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Research data and software are widely accepted as an outcome of scientific work. However, in comparison to text-based publications, there is not yet an established process to assess and evaluate quality of research data and research software publications. This paper presents an attempt to fill this gap. Initiated by the Working Group Open Science of the Helmholtz Association, the Task Group Helmholtz Quality Indicators for Data and Software Publications currently develops a quality indicator for research data and research software publications to be used within the Association. This report summarizes the vision of the group of what all contributes to such an indicator. The proposed approach relies on generic well-established concepts for quality criteria, such as the FAIR Principles and the COBIT Maturity Model. It does – on purpose – not limit itself to technical implementation possibilities to avoid using an existing metric for a new purpose. The intention of this paper is to share the current state for further discussion with all stakeholders, particularly with other groups also working on similar metrics but also with entities that use the metrics.

Purpose: An increasing number of scholarly publications on autism spectrum disorder (ASD) have urged researcher interest in this topic; however, there is still a lack of quantitative analysis. Therefore, this study aims to cover the knowledge gap between the amount of literature published on ASD research on architectural and designers' perspectives compared to the medical and psychological fields. The study has analyzed global research output on ASD from a designer's perspective to recognize this gap related to designing the physical environment. Methodology: The bibliometric method was employed to analyze the published literature from 1992–to 2021. 812 papers were downloaded from the Web of Science for analysis based on annual growth of literature, prolific authors, authorship pattern, organizations, countries, international collaboration, and subject development by keywords and thematic map analyses. Various bibliometric and scientometric software was used to analyze the data, namely Bibexcel, Biblioshiny, and VOS viewer. Results: The812 research papers were published in 405 sources. 2019 appeared as a productive year (NP=101), and 2014 received the highest number of citations (TC=6634). Researchers preferred to publish as journal articles (NP=538; TC=24922). The University of Toronto, Canada, was identified as a productive institution with 42 publications and 5358 citations. The USA was the leading producing country with 433 publications, and most of the researchers published in the journal ' Scientific Reports' (NP=16). The word autism (NP=257) and architecture (NP=165) were more frequently used keywords. Conclusion: The study identified a massive gap in the development of literature in ASD for architecture design and built environment perspective, the most important and trending keywords are missing, and the analyses also showed a lack of subject development. The authors have suggested areas and keywords for further research to fulfill the gap in the future.

Background: One of the countries most adversely affected by the COVID-19 outbreak was Peru. Worldwide scientific knowledge creation has significantly grown because of this pandemic. This systematic study aims to examine several facets of Peru’s experimental scientific production concerning COVID-19. Methods: Between December 2019 and June 2022, searches were made in the PubMed database for experimental scientific articles created in Peruvian institutions. Data were extracted and analyzed on the type of biomedical research, the study’s applicability, the thematic area and specific thematic, journal impact factor and quartile, funding, grants, and institution of affiliation for the first and correspondence authors. Results: The systematic review resulted in nine studies that met the requirements. The results revealed that Peru needs to promote policies to boost research funding and the number of researchers to produce information that will be useful for managing diseases in the future. Yet, despite the funding provided by national organizations like National Council for Science, Technology, and Technological Innovation (CONCYTEC), there were few publications and little international collaboration. The studies that have been published focus mostly on applied research in the areas of diagnostics, sanitary products, and treatment and transmission, and they have great visibility because they are indexed in Q1 journals. Conclusions: This thorough study revealed Peru’s inadequate reaction to COVID-19 regarding experimental scientific research. Peruvian authorities should think about supporting the required policies to boost the number of researchers and financial aid to produce information that may be utilized to manage potential new diseases in the future. Inplasy registration: INPLASY202340080 (23/04/2023).

Background As wine has become more than just a drink, exploring wine consumer studies provides a better understanding of various factors that shape the wine industry. Therefore, this paper aims to review and map the landscape of wine consumer literature using bibliometric analysis and systematic review. It identifies the key areas, clusters, antecedents, mediators, moderators, and outcomes to propose the framework for future research directions. Methods This study adopts an integrative review approach: a bibliometric and systematic review. The data for this study were retrieved from the Scopus database. While the bibliometric analyses are conducted using VoSviewer software, a systematic review is conducted using a content analysis approach. Results Four main topics in the extant wine consumer literature are identified: sustainability and wine, wine preferences and choice, wine consumer behavior, and wine consumer insights. The five critical areas of wine consumers’ literature recognized are decision-making, consumer preferences, consumer behavior, segmentation, and consumer involvement. This study also recognizes theoretical and methodological advancements in the wine consumer literature. Conclusions The findings contribute to advancing knowledge development, identifying research gaps and shedding light on future research in the wine consumer domain. The results offer practical insight for wine industry stakeholders, researchers, and influencers.

