Abstract:  Knowledge of how science is consumed in public domains is essential for understanding the role of science in human society. Here we examine public use and public funding of science by linking tens of millions of scientific publications from all scientific fields to their upstream funding support and downstream public uses across three public domains—government documents, news media and marketplace invention. We find that different public domains draw from various scientific fields in specialized ways, showing diverse patterns of use. Yet, amidst these differences, we find two important forms of alignment. First, we find universal alignment between what the public consumes and what is highly impactful within science. Second, a field’s public funding is strikingly aligned with the field’s collective public use. Overall, public uses of science present a rich landscape of specialized consumption, yet, collectively, science and society interface with remarkable alignment between scientific use, public use and funding.


Early firm engagement, government research funding, and the privatization of public knowledge | SpringerLink

Abstract:  Early firm engagement in the scientific discovery process in public institutions is an important form of science-based innovation. However, early firm engagement may negatively affect the academic value of public papers due to firms’ impulse to privatize public knowledge. In this paper, we crawl all patent and paper text data of the Distinguished Young Scholars of the National Science Foundation of China (NSFC) in the chemical and pharmaceutical field. We use semantic recognition techniques to establish the link between scientific discovery papers and patented technologies to explore the relationship between the quality of public knowledge production, government research funding, and early firm engagement in the science-based innovation process. The empirical results show that, first, there is a relatively smooth inverted U-shaped relationship between government research funding for scholars and the quality of their publications. An initial increase in government research funding positively drives the quality of public knowledge production, but the effect turns negative when research funding is excessive. Second, government research funding for scholars can act as a value signal, triggering the firm’s impulse to privatize high-value scientific discoveries. Hence, early firm engagement moderates the inverted U-shaped relationship such that at low levels of research funding, early firm engagement can improve the quality of public knowledge production, and at high levels of research funding, early firm engagement can further reduce the quality of public knowledge production.



“The European Commission’s proposal for the Data Act has introduced a narrow business-to-government (B2G) data sharing mandate, limited only to situations of public emergency and exceptional need. While being a step in the right direction, it fails to deliver a “data sharing for the public good” framework. 

The policy vision for such a framework has been presented in the European strategy for data, and specific recommendations for a robust B2G data sharing model have been made by the Commission’s high-level expert group.

The European Union is uniquely positioned to deliver a data governance framework that ensures broader B2G data sharing, in the public interest. In our latest policy brief, Public Data Commons. A public-interest framework for B2G data sharing in the Data Act, we propose such a model, which can serve as a basis for amendments to the proposed Data Act.  Our proposal not only extends the scope of B2G data sharing provisions, but includes the creation of the European Public Data Commons, a body that acts as a recipient and clearinghouse for the data made available.”

PUBLIC DATA COMMONS: A public-interest framework for B2G data sharing in the Data Act

“The Data Act represents a unique opportunity for the European legislator to deliver on the “data sharing for public good” narratives, which have been discussed for over a decade now. To make this happen the framework for B2G data sharing contained in Chapter V of the proposal needs to be strengthened so that it can serve as a robust baseline for sectoral regulations. As such, it will contribute to a European Public Data Commons that can serve as a public interest steward for data sharing and use in support of public interest objectives, such as securing public health and education, combatting the climate crisis and ensuring strong and just public institutions.”

Artificial Intelligence for Public Domain Drug Discovery: Recommendations for Policy Development

