Find research datasets worth reusing

opencc-by-4.0Jun 2021View details →

Tortured phrases: A dubious writing style emerging in science. Evidence of critical issues affecting established journals.

Supplementary materials to preprint <a href="https://arxiv.org/abs/2107.06751">https://arxiv.org/abs/2107.06751</a>.

opencc-by-4.0Jul 2021View details →

Austrian Science Fund (FWF) Open Access Compliance Monitoring 2020

I. Executive summary The Austrian Science Fund (FWF), which is Austria's main funding organisation for basic research, encourages and helps all project leaders and project staff members to make their peer-reviewed research results freely available on the Internet. Any exceptions must be clearly indicated and justified. For projects that started after 1 January 2015, open access has been compulsory for all peer-reviewed publications. All principal investigators in FWF-funded projects are obliged to submit a final report within four months of completing their projects. In 2020, a total of 483 final reports were submitted to the FWF, 32 of which could not report any publications so far. The publications and other data mentioned in those reports are archived and analysed by the FWF. This report examines the state of compliance with open access requirements for peer-reviewed publications on the basis of final project reports submitted in the year 2020. 2020 shows a significant decline in the number of publications compared to 2019. This decline can be explained by the fact that 15% fewer final project reports were received as a result of weaker funding years in the mid-2010s as well as an increased shift of final report submissions from 2020 to later points in time (‘corona effect’). Especially in the programmes with the highest number of publications (Doctoral Programmes, Special Research Programmes) as well as in programmes with many projects (Stand-Alone Projects, International Projects), there were fewer final project reports submitted, which has a massive impact on the total number of publications. It must be taken into account that the method (recording the number of publications via final project reports) is a look into the past, as the final project reports show publications that were produced in previous years during the project term. The publication activity in relation to the year of publication itself is relatively constant according to databases such as Dimensions. Due to the automation of the monitoring processes and the introduction of Plan S of cOAlition S, the category of ‘Other open access’ (self-archiving in a non-maintained repository, homepage, or archiving of preprints), which was previously determined manually, is no longer taken into account, and thus the open access share of peer-reviewed publications has decreased compared to previous years. Main findings: -A total of 6,196 publications were listed in the final project reports submitted in 2020. -Of those publications, 4,809 were conclusively identified as peer-reviewed. -Regarding compliance with the FWF's Open Access Policy, the analysis shows that 84% of the peer-reviewed publications listed in the final project reports submitted in 2020 were openly accessible (2015: 83%, 2016: 92%, 2017: 90%, 2018: 92%, 2019: 89%). -The most frequently chosen option was hybrid open access (40%). The share of old open access was 21%, the share of green open access 23%, and no open access 16%. -The majority of peer-reviewed publications submitted were journal articles (89%), 88% of which were openly accessible. -The lowest rate of compliance with the FWF's Open Access Policy could be found in editions, contributions to edited volumes, and monographs (38%). -The absolute number of publications listed in final reports in 2020 included 362 publications that were mentioned several times in different projects; however, those repetitions did not ultimately affect the relative share of open access publications (83%). II. Bias Most of the publications were submitted to the FWF via a research documentation system (provided by ©Researchfish), in which FWF-funded researchers are able to enter and update their research data on an ongoing basis. The last check of the open access status was performed in March 2020. In some cases, the embargo period may have already expired, and publications labelled ‘no open access’ in the FWF’s database may now be accessible through green open access. Whenever the status ‘peer-reviewed’ could not be clearly identified according to the FWF’s guidelines, the publications were classified as non-peer reviewed. Openly available non-peer reviewed publications were entered as 'openly available’.

opencc-by-4.0May 2021View details →

Data and Code for the manuscript PhD students in life sciences can benefit from team cohesion

This folder contains data and code to reproduce regression results of the manuscript "PhD students in life sciences can benefit from team cohesion".

opencc-by-4.0Jul 2021View details →

Survey on how do Brazilian Software Engineering Researchers Perceive and Practice Open Science

This document provides our survey questionnaire and the responses of 31 researchers.

dryad36/100

Data from: Assessing the usefulness of Citizen Science Data for habitat suitability modelling: opportunistic reporting versus sampling based on a systematic protocol

