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1,311 results for “literature”
Classification and frequency of climate change drivers and responses of small-scale fishers found in literature review
<p>Climate change hazards were classified into resource availability and fishing operations or both following the framework proposed by Cheung et al (2012). Response units were firstly classified into overarching responses and then categorized as suggested by the adaptive-transformative framework of Barnes et al.<sup> </sup>(2020). Adaptation units that did not represent an active adaptation response were classified as remaining. More than one hazard could be attributed to each fishers' response.</p>
Digital government HRM literature review
<p>Digital government HRM index</p> <p> </p> <p>Data collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (<em>Project ID: HORIZON MSCA-SE 101086381)</em></p>
Sample Records: Disinformation as a strategy of obstructionism on climate action: analysis of the limitations of the scientific literature for a systemic understanding of the phenomenon
<p>The project contains several underlying datasets essential for replicating the study's findings. The dataset <strong>01.1_PRIMERPRISMA_IDENTIFICATION.xlsx</strong> includes the initial selection of 6 general terms related to environment and sustainability and 11 specific terms related to disinformation, summarizing the selected keywords, generated Boolean operators, and initial search results, yielding 783 records. The <strong>01.2_PRIMER PRIMA-SCREENING.xlsx</strong> file details the screening process, eliminating duplicates and non-English documents, resulting in 271 retained records. The <strong>01.3_PRIMER PRISMA_INCLUDED.xlsx</strong> file contains results after further screening, retaining 82 documents with expanded bibliometric details. The <strong>02.1_SEGUNDOPRISMA_IDENTIFICATION.xlsx</strong> file documents the second phase of identification using new terms related to climate and disinformation, retrieving 174 records. The <strong>02.2_SEGUNDOPRISMA_SCREENING.xlsx</strong> file includes the screening process for the second phase, reducing records to 75, with an abstract review retaining 2 documents. The <strong>02.3_SEGUNDOPRISMA_INCLUDED.xlsx</strong> file integrates documents from both search phases and other sources, culminating in a final review of 86 documents. The <strong>3.1_Other sources.xlsx</strong> file includes additional relevant sources identified during the review process. Finally, the <strong>4-Final included.xlsx</strong> file contains the final set of 75 publications subjected to the DESLOCIS analysis model.</p>
Sample Records (Analytical procedure): Disinformation as a strategy of obstructionism on climate action: analysis of the limitations of the scientific literature for a systemic understanding of the phenomenon
<p>This dataset includes t<span>he online form and the results from the quantitative phase of the study: Disinformation as an obstructionist strategy in climate change mitigation: A review of the scientific literature for a systemic understanding of the phenomenon</span></p> <p>To duplicate the form you can use: https://forms.office.com/Pages/ShareFormPage.aspx?id=6sSEXw03nkuDDHVvi_G1Hw0s3dVrMb1NsO12gDNTB9BUREo4WENRMFFDN1lOSlRSU0xJNkVHWURWUS4u&sharetoken=rg4Qfg19O4UgYzUB084C </p>
Sample Records (PRISMA Checklist and Flow diagram): Disinformation as a strategy of obstructionism on climate action: analysis of the limitations of the scientific literature for a systemic understanding of the phenomenon
<p>This dataset includes: the PRISMA Checklist and the <span>PRISMA Flow diagram of the study titled: Disinformation as an obstructionist strategy in climate change mitigation: A review of the scientific literature for a systemic understanding of the phenomenon.</span></p>
gEneSys Project - Systematic Literature on the Nexus between Gender and Energy Transition Database
<p>The present Dataset containes the data collected for the gEneSys Systematic Literature Review on the nexus between gender and energy transition. Data have been collected from 152 papers published between 2000 and 2023. The publications have been identified through an hoc research query and retrieved from the Web of Science Database.</p> <p>The dataset inscludes the following variables:</p> <ol> <li>Title of the publication, category of the categorization of Bell et al., 2020 (Political, Economic, Socio-Ecological, Technological).</li> <li>Cluster in which the publication has been included.</li> <li>Parts of the publication’s results about the nexus between gender and energy.</li> <li>Parts of the publication’s text about the gender gap assessed by the publication.