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28 results for “literature database”
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>
Multicontextual Phenotype Models: Biomedical Database and Literature Phenotype and Social Media Phenotype
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SheepNet scientific literature database
<p>Searchable database containing reviewed and catalogued papers of relevance to the 3 SheepNet themes: reproductive efficiency, gestation efficiency and lamb survival.</p>
Linked collectors and determiners for: Corvids Literature Database.
Natural history specimen data linked to collectors and determiners held within, "Corvids Literature Database". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/829cf3b4-f762-11e1-a439-00145eb45e9a">https://bionomia.net/dataset/829cf3b4-f762-11e1-a439-00145eb45e9a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/829cf3b4-f762-11e1-a439-00145eb45e9a">https://gbif.org/dataset/829cf3b4-f762-11e1-a439-00145eb45e9a</a>. Formatted as a Frictionless Data package.
GOhydro Literature Review Light Database
<p>GOhydro Literature Review Light Database contains information on microgreens production environments, with a focus on light impacts. It contains data on both environmental conditions and the resulting outputs for microgreens; this includes data on production conditions (i.e. quality and quantity of light, duration, temperature, relative humidity, CO2 concentration, etc.), and outputs (e.g. ascorbic acid, fresh weight, glucosinolates, etc.). There are 42 papers on microgreens production that vary light conditions in this database, with each paper described by title, author, methodology, yield parameters, and results. Values presented in the papers were extracted from both tables and figures. Data was mined from figures via the Automeris software (https://apps.automeris.io/wpd/). Data is presented per row, with each unique treatment's value having a corresponding row, including common environmental description (such as temperature, relative humidity, etc.). The only modification to the data was made for either a) converting between metric units, or b) transforming data from dry weight to fresh weight, using experimental values for species-specific conversion ratios, as mentioned in GOhydro Deliverable 1.1, which presents both discussion about, and presentation of, the data contained in this dataset. </p> <p>Where the data is highlighted in red, this means that the data is either a) a variable that cannot be compared to others, or b) was such an outlier that it was not used for comparison purposes. Either way, the highlighted red data was not used for comparison purposes which presented results in the Deliverable 1.1. </p> <p>Where possible, all data are presented for both means and standard errors. For instance, the standard errors are presented in the adjacent columns next to labeled value columns. </p> <p>Extra sheets contain screenshots or data extracted from the corresponding papers. A full reference sheet can be found in GOhydro Deliverable 1.1 to locate specific papers. </p>
Database: Frameworks 21 century skills for development future skills in education 4.0: Systematic Literature Review
<p> Los datos revelan (a) la literatura de los frameworks destacan estudios de casos y estrategias de enseñanza aprendizaje vinculadas con las competencias del siglo XXI; (b) se ubican áreas de oportunidad para evidenciar publicaciones que aborden competencias de carácter y de metalearning; (c) los componentes de educación 4.0 que han sido abordados en los frameworks son: research strategies to apply knowledge and reflection strategies to encourage self system thinking; (d) las dimensiones de aprendizaje donde se han ubicado los frameworks son Skills and Knowledge y, (e ) destaca ausencia de frameworks dirigidos hacia profesores y a escuelas</p>
[SZESLR] Semi-automated Systematic Literature Review (SLR) Design and P-graph (Process Graph Theory) SLR Database
<p>(c) Széchenyi István University and Artificial Intelligence National Laboratory (MILAB)</p> <p>A proposed semi-automated Systematic Literature Review (SLR) design has been deployed to conduct an exhaustive literature review on contributions concerning applications of the P-graph framework as a case study. The P-graph framework (<a href="https://p-graph.org/">https://p-graph.org</a>) was initially conceived for solving problems related to the synthesis of chemical processes; in particular, the framework has been useful for developing sustainable and resilient systems.</p> <p>The current contribution includes the P-graph SLR database itself, and additionally, the Python scripts used to generate such results. The case study has been selected in view of the authors’ familiarity with the P-graph framework, and because they maintain a manually-collected database of works on the subject. The contributions concerning the framework are easily distinguishable from others involving similar methodologies. It was observed that the implementation of the proposed SLR design extended prior review papers on the P-graph framework and provided additional information on authors and institutions devoted to research on this subject.</p> <p>Generally, it is expected that the dataset will assist researchers, scholars, and practitioners concerned with industrial sustainability in streamlining their literature reviews, thus accelerating the acquisition of pertinent publications that could advance and enrich their own research works on such a subject. Moreover, it is expected that, with proper adaptation, the proposed semi-automated SLR design can be applied to conduct literature reviews in other scientific fields whose results can be validated against existing reviews when available.</p> <p>The normalized P-graph database hereby presented thus can be used as a source of validated information for researchers. The P-graph database was uploaded in various file formats that support database management software (e.g. Zotero .RIS) as well as an "EasyHandle" MS Office (.XLSX) file.</p>