Aim: To evaluate the potential of models based on opportunistic reporting (OR) compared to models based on data from a systematic protocol (SP) for modelling species distributions. We compared model performance for eight forest bird species with contrasting spatial distributions, habitat requirements, and rarity. Differences in the reporting of species were also assessed. Finally, we tested potential improvement of models when inferring high quality absences from OR based on questionnaires sent to observers. Location: Both datasets cover the same large area (Sweden) and time period (2000 -2013). Methods: Species distributions were modelled using logistic regression. Predictive performance of OR models to predict SP data were assessed based on AUC. We quantified the congruence in spatial predictions using Spearman's rank correlation coefficient. We related these results to species characteristics and reporting behaviour of observers. We also assessed the gain in predictive performance of OR models by adding inferred absences. Finally, we investigated the potential impact of sampling bias in OR. Results: For all species, and despite the sampling biases, results from OR overall agreed well with those of SP, for the nationwide spatial congruence of habitat suitability maps and the selection and directions of species-environment relationships. The OR models also performed well in predicting the SP data. The predictive performance of the OR models increased with species rarity and even outperformed the SP model for the rarest species. No significant impact of observer behaviour was found. Main Conclusions: Relatively simple analyses with inferred absences could produce reliable spatial predictions of habitat suitability. This was especially true for rare species. OR data should be seen as a complement to SP, as the weakness of one is the strength of the other, and OR may be especially useful at large spatial scales or where no systematic data collection protocols exist.

opencc-zeroJul 2021View details →

opencc-by-4.0Jul 2021View details →

Open Science for Action (OS4A): A working model for libraries

A diagram outlining a conceptual model for how libraries can contribute to and advance open science in principle and practice.

opencc-by-4.0Aug 2021View details →

Supporting Information 1 to the paper "Human-machine-learning integration and task allocation in citizen science".

This appendix - Supporting Information 1 - is a dataset excel file directly related to the following paper: Ponti, M., Seredko, A. <a href="http://doi.org/10.1057/s41599-022-01049-z">Human-machine-learning integration and task allocation in citizen science.</a> Humanit Soc Sci Commun 9, 48 (2022). https://doi.org/10.1057/s41599-022-01049-z The dataset in this excel file is a detailed result of the integrative literature review conducted for the manuscript.

Eurodoc Survey on Publishing in Open Science 2020

The Eurodoc Survey on Publishing in Open Science 2020 was a survey launched to collect data and the state-of-art about Open Science and publishing platform, realised by Eurodoc within the 'Open Research Europe' (ORE) project. ORE is an open access Publishing Platform for Horizon 2020 beneficiaries offering rapid publication of a wide range of article types without editorial bias. All articles benefit from transparent peer review and will be published under an open license. ORE is a significant step towards Open Science in Europe. Eurodoc, as an expert partner in the project, will ensure that the voice of early-career researchers is heard. This survey aims to provide the ORE project team with insights related to awareness, perception and experience with open practices and tools, from the perspective of doctoral candidates and junior researchers. Survey results and the underlying data are published in F1000: https://f1000research.com/articles/10-1306/v1.   About Eurodoc <a href="http://www.eurodoc.net/">Eurodoc</a>, the European Council of <a href="http://www.eurodoc.net/sites/default/files/attachments/2017/133/defining-doctoral-candidates-and-doctoral-trainingmay2012.pdf">Doctoral Candidates</a> and <a href="http://www.eurodoc.net/sites/default/files/attachments/2017/133/eurodoc2017-juniorresearchersdefinitionandchallenges.pdf">Junior Researchers</a>, is a grassroots federation of national associations of early career researchers (ECRs) from European countries. Eurodoc was founded in 2002 and then established in 2005 as a non-profit, international volunteer organisation based in Brussels. As representatives of ECRs at European level, we engage with all major stakeholders in research and innovation in Europe. Eurodoc primarily focuses and advocates for <a href="http://www.eurodoc.net/sites/default/files/attachments/2017/133/defining-doctoral-candidates-and-doctoral-trainingmay2012.pdf">doctoral candidates</a> and <a href="http://www.eurodoc.net/sites/default/files/attachments/2017/133/eurodoc2017-juniorresearchersdefinitionandchallenges.pdf">junior researchers</a><a href="http://eurodoc.net/eurodoc/mission-and-vision#_ftn1">[1]</a>, that is, researchers at <a href="https://euraxess.ec.europa.eu/europe/career-development/training-researchers/research-profiles-descriptors">R1 and R2 stages.</a>