Purpose: The primary objective of this research paper was to explore the current state-of-the-art research on autism spectrum disorder from a designer's perspective. An increasing number of scholarly publications in this discipline have urged researcher interest in this topic; however, there is still a lack of quantitative analysis. Therefore, this paper aims to analyze global research output on autism spectrum disorder from a designer's perspective during 1992–2021. Methodology: A bibliometric method was employed to analyze the published literature from 1992–2021. 812 papers were downloaded from the Web of Science core collection for analysis focused on annual growth of literature, prolific authors, authorship pattern, productive organizations, countries, international collaboration, literature trends by keyword analysis, and identifying the funding agencies. Various bibliometrics and scientometrics software were used to analyze the data, namely Bibexcel, Biblioshiny, and VOS viewer. Results: There were 812 research papers published in 405 sources during 1992–2021. 2019 was noted as the most productive year (NP=101), and 2014 received the highest number of citations (TC=6634). Researchers preferred to publish as journal articles (NP=538; TC=24922). The University of Toronto, Canada, was identified as a productive institution with 42 publications and 5358 citations. The USA was the leading producing country with 433 publications, and most of the researchers publish their work in the journal 'Scientific Reports' (NP=16). The word 'autism' (NP=257) and 'architecture' (NP=165) were the most frequently used keywords in autism research.

Background: Sporotrichosis has recently emerged as an important mycosis worldwide, with diverse transmission and epidemiologic profiles. For instance, in Brazil most cases are related to zoonotic transmission from naturally infected cats, and the majority of cases in China are due to external injury with environmental materials. Publications on sporotrichosis and on its etiologic agent may guide the direction of the research in this field. It can also define priorities for future studies. Methods: In this study, we evaluated the trends of global research in Sporothrix and sporotrichosis, based on publications records retrieved from Scopus and Web of Science databases for the period of 1945 to 2018. The overall productivity in the field, its geographical and temporal distribution, research themes, co-authorship networks, funding sources, and if audience and research findings are addressed in the abstracts. Results: A total of 4,007 unique publications involving 99 countries were retrieved, most of them published after 2000. Authors based on institutions from the United States of America and Brazil accounted for 57.4% of the publications. Brazil was the leading country in terms of research collaboration and networking, with co-authorship with 45 countries. The thematic mapping revealed a temporal shift from clinical to applied research. Despite the large number of countries publishing in this field, most of funded studies came from Brazil, Mexico, China, South Africa, or the United States of America. The analysis of content identified few specific public health recommendations for prevention, case-management, or research. Moreover, most papers do not have a clearly defined intended audience. Conclusion: As the research in this field is emerging in several countries, with the generation of a large amount of data, it is necessary that scientists strengthen efforts to translate the research results into practice to curb this neglected infection.

This paper describes a unique two-step methodology used to construct six linked bibliometric datasets covering the sequencing of Saccharomyces cerevisiae, Homo sapiens, and S us scrofa genomes. First, we retrieved all sequence submission data from the European Nucleotide Archive (ENA), including accession numbers associated with each species. Second, we used these accession numbers to construct queries to retrieve peer-reviewed scientific publications that first linked to these sequence lengths in the scientific literature. For each species, this resulted in two associated datasets: 1) A .csv file documenting the PMID of each article describing new sequences, all paper authors, all institutional affiliations of each author, countries of institution, year of first submission to the ENA, and the year of article publication, and 2) A .csv file documenting all institutions submitting to the ENA, number of nucleotides sequenced, number of submissions per institution in a given year, and years of submission to the database. In several upcoming publications, we utilise these datasets to understand how institutional collaboration shaped sequencing efforts, and to systematically identify important institutions and changes in network structures over time. This paper, therefore, should aid researchers who would like to use these data for future analyses by making the methodology that underpins it transparent. Further, by detailing our methodology, researchers may be able to utilise our approach to construct similar datasets in the future.

