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Addressing sustainability issues requires a radical systemic change across multiple dimensions, including policy, culture, and civil society. This also implies that no blueprints for governing critical sustainability issues both at the local and global levels exist. As a result, rather than imposing decisions, policymakers should engage in a learning process. In this paper, we contend that appropriate policies should be developed and fine-tuned over time through a collective, social endeavour. To support this hypothesis, the study focuses on a shared methodology based on backcasting, a specific type of foresight, to facilitate policy learning (and thus policymaking) within a wide range of territories, regardless of their wealth, geographic characteristics and internal political organisation. This methodology was developed over a three-year period as part of the Territorial Strategies for Innovation (TSI) programme. The overall objective of our assignment was to build capacity and raise awareness within the EU's Overseas Countries and Territories about policymaking and implementation of innovative approaches to development. This innovative approach, which incorporates a systemic innovation perspective, highlights new options and opportunities for adopting and implementing adequate policies to positively impact sustainable development and long-term transformative change. Using empirical examples from Anguilla, Curaçao, and New Caledonia, the paper focuses on the learning processes required to deal with complexity and uncertainty in these remote territories. We conclude by discussing the potential implications of this foresight approach for the sustainable development and transformation of other less-favoured regions and territories.

A wide array of existing metrics quantifies a scientific paper's prominence or the author's prestige. Many who use these metrics make assumptions that higher citation counts or more public attention must indicate more reliable, better quality science. While current metrics offer valuable insight into scientific publications, they are an inadequate proxy for measuring the quality, transparency, and trustworthiness of published research. Three essential elements to establishing trust in a work include: trust in the paper, trust in the author, and trust in the data. To address these elements in a systematic and automated way, we propose the ripetaScore as a direct measurement of a paper's research practices, professionalism, and reproducibility. Using a sample of our current corpus of academic papers, we demonstrate the ripetaScore's efficacy in determining the quality, transparency, and trustworthiness of an academic work. In this paper, we aim to provide a metric to evaluate scientific reporting quality in terms of transparency and trustworthiness of the research, professionalism, and reproducibility.

Bibliometric data are relatively simple and describe objective processes of publishing articles and citing others. It seems quite straightforward to define reasonable measures of a researcher's productivity, research quality, or overall performance based on these data. Why do we still have no acceptable bibliometric measures of scientific performance? Instead, there are hundreds of indicators with nobody knowing how to use them. At the same time, an increasing number of researchers and some research fields have been excluded from the standard bibliometric analysis to avoid manifestly contradictive conclusions. I argue that the current biggest problem is the inadequate rule of credit allocation for multiple authored articles in mainstream bibliometrics. Clinging to this historical choice excludes any systematic and logically consistent bibliometrics-based evaluation of researchers, research groups, and institutions. During the last 50 years, several authors have called for a change. Apparently, there are no serious methodologically justified or evidence-based arguments in the favor of the present system. However, there are intractable social, psychological, and economical issues that make adoption of a logically sound counting system almost impossible.

Scholarly publishing lives on traditioned terminology that gives meaning to subjects such as authors, inhouse editors and external guest editors, artifacts such as articles, journals, special issues, and collected editions, or practices of acquisition, selection, and review. These subjects, artifacts, and practices ground the constitution of scholarly discourse. And yet, the meaning ascribed to each of these terms shifts, blurs, or is disguised as publishing culture shifts, which becomes manifest in new digital publishing technology, new forms of publishing management, and new forms of scholarly knowledge production. As a result, we may come to over- or underestimate changes in scholarly communication based on traditioned but shifting terminology. In this article, we discuss instances of scholarly publishing whose meaning shifted. We showcase the cultural shift that becomes manifest in the new, prolific guest editor. Though the term suggests an established subject, this editorial role crystallizes a new cultural setting of loosened discourse communities and temporal structures, a blurring of publishing genres and, ultimately, the foundations of academic knowledge production.

Meat production plays a vital socioeconomic role for sustainable development and for promoting food security in most countries. However, not much is known about research agendas done globally and the advancement of knowledge-generating networks in this area of study. The present study aims to reveal and analyze scientific research outputs on meat production linked with recent nanotechnology research work done till date. A compilation of research advancement and development within the sphere was realized through a scientometric study to comprehend the trend of research outputs, scientific impacts, authors' involvement, collaboration networks, and the advancement of knowledge gaps for future research endeavors on the current subject matter. Scholarly published articles were retrieved from the web of science (WOS) and Scopus databases from 1985 to 2020 and they were merged together using bibliometric package in R studio. All duplicated articles (438) from both data bases were excluded. A combination of terms (nano* AND (livestock* OR meat* OR beef* OR mutton* OR pork* OR chevon* OR chicken* OR turkey*)), and conversely analyzed for scientometric indices. A collection of 656 peer-reviewed, research articles were retrieved for the study period and authored by 2,133 researchers with a collaboration index of 3.31. The research outputs were highest in the year 2020 with total research outputs of 140 articles. The topmost three authors' keywords commonly used by authors were nanoparticles, meat, and chitosan with a respective frequency of 75, 62, and 57. China, Iran, and India ranked top in terms of meat production research outputs linked to nanotechnology and total citation with respective article productivity (total citations) of 160 (3,193), 111 (1,765), and 37 (552). Our findings revealed an increasing trend in research (with an annual growth rate of 25.18%) tending toward advancing meat production with the use of nanotechnology. Likewise, there is an increasing pointer to the fact that research work on nanotechnology and meat production has the prospect to influence positively, decision-making on research direction, and collaborations, hereby increasing the production of meat and its products in the future.