Austrian Science Fund (FWF) Publication Cost Data 2020

The following data set provides information on the publication costs spent by the Austrian Science Fund (FWF) via the programmes Peer-reviewed Publications (<a href="https://www.fwf.ac.at/en/research-funding/fwf-programmes/peer-reviewed-publications/">https://www.fwf.ac.at/en/research-funding/fwf-programmes/peer-reviewed-publications/</a>) and Stand-Alone Publications (<a href="https://www.fwf.ac.at/en/research-funding/fwf-programmes/stand-alone-publications/">https://www.fwf.ac.at/en/research-funding/fwf-programmes/stand-alone-publications/</a>) in 2020.

Mini Talks/Videos about Open Science from OLS-3 Cohort

We aim to present important topics in Open Science (e.g. open Licence, open review, open access, open sources, agile, open protocols, ...) within 10-15 minutes videos with subtitles and translations. This is a collection of Open Life Science (OLS-3) videos and captions in order to make them accessible, re-useable, and encourage further translation in other languages beyond English and Arabic. All original videos are available on <a href="https://www.youtube.com/channel/UCs12-ZgnDJOWIWN3Vo1XHXA">Open LifeSci YouTube channel</a>. This project was initiated by <a href="https://twitter.com/talarify?lang=en">Talarify</a> and <a href="https://twitter.com/OpenSciSaudi">Open Science Community in Saudi Arabia</a> to facilitate learning of Open science practices to novice learners. Individual videos can be downloaded from the GitHub repository: <ul> <li><a href="https://www.youtube.com/watch?v=xcTwm7D1XsQ&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=1">Introduction to Open Life Sciences</a></li> <li><a href="https://www.youtube.com/watch?v=g-ozvoNadL4&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=2">Open Canvas for Project Strategy</a></li> <li><a href="https://www.youtube.com/watch?v=OnQgdneO3zY&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=3">Roadmapping for Open Projects</a></li> <li><a href="https://www.youtube.com/watch?v=xdBwuut6dRY&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=4">A Primer on Open Licenses</a></li> <li><a href="https://www.youtube.com/watch?v=Jgv34Kwgga8&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=5">README for Open Projects</a></li> <li><a href="https://www.youtube.com/watch?v=iu34Pd2PeYM&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=6">Contributing Guidelines and Codes of Conduct for Open Projects</a></li> <li><a href="https://www.youtube.com/watch?v=obnnT722PDg&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=7">Agile and Iterative Project Management Methods</a></li> <li><a href="https://www.youtube.com/watch?v=OskC2LNtPkU&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=8">Open Source in Research</a></li> <li><a href="https://www.youtube.com/watch?v=qjsLA1jhK6c&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=9">Open Data</a></li> <li><a href="https://www.youtube.com/watch?v=KymHGq9SAgM&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=10">Open Source/Science Hardware</a></li> <li><a href="https://www.youtube.com/watch?v=j_G6flATV1c&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=11">Preprint adoption in the life sciences by ASAPbio</a></li> <li><a href="https://www.youtube.com/watch?v=1wN6RqCmpqM&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=12">Open Protocols</a></li> <li><a href="https://www.youtube.com/watch?v=hTT8xsS3s_I&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=13">Participatory Citizen Science</a></li> <li><a href="https://www.youtube.com/watch?v=-EdD3JKA6WA&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=14">FAIR Data</a></li> <li><a href="https://www.youtube.com/watch?v=I_5Tn50KCQ4&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=15">FAIR Training</a></li> <li><a href="https://www.youtube.com/watch?v=ME8_NRGRhSs&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=16">FAIR software</a></li> <li><a href="https://www.youtube.com/watch?v=Vj15O_bDFhI&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=17">Open Leadership Career Guidance: Social Entrepreneurship</a></li> <li><a href="https://www.youtube.com/watch?v=Q2DBOAHWThk&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=18">Open Science Hardware</a></li> <li><a href="https://www.youtube.com/watch?v=PnrUmQdzUA8&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=22">Indonesia and the Impact on Open Science</a></li> <li><a href="https://www.youtube.com/watch?v=cf4MZZ2j4ak&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=19">Unconscious Bias</a></li> <li><a href="https://www.youtube.com/watch?v=fYJvxR3PcdY&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=20">Personas and Pathways</a></li> <li><a href="https://www.youtube.com/watch?v=BRik7qB7IuA&list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9&index=21">Explore the Mountain of Engagement in 10 Minutes</a></li> </ul> They are also available on <a href="https://www.youtube.com/playlist?list=PL1CvC6Ez54KDvJbbdLn5rPvf1kInifEh9">a playlist on YouTube</a>. Contributing 💝 We welcome all contributions to improve this project especially first-timers to expand the translation! You don't need to know git to start contributing, we use <a href="https://crowdin.com/project/ols3">Crowdin localisation</a>, which enables you to translate strings of SRT files while watching the video and adding content to your translation. More details are added to our <a href="https://github.com/open-life-science/ols3-cohort-talks-and-transcripts/blob/main/CONTRIBUTING.md">Contribution Guide</a>.