This paper describes a unique two-step methodology used to construct six linked bibliometric datasets covering the sequencing of Saccharomyces cerevisiae, Homo sapiens, and S us scrofa genomes. First, we retrieved all sequence submission data from the European Nucleotide Archive (ENA), including accession numbers associated with each species. Second, we used these accession numbers to construct queries to retrieve peer-reviewed scientific publications that first linked to these sequence lengths in the scientific literature. For each species, this resulted in two associated datasets: 1) A .csv file documenting the PMID of each article describing new sequences, all paper authors, all institutional affiliations of each author, countries of institution, year of first submission to the ENA, and the year of article publication, and 2) A .csv file documenting all institutions submitting to the ENA, number of nucleotides sequenced, number of submissions per institution in a given year, and years of submission to the database. In several upcoming publications, we utilise these datasets to understand how institutional collaboration shaped sequencing efforts, and to systematically identify important institutions and changes in network structures over time. This paper, therefore, should aid researchers who would like to use these data for future analyses by making the methodology that underpins it transparent. Further, by detailing our methodology, researchers may be able to utilise our approach to construct similar datasets in the future.

Background: There is an increasing need to understand the wider impacts of research on society and the economy. For health research, a key focus is understanding the impact of research on practice and ultimately on patient outcomes. This can be challenging to measure, but one useful proxy for changes in practice is impact on guidelines. Methods: The aim of this study is to map the contribution of UK research and UK research funders to the National Institute for Health and Clinical Excellence (NICE) public health guidelines, understanding areas of strengths and weakness and the level of collaboration and coordination across countries and between funders. The work consisted of two main elements: analysis of the references cited on NICE guidelines and interviews with experts in public health. Results: Across the papers cited on 62 NICE public health guidelines, we find that 28% of the papers matched include at least one UK affiliation, which is relatively high when compared to other health fields. In total, 165 unique funders were identified with more than three acknowledgements, based in 20 countries. 68% of papers which acknowledge funding cite at least one UK funder, and NIHR is the most highly cited funder in the sample. Conclusions: The UK makes an important contribution to public health research cited on NICE PH guidelines, although the research does not appear to be bibliometrically distinct from other research sectors, other than having a relatively low level of international collaboration. However, the extent to which NICE public health guidelines reflect practice at the local authority level is less clear. More research is needed to understand the sources of evidence to support public health decision making at the local level and how NICE guidance can be made more applicable, timely and accessible in this new context.

This data note describes a unique two-step methodology to construct six linked datasets covering the sequencing of Saccharomyces cerevisiae, Homo sapiens, and Sus scrofa genomes. The datasets were used as evidence in a project that investigated the history of genomic science. To design the datasets, we first retrieved all sequence submission data from the European Nucleotide Archive (ENA), including accession numbers associated with each of our three species. Second, we used these accession numbers to construct queries to retrieve peer-reviewed scientific publications that first described these sequence submissions in the scientific literature. For each species, this resulted in two associated datasets: 1) A .csv file documenting the PMID of each article describing new sequences, all paper authors, all institutional affiliations of each author, countries of institution, year of first submission to the ENA (when available), and the year of article publication, and 2) A .csv file documenting all institutions submitting to the ENA, number of nucleotides sequenced and years of submission to the database. We utilised these datasets to understand how institutional collaboration shaped sequencing efforts, and to systematically identify important institutions and changes in the structure of research communities throughout the history of genomics and across our three target species. This data note, therefore, should aid researchers who would like to use these data for future analyses by making the methodology that underpins it transparent. Further, by detailing our methodology, researchers may be able to utilise our approach to construct similar datasets in the future.

Background Citations of papers are positively influenced by the journal’s impact factor (IF). For non-open access (non-OA) journals, this influence may be due to the fact that high-IF journals are more often purchased by libraries, and are therefore more often available to researchers, than low-IF journals. This positive influence has not, however, been shown specifically for papers published in open access (OA) journals, which are universally accessible, and do not need library purchase. It is therefore important to ascertain if the IF influences citations in OA journals too. Methods 203 randomized controlled trials (102 OA and 101 non-OA) published in January 2011 were included in the study. Five-year citations for papers published in OA journals were compared to those for non-OA journals. Source papers were derived from PubMed. Citations were retrieved from Web of Science, Scopus, and Google Scholar databases. The Thompson-Reuter’s IF was used. Results OA journals were found to have significantly more citations overall compared to non-OA journals (median 15.5 vs 12, p=0.039). The IF did not correlate with citations for OA journals (Spearman’s rho =0.187, p=0.60). The increase in the citations with increasing IF was minimal for OA journals (beta coefficient = 3.346, 95% CI -0.464, 7.156, p=0.084). In contrast, the IF did show moderate correlation with citations for articles published in non-OA journals (Spearman’s rho=0.514, p Conclusion It is better to publish in an OA journal for more citations. It may not be worth paying high publishing fees for higher IF journals, because there is minimal gain in terms of increased number of citations. On the other hand, if one wishes to publish in a non-OA journal, it is better to choose one with a high IF.