Many Indigenous people have a deep mistrust of research, with some describing research as one of the “dirtiest” words in Indigenous language. The histories and experiences behind such mistrust are long and painful. Given what has been perceived as Indigenous objectification at the hands of largely Anglo-European others for research from which they fail to benefit, many communities now refuse research unless it is undertaken under certain, Indigenous-defined circumstances. Such refusal is a move away from others purposes and a move towards autonomy and self-determination. For some, this is a statement of sovereignty and it applies to all areas of endeavour, including the new frontiers of research and the structures that support them, such as datification of knowledge. This article examines data sovereignty from the perspective of Indigenous peoples. While data sovereignty has become a ubiquitous concern, Indigenous data sovereignty arises from contexts specific to Indigenous peoples. The focus of this article is to provide a brief overview of recent data sovereignty developments, along with the context that lies behind these activities. Through this examination, implications for trust in scholarly communications will be discussed.

Molecular research and researchers engage in studies that seek to understand the structures, functions, and interactions of biomolecules as the basis for cellular and systemic effects in living organisms. This research approach was made possible by considerable technological advancements that equip researchers with tools to view biomolecules. Although molecular research holds great promises for improving lives and living, the technological requirements and equipment to undertake molecular research are quite expensive, often requiring a heavy start-up capital or investment. In developing countries such as Nigeria, where the majority of the population lives below the poverty line and research funding is abysmally low, such heavy investments into research that do not provide immediate solutions to societal problems are difficult. This is mostly due to limited resources available to tackle many urgent and pressing needs, and limited perspective and understanding of policymakers, leading to infrastructural and skilled personnel deficit to support molecular research. Despite all these, the field of molecular research continues to grow exponentially globally, hence, funding and investments into this critical life science research area have become imperative. With the rich biodiversity of humans, animals, and plants in Nigeria, and the huge burden of infectious diseases in the country or region, global advances in genomics and proteomics studies will be incomplete without adequate contribution from Nigeria and sub-Saharan Africa region. This paper examines the progression and challenges of undertaking molecular research in Nigeria, and how Nigerian molecular research scientists are tackling these issues, with recommendations for improved molecular research capacity and output in the country or region.

This article presents an analysis of the uptake of the GPRC label (Guaranteed Peer Reviewed Content label) since its introduction in 2010 until 2019. GPRC is a label for books that have been peer reviewed introduced by the Flemish publishers association. The GPRC label allows locally published scholarly books to be included in the regional database for the Social Sciences and Humanities which is used in the Flemish performance-based research funding system. Ten years after the start of the GPRC label, this is the first systematic analysis of the uptake of the label. We use a mix of qualitative and quantitative methods. Our two main data sources are the Flemish regional database for the Social Sciences and Humanities, which currently includes 2,580 GPRC-labeled publications, and three interviews with experts on the GPRC label. Firstly, we study the importance of the label in the Flemish performance-based research funding system. Secondly, we analyse the label in terms of its possible effect on multilingualism and the local or international orientation of publications. Thirdly, we analyse to what extent the label has been used by the different disciplines. Lastly, we discuss the potential implications of the label for the peer review process among book publishers. We find that the GPRC label is of limited importance to the Flemish performance-based research funding system. However, we also conclude that the label has a specific use for locally oriented book publications and in particular for the discipline Law. Furthermore, by requiring publishers to adhere to a formalized peer review procedure, the label affects the peer review practices of local publishers because not all book publishers were using a formal system of peer review before the introduction of the label and even at those publishers who already practiced peer review, the label may have required the publishers to make these procedures more uniform.

The EU's response to the COVID-19 crisis, namely the approval of the Next Generation package, provides an opportunity to explore to what extent the existing Smart Specialisation regional strategies and related ecosystems have been taken into account in the highly relevant territorial context in which the national Recovery Plans have been designed. According to our results the potential of the Smart Specialisation approach (S3) in relation with its place-based strategic prioritisation may have been overlooked in the process. The research is based on a desk review of relevant documents and recent literature in this field; followed by semi-structured interviews with regional planners and practitioners from 10 Spanish regions (autonomous communities); complemented, in a second phase, by the organisation of a focus group to validate the initial results. During our research we identified the main contributions that the Smart Specialisation approach has so far made to the regions (mainly in terms of participative governance and creation of regional ecosystems); and the unanimous perception shared by all the practitioners interviewed that the S3 approach has led to a change of vision in public intervention. However, all of the interviewed regions have confirmed that the drafting of the national recovery and resilience plan lacked an ex-ante alignment with the regional S3 strategies, and failed to consider the existing regional S3 ecosystems. The separation of the recovery logic (based on the operation of public consultations at national level to identify strategic projects) from the S3 logic (based on a strategic prioritisation exercise conducted by each regional ecosystem) confirms that an opportunity may have been missed in the recovery planning process to consolidate the multi-actor, multilevel and place-based S3 approach. Although there is a certain degree of disappointment among regional practitioners as a result of this misalignment, the majority of them believe in the possibility of an ex-post alignment between the two processes, that can protect existing regional shared visions. However, without clear recognition of the S3 ecosystems and the S3 managing bodies, the significant role that Smart Specialisation could play in the recovery process may be at risk.

