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11 results for “Scientific research analysis”
Data Matrix Theme-Specific Analysis of the Recommendation on Science and Scientific Researchers (RSSR): Public and Stakeholder Engagement
<p>This Table sets out findings from the mapping exercise conducted as part of the objectives of subtask 6.1 of the RRING project.</p> <p>Aim: Alignment of RRI to advance the UN SDGs.</p> <p>Objectives:</p> <ul> <li>Mapping the RSSR to the SDGs </li> </ul> <p>Mapping the RSSR to the SDGs is aimed at providing new perspectives, ideas and approaches that can help to improve the operationalization and implementation of each SDG, <em>by facilitating the integration of RRI (or RRI-like) practices in the SDGs, to make them more achievable.</em> The impact of the new perspectives, ideas and approaches in SDG operationalization and implementation will be aimed at the level of <em>national and international policy (making); future research and innovation projects (in industry and academia); as well as education and training of researchers, policy makers and other stakeholders.</em></p> <p>Two documents were used for this task:</p> <ul> <li>2017 Recommendation on Science and Scientific Researchers ([RSSR], UNESCO), and</li> <li>the United Nations 2030 Agenda for Sustainable Development with the 17 Sustainable Development Goals (SDGs).</li> </ul>
Data Matrix Theme-Specific Analysis of the Recommendation on Science and Scientific Researchers (RSSR): Ethics and Ethical Governance
<p>This Table sets out findings from the mapping exercise conducted as part of the objectives of subtask 6.1 of the RRING project.</p> <p>Aim: Alignment of RRI to advance the UN SDGs.</p> <p>Objectives:</p> <ul> <li>Mapping the RSSR to the SDGs </li> </ul> <p>Mapping the RSSR to the SDGs is aimed at providing new perspectives, ideas and approaches that can help to improve the operationalization and implementation of each SDG, <em>by facilitating the integration of RRI (or RRI-like) practices in the SDGs, to make them more achievable.</em> The impact of the new perspectives, ideas and approaches in SDG operationalization and implementation will be aimed at the level of <em>national and international policy (making); future research and innovation projects (in industry and academia); as well as education and training of researchers, policy makers and other stakeholders.</em></p> <p>Two documents were used for this task:</p> <ul> <li>2017 Recommendation on Science and Scientific Researchers ([RSSR], UNESCO), and</li> <li>the United Nations 2030 Agenda for Sustainable Development with the 17 Sustainable Development Goals (SDGs).</li> </ul>
Analysis of shared research data in Spanish scientific papers about COVID-19: a first approach
<p><strong>Introduction:</strong> During the coronavirus pandemic, changes in the way science is done and shared occurred, which motivates meta-research to help understand science communication in crises and improve its effectiveness. <strong>Objective: </strong>To study how many Spanish scientific papers on COVID-19 published during 2020 share their research data. <strong>Methodology:</strong> Qualitative and descriptive study applying nine attributes: (1) availability, (2) accessibility, (3) format, (4) licensing, (5) linkage, (6) funding, (7) editorial policy, (8) content and (9) statistics. <strong>Results:</strong> We analyzed 1340 papers, 1173 (87.5%) did not have research data. 12.5% share their research data of which 2.1% share their data in repositories, 5% share their data through a simple request, 0.2% do not have permission to share their data and 5.2% share their data as supplementary material. <strong>Conclusions:</strong> There is a small percentage that shares their research data, however it demonstrates the researchers' poor knowledge on how to properly share their research data and their lack of knowledge on what is research data.</p>
Mapping of Global Scientific Research in Comorbidity and Multimorbidity: A Cross-Sectional Analysis
<p>"Mapping of Global Scientific Research in Comorbidity and Multimorbidity: A Cross-Sectional Analysis" -- October<br> 2017, prepared by F. Catalá López, A. Adolfo Alonso-Arroyo and R. Aleixandre-Benavent (on behalf of the team of co-authors).</p> <p>Publication of the results is under preparation (manuscript submitted to PLOS ONE).</p>
Current trends in scientific research on global warming: A bibliometric analysis (2005-2014)