Software is as integral as a research paper, monograph, or dataset in terms of facilitating the full understanding and dissemination of research. This article provides broadly applicable guidance on software citation for the communities and institutions publishing academic journals and conference proceedings. We expect those communities and institutions to produce versions of this document with software examples and citation styles that are appropriate for their intended audience. This article (and those community-specific versions) are aimed at authors citing software, including software developed by the authors or by others. We also include brief instructions on how software can be made citable, directing readers to more comprehensive guidance published elsewhere. The guidance presented in this article helps to support proper attribution and credit, reproducibility, collaboration and reuse, and encourages building on the work of others to further research.

Software is as integral as a research paper, monograph, or dataset in terms of facilitating the full understanding and dissemination of research. This article provides broadly applicable guidance on software citation for the communities and institutions publishing academic journals and conference proceedings. We expect those communities and institutions to produce versions of this document with software examples and citation styles that are appropriate for their intended audience. This article (and those community-specific versions) are aimed at authors citing software, including software developed by the authors or by others. We also include brief instructions on how software can be made citable, directing readers to more comprehensive guidance published elsewhere. The guidance presented in this article helps to support proper attribution and credit, reproducibility, collaboration and reuse, and encourages building on the work of others to further research.

Background: Sporotrichosis has recently emerged as an important mycosis worldwide, with diverse transmission and epidemiologic profiles. For instance, in Brazil most cases are related to zoonotic transmission from naturally infected cats, and the majority of cases in China are due to external injury with environmental materials. Publications on sporotrichosis and on its etiologic agent may guide the direction of the research in this field. It can also define priorities for future studies. Methods: In this study, we evaluated the trends of global research in Sporothrix and sporotrichosis, based on publications records retrieved from Scopus and Web of Science databases for the period of 1945 to 2018. The overall productivity in the field, its geographical and temporal distribution, research themes, co-authorship networks, funding sources, and the implications of research findings for health practice were assessed using bibliometric approaches. Results: A total of 4,007 unique publications involving 99 countries were retrieved, most of them published after 2000. Authors based on institutions from the United States of America and Brazil accounted for 57.4% of the publications. Brazil was the leading country in terms of research collaboration and networking, with co-authorship with 45 countries. The thematic mapping revealed a temporal shift from clinical to applied research. Despite the large number of countries publishing in this field, most of funded studies came from Brazil, Mexico, China, South Africa, or the United States of America. The analysis of content identified few specific public health recommendations for prevention, case-management, or research. Moreover, most papers do not have a clearly defined intended audience. Conclusion: As the research in this field is emerging in several countries, with the generation of a large amount of data, it is necessary that scientists strengthen efforts to translate the research results into practice to curb this neglected infection.

Background: Over the past few decades, there has been an increase in the number of open access (OA) journals in almost all disciplines. This increase in OA journals was accompanied an increase in funding to support such movements. Medical fields are among the highest funded fields, which further promoted its journals to move toward OA publishing. Here, we aim to compare OA and non-OA journals in terms of citation metrics and other indices. Methods: We collected data on the included journals from Scopus Source List on 1 st November 2018. We filtered the list for medical journals only. For each journal, we extracted data regarding citation metrics, scholarly output, and wither the journal is OA or non-OA. Results: On the 2017 Scopus list of journals, there was 5835 medical journals. Upon analyzing the difference between medical OA and non-OA journals, we found that OA journals had a significantly higher CiteScore (p< 0.001), percent cited (p< 0.001), and source normalized impact per paper (SNIP) (p< 0.001), whereas non-OA journals had higher scholarly output (p< 0.001). Among the five largest journal publishers, Springer Nature published the highest frequency of OA articles (31.5%), while Wiley-Blackwell had the lowest frequency among its medical journals (4.4%). Conclusion: Among medical journals, although non-OA journals still have higher output in terms of articles per year, OA journals have higher citation metrics.

Background: Machine learning researches algorithms that allow a machine to learn about resolving problems in different application domains. Due to the wide number of machine learning applications, it is necessary for newcomers to the field to have alternatives to explore this field faster. Methods: In this paper, we present a science mapping analysis on the machine learning research in the period 2007-2017. This study was develop using the CiteSpace tool based on results from Clarivate Web of Science. This analysis shows how the field has evolved, by highlighting the most notable authors, institutions, keywords, countries, categories, and journals. Results: The results provide information on trends and possibilities in the near future, particularly in areas such as health, biology and banking, where machine learning is a valuable tool to generate solutions. Conclusions: Machine learning is being widely studied, and several institutions in countries like the USA and China constantly generate machine learning based solutions. Diseases, such as cancer or Alzheimer’s disease, studies in biology, such as the protein molecule, virtual reality, commerce, smartphones, and ubiquitous computing, are all fields where machine learning contributes to resolving problems.