Basic research is believed to be a crucial factor for building national innovation capacity and therefore was perceived as a key battleground for national technological and economic competition. Since the economic reform and opening up in the late 1970s, China has made great achievements in building up its national research system. However, the lacking capabilities to conduct ground-breaking scientific work remain one of the daunting challenges for the country. How to restructure its funding system for basic research so to reinvigorate its indigenous innovation capacity has been one of the main concerns for the Chinese government in recent years. To address this, the paper proposes a conceptual framework to analyze how China’s central government funding system for basic research has evolved since 1985. The paper concludes with a discussion of the identified problems and challenges that China is facing in its current funding system for basic research.

The current digital content industry is heavily oriented towards building platforms that track users’ behaviour and seek to convince them to stay longer and come back sooner onto the platform. Similarly, authors are incentivised to publish more and to become champions of dissemination. Arguably, these incentive systems are built around public reputation supported by a system of metrics, hard to be assessed. Generally, the digital content industry is permeable to non-human contributors (algorithms that are able to generate content and reactions), anonymity and identity fraud. It is pertinent to present a perspective paper about early signs of track and persuasion in scholarly communication. Building our views, we have run a pilot study to determine the opportunity for conducting research about the use of “track and persuade” technologies in scholarly communication. We collected observations on a sample of 148 relevant websites and we interviewed 15 that are experts related to the field. Through this work, we tried to identify 1) the essential questions that could inspire proper research, 2) good practices to be recommended for future research, and 3) whether citizen science is a suitable approach to further research in this field. The findings could contribute to determining a broader solution for building trust and infrastructure in scholarly communication. The principles of Open Science will be used as a framework to see if they offer insights into this work going forward.

Chemical reactions and experimental conditions are fundamental information for chemical research and pharmaceutical applications. However, the latest information of chemical reactions is usually embedded in the free text of patents. The rapidly accumulating chemical patents urge automatic tools based on natural language processing (NLP) techniques for efficient and accurate information extraction. This work describes the participation of the Melax Tech team in the CLEF 2020—ChEMU Task of Chemical Reaction Extraction from Patent. The task consisted of two subtasks: (1) named entity recognition to identify compounds and different semantic roles in the chemical reaction and (2) event extraction to identify event triggers of chemical reaction and their relations with the semantic roles recognized in subtask 1. To build an end-to-end system with high performance, multiple strategies tailored to chemical patents were applied and evaluated, ranging from optimizing the tokenization, pre-training patent language models based on self-supervision, to domain knowledge-based rules. Our hybrid approaches combining different strategies achieved state-of-the-art results in both subtasks, with the top-ranked F1 of 0.957 for entity recognition and the top-ranked F1 of 0.9536 for event extraction, indicating that the proposed approaches are promising.

The field of law has retained its distinctiveness regarding peer review to this day, and reviews are often conducted without following standardized rules and principles. External and independent evaluation of submissions has recently become adopted by European law journals, and peer review procedures are still poorly defined, investigated, and attuned to the legal science publishing landscape. The aim of our study was to gain a better insight into current editorial policies on peer review in law journals by exploring editorial documents (instructions, guidelines, policies) issued by 119 Croatian, Italian, and Spanish law journals. We relied on automatic content analysis of 135 publicly available documents collected from the journal websites to analyze the basic features of the peer review processes, manuscript evaluation criteria, and related ethical issues using WordStat8. Differences in covered topics between the countries were compared using the chi-square test. Our findings reveal that most law journals have adopted a traditional approach, in which the editorial board manages mostly anonymized peer review (104, 77%) engaging independent/external reviewers (65, 48%). Submissions are evaluated according to their originality and relevance (113, 84%), quality of writing and presentation (94, 70%), comprehensiveness of literature references (93, 69%), and adequacy of methods (57, 42%). The main ethical issues related to peer review addressed by these journals are reviewer’s competing interests (42, 31%), plagiarism (35, 26%), and biases (30, 22%). We observed statistically significant differences between countries in mentioning key concepts such as “Peer review ethics”, “Reviewer”, “Transparency of identities”, “Publication type”, and “Research misconduct”. Spanish journals favor reviewers’ “Independence” and “Competence” and “Anonymized” peer review process. Also, some manuscript types popular in one country are rarely mentioned in other countries. Even though peer review is equally conventional in all three countries, high transparency in Croatian law journals, respect for research integrity in Spanish ones, and diversity and inclusion in Italian are promising indicators of future development.

We present a small case study on citations of conference posters using poster collections from both Figshare and Zenodo. The study takes into account the years 2016–2020 according to the dates of publication on the platforms. Citation data was taken from DataCite, Crossref and Dimensions. Primarily, we want to know to what extent scientific posters are being cited and thereby which impact posters potentially have on the scholarly landscape and especially on academic publications. Our data-driven analysis reveals that posters are rarely cited. Citations could only be found for 1% of the posters in our dataset. A limitation in this study however is that the impact of academic posters was not measured empirical but rather descriptive.

Since 2000, there has been qualitative growth in the field of scientometrics. Innovations such as the DOI and the ORCID have irrevocably changed the scientific landscape. They have enabled analyses previously unheard of, in the decades preceding the new millennium. This paper proposes open science indicators (open data, open material, preregistration) as article-specific metadata fields. The authors reference the history of funding information, from bare acknowledgements to metadata field. The authors describe the mission of the Center for Open Science, and its TOP Factor database, as well as the performance of open science badges. Possibilities for a pilot study are explored, with an acknowledgement of the complexity of this undertaking.