</li> <li>Parts of the publication’s text about the gender gap identified to be bridged by future research.</li> <li>The type of the gender issue/s addressed by the publication. </li> <li>The type of the gender issue/s addressed by the publication. </li> <li>Technology/ies mentioned in the publication.</li> <li>The name of the country or countries studied by the publication.</li> <li>World Bank classification of the level of income of the country or countries studied by the publication.</li> <li>World Bank classification of the region of the country or countries studied by the publication.</li> <li>Spatial Context (e.g. international, national, inner-country, peri-urban, rural) of the country or countries studied by the publication.</li> <li>Research method employed in the publication (qualitative, quantitative, mixed).</li> <li>Specific qualitative, quantitative or mixed method or methods employed in the publication.</li> <li>Number of observations for the methods used.</li> <li>Parts of the publication’s text about the policy recommendations elaborated in the publication.</li> <li>If the publication mentions a pathway.</li> <li>Year of publication.</li> <li>Author/s surname and name initial. </li> <li>Author/s full surnames and names. </li> <li>Keywords chosen by the author/s. </li> <li>Abstract of the publication. </li> <li>Name of the source or journal. </li> <li>Type of publication. </li> <li>Category/ies identified by Web of Science. </li> <li>Publication’s language. </li> <li>Keywords identified by Web of Science. </li> <li>Number of references cited by the publication. </li> <li>Number of times the publication has been cited in Web of Science Core Database. </li> <li>Number of times the publication has been cited in Web of Science All Databases. </li> <li>Name of the publisher. </li> <li>Digital Object Identifier. </li> <li>Digital Object Identifier link. </li> <li>Publication’s number of pages. </li> <li>Web of Science citation index. </li> <li>Research area or areas of the publication. </li> <li>Web of Science Unique Identifier.</li> </ol>
Deep Reference Mining from Scholarly Literature in the Arts and Humanities - Pre-trained word embeddings
<p>Pre-trained word vectors of dimensionality 100 and 300 for the publication: Deep Reference Mining from Scholarly Literature in the Arts and Humanities, submitted to Frontiers in Digital Humanities.</p> <p>The corpus of scholarly publications from which these vectors were trained is under copyright, therefore we publish these vectors for reproducibility. Please refer to the publication's repository for further details: <a href="https://github.com/dhlab-epfl/LinkedBooksDeepReferenceParsing">https://github.com/dhlab-epfl/LinkedBooksDeepReferenceParsing</a>.</p> <p>These vectors were trained using Gensim 3.1.0. The corpus was preprocessed as follows:</p> <ol> <li>word tokenization with NLTK word_punct tokenizer.</li> <li>digits were converted into the $NUM$ token</li> <li>words less frequent than 5 times, for every document, were converted to the $UNK$ token</li> <li>vectors were trained using the function: Word2Vec(window=5, min_count=5, sg=1)</li> </ol>
CATCH-EyoU Work Package 2 Dataset 2.2a - Aggregation of Literature
<p>The data is an aggregated dataset collected from all contributing partners, and includes a bibliography, concerning Europe, youth engagement and active citizenship across the disciplines represented in the Consortium (Political Science, Sociology, History, Media and Communications, Psychology and Education).</p> <p>The dataset contains reference to 770 individual texts.</p> <p>It is highly unlikely that a similar aggregated bibliography exists elsewhere.</p> <p>As this is new data, the reasons no suitable existing data are available is due to the breadth and scope of the aggregated dataset, which for the first time brings together literature from various disciplinary perspectives of young people and active citizenship across Europe, thus bridging a gap between previous studies that have mainly been limited to explorations of citizenship literatures within specific disciplines (and not across).</p> <p>The data sources are provided via csv document bibliography.</p> <p>The data set cleans and aggregates raw bibliographic data collected by consortium members during Months 1-3 of the research study.</p> <p>The aggregated literature dataset constitutes bibliographic data which can be reused by researchers who want to compare our data with similar data collected in different countries.</p>
CATCH-EyoU Work Package 2 Dataset 2.1a - Full Consortium Collection of Literature Matrix