Background: Reports have suggested that academic medicine may be in decline within the UK. Further evidence suggests that rates of subsequent full publication of abstracts presented at major scientific meetings are low and may be declining. We have compared the publication rates of abstracts presented at meetings of the British Society of Gastroenterology (BSG) between 1995 and 2005 and examined factors associated with full paper publication. Methods: Abstracts presented at BSG meetings in 1995 and 2005 were assessed by cross-referencing with multiple databases. Abstract characteristics associated with publication were analysed. Results: There were no differences in overall publication rates, impact factors or time to publication between 1995 and 2005. Overall, basic-science abstracts were twice as likely to achieve full publication than non-basic science. There was a significant fall in the publication rates for case series and audits, and significantly increased rates for fundamental/basic-science abstracts over the study period. There were non-significant increases in publication rates for controlled trials and systematic reviews. In general, publication rates for all predominantly clinically orientated abstracts reduced between the two periods with the most notable fall occurring in nutrition. Conclusions: There was no evidence of a decline in overall abstract publication rates between 1995 and 2005. There seemed to be trend for increased publication rates of abstracts using perceived high-quality study methodologies with a corresponding decrease in those with lower quality methods. The proportion of basic-science abstracts is likely to be a determinant of overall full publication rates following scientific meetings.

Background: The EMPIRE (EMpirical Publication Impact and Reach Evaluation) Index is a value-based, multi-component metric framework to assess the impact of medical publications in terms of relevance to different stakeholders. It comprises three component scores (social, scholarly and societal impact), each incorporating related altmetrics that indicate a different aspect of engagement with the publication. Here, we present an exploratory investigation of whether publication types or disease indications influence EMPIRE Index scores. Methods: Article-level metrics were extracted and EMPIRE Index scores were calculated for 5825 journal articles published from 1 May 2017 to 1 May 2018, representing 12 disease indications (chosen to reflect a wide variety of common and rare diseases with a variety of aetiologies) and five publication types. Results: There were significant differences in scores between article types and disease indications. Median (95% CI) social and scholarly impact scores ranged from 1.2 (0.3–1.6) to 4.8 (3.1–6.6), respectively, for phase 3 clinical trials, and from 0.3 (0.3–0.4) to 2.3 (1.9–2.6), respectively, for observational studies. Social and scholarly impact scores were highest for multiple sclerosis publications and lowest for non-small cell lung cancer publications. Systematic reviews achieved greater impact than regular reviews. Median trends in the social impact of different disease areas matched the level of public interest as assessed through Google search interest. Although most articles did not register societal impact, mean societal impact scores were highest for migraine publications. Conclusions : The EMPIRE Index successfully identified differences in impact by disease area and publication type, which supports the notion that the impact of each publication needs to be evaluated in the context of these factors, and potentially others. These findings should be considered when using the EMPIRE Index to assess publication impact.

Background: The EMPIRE (EMpirical Publication Impact and Reach Evaluation) Index is a value-based, multi-component metric framework to assess the impact of medical publications in terms of relevance to different stakeholders. It comprises three component scores (social, scholarly and societal impact), each incorporating related altmetrics that indicate a different aspect of engagement with the publication. Here, we present an exploratory investigation of whether publication types or disease indications influence EMPIRE Index scores. Methods: Article-level metrics were extracted and EMPIRE Index scores were calculated for 5825 journal articles published from 1 May 2017 to 1 May 2018, representing 12 disease indications (chosen to reflect a wide variety of common and rare diseases with a variety of aetiologies) and five publication types. Results: There were significant differences in scores between article types and disease indications. Median (95% CI) social and scholarly impact scores ranged from 1.2 (0.3–1.6) to 4.8 (3.1–6.6), respectively, for phase 3 clinical trials, and from 0.3 (0.3–0.4) to 2.3 (1.9–2.6), respectively, for observational studies. Social and scholarly impact scores were highest for multiple sclerosis publications and lowest for non-small cell lung cancer publications. Systematic reviews achieved greater impact than regular reviews. Median trends in the social impact of different disease areas matched the level of public interest as assessed through Google search interest. Although most articles did not register societal impact, mean societal impact scores were highest for migraine publications. Conclusions : The EMPIRE Index successfully identified differences in impact by disease area and publication type, which supports the notion that the impact of each publication needs to be evaluated in the context of these factors, and potentially others. These findings should be considered when using the EMPIRE Index to assess publication impact.