This article is a modest attempt to shed some light on the question of linkages between backward and forward citations in technical fields posed by Trajtenberg et al. (1997). They found interesting similarities and high correlations between equivalent measures looking forward and backward. They also implied the linkage between distant backward and distant forward citations. There are several questions to be posed in applying their insights to Japanese patent applications, however, due to the differences in the patent classification system and the subject of citation, i.e., citations by the applicant or examiner, between the US and Japan. In addition, and most importantly, the possibility that subsequent classifications may match, even if the first classification is different, is unavoidable with existing measurement methods of technical distance. In order to investigate these research questions, the author proposes a new measurement method for the technological proximity between examiner’s citations and their originating patents using IPC-based patent classifications. Using such a proposed method, the author created two hypotheses and tested them for about 14,000 examined patent applications filed in 2008 with the JPO. As a result of testing Hypothesis I, the author confirmed that Trajtenberg et al.’s insights can be applied to Japanese patent applications using citations by the examiners and IPC-based patent classifications. In other words, it was confirmed that patent applications citing backward citations categorized in a technical field distant from the invention are more likely to be cited by forward citations categorized in a technical field distant from the invention. As a result of the verification of Hypothesis Ⅱ, it was further confirmed in some technical fields that the backward citations categorized in a technical field distant from the invention are more likely to be in the same technical field as the forward citations categorized in a technical field distant from the invention. The author believes that these verified results indicate the possibilities of using backward citations as a starting point from which we can find patent applications for inventions at an early stage with potential applicability to other technical fields.

International audience; This paper explores the relationship between the industry collaborations of grant applicant teams and the outcomes of a multistage grant evaluation process. We studied this relationship by focusing on two possible channels of impact of industry engagement—team diversity (or the diversity effect) and prior collaboration experience (or the experience effect)—and examined their influence on the evaluators' decision by using the proxies of direct industry engagement (i.e., the involvement of a company-affiliated researcher in the grant applicant team) and indirect industry engagement (i.e., joint publications with a company-affiliated researcher prior to the grant application), respectively. We analyzed data extracted from the application and reviewed materials of a multidisciplinary, pan-European research funding scheme—European Collaborative Research (EUROCORES)—for the period 2002–2010 and conducted an empirical investigation of its three consecutive grant evaluation stages at the team level. We found that teams presenting an indirect engagement were more likely to pass the first stage of selection, whereas no significant relationships were found at any of the three evaluation stages for teams presenting a direct engagement. Our findings point to the heterogeneity of the decision-making process within a multistage grant evaluation scheme and suggest that the policy objective of fostering university–industry collaboration does not significantly impact the funding process.

Many journals now rely on editorial management systems, which are supposed to support the administration and decision making of editors, while aiming at making the process of communication faster and more transparent to both reviewers and authors. Yet, little is known about how these infrastructures support, stabilize, transform or change existing editorial practices. Research suggests that editorial management systems as digital infrastructures are adapted to the local needs at scholarly journals and reflect main realms of activities. Recently, it has been established that in a minimal case, the peer review process is comprised of postulation, consultation, decision and administration. By exploring process generated data from a publisher’s editorial management system, we investigate the ways by which the digital infrastructure is used and how it represents the different realms of the process of peer review. How does the infrastructure support, strengthen or restrain editorial agency for administrating the process? In our study, we investigate editorial processes and practices with their data traces captured by an editorial management system. We do so by making use of the internal representation of manuscript life cycles from submission to decision for 14,000 manuscripts submitted to a biomedical publisher. Reconstructing the processes applying social network analysis, we found that the individual steps in the process have no strict order, other than could be expected with regard to the software patent. However, patterns can be observed, as to which stages manuscripts are most likely to go through in an ordered fashion. We also found the different realms of the peer review process represented in the system, some events, however, indicate that the infrastructure offers more control and observation of the peer review process, thereby strengthening the editorial role in the governance of peer review while at the same time the infrastructure oversees the editors’ performance.

Background: The challenge of research funding constraints has brought to bear enormous pressure on researchers. Research productivity is relevant to prestige and career progression of academic staff. However, this study aimed to explore significant challenges associated with researchers’ productivity and the impact of non-funding of research in Nigerian research and tertiary institutions.Methods: This study adopted a qualitative exploratory design involving academics at various research and tertiary institutions across the six geographical regions in Nigeria. A semi-structured questionnaire was distributed electronically to all participants who consented to take part in this study. Exactly 4,159 questionnaires were administered and 2,350 were completely filled and returned. Pearson correlation matrices with logistic regression were used for data analysis and are presented in frequencies and percentages.Results: On challenges faced by respondents, 42.98% reported a lack of research funding, 17.11% mentioned brain drain challenge while 8.85% indicated a lack of motivation. Of the 23,927 publications reported, the number of those in sciences, engineering, and medical sciences averaged 9.6, 11.5, and 9.5 respectively. The average number of publications by women (10.8) was more than by men (9.7). Lecturers had the highest average research publication number (11.8) followed by researchers (10.2) and others (3.9). Men had the highest (11.9) average number of conferences compared to women (9.2). Participants in engineering had an average number of 13.8 conferences per respondents followed by those in education (11.2), sciences (11.1), and 10.9 for those in agricultural sciences. The result revealed a negative significant correlation between research publication and academic qualification at p < 0.01. Positive significant correlation was observed between research productivity and discipline at p < 0.05. Findings show that the combined influence of the independent variables on research productivity was significant using linear regression analysis.Conclusions: The failure to prioritize research has resulted in underdevelopment in Nigeria. It is therefore imperative that the federal government prioritize research and establish a functional Special Research Trust Fund to oversee research funding in Nigeria.