<p>This dataset was created in the context of the project: " Current trends in scientific research on global warming: A bibliometric analysis (2005-2014)".</p> <p>---</p> <p>Global warming is a topic of increasing public importance, but there have not been published scientometric studies on this topic. The objective of this paper is to contribute to a better understanding of the scientific knowledge in global warming and his effect, as well as to investigate its evolution through the published papers included in Web of Science database. Items under study were collected from Web of Science database from Thomson Reuters. A bibliometric and social network analyses was performed to obtain indicators of scientific productivity, impact and collaboration between researchers, institutions and countries. A subject analysis was also carried out taking into account the key words assigned to papers and subject areas of journals. 1,672 articles were analysed since 2005 until 2014. The most productive journals were Journal of Climate (n=95) and Geophysical Resarch Letters (n=78). The most frequent keywords have been Climate Change (n=722), Model (n=216) and Temperature (n=196). The network of collaboration between countries shows the central position of the United States, together with other leading countries such as United Kingdom, Germany, France and Peoples Republic of China. The research on global warming had grown steadily during the last decade. A vast amount of journals from several subject areas publishes the papers on the topic, including journals of general purpose with high impact factor. Almost all the countries have USA as the main country with which one collaborates. The analysis of key words shows that topics related with climate change, impact, temperature, models and variability are the most important concerns on global warming.</p> <p>---</p> <p>The dataset consist of the following:</p> <p>1) The list of papers included in the analyses: Papers.xlsx</p> <p>This file contains 1672 titles, each line representing a paper (including title of the paper, journal ISSN and year of publication).</p> <p>2) The list of authors: Authors.xlsx</p> <p>This file contains all 4488 authors, each line representing an author (including full name, total number of papers and year of publication).</p> <p>3) The list of scientific journals: Journals.xlsx</p> <p>This file containts all 687 journals, each line representing a journal (including name of the journal, ISSN, total number of papers and year of publication).</p> <p>4) The list of countries: Country.xlsx</p> <p>This file contains all 84 countries, each line representing a country (including country name, total number of papers, total number of citations, and number of citations per paper).</p> <p>5) The list of keywords: Keywords.xlsx</p> <p>This file contains all 6422 keywords, each line representing a keyword (including keywords, number of papers and year of publication)</p>
Data underlying the manuscript: "Analysis of Research Data Sharing in Scientific Articles on Climate Change in the Covid-19 Year. The Spanish case 2020".
<p>This is the research data for the manuscript "Analysis of Research Data Sharing in Scientific Articles on Climate Change in the Covid-19 Year. The Spanish case 2020".<br>The following is the original abstract: Introduction: Sharing research data on climate change would facilitate the development of solutions to curb its impact, for this, data needs to be shared in an optimal way. General objective: To identify how many Spanish scientific articles on climate change published during 2020 share their research data in some way. Specific objectives: a) Identify the attributes of shared research data b) Describe the characteristics of the case studies found on how research data are shared. Methodology: Qualitative and descriptive study analyzing nine attributes: availability (1), accessibility (2), format (3), license (4), linkage (5), funding (6), editorial policy (7), content (8), statistics (9). Results: We analyzed 2212 articles were analyzed, 1867 (84%) articles had no associated research data. The remaining 16% have associated research data: 152 (7%) articles deposited their data in repositories, 42 (2%) submitted their data as supplementary material, 136 (6%) will share their data upon request to the author and 15 (1%) do not have publication permissions. Conclusions: Researchers are willing to share their research data, but under different conditions. Researchers who reused research data did not share the new data they generated. There is a lack of training among researchers on how to manage their research data. There is information on the web on this topic, but it is not just a matter of publishing manuals, but also of creating training spaces within universities, institutes and research centers to build a community of researchers committed to Open Science.</p>
Data Matrix Theme-Specific Analysis of the Recommendation on Science and Scientific Researchers (RSSR): Open Access, Open Data, and Open Science