Shared motivations, goals and values in the practice of personal science - Qualitative data set

269 transcribed excerpts coded from 22 interviews to self-researchers for the study "Shared motivations, goals and values in the practice of personal science - A community perspective on self-tracking for empirical knowledge". Interviews with participants were conducted via video conferencing and were based on a list of open-ended questions, separated into key sections around participation and collaboration in personal science. Participants who agreed to be interviewed, gave informed consent in like with the ethics approval by the Inserm Institutional Review Board (IRB) for this study, and regarding this data set, previous agreement in compliance with privacy and anonymity requirements. Academic article based on this dataset: Senabre Hidalgo, E., Ball, M. P., Opoix, M., & Greshake Tzovaras, B. (2022). Shared motivations, goals and values in the practice of personal science: a community perspective on self-tracking for empirical knowledge. Humanities and Social Sciences Communications, 9(1), 1-12. <a href="https://doi.org/10.1057/s41599-022-01199-0">https://doi.org/10.1057/s41599-022-01199-0</a>

A Systematic Mapping of the Classification of Open Educational Resources for Computer Science Education in Digital Sources (Data)

Data from a Systematic Mapping of the classification of Open Educational Resources for Computer Science Education. Content: <ul> <li>Studies selected</li> <li>Digital sources used to classify Open Educational Resources for Computer Science Education</li> <li>Computer Science domains explored by Open Educational Resources</li> <li>Approaches for the classification of Open Educational Resources for Computer Science Education</li> </ul>

opencc-by-4.0Oct 2021View details →

Corresponding Dataset of Advanced Water Vapor Radiometer Data for Juno Gravity Science