<p>The dataset includes <strong>one master spreadsheet containing literatures searched, catalogued and summarised in the fields of Cultural Studies, Education, History, Media and Communication, Philosophy, Political Science, Psychology and Sociology,</strong> which contains <strong>770 selected texts.</strong></p> <p> </p> <p>The aims of the data collected are to produce an integrated theory that builds on the findings of different disciplines (Cultural Studies, Education, History, Media and Communication, Philosophy, Political Science, Psychology and Sociology) focused on the understanding of factors and processes (from the macro social level to the social and psychological level), within the different life contexts, that promote or hinder youth active citizenship in EU.</p> <p> </p> <p>It is possible that similar databases of literature around Europe, Young People and Active Citizenship across the fields of Cultural Studies, Education, History, Media and Communication, Philosophy, Political Science, Psychology and Sociology exist in other forms, perhaps collected for studies on one or more of the included disciplines, but we do not currently have access to a similar repository.</p> <p> </p> <p>With that said, it is highly unlikely that an exact dataset corresponding to the specifics of this study exist in any form elsewhere, thus justifying the creation of new data for this study in the absence of suitable existing data. Data collected here will bridge the gap between global aggregated literatures on youth and citizenship separated by discipline on the one hand, and a new dataset offering an integrated literature analysis of different fields of study.</p> <p> </p> <p>The data sources are available in bibliographic format and attached via csv document.</p> <p> </p> <p>The dataset relies on the following information taken from the data sources: specific identifying information about the text itself (title/author/year/publisher); and abstract or summarizing information either taken directly from the text or summarized by the researcher.</p> <p> </p> <p>Finally, the aggregated literature review spreadsheet constitutes raw data which can be reused by researchers who want to compare our data with similar data collected in different countries, or to perform textual analysis (content analysis and/or data mining) on our data.</p>
Unpacking the concept of "educators' data literacy in Higher Education" - Systematic Review of the literature and Keyword Map
<p>As algorithmic decision-making and data collection become pervasive within higher education, how can educators make sense of the systems that shape life and learning in the 21st century? Through a systematic review of the literature, the paper investigates the gaps in the literature, which prevent the formulation of potential pathways and principles on which educators’ data literacy can - and should - be developed and fostered. The analysis of 137 papers through the methods of classification under relevant categories, and key words mapping, showed that there is little attention on HE teachers, and most approaches to educators’ data literacy address management and technical abilities for data processing, with less concern on critical, ethical and personal approaches to datafication in education.</p> <p>The present dataset shows the full list of articles analysed.</p> <p>The dataset, and ods file, is composed by the following sheets:</p> <ol> <li>Codebook</li> <li>List of articles extracted from SCOPUS</li> <li>List of articles extracted from WOS</li> <li>List of articles extracted from ERIC</li> <li>List of articles extracted from DOAJ</li> <li>Interrater Agreement</li> <li>PRISMA workflow</li> <li>Analysis - First Level (classification of 137 articles selected)</li> <li>Analysis - Second Level (List of articles relating faculty development)</li> <li>Supplementary tables (counting articles in relation to the categories of analysis).</li> </ol> <p>As for the Keywords' Map, a second file .csv displays the text over which basis was performed the keyword maps analysis. A .txt file shows notes relating the analysis procedures using the software VOS-Viewer <a href="http://www.vosviewer.com/">http://www.vosviewer.com/</a></p> <p> </p>
[Dataset] Software Process Line as an Approach to Support Software Process Reuse: a Systematic Literature Review
<p>Dataset of a Systematic Literature Review on Software Process Line as an Approach to Support Software Process Reuse</p> <p>Please, read README.txt file before go through dataset.</p>
Preprints in biology as a fraction of the biomedical literature