Background: The EMPIRE (EMpirical Publication Impact and Reach Evaluation) Index is a value-based, multi-component metric framework to assess the impact of medical publications in terms of relevance to different stakeholders. It comprises three component scores (social, scholarly and societal impact), each incorporating related altmetrics that indicate a different aspect of engagement with the publication. Here, we present an exploratory investigation of whether publication types or disease indications influence EMPIRE Index scores. Methods: Article-level metrics were extracted and EMPIRE Index scores were calculated for 5825 journal articles published from 1 May 2017 to 1 May 2018, representing 12 disease indications (chosen to reflect a wide variety of common and rare diseases with a variety of aetiologies) and five publication types. Results: There were significant differences in scores between article types and disease indications. Median (95% CI) social and scholarly impact scores ranged from 1.2 (0.3–1.6) to 4.8 (3.1–6.6), respectively, for phase 3 clinical trials, and from 0.3 (0.3–0.4) to 2.3 (1.9–2.6), respectively, for observational studies. Social and scholarly impact scores were highest for multiple sclerosis publications and lowest for non-small cell lung cancer publications. Systematic reviews achieved greater impact than regular reviews. Median trends in the social impact of different disease areas matched the level of public interest as assessed through Google search interest. Although most articles did not register societal impact, mean societal impact scores were highest for migraine publications. Conclusions : The EMPIRE Index successfully identified differences in impact by disease area and publication type, which supports the notion that the impact of each publication needs to be evaluated in the context of these factors, and potentially others. These findings should be considered when using the EMPIRE Index to assess publication impact.

Background: Data sharing is now a mandatory prerequisite for several major funders and journals, where researchers are obligated to deposit the data resulting from their studies in an openly accessible repository. Biomedical open data are now widely available in almost all disciplines, where researchers can freely access and reuse these data in new studies. We aim to study the BioLINCC datasets, number of publications that used BioLINCC open access data, and the citations received by these publications. Methods: As of July 2019, there was a total of 194 datasets stored in BioLINCC repository and accessible through their portal. We requested the full list of publications that used these datasets from BioLINCC, and we also performed a supplementary PubMed search for other publications. We used Web of Science (WoS) to analyze the characteristics of publications and the citations they received, where WoS database index high quality articles. Results: 1,086 published articles used data from BioLINCC repository for 79 (40.72%) datasets, where 115 (59.28%) datasets did not have any publications associated with it. Of the total publications, 987 (90.88%) articles were WoS indexed. The number of publications has steadily increased since 2002 and peaked in 2018 with a total number of 138 publications on that year. The 987 open data publications (i.e., secondary publications) received a total of 34,181 citations up to 1 st October 2019. The average citation per item for the open data publications was 34.63. The total number of citations received by open data publications per year has increased from only 2 citations in 2002, peaking in 2018 with 2361 citations. Conclusion: Majority of BioLINCC datasets were not used in secondary publications. Despite that, the datasets used for secondary publications yielded publications in WoS indexed journals and are receiving an increasing number of citations.

Background: Data sharing is now a mandatory prerequisite for several major funders and journals, where researchers are obligated to deposit the data resulting from their studies in an openly accessible repository. Biomedical open data are now widely available in almost all disciplines, where researchers can freely access and reuse these data in new studies. We aim to study the BioLINCC datasets, number of publications that used BioLINCC open access data, and the impact of these publications through the citations they received. Methods: As of July 2019, there was a total of 194 datasets stored in BioLINCC repository and accessible through their portal. We requested the full list of publications that used these datasets from BioLINCC, and we also performed a supplementary PubMed search for other publications. We used Web of Science (WoS) to analyze the characteristics of publications and the citations they received, where WoS database index high quality articles. Results: 1,086 published articles used data from BioLINCC repository for 79 (40.72%) datasets, where 115 (59.28%) datasets didn’t have any publications associated with it. Of the total publications, 987 (90.88%) articles were WoS indexed. The number of publications has steadily increased since 2002 and peaked in 2018 with a total number of 138 publications on that year. The 987 open data publications received a total of 34,181 citations up to 1 st October 2019. The average citation per item for the open data publications was 34.63. The total number of citations received by open data publications per year has increased from only 2 citations in 2002, peaking in 2018 with 2361 citations. Conclusion: Majority of BioLINCC datasets were not used in secondary publications. Despite that, the datasets used for secondary publications yielded publications in WoS indexed journals and are receiving an increasing number of citations.