Corresponding Dataset of Advanced Water Vapor                Radiometer Data for Juno Gravity Science                      Troposphere Calibrations                           README FILE                          Dustin Buccino                           August 24, 2021                     Jet Propulsion Laboratory                California Institute of Technology ============================================================================= INTRODUCTION =============================================================================     This dataset contains high rate data collected by the Advanced Water Vapor Radiometer (AWVR) at the Deep Space Network's Goldstone Complex in  California. This dataset is provided in order to supplement the submitted article to the "Radio Science" journal     Buccino, D.R., et al (2021), Performance of Earth Troposphere      Calibration Measurements with the Advanced Water Vapor Radiometer      for the Juno Gravity Science Investigation, Radio Science, submitted     October 2021.     ******************************************************************     * ANY USERS OF JUNO GRAVITY SCIENCE DATA ARE HIGHLY ENCOURAGED   *     * TO INSTEAD REFER TO THE OFFICIAL ARCHIVE ON THE NASA PLANETARY *     * DATA SYSTEM. THIS SUPPLEMENTAL DATA SET DOES NOT CONTAIN ANY   *     * GRAVITY SCIENCE DATA; IT ONLY CONTAINS HIGHER RATE AWVR DATA   *     ******************************************************************     Additional Juno Gravity Science Data may be found at the Planetary Data System:     Buccino, D. R. (2016). Juno jupiter gravity science raw data set      V1.0, JUNO-J-RSS-1 JUGR-V1.0, NASA planetary data system (PDS).      Retrieved from https://atmos.nmsu.edu/PDS/data/jnogrv_1001/      ============================================================================= ARCHIVE INFORMATION =============================================================================     This archive contains several data types, located within subdirectories.          ROOT      `- PJ03/                This directory contains all PJ-03 related data, including          path delay, path delay rate, calibration values, and frequency          residuals.            `- PJ06/                This directory contains all PJ-06 related data, including          path delay, path delay rate, and calibration values.            `- PJ08/                This directory contains all PJ-08 related data, including          path delay, path delay rate, and calibration values.            `- ADEV/                This directory contains troposphere scintillation Allan deviations          from each perijove. Files are named using the start time of the file,          in YYYYMMDDHHMM format, where YYYY is the year, MM is the month,          DD is the day of month, HH is the hour, and MM is the minute.            `- STATS/                This directory contains the Juno perijove frequency residual           statistics. Only one file is present in this directory. ============================================================================= FILE FORMAT =============================================================================     This dataset contains two separate file formats as described below. ASCII plain-text files are given with the "*.txt" extension and the comma-separated text files are given with the "*.csv" extension.     TXT FILES     -------------------------------------------------------------------------     The ASCII plain-text files are human-readable, space-delimited     text files. Each column is defined by a header row which provides     a description of each column. Additional comments may be optionally     specified by starting a row with the character "#".     CSV FILES     -------------------------------------------------------------------------     The Comma-Separated Value (CSV) files are plain-text files. Values in     each data file are separated using a comma ",". Each column is defined      by a header row which provides a description of each column. ============================================================================= FIGURE REPRODUCTION =============================================================================     This section will describe the data that are used to produce the figures in the article that describes this dataset.     FIGURE 1     -------------------------------------------------------------------------     Figure 1 is a photograph and is not included in this dataset.     FIGURE 2     -------------------------------------------------------------------------     Figure 2 is produced using files within the "PJ03", "PJ06", and "PJ08"     directories.          The first row of subfigures are produced by plotting the final three      columns of "pjXX_bt_zenith.txt" as a function of time.          The second row of subfigures are produced by plotting the path delay     componets as a function of time from the "pjXX_pd_awvr.txt" and      "pjXX_pd_tsac.txt" data files.     FIGURE 3     -------------------------------------------------------------------------     Figure 3 is produced using files within the "PJ03", "PJ06", and "PJ08"     directories.          The first row of subfigures are produced by plotting the last column     of "pjXX_freq_awvr.txt" and "pjXX_freq_tsac.txt".          The second row of subfigures are produced by differencing the values.          FIGURE 4     -------------------------------------------------------------------------     Figure 4 is produced using files within the "ADEV" directory.          Each individual file within the "ADEV" directory contains the Allan      deviation. Each Allan deviation is plotted on a log-log scale and is     color-mapped to the calendar date. The file naming convention gives     the calendar date of data collection, with the filenames starting with     YYYYMMDD, where YYYY is 4-digit year, MM is 2-digit month, and DD is     2-digit day of month in UTC time.     FIGURE 5     -------------------------------------------------------------------------     Figure 5 is produced using files within the "PJ03" directory. The     frequency residual from the "pj03_resid_awvr.csv" and     "pj03_resid_tsac.csv" is simply plotted as a function of time.          FIGURE 6     -------------------------------------------------------------------------     Figure 6 is produced using files within the "STATS" directory. This      directory contains a single file, "AWVR_stats_jul2021_v3.csv" and     contains the root-mean-square of the frequency residuals from Juno      perijove passes. The root-mean-square of the frequency residuals     are plotted using a bar plot and the percent improvement is plotted      with a scatterplot.      ============================================================================= ACKNOWLEDGMENTS ============================================================================= This work was carried out at the Jet Propulsion Laboratory,  California Institute of Technology, under contract with the National  Aeronautics and Space Administration. Government sponsorship acknowledged. ============================================================================= PRIMARY POINT OF CONTACT ============================================================================= Dustin Buccino Jet Propulsion Laboratory Planetary Radar and Radio Sciences (818) 393 - 1072 Dustin.R.Buccino@jpl.nasa.gov ============================================================================= ACRONYMS AND ABBREVIATIONS =============================================================================      ASCII  American Standard Code for Information Interchange      DOY    Day of year      DSN    Deep Space Network      JPL    Jet Propulsion Laboratory      NAIF   Navigation Ancillary Information Facility      NASA   National Aeronautics and Space Administration      PDS    Planetary Data System      RS     Radio Science      RSS    Radio Science Subsystem      SIS    Software Interface Specification      TXT    Text file      UTC    Universal Time, Coordinated