This article surveys topic distributions of the academic literature that employs the terms bibliometrics, scientometrics, and informetrics. This exploration allows informing on the adoption of those terms and publication patterns of the authors acknowledging their work to be part of bibliometric research. We retrieved 20,268 articles related to bibliometrics and applied methodologies that exploit various features of the dataset to surface different topic representations. Across them, we observe major trends including discussions on theory, regional publication patterns, databases, and tools. There is a great increase in the application of bibliometrics as science mapping and decision-making tools in management, public health, sustainability, and medical fields. It is also observed that the term bibliometrics has reached an overall generality, while the terms scientometrics and informetrics may be more accurate in representing the core of bibliometric research as understood by the information and library science field. This article contributes by providing multiple snapshots of a field that has grown too quickly beyond the confines of library science.

Draws parallels between the problematic use of GDP to evaluate economic success with the use of global university rankings to evaluate university success. Inspired by Kate Raworth’sDoughnut Economics,this perspective argues that the pursuit of growth as measured by such indicators creates universities that ‘grow’ up the rankings rather than those which ‘thrive’ or ‘mature.’ Such growth creates academic wealth divides within and between countries, despite the direction of growth as inspired by the rankings not truly reflecting universities’ critical purpose or contribution. Highlights the incompatibility between universities’ alignment with socially responsible practices and continued engagement with socially irresponsible ranking practices. Proposes four possible ways of engendering change in the university rankings space. Concludes by calling on leaders of ‘world-leading’ universities to join together to ‘lead the world’ in challenging global university rankings, and to set their own standards for thriving and maturing universities.

We review the literature on entrepreneurial team formation with a focus on data to study academic teams and summarize our empirical work on the life sciences industry. We consider how academics form teams to start new companies and the implications of various configurations on firm behavior with regards to patenting, survival and firm growth. We present several empirical challenges facing research on academic teams and conclude with suggestions for future research.

Acknowledgement of scientific achievements was and is essentially achieved through the citation of a publication. Increasingly, however, it is no longer just the publication itself that plays an important role, but also the degree of attention that a scientist achieves with this very publication. Thus, the importance of strategic behavior in science is progressing and an awareness mentality is spreading. In this paper, the causes and backgrounds of this development are discussed, identifying the use of reductionist, quantitative systems in science management and research funding, the loss of critical judgment and technocratic dominance, quantitative assessments used for decision making, altmetrics and the like as alternative views, the use of perception scores in reference databases and universities as well as ambitions of journals as main drivers. Besides, different forms of strategic behavior in science and the resulting consequences and impacts are being highlighted.

New conference formats are emerging in response to COVID-19 and climate change. Virtual conferences are sustainable and inclusive regardless of participant mobility (financial means, caring commitments, disability), but lack face-to-face contact. Hybrid conferences (physical meetings with additional virtual presentations) tend to discriminate against non-fliers and encourage unsustainable flying. Multi-hub conferences mix real and virtual interactions during talks and social breaks and are distributed across nominally equal hubs. We propose a global multi-hub solution in which all hubs interact daily in real time with all other hubs in parallel sessions by internet videoconferencing. Conference sessions are confined to three equally-spaced 4-h UTC timeslots. Local programs comprise morning and afternoon/evening sessions (recordings from night sessions can be watched later). Three reference hubs are located exactly 8 h apart; additional hubs are within 2 h and their programs are aligned with the closest reference hub. The conference experience at each hub depends on the number of local participants and the time difference to the nearest reference. Participants are motivated to travel to the nearest hub. Mobility-based discrimination is minimized. Lower costs facilitate diversity, equity, and inclusion. Academic quality, creativity, enjoyment, and low-carbon sustainability are simultaneously promoted.

Science, technology, and innovation (STI) is increasingly gaining in importance on the foreign policy agenda of governments worldwide. However, the implementation of science diplomacy strategies requires STI institutional capacity and strong interfaces with policy and diplomacy. This research first maps the STI public institutions of the six member countries of the Central American Integration System (Guatemala, El Salvador, Honduras, Nicaragua, Costa Rica and Panama) and then draws their capacity to connect internationally in order to highlight their potential for science diplomacy. Variables such as the year of creation and mandates of scientific councils, secretariats, national academies, international cooperation departments and ministries are analyzed. The study reveals several public management challenges stemming from the institutional disparity and complexity of the region, already marked by significant asymmetries of human development between the various countries. Highlighting and understanding such challenges may be helpful for countries in the region in developing meaningful strategies around science diplomacy.

We deal with a heterogeneous pharmaceutical knowledge-graph containing textual information built from several databases. The knowledge graph is a heterogeneous graph that includes a wide variety of concepts and attributes, some of which are provided in the form of textual pieces of information which have not been targeted in the conventional graph completion tasks. To investigate the utility of textual information for knowledge graph completion, we generate embeddings from textual descriptions given to heterogeneous items, such as drugs and proteins, while learning knowledge graph embeddings. We evaluate the obtained graph embeddings on the link prediction task for knowledge graph completion, which can be used for drug discovery and repurposing. We also compare the results with existing methods and discuss the utility of the textual information.