Biological invasions: a field synopsis, systematic review, and database of the literature
Species introductions of anthropogenic origins are a major aspect of rapid ecological change globally. Research on biological invasions has generated literature on many different aspects of this phenomenon. This literature is enormous and has grown rapidly since the mid‐twentieth century. Therefore, we created this dataset in order to describe and categorize some aspects of this literature, to better understand what has been studied and what we know, mapping well‐studied areas and important gaps. To do so, we employed the techniques of systematic reviewing widely adopted in other scientific disciplines. We identified 2398 relevant studies in a field synopsis of the biological invasions literature. The purpose of the field synopsis was to map and categorize the scope of available information (and what is not known) from the literature addressing a fundamental understanding of biological invasions. We then examined 1537 papers in greater detail in a systematic review. The systematic review addressed the state of our knowledge about the mechanisms that permit species to invade novel environments. We carried this out by attempting to identify and characterize the literature, including what hypotheses have been tested, and what organisms and systems have been studied. A secondary goal of our work was to create a publicly accessible database of this literature for future research.
Database of Systematic review of the literature. Planning of ICT in educational centers
<pre>These documents include a database of RSL articles developed on strategic planning in the integration of ICT in educational centers.</pre>
International comparison of cross-disciplinary integration in industry 4.0: A co-authorship analysis using academic literature databases
<p>In innovation strategy, a type of Schumpeterian competitive strategy in business administration, "intra-individual diversity" has attracted attention as one factor for creating innovation. In this study, we redefine "framework for identifying researchers' areas of expertise" as "a framework for quantifying intra-individual diversity among researchers. Note that diversity here refers to authorship of articles in multiple research fields. The application of this framework then made it possible to visualize organizational diversity by accumulating the intra-individual diversity of researchers and to discuss the innovation strategy of the organization. The analysis in this study discusses how countries are promoting research on the topics of artificial intelligence (AI), big data, and Internet of Things (IoT) technologies, which are at the core of Industry 4.0, from an innovation perspective. Note that Industry 4.0 is a technological framework that aims to "improve the efficiency of all social systems," "create new industries," and "increase intellectual productivity." For the analysis, we used 19-year bibliographic data (2000–2018) from the top 20 countries in terms of the number of papers in AI, big data, and IoT technologies. As the results, this study classified the styles of cross-disciplinary fusion into four patterns in AI and three patterns in big data. This study did not consider the results in IoT because of only small differences between countries. Furthermore, regional differences in the style of cross-disciplinary fusion were also observed, and the global innovation patterns in Industry 4.0 were classified into seven categories. In Europe and North America, the cross-disciplinary integration style was similar to that between the United States, Germany, the Netherlands, Spain, England, Italy, Canada, and France. In Asia, the cross-disciplinary fusion style was similar between China, Japan, and South Korea.</p>
Literature consistency of bioinformatics sequence databases is effective for assessing record quality
<p>Bioinformatics sequence databases such as Genbank or UniProt contain hundreds of millions of records of genomic data. These records are derived from direct submissions from individual laboratories, as well as from bulk submissions from large-scale sequencing centres; their diversity and scale means that they suffer from a range of data quality issues including errors, discrepancies, redundancies, ambiguities, incompleteness and inconsistencies with the published literature. In this work, we seek to investigate and analyze the data quality of sequence databases from the perspective of a curator, who must detect anomalous and suspicious records. Specifically, we emphasize the detection of inconsistent records with respect to the literature. Focusing on GenBank, we propose a set of 24 quality indicators, which are based on treating a record as a query into the published literature, and then use query quality predictors. We then carry out an analysis that shows that the proposed quality