“The current drug discovery market is not responding sufficiently to health care needs where it is not adequately lucrative to do so. Unfortunately, there are a number of important yet non-lucrative fields of research in domains including pandemic prevention and antimicrobial resistance, with major current and future costs for society. In these domains, where high-risk public health needs are being met with low R&D investment, government intervention is critical. To maximize the efficiency of the government’s involvement, it is recommended that the government couple its work catalyzing R&D with the creation of a drug development ecosystem that is more conducive to the use of high-impact artificial intelligence (AI) technologies. The scientific and political communities have been ringing alarm-bells over the threat of bacterial resistance to our current antibiotics arsenal and, more generally, the evolving resistance of microbes to existing drugs. Yet, a combination of technical capacity issues and economic barriers has led to an almost complete halt of R&D into treatments that would otherwise address this threat. When a gap arises between what the market is incentivized to produce and the healthcare needs of society, governments must step in. The COVID-19 pandemic illustrates the importance of bridging that gap to ensure we are protected from future threats that would result in similarly devastating consequences. Artificial intelligence (AI) capabilities have contributed to watershed moments across a variety of industries already. The transformative power of AI is showing early signs of success in the drug discovery industry as well. Should AI for drug discovery reach its full potential, it offers the ability to discover new categories of effective drugs, enable intelligent, targeted design of novel therapies, vastly improve the speed and cost of running clinical trials, and further our understanding about the basic science underlying drug and disease mechanics. However, the current drug discovery ecosystem is suboptimal for AI research, and this threatens to limit the positive impact of AI. The field requires a shift towards open data and open science in order to feed the most powerful, data-hungry AI algorithms. This shift will catalyze research in areas of high social impact, such as addressing neglected diseases and developing new antibiotic solutions to incoming drug-resistant threats. Yet, while open science and AI promise successes on producing new compounds, they cannot address the challenges associated with market-failure for certain drug categories. Government interventions to stimulate AI-driven pharmaceutical innovation for these drug categories must therefore target the entire drug development and deployment lifecycle to ensure that the benefits of AI technology, as applied to the pharmaceutical industry, result in strong value added to improve healthcare outcomes for the public….

This document puts forward a set of recommendations that, taken together, task governments with the responsibility to promote: 1. Research and development in fields of drug discovery that are valuable to society and necessary to public health, but for which investments are currently insufficient because of market considerations. 2. Uptake of AI throughout the entire drug discovery and development pipeline. 3. A shift in culture and capabilities towards more open-data among stakeholders in academia and industry when undertaking research on drug discovery and development….”

AI-assisted drug discovery held back by private sector secrecy on datasets | Science|Business

“The discovery of new drugs is being held back because pharmaceutical firms are not sharing their data, limiting the potentially revolutionary impact of artificial intelligence on the field, according to AI experts….

Last year, for example, a team at the Massachusetts Institute of Technology reported discovering a new antibiotic compound using a computer model that can screen more than 100 million compounds in a matter of days.  

But such breakthroughs are being hampered by a lack of data sharing by private companies, stymying efforts to use powerful AI models to improve healthcare, said Yoshua Bengio, an AI pioneer at the University of Montreal and one of the leaders of an OECD-backed investigation into the issue.

“The lack of open datasets is a failure of the principle of profit maximization by individual actors,” he said.

Releasing datasets “hurts their competitiveness, even though it would help the overall market to progress faster to technological solutions,” Bengio said.  …

“The field requires a shift towards open data and open science in order to feed the most powerful, data-hungry AI algorithms,” says Artificial Intelligence for Public Domain Drug Discovery, presented at the annual conference of the Global Partnership on Artificial Intelligence (GPAI), an initiative launched in 2020 under French and Canadian leadership.

In the academic community, data sharing has taken off, and is now mandatory under most government funded grants, said Bengio. Researchers are rewarded through downstream citations if they allow others to use their data.

But the incentives for the private sector are still to keep data closed. Companies need to be encouraged to share their data, “by force of contract and financial rewards for doing the right things”, Bengio said. The GPAI report also calls for government intervention to “strongly encourage” data-sharing….”

Senators unveil bipartisan bill requiring social media giants to open data to researchers | TheHill

“Meta and other social media companies would be required to share their data with outside researchers under a new bill announced by a bipartisan group of senators on Thursday. …

The bill, the Platform Accountability and Transparency Act, would allow independent researchers to submit proposals to the National Science Foundation. If the requests are approved, social media companies would be required to provide the necessary data subject to certain privacy protections. …”

FDA looks on while major U.S. institutions violate medical research rules

“The FDA has issued warnings to only a handful of the companies and institutions with the worst track records of violating a key clinical trial disclosure law, a new report finds.