The experience of building and participating in women scientists’ communities in Central America is a multi-layered topic worthy of study. Understanding the dynamics of these women’s groups, associations, and other forms of collective participation, could assist in shedding light on why women are typically under-represented in Science, Technology, Engineering, and Mathematics (STEM) research in countries within this region. The objectives of this study are (i) to explore the experiences of participation in communities of women scientists in Guatemala, El Salvador, Honduras and Panama, and (ii) to systematize the challenges and opportunities derived from such activities. Additionally, this work elaborates on some best practices from the Science Diplomacy (SD) perspective, which could provide a helpful framework to encourage these types of collective participatory communities. The qualitative research methodology was based on the collection of primary data from semi-structured interviews and responses to an online survey sent out to Central American women scientists. The findings of this study revealed few cases of community building experiences among women scientists within the studied countries. Evidence also showed the emergence of shared patterns in terms of barriers and disincentives to participating in such communities. Meanwhile, data collected from the few existing community groups is used to identify successful incentives and motivations. The analysis of the collected data offered relevant implications for Science Diplomacy. Most respondents referred to the Organization of Women in Science for the Developing World (OWSD) as one of the main organizations that can impact and further Science Diplomacy. This organization promotes international engagement and networking among women scientists from developing countries across regions and this article shows how this has been used to foster women science community building in Central America. Exploring similar practices in-depth may offer opportunities to overcome traditional barriers and build further gender equality in science in Central America.

Analysis of high-throughput experiments in the life sciences frequently relies upon standardized information about genes, gene products, and other biological entities. To provide this information, expert curators are increasingly relying on text mining tools to identify, extract and harmonize statements from biomedical journal articles that discuss findings of interest. For determining reliability of the statements, curators need the evidence used by the authors to support their assertions. It is important to annotate the evidence directly used by authors to qualify their findings rather than simply annotating mentions of experimental methods without the context of what findings they support. Text mining tools require tuning and adaptation to achieve accurate performance. Many annotated corpora exist to enable developing and tuning text mining tools; however, none currently provides annotations of evidence based on the extensive and widely used Evidence and Conclusion Ontology. We present the ECO-CollecTF corpus, a novel, freely available, biomedical corpus of 84 documents that captures high-quality, evidence-based statements annotated with the Evidence and Conclusion Ontology. This work was supported by the National Science Foundation, Division of Biological Infrastructure (1458400) and the National Institutes of Health (R01GM089636, U41HG008735), and by a management commission from Plan TL (Plan de Impulso de las Tecnologías del Lenguaje) of the Spanish Ministerio de Asuntos Económicos y Transformación Digital to BSC-CNS.

Science is increasingly expected to help in solving complex societal problems in collaboration with societal stakeholders. However, it is often unclear under what conditions this can happen, i.e., what kind of challenges occur when science interacts with society and what kind of quality expectations prevail. This is particularly pertinent for Social Sciences and Humanities (SSH), which are part of the object they study and whose knowledge is always subject to provisionality. Here we discuss how SSH researchers can contribute to societal problems, what challenges might occur when they interact with societal stakeholders, and what quality expectations arise in these arrangements. We base our argumentation on the results of an online consultation among 125 experts in Germany (representatives from SSH, learned societies, stakeholders from different societal groups, and relevant intermediaries).

Chemical patents are an important source of information about novel chemicals and chemical reactions. With the increasing volume of such patents, mining information about these chemicals and chemical reactions has become a time-intensive and laborious endeavor. In this paper, we present a system to automatically extract chemical reaction events from patents. Our approach consists of two steps: 1) Named Entity Recognition (NER) -- the automatic identification of chemical reaction parameters from the corresponding text; and 2) Event Extraction (EE) -- the automatic classifying and linking of entities based on their relationships to each other. For our NER system, we evaluate Bidirectional Long Short Term Memory (BiLSTM)-based and Bidirectional Encoder Representations from Transformers (BERT)-based methods. For our RE system, we evaluate two BERT-based, Convolutional Neural Networks (CNN)-based, and rule-based methods. We evaluate our NER and EE components separately and also as an end-to-end system, reporting the precision, recall, and F- score. From the results, we can conclude the BiLSTM-based method performed well at identifying the entities, and the CNN-based method performed well at extracting events. CNN-based and BERT-based methods performed well with the classes with more instances to train on, and the rule-based method performed well with classes with fewer instances.

We constructed a survey to understand how authors and scientists view the issues around reproducibility, focusing on interactive elements such as interactive figures embedded within online publications, as a solution for enabling the reproducibility of experiments. We report the views of 251 researchers, comprising authors who have published in eLIFE Sciences, and those who work at the Norwich Biosciences Institutes (NBI). The survey also outlines to what extent researchers are occupied with reproducing experiments themselves. Currently, there is an increasing range of tools that attempt to address the production of reproducible research by making code, data, and analyses available to the community for reuse. We wanted to collect information about attitudes around the consumer end of the spectrum, where life scientists interact with research outputs to interpret scientific results. Static plots and figures within articles are a central part of this interpretation, and therefore we asked respondents to consider various features for an interactive figure within a research article that would allow them to better understand and reproduce a published analysis. The majority (91%) of respondents reported that when authors describe their research methodology (methods and analyses) in detail, published research can become more reproducible. The respondents believe that having interactive figures in published papers is a beneficial element to themselves, the papers they read as well as to their readers. Whilst interactive figures are one potential solution for consuming the results of research more effectively to enable reproducibility, we also review the equally pressing technical and cultural demands on researchers that need to be addressed to achieve greater success in reproducibility in the life sciences.