Cohort studies collect, generate and distribute data over long periods of time – often over the lifecourse of their participants. It is common for these studies to host a list of publications (which can number many thousands) on their website to demonstrate the impact of the study and facilitate the search of existing research to which the study data has contributed. The ability to search and explore these publication lists varies greatly between studies. We believe a lack of rich search and exploration functionality of study publications is a barrier to entry for new or prospective users of a study’s data, since it may be difficult to find and evaluate previous work in a given area. These lists of publications are also typically manually curated, resulting in a lack of rich metadata to analyse, making bibliometric analysis difficult. We present here a software pipeline that aggregates metadata from a variety of third-party providers to power a web based search and exploration tool for lists of publications. Alongside core publication metadata (i.e. author lists, keywords etc.), we include geocoding of first authors and citation counts in our pipeline. This allows a characterisation of a study as a whole based on common locations of authors, frequency of keywords, citation profile etc. This enriched publications metadata can be useful for generating study impact metrics and web-based graphics for public dissemination. In addition, the pipeline produces a research data set for bibliometric analysis or social studies of science. We use a previously published list of publications from a cohort study as an exemplar input data set to show the output and utility of the pipeline here.

Background: Data sharing is now a mandatory prerequisite for several major funders and journals, where researchers are obligated to deposit the data resulting from their studies in an openly accessible repository. Biomedical open data are now widely available in almost all disciplines, where researchers can freely access and reuse these data in new studies. We aim to study the BioLINCC datasets, number of publications that used BioLINCC open access data, and the impact of these publications through the citations they received. Methods: As of July 2019, there was a total of 194 datasets stored in BioLINCC repository and accessible through their portal. We requested the full list of publications that used these datasets from BioLINCC, and we also performed a supplementary PubMed search for other publications. We used Web of Science (WoS) to analyze the characteristics of publications and the citations they received. Results: 1,086 published articles used data from BioLINCC repository for 79 (40.72%) datasets, where 115 (59.28%) datasets didn’t have any publications associated with it. Of the total publications, 987 (90.88%) articles were WoS indexed. The number of publications has steadily increased since 2002 and peaked in 2018 with a total number of 138 publications on that year. The 987 open data publications received a total of 34,181 citations up to 1 st October 2019. The average citation per item for the open data publications was 34.63. The total number of citations received by open data publications per year has increased from only 2 citations in 2002, peaking in 2018 with 2361 citations. Conclusion: Majority of BioLINCC datasets were not used in secondary publications. Despite that, the datasets used for secondary publications yielded publications in WoS indexed journals and are receiving an increasing number of citations.

Cohort studies collect, generate and distribute data over long periods of time – often over the lifecourse of their participants. It is common for these studies to host a list of publications (which can number many thousands) on their website to demonstrate the impact of the study and facilitate the search of existing research to which the study data has contributed. The ability to search and explore these publication lists varies greatly between studies. We believe a lack of rich search and exploration functionality is a barrier to entry for new or prospective users of a study’s data, since it may be difficult to find and evaluate previous work in a given area. These lists of publications are also typically manually curated, resulting in a lack of rich metadata to analyse, making bibliometric analysis difficult. We present here a software pipeline that aggregates metadata from a variety of third-party providers to power a web based search and exploration tool for lists of publications. Alongside core publication metadata (i.e. author lists, keywords etc.), we include geocoding of first authors and citations in our pipeline. This allows a characterisation of a study as a whole based on common locations of authors, frequency of keywords, citation profile etc. This enriched publications metadata can be useful for generating project impact metrics and web-based graphics useful for public dissemination. In addition, the pipeline produces a research data set for bibliometric analysis or social studies of science.

Background: Data sharing is now a mandatory prerequisite for several major funders and journals, where researchers are obligated to deposit the data resulting from their studies in an openly accessible repository. Biomedical open data are now widely available in almost all disciplines, where researchers can freely access and reuse these data in new studies. We aim to assess the impact of open data in terms of publications generated using open data and citations received by these publications, where we will analyze publications that used the Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) as an example. Methods: As of July 2019, there was a total of 194 datasets stored in BioLINCC repository and accessable through their portal. We requested the full list of publications that used these datasets from BioLINCC, and we also performed a supplementary PubMed search for other publications. We used Web of Science (WoS) to analyze the characteristics of publications and the citations they received. Results: 1,086 published articles used data from BioLINCC repository, but only 987 (90.88%) articles were WoS indexed. The number of publications has steadily increased since 2002 and peaked in 2018 with a total number of 138 publications on that year. The 987 open data publications received a total of 34,181 citations up to 1 st October 2019. The average citation per item for the open data publications was 34.63. The total number of citations received by open data publications per year has increased from only 2 citations in 2002, peaking in 2018 with 2361 citations. Conclusion: The vast majority of studies that used BioLINCC open data were published in WoS indexed journals and are receiving an increasing number of citations.