<p>This Table sets out findings from the mapping exercise conducted as part of the objectives of subtask 6.1 of the RRING project.</p> <p>Aim: Alignment of RRI to advance the UN SDGs.</p> <p>Objectives:</p> <ul> <li>Mapping the RSSR to the SDGs </li> </ul> <p>Mapping the RSSR to the SDGs is aimed at providing new perspectives, ideas and approaches that can help to improve the operationalization and implementation of each SDG, <em>by facilitating the integration of RRI (or RRI-like) practices in the SDGs, to make them more achievable.</em> The impact of the new perspectives, ideas and approaches in SDG operationalization and implementation will be aimed at the level of <em>national and international policy (making); future research and innovation projects (in industry and academia); as well as education and training of researchers, policy makers and other stakeholders.</em></p> <p>Two documents were used for this task:</p> <ul> <li>2017 Recommendation on Science and Scientific Researchers ([RSSR], UNESCO), and</li> <li>the United Nations 2030 Agenda for Sustainable Development with the 17 Sustainable Development Goals (SDGs).</li> </ul>
LA INVESTIGACIÓN CIENTÍFICA SOBRE LA GUACAMAYA VERDE (Ara militaris Linnaeus, 1766) Y LA COTORRA SERRANA (Rhynchopsitta pachyrhyncha Swainson, 1827): ANÁLISIS BIBLIOMÉTRICO = THE SCIENTIFIC RESEARCH ON MILITARY MACAW (Ara militaris Linnaeus, 1766) AND THICK-BILLED PARROT (Rhynchopsitta pachyrhyncha Swainson, 1827): BIBLIOMETRIC ANALYSIS
<p>Research data from an article with the abstract: Thick-billed Parrot (<em>Rhynchopsitta pachyrhyncha</em>) and Military Macaw (<em>Ara militaris</em>) are two species of endangered parrots due to habitats destruction and land-use change. Review the actual scientific research and its trends helps to assess whether the efforts made contribute to efficient conservation. The goal of this work is to obtain an overview of the scientific research on these birds, as well as to identify the most studied topics and those ones necessary to be research. 82 records related to this matter were obtained from Scopus and Web of Science databases, which were published from 1967 to 2019. Unidimensional and bidimensional bibliometric indicators were realyzed. The least inquired topics correspond to pathologies, controlled studies, animal experimentation and molecular biology. Important topics were proposed for research and conservation of this species.</p>
Players of the Innovation Ecosystem: A Quantitative Analysis of the Scientific Collaboration of a State-Run Research Institute in Brazil
<p>Análise de colaborações em artigos do Instituto Nacional de Tecnologia. </p>
Analysis of the Impact of Major Emergencies on Scientific Research
<p>All the data is downloaded from the China National Knowledge Infrastructure (CNKI) database and the Web of Science (WoS) database. We employ bibliometrics and data visualization methods to analyze the published literature. Our extensive experiments using CiteSpace from the aspects of keyword analysis, co-occurrence analysis, and other measures confirm that this framework can provide an effective reference for the research direction mining of similar events.</p>
Filtered Data from the Retrospective Analysis of Antarctic Tracking Data Project from the Scientific Committee on Antarctic Research
<p>The Retrospective Analysis of Antarctic Tracking Data (RAATD) is a Scientific Committee for Antarctic Research (SCAR) project led jointly by the Expert Groups on Birds and Marine Mammals and Antarctic Biodiversity Informatics, and endorsed by the Commission for the Conservation of Antarctic Marine Living Resources. The RAATD project team consolidated tracking data for multiple species of Antarctic meso- and top-predators to identify Areas of Ecological Significance. These datasets constitute the compiled tracking data from a large number of research groups that have worked in the Antarctic since the 1990s.<br> <br> This metadata record pertains to the "filtered" version of the data files. These files contain position estimates that have been processed using a state-space model in order to estimate locations at regular time intervals. For technical details of the filtering process, consult the data paper. The filtering code can be found in the https://github.com/SCAR/RAATD repository.<br> <br> This data set comprises one metadata csv file that describes all deployments, along with data files (3 files for each of 17 species). For each species there is:<br> - an RDS file that contains the fitted TMB filter model object and model predictions (this file is RDS format that can be read by the R statistical software package)<br> - a PDF file that shows the quality control results for each individual model<br> - a CSV file containing the interpolated position estimates<br> <br> For details of the file contents and formats, consult the data paper.</p> <p>The original copy of these data are available through the Australian Antarctic Data Centre (https://data.aad.gov.au/metadata/records/SCAR_EGBAMM_RAATD_2018_Filtered)</p> <p><br> The data are also available in a standardized version (see https://data.aad.gov.au/metadata/records/SCAR_EGBAMM_RAATD_2018_Standardised) that contain position estimates as provided by the original data collectors (generally, raw Argos or GPS locations, or estimated GLS locations) without state-space filtering.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.