Research and Technology Organizations (RTOs) have key roles in stories of national industrial development in many countries, and in various contexts they have transformed according to changes in their surrounding economic and policy environments. This paper proposes a conceptual framework of ‘RTOs as super intermediaries’ as they play multiple intermediary roles in the triple helix (government, research and industry), the overlap of industrial policy and research policy, and research-industry frontiers. The framework helps in understanding and advancing the role of RTOs in industrial development, particularly in developing countries. For a case study, the paper showcases research in Tanzania that explored possibilities of revamping RTOs and whether investing in them would help in spurring Tanzania's industrial development. Through key informant interviews and systemic literature review, a case study on the challenges and opportunities of RTOs was designed to examine their role and potential in industrial development and technology innovation processes. The study findings were overall in-line with two main lenses of inquiry: 1) that for RTOs to play their key roles in Tanzania, industrial policies shaped by the command economy era before the 1990s need to be reviewed and modified; and 2) that more investment in revamping RTOs will take place if policymaking processes acknowledge RTOs as super intermediaries. To organize policy lessons drawn, a multi-level policy map—micro, meso and macro—was utilized as an analytical tool.

Science, technology and innovation are taking center stage in international affairs and are increasingly influencing the geopolitical dynamics and a country’s standing on the global stage. New scientific and technological advancements are acquiring greater strategic relevance to ensure competitive advantages in the 21st century global order. At the same time, international scientific collaboration contributes to generating and democratizing knowledge and improving relations between countries to coordinate science-based solutions to transboundary problems, and to build bridges between nations with tense or non-existent diplomatic relations. Science diplomacy is not a new concept, but most of its intellectual foundations and practical applications have emerged over the past decade in the Global North. This article describes the diverse approaches, policies and practices adopted by Latin American and Caribbean countries at the national, sub-national and regional levels. It analyzes their successes and challenges and identifies opportunities to guide the region towards a common science diplomacy strategy to achieve sustainable development through incorporating science as a permanent element in the foreign policy toolkit of Latin American nations. By documenting and illuminating successful models and best practices in the region, this article also seeks to balance the emphasis that has so far been largely concentrated on the regions of Europe and North America and contribute to future efforts and strategies for the development of long-term science diplomacy mechanisms at the national, regional, North-South and South-South levels.

Towards the objectives of the UnitedStates Food and Drug Administration (FDA) generic drug science and research program, it is of vital importance in developing product-specific guidances (PSGs) with recommendations that can facilitate and guide generic product development. To generate a PSG, the assessor needs to retrieve supportive information about the drug product of interest, including from the drug labeling, which contain comprehensive information about drug products and instructions to physicians on how to use the products for treatment. Currently, although there are many drug labeling data resources, none of them including those developed by the FDA (e.g., Drugs@FDA) can cover all the FDA-approved drug products. Furthermore, these resources, housed in various locations, are often in forms that are not compatible or interoperable with each other. Therefore, there is a great demand for retrieving useful information from a large number of textual documents from different data resources to support an effective PSG development. To meet the needs, we developed a Natural Language Processing (NLP) pipeline by integrating multiple disparate publicly available data resources to extract drug product information with minimal human intervention. We provided a case study for identifying food effect information to illustrate how a machine learning model is employed to achieve accurate paragraph labeling. We showed that the pre-trained Bidirectional Encoder Representations from Transformers (BERT) model is able to outperform the traditional machine learning techniques, setting a new state-of-the-art for labelling food effect paragraphs from drug labeling and approved drug products datasets.

Carrying out bibliometric reports is one of the common tasks performed by librarians and practitioners within the framework of their professional duties. The emergence of novel data sources, the need to measure new research activities and the growing demand for fairer and more equitable evaluation within the framework of the Responsible Metrics movement has led to calls for a review of the traditional approaches to these types of reports. The main goal of this study is to outline a series of recommendations for bibliometricians, consultants and research support librarians when drafting bibliometric reports in their institutions. These best practices can significantly enhance the quality and utility of bibliometric reports, posing their practitioners as key players in the science management process.

In this paper, we describe how we applied LBD techniques to discover lecithin cholesterol acyltransferase (LCAT) as a druggable target for cardiac arrest. We fully describe our process which includes the use of high-throughput metabolomic analysis to identify metabolites significantly related to cardiac arrest, and how we used LBD to gain insights into how these metabolites relate to cardiac arrest. These insights lead to our proposal (for the first time) of LCAT as a druggable target; the effects of which are supported by in vivo studies which were brought forth by this work. Metabolites are the end product of many biochemical pathways within the human body. Observed changes in metabolite levels are indicative of changes in these pathways, and provide valuable insights toward the cause, progression, and treatment of diseases. Following cardiac arrest, we observed changes in metabolite levels pre- and post-resuscitation. We used LBD to help discover diseases implicitly linked via these metabolites of interest. Results of LBD indicated a strong link between Fish Eye disease and cardiac arrest. Since fish eye disease is characterized by an LCAT deficiency, it began an investigation into the effects of LCAT and cardiac arrest survival. In the investigation, we found that decreased LCAT activity may increase cardiac arrest survival rates by increasing ω-3 polyunsaturated fatty acid availability in circulation. We verified the effects of ω-3 polyunsaturated fatty acids on increasing survival rate following cardiac arrest via in vivo with rat models.