<p>These data and chart present an approximate calculation of the proportion of preprints in biology when compared to publications in PubMed, based on monthly figures and incorporating monthly preprint submissions (or counts) across a selection of servers relevant to biology. </p> <p>Version 1.0 of these data represents data from January 2007 until May 31, 2019 for preprint servers: arXiv q-bio, Nature Precedings, F1000Research*, PeerJ Preprints*, bioRxiv**, Winnower*, <a href="http://preprints.org">preprints.org</a>, Wellcome Open Research*. </p> <p>* Counts may not be specific to biology preprints only; ** Counts may include all versions posted that month, so may be an overestimate for version 1 submissions.</p> <p>From January 2019, data has been gathered manually by the authors, as per the methods described in the .csv here, and is included here in 'Preprints_per_month_direct_2019-01to05.csv'. Until December 2018, monthly preprint submissions data are based on those contributed by Jordan Anaya (ORCID: <a href="https://orcid.org/0000-0002-6166-4113">https://orcid.org/0000-0002-6166-4113</a>) for PrePubMed, source: <a href="https://raw.githubusercontent.com/OmnesRes/prepub/master/analyses/preprint_data.txt">https://raw.githubusercontent.com/OmnesRes/prepub/master/analyses/preprint_data.txt</a>; Github repository: <a href="https://github.com/OmnesRes/prepub">https://github.com/OmnesRes/prepub</a>; website: <a href="http://www.prepubmed.org/">http://www.prepubmed.org</a>). Data are not included here, they are provided from the source linked above under MIT license associated with the website code: <a href="https://github.com/OmnesRes/prepub/blob/master/LICENSE">https://github.com/OmnesRes/prepub/blob/master/LICENSE</a>.</p> <p>A live version of these data and the chart are available from this GSheet: <a href="https://docs.google.com/spreadsheets/d/1bkGEcfQcL0LpIanVqNHci1ZFY6oVNGz7IQbEugzkqkU/edit?usp=sharing">https://docs.google.com/spreadsheets/d/1bkGEcfQcL0LpIanVqNHci1ZFY6oVNGz7IQbEugzkqkU/edit?usp=sharing</a>. Between version updates here, please refer to this sheet for updated counts and method updates e.g. to include more servers and ensure only version 1 submissions are counted.</p> <p>For more information, please contact naomi.penfold@asapbio.org.</p> <p>When presenting these data and/or chart, please attribute to ASAPbio (https://asapbio.org, twitter: @ASAPbio_).</p>
Serverless Literature Dataset
<p>Systematic database of literature around serverless computing and applications, cloud functions, Function-as-a-Service (FaaS) and closely related topics. Retrieved through keyword search from DBLP and manual additions. Covering 2016-first bits of 2019. Insights into technologies and trends. Evolving through open community curation.</p>
Literature Curated PPIs from "Accurate and Sensitive Interactome Profiling Using a Quantitative Protein-Fragment Complementation Assay"
<p>This dataset includes the literature curated protein-protein interactions supporting the manuscript titled 'Accurate and Sensitive Interactome Profiling Using a Quantitative Protein-Fragment Complementation Assay'.</p>
RDF version of the data from Hagar I. Labouta et al. Meta-Analysis of Nanoparticle Cytotoxicity via Data-Mining the Literature. NanoImpact (2019)
<p>This is an RDFied version of the dataset published by Hagar I. Labouta et al. Meta-Analysis of Nanoparticle Cytotoxicity via Data-Mining the Literature. NanoImpact (2019).</p> <p>The original dataset publication DOI: <a href="https://doi.org/10.1021/acsnano.8b07562">https://doi.org/10.1021/acsnano.8b07562</a></p> <p>The Original publication authors: Hagar I. Labouta, Nasimeh Asgarian, Kristina Rinker, and David T. Cramb</p>
S74 | REFTPS | Transformation Products and Reactions from Literature
<p>This is the collection associated with list S74 REFTPS Transformation Products and Reactions from Literature on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>This dataset is designed to provide an entry point for users to contribute transformation products and reactions documented in the literature for addition to the NORMAN SLE, SusDat and the PubChem Transformations section.</p> <p>Change logs and version tracking at the <a href="https://gitlab.com/uniluxembourg/lcsb/eci/pubchem/-/tree/master/annotations/tps/REFTPS">ECI GitLab site</a>.