Out of 51 large US-based companies and institutions that have failed to make five or more clinical trial results public, only three have been contacted by the U.S. drug regulator, and only one has received a final warning, FDA enforcement data show.



Failing to rapidly make clinical trial results public on the American trial registry harms patients because it slows down medical progress, leaves gaps in the medical evidence base, and wastes public funds. …”

Giving drug researchers control of their data

“Drug industry–led efforts, like the Allotrope Foundation, have advanced common terms for data management, Plasterer says. Most recently, the FAIR principles—guidelines for ensuring data in storage are findable, accessible, interoperable, and reusable—have been adopted by drug companies including AstraZeneca and Pfizer….”

Yes, Alternative Proteins Really Do… | The Breakthrough Institute

“Federally funded research dramatically lowers barriers for scientists in the public and private sector to conduct research and accelerate technological development. Unlike its private counterpart, federally funded research can be open-access and makes knowledge and technologies publicly available. Open-access research benefits everyone, companies and academic researchers alike, and would prevent the siloing of intellectual property within specific companies. Such non-proprietary technology and knowledge can help bring new competitors into the market and help drive both competition and further innovation based on the open-access findings. Although open-access research will also benefit incumbents to the industry, federal support to develop the alternative can build the alternative protein industry’s capacity to compete with conventional products in the long term….”

Drug discovery project shows potential of smart openness – Research Professional News

“Commitment to sharing doesn’t mean you can’t work with industry, say Hamish Evans and colleagues

There are several ways for scientific research and innovation to have an impact on society. Different routes to impact are, however, often seen as being in tension. In particular, commercialisation and open science can sometimes seem to be mutually exclusive….”

Does open access to academic research help small, science-based companies? | Emerald Insight

Abstract:  Purpose

This study investigates the extent to which a company’s usage of open access (OA) literature for R&D activities depends on its size. The authors’ assumption is that smaller pharmaceutical companies have less access to (usually expensive) journal subscriptions.


A fixed-effect Poisson model was used to study a panel dataset of USPTO pharmaceutical company patents. The dependent variable is the count of citations to OA resources in a given company patent.


Results support current anecdotal evidence that many SMEs suffer from high journal prices.


This result justifies the assumption made by policymakers about the potentially positive impact OA mandates have on national innovation activity. It was also shown that collaborating with universities can be a potential coping mechanism for companies that struggle to gain access to the journals they need. In addition to the novelty of its findings, this study introduces a new way to study the impact of OA in nonacademic contexts.

SocArXiv Papers | Dynamics of Cumulative Advantage and Threats to Equity in Open Science – A Scoping Review

Open Science holds the promise to make scientific endeavours more inclusive, participatory, understandable, accessible, and re-usable for large audiences. However, making processes open will not per se drive wide re-use or participation unless also accompanied by the capacity (in terms of knowledge, skills, financial resources, technological readiness and motivation) to do so. These capacities vary considerably across regions, institutions and demographics. Those advantaged by such factors will remain potentially privileged, putting Open Science’s agenda of inclusivity at risk of propagating conditions of “cumulative advantage”. With this paper, we systematically scope existing research addressing the question: “What evidence and discourse exists in the literature about the ways in which dynamics and structures of inequality could persist or be exacerbated in the transition to Open Science, across disciplines, regions and demographics?” Aiming to synthesise findings, identify gaps in the literature, and inform future research and policy, our results identify threats to equity associated with all aspects of Open Science, including Open Access, Open/FAIR Data, Open Methods, Open Evaluation, Citizen Science, as well as its interfaces with society, industry and policy. Key threats include: stratifications of publishing due to the exclusionary nature of the author-pays model of Open Access; potential widening of the digital divide due to the infrastructure-dependent, highly situated nature of open data practices; risks of diminishing qualitative methodologies as “reproducibility” becomes synonymous with quality; new risks of bias and exclusion in means of transparent evaluation; and crucial asymmetries in the Open Science relationships with industry and the public, which privileges the former and fails to fully include the latter.