The exponential growth of scientific literature yields the need to support users to both effectively and efficiently analyze and understand the some body of research work. This exploratory process can be facilitated by providing graphical abstracts–a visual summary of a scientific publication. Accordingly, previous work recently presented an initial study on automatic identification of a central figure in a scientific publication, to be used as the publication’s visual summary. This study, however, have been limited only to a single (biomedical) domain. This is primarily because the current state-of-the-art relies on supervised machine learning, typically relying on the existence of large amounts of labeled data: the only existing annotated data set until now covered only the biomedical publications. In this work, we build a novel benchmark data set for visual summary identification from scientific publications, which consists of papers presented at conferences from several areas of computer science. We couple this contribution with a new self-supervised learning approach to learn a heuristic matching of in-text references to figures with figure captions. Our self-supervised pre-training, executed on a large unlabeled collection of publications, attenuates the need for large annotated data sets for visual summary identification and facilitates domain transfer for this task. We evaluate our self-supervised pretraining for visual summary identification on both the existing biomedical and our newly presented computer science data set. The experimental results suggest that the proposed method is able to outperform the previous state-of-the-art without any task-specific annotations.

According to the United Nations Educational, Scientific, and Cultural Organization (UNESCO), Open Science is the movement to make scientific research and data accessible to all. It has great potential for advancing science. At its core, it includes (but is not limited to) open access, open data, and open research. Some of the associated advantages are promoting collaboration, sharing, and reproducibility in research, and preventing the reinvention of the wheel, thus saving resources. As research becomes more globalized and its output grows exponentially, especially in data, the need for open scientific research practices is more evident — the future of modern science. This has resulted in a concerted global interest in open science uptake. Even so, barriers still exist. The formal training curriculum in most, if not all, universities in Kenya does not equip students with the knowledge and tools to subsequently practice open science in their research. Therefore, to work openly and collaboratively, there is a need for awareness and training in the use of open science tools. These have been neglected, especially in most developing countries, and remain barriers to the cause. Moreover, there is scanty research on the state of affairs regarding the practice and/or adoption of open science. Thus, we developed, through the OpenScienceKE framework, a model to narrow the gap. A sensitize-train-hack-collaborate model was applied in Nairobi, the economic and administrative capital of Kenya. Using the model, we sensitized through seminars, trained on the use of tools through workshops, applied the skills learned in training through hackathons to collaboratively answer the question on the state of open science in Kenya. While the former parts of the model had 20 - 50 participants, the latter part mainly involved participants with a bioinformatics background, leveraging their advanced computational skills. This model resulted in an open resource that researchers can use to publish as open access cost-effectively. Moreover, we observed a growing interest in open science practices in Kenya through literature search and data mining, and that lack of awareness and skills may still hinder the adoption and practice of open science. Furthermore, at the time of the analyses, we surprisingly found that out of the 20,069 papers downloaded from BioRXiv, only 18 had Kenyan authors, a majority of which are international (16) collaborations. This may suggest poor uptake of the use of preprints among Kenyan researchers. The findings in this study highlight the state of open science in Kenya and the challenges facing its adoption and practice while bringing forth possible areas for primary consideration in the campaign towards open science. It also proposes a model (sensitize-train-hack-collaborate model) that may be adopted by researchers, funders, and other proponents of open science to address some of the challenges faced in promoting its adoption in Kenya.

This paper applied a literature-based discovery methodology utilizing citation networks and text mining in order to extract and represent shared terminologies found in disjoint academic literature on food security and the Internet of Things. The topic of food security includes research on improvements in nutrition, sustainable agriculture, and a plurality of other social challenges, while the Internet of Things refers to a collection of technologies from which solutions can be drawn. Academic articles on both topics were classified into subclusters, and their text contents were compared against each other to find shared terms. These terms formed a network from which clusters of related keywords could be identified, potentially easing the exploration of common themes. Thirteen transversal themes, including blockchain, healthcare, and air quality, were found. This method can be applied by policymakers and other stakeholders to understand how a given technology could contribute to solving a pressing social issue.

Although the impact of so-called “sponsorship bias” has been the subject of increased attention in the philosophy of science, what exactly constitutes its epistemic wrongness is still debated. In this paper, I will argue that neither evidential accounts nor social–epistemological accounts can fully account for the epistemic wrongness of sponsorship bias, but there are good reasons to prefer social–epistemological to evidential accounts. I will defend this claim by examining how both accounts deal with a paradigm case from medical epistemology, recently discussed in a paper by Bennett Holman. I will argue that evidential accounts cannot adequately capture cases of sponsorship bias that involve the manufacturing of certainty because of their neutrality with respect to the role of non-epistemic values in scientific practice. If my argument holds, it further highlights the importance of integrating social and ethical concerns into epistemological analysis, especially in applied contexts. One can only properly grasp sponsorship bias as an epistemological problem if one resists the methodological tendency to analyze social, ethical, and epistemological issues in isolation from each other.

Private companies provide by far the most funding for scientific research and development. Nevertheless, relatively little attention has been paid to the dynamics of industry‐funded research by philosophers of science. This paper first provides an overview of the epistemic concerns expressed within the philosophy of science literature. Next I turn to a completely parallel literature in the field of science policy that full-throatedly promotes industry-academic collaboration. Surprisingly, this line of research is almost, if not completely, independent from the philosophical literature. After providing an overview of this literature, I focus on understanding how the science-policy field understands such collaborations and why they seem to have no reservations about such relationships and why philosophy of science is generally focussed on the drawbacks of industry funidng. I conclude by considering how the two literatures might be fruitfully integrated and the challenges that each poses for the other.