opencc-by-4.0Dec 2018View details →

[DATA_SCIENCE] Interviews Plant Phenomics, 2015

Here are two transcripts from a set of interviews executed by Sabina Leonelli in the fall of 2015 as part of the ERC project "The Epistemology of Data-Intensive Science", and in the context of a case study of phenotyping practices at the National Plant Phenomics Centre in Aberystwyth and collaborators. The transcripts document researchers' experience of data curation practices. Researchers have consented to have these transcripts made available as Open Data. Other interviewees did not give consent or ended up providing sensitive information in their interviews, so those transcripts cannot be made open and are held securely by the research team in Exeter. You also find the information sheet provided to interviewees, which gives you the context for this project. Further information can be found at <a href="http://www.datastudies.eu">www.datastudies.eu</a>. The transcripts have been redacted to exclude names of people who have not given consent to participate in the study, but have otherwise been left unedited and therefore contain several colloquial expressions. A paper by Sabina Leonelli which specifically makes use of these interviews will be published in 2019 in the European Journal for Philosophy of Science, under the title “What Distinguishes Data from Models?”. Freely accessible preprint here: <a href="http://philsci-archive.pitt.edu/id/eprint/15485">http://philsci-archive.pitt.edu/id/eprint/15485</a> . Several related publications can be found in Open Access formats on the project website: <a href="http://www.datastudies.eu">www.datastudies.eu</a>.

opencc-by-4.0Oct 2022View details →

Database of the educational role of Citizen Science in the framework of Open Science from the paradigm of complex thinking

Database for the analysis of the educational role of Citizen Science projects in the framework of Open Science from the paradigm of complex thinking

Data Set Literature Review Digital Forensic and Forensic Sciences

Data ini digunakan untuk membuat penelitian sesuai dengan tinjauan literatur dengan kata kunci "Digital Forensic" dan "Forensic Sciences"

Dataset Literature Review Digital Forensic AND Forensic Sciences

Data ini digunakan untuk membuat penelitian berdasarkan tinjauan literatur dengan kata kunci "Digital Forensic" dan "Forensic Sciences"

opencc-zeroNov 2022View details →

dryad36/100

The productivity puzzle in invasion science: Declining but persisting gender imbalances in research performance

We analyzed 27,234 publications published since the rise of the field of invasion science in 1980 to evaluate the presence of gender differences in research productivity, the extent of collaboration, and the research impact of those differences. Our analysis revealed significantly fewer female- than male-authored publications, both per capita and as a group, and the underrepresentation of women as first and single authors persists despite improvements in the gender gap. At the current rate of increase, gender parity in first authorship will not be achieved until 2100, and men will continue to constitute the principal voice of first or single authors in invasion science. Women collaborate with fewer coauthors and are cited less frequently than men, on average, which may influence recruitment and retention to more senior academic positions. These gender disparities in this aspect of research performance suggest that, although the gender gap is lessening, women experience barriers in invasion science.

Data for Bradter, Altringham, Kunin, Thom, O'Connell & Benton: Variable ranking and selection with random forest for unbalanced data. Environmental Data Science

The data are used in 'Bradter, Altringham, Kunin, Thom, O'Connell & Benton: Variable ranking and selection with random forest for unbalanced data. Environmental Data Science' and are described in the ReadMe file and in the manuscript and Supporting information.

Job offers of remote and data-science related positions - Source: Remotive.com

Most relevant job offers published in the categories of software development, data and sysadming and devops of the web Remotive.com