</p> <p>Change log: v0.0.2 added InChIKey file. v0.1.0 added new reactions from Anca Baesu and DTXSIDs. v0.2.0 added PFAS TPs from Parviel Chirsir. v0.2.1 more PFAS TPs from Parviel. v0.3.0 Emma added HMMM TPs; v0.3.1 updated references and added new CIDs; added new MS/MS file. v0.4.0 new PFAS TPs plus MS/MS and NMR. v0.4.1 new CID added, plus CID 67543 updated to 14571268. v0.5.0 new 8:2 FT TPs plus annotation data; new structures. v0.5.1 added new CIDs. v0.5.2 added 2:2 to 6:2 FT TPs, updated ref for Bugsel. v0.5.3: added new CIDs. v0.6.0 added new structures. v0.7.0 added more new structures. v 0.7.1: updated CIDs in substances, fixed PFHpA mapping in transformations (some were mismapped to CID 67819). v 0.7.2: updated Biosystem description for many records. v0.8.0: updated CID 163201609 => 166001338, adjusted last 4 MS/MS, added Barisci AOP transformations. v0.9.0 added new structures. v0.9.1 updated CIDs and added radical structures from deposition. v0.10.0 added new irgarol reaction; v0.10.1 added new CID. v0.11.0 added Avendano and Mabury transformations from Parviel. v0.12.0 added Washington MS/MS and Marjanovic MS/MS and reactions. v0.13.0 added Galaxolide transformation. v0.14.0 added Zweigle PFAS TPs with MSMS. v0.14.1 added new CIDs. v0.15.0 added antibiotic TPs from Paul Löffler, SLU, incl. entries with no CID. v0.15.1 added new CIDs. v0.16.0 added benzothiazole reactions. v0.17.0 added TooCOLD TPs from Rick. v0.18.0 added new TFA reactions. v0.19.0 added pak choi reactions, several with no CID. v0.19.1 added new CIDs. v0.20.0 added dimers from Li Ji. v0.20.1 added new CIDs. v0.21.0 added the EJ Weber PFAS libraries "EnvLib" and "MetaLib", curation by Parviel and Emma. Some new CIDs to come. v0.21.1: fixed char issues in substance & transformation files. v0.21.2 added new CIDs. v0.22.0 added "Class_parent" column to the substance deposition file to aid annotation. v0.23.0: added Parviel's zebrafish entries</p>
Co-citations Map: Literature review on Learning Ecologies, 1991-2018
<p>The co-citation map was adopted as type of analysis over 85 papers sampled from five scientific databases (pls. cfr: <a href="https://zenodo.org/record/1503775#.W_rUn-hKg2w">Systematic Review on the Research Topic "Learning Ecologies" - Dataset and Analysi</a>s". This was adopted as method to further understand the relationships and advancement of work relating the concept of LE.</p> <p>The software tool to carry out this phase of the study was <a href="http://www.citnetexplorer.nl/ ">Citenet Explorer</a> for the analysis and visualization of co-citations along the period 1999-2018.</p> <p>The total number of citations and the relationships between most cited authors and all authors were extracted from the corpus analyzed (<a href="https://zenodo.org/record/1503775#.W_rUn-hKg2w">Systematic Review on the Research Topic "Learning Ecologies" - Dataset and Analysi</a>s"; a specific dataset was created and the outputs were processed by the specialized software that delivers the bibliometric maps as output.</p> <p>All the instructions to use the two files that compose the dataset requested by the software, as well as the software specifications can be found at CiteNet Explore page: http://www.citnetexplorer.nl/ </p> <p>Finally, the Fig. 7 with the analysis we performed shows the co-citations map, where at a first sight it is possible to see two main groups of nodes or authors cited (X axis) across a timespan (Y axis), and sparse elements at the center and at the beginning of the period (1991). The main and more compact group (also in terms of clusterisation of nodes, which are showed in green) related the publications that cite the seminal work of Barron (2004). These publications are mostly classified as using socio-constructivist theories and are placed in the area of social sciences, while for other categories (such as the methodological approach, research applications and the alignment are more fragmented). There are four seminal works (Abd-El-Khalick & Akerson, 2004; Barron, 2004; T ; Okamoto, Kayama, Inoue, & Cristea, 2002; Toshio Okamoto & Kayama, 2004) to which other papers can be connected. Beyond the mentioned work of Barron, the other three works can be placed in the area of technology (development of eLearning environments) and STEM education, supporting the idea of disciplinary fragmentation.</p>
Literature search for publication: A meta-analysis on the role older adults with cancer favour in treatment decision making
<p>Dataset belonging to 10.5281/zenodo.7308287 including data of literature search regardign outcome preference scale in geriatric oncology</p>
Flowchart on the methodology used to conduct the literature search on provenance representation models and change-tracking in RDF
<p>The image contains a flowchart on the methodology used to conduct the literature search on provenance representation models and change-tracking in RDF. This methodology was used in the Abstract submitted to the DH2023 conference in Graz.</p>
GERDAT014 Self-management and self-monitoring literature search
<p>Dataset used for the literature on suitable self-monitoring or self-management tools or applications that could be used for older patients with cancer and/or multimorbidity</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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.