Background: Scientific writing guidelines recommend that a scientific text should be straightforward, without prolixity, and informative, without obscurity. However, the extent to which researchers follow these recommendations is unknown. Considering that the most cited journals provide more detailed instructions for authors, we aimed to investigate the degree of relative prolixity (i.e., length versus amount of information) among journals with different citation impact scores. Methods: We analyzed journals whose articles follow the classic Introduction, Method, Results, and Discussion structure, written in English and with a CiteScore value ≥ 0.01 classified in the ‘Pharmaceutical Science’ area. Relative prolixity was calculated as the ratio between the number of characters and the number of citations contained in the introductory section of original articles. Additionally, we collected the number of paragraphs and words. Results: The number of characters, words and citations in the Introduction section were significantly higher in the journals with higher CiteScore values. The median number of paragraphs in the Introduction was not affected by the citation impact of the journals. The degree of relative prolixity in the Introduction section of the articles was negatively correlated with the CiteScore values. Conclusions: Articles published in journals with higher CiteScore values have lower degrees of relative prolixity (i.e., shorter texts to transmit a certain amount of information) and obscurity.

Background: Machine learning is becoming increasingly important for companies and the scientific community. In this study, we perform a bibliometric analysis on machine learning research, in order to provide an overview of the scientific work during the period 2007-2017 in this area and to show trends that could be the basis for future developments in the field. Methods: This study is carried out using the SciMAT tool based on results extracted from Scopus. This analysis shows the strategic diagrams of evolution and a set of thematic networks. The results provide information on broad tendencies of machine learning. Results: The results show that SciMAT is a useful tool to carry out a science mapping analysis, and emphasizes the premise that machine learning has boundless applications and will continue to be an interesting research field in the future. Conclusions: Some of the conclusions exposed in this study show that classification algorithms have been widely studied and represent a relevant tool for generating different machine learning applications. Nonetheless, regression algorithms are becoming increasingly important in the scientific community, allowing the generation of solutions to predict diseases, sales, and yields, for example.

Data from open access biomolecular data resources, such as the European Nucleotide Archive and the Protein Data Bank are extensively reused within life science research for comparative studies, method development and to derive new scientific insights. Indicators that estimate the extent and utility of such secondary use of research data need to reflect this complex and highly variable data usage. By linking open access scientific literature, via Europe PubMedCentral, to the metadata in biological data resources we separate data citations associated with a deposition statement from citations that capture the subsequent, long-term, reuse of data in academia and industry. We extend this analysis to begin to investigate citations of biomolecular resources in patent documents. We find citations in more than 8,000 patents from 2014, demonstrating substantial use and an important role for data resources in defining biological concepts in granted patents to both academic and industrial innovators. Combined together our results indicate that the citation patterns in biomedical literature and patents vary, not only due to citation practice but also according to the data resource cited. The results guard against the use of simple metrics such as citation counts and show that indicators of data use must not only take into account citations within the biomedical literature but also include reuse of data in industry and other parts of society by including patents and other scientific and technical documents such as guidelines, reports and grant applications.

Studying publication volumes at the country level is key to understanding and improving a country’s research system. PubMed is a public search engine of publications in all life sciences areas. Here, we show how this search engine can be used to assess the outputs of life science-related research by country. We have measured the numbers of publications during different time periods based on the country of affiliation of the first authors. Moreover, we have designed scores, which we have named Attraction Scores, to appraise the relative focus either toward particular types of studies, such as clinical trials or reviews, or toward specific research areas, such as public health and pharmacogenomics, or toward specific topics, for instance embryonic stem cells; we have also investigated a possible use of these Attraction Scores in connection with regulatory policies. We have weighed the statistics against general indicators such as country populations and gross domestic products (GDP). During the 5-year period 2008-2012, the United States was the country with the highest number of publications and Denmark the one with the highest number of publications per capita. Among the 40 countries with the highest GDPs, Israel had the highest publications-to-GDP ratio. Among the 20 countries with the most publications, Japan had the highest Attraction Score for induced pluripotent stem (iPS) cells and Italy the highest proportion of review publications. More than 50% of publications in English were from countries in which English is not the primary language. We show an assorted and extensive collection of rankings and charts that will inform scholars and policymakers in studying and improving the research systems both at the national and international level.