indicators and the quality of the records have a mutual relationship, in which one depends on the other. We propose to represent record literature consistency as a vector of these quality indicators. By reducing the dimensionality of this representation for visualization purposes using principal component analysis, we show that records which have been reported as inconsistent with the literature fall roughly in the same area, and therefore share similar characteristics. By manually analyzing records not previously known to be erroneous that fall in the same area than records know to be inconsistent, we show that one record out of four is inconsistent with respect to the literature. This high density of inconsistent record opens the way towards the development of automatic methods for the detection of faulty records. We conclude that literature inconsistency is a meaningful strategy for identifying suspicious records.</p>
D6.1 - Report on non-technical barrier and legal issues - Literature-mapping database
<p>This data set presents a literature map for D6.1 "Report on non-technical barrier and legal issues" considering relevant non-technical and legal challenges for consideration during the deployment of a pay-per-wash business model in European.</p>
Systematic Literature Review Database
<p>Database used in the point 2.2 of my thesis "Intercultural competencies development to foster professional collaboration among countries". </p>
International comparison of cross-disciplinary integration in industry 4.0: A co-authorship analysis using academic literature databases
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Literature database on natural climate solutions implementation
<p>Database of literature reviewed in the publication "What influences the implementation of natural climate solutions? A systematic map and review of the evidence" (Schulte et al., 2021). </p>
RegEl Database: text-mined regulatory elements from the literature and their associations to genes and disease
<pre>@article{garda2022regel, title={RegEl corpus: identifying DNA regulatory elements in the scientific literature}, author={Garda, Samuele and Lenihan-Geels, Freyda and Proft, Sebastian and Hochmuth, Stefanie and Sch{\"u}lke, Markus and Seelow, Dominik and Leser, Ulf}, journal={Database}, volume={2022}, year={2022}, publisher={Oxford Academic} } </pre> <p># RegEl PubMed Database</p> <p>This database contains the annotations generated by running [HunFlair](https://github.com/flairNLP/flair/blob/master/resources/docs/HUNFLAIR.md) models trained on the [RegEl corpus](https://zenodo.org/record/5776679) over >20M PubMed abstracts.</p> <p>By pairing these annotations with the one provided by PubTator this generates a large text mining database of regulatory elements associated with genes (normalized to NCBI Gene ids) and disease (normalized to either MeSH or OMIM).</p> <p>The tables composing the database are:</p> <p>* abstracts.db:<br> - pmid = PubMed ID of the given abstracts<br> - sid = sentence ID of the given abstracts (from 0 to # of sentences)<br> - text = text of the given sentence</p> <p>* gene.db and disease.db:<br> - pmid = PubMed ID of the given abstracts<br> - sid = sentence ID of the given abstracts (from 0 to # of sentences)<br> - etype = entity type (enhancer, promoter, TFBS)<br> - ann_text = mention of the regulatory element as found in the abstract<br> - start = position (# character) in which the mention begins<br> - end = position (# characters) in which the mention ends<br> - score = model's confidence<br> - cui = gene or disease identifier<br> - cui_symbol = official symbol of cui (if available)</p>
Body length trait values from the BETSI database, on all Collembola species, all literature sources, requested on 01-06-2017
<p><strong>This table gathers 'Body length' trait values extracted from the BETSI database, on all Collembola species, all literature sources, on 01/06/2017 (DD/MM/YYYY).</strong><br> <br> The BETSI database hosts soil invertebrates trait data.<br> The BETSI database is available here: <a href="http://betsi.cesab.org">http://betsi.cesab.org</a><br> The BETSI database is regularly updated. Please follow the link and contact its administrators if you want to obtain the most up-to-date data ; or contact the dataset's author if you need information on how to use the present dataset.</p> <p><br> <strong>Information in this table</strong><br> <em>BETSI coder</em>: First name and family name of the person that provided the trait value and uploaded it into the BETSI database<br> <em>Collembola species</em>: Collembola species name, taxonomy according to Fauna Europaea<br> <em>Body length value</em>: Trait value, in mm<br> <em>Literature source</em>: Literature source in which the trait value was collected by the BETSI coder<br> <br> This dataset was created, used, and shared with the approval of all concerned BETSI coders (data collectors) and administrators (data managers).</p> <p> </p> <p><strong>If you aim to re-use this dataset:</strong><br> <br> - please cite <strong>Bonfanti et al. (2018) <em>Functional ecology </em></strong><a href="https://doi.org/10.1111/1365-2435.13194">https://doi.org/10.1111/1365-2435.13194</a>, study for which this dataset was originally requested and compiled ;<br> - please give appropriate credit to the concerned BETSI coders and administrators, BETSI database project, and to the authors of the literature sources mentioned in the dataset.</p>
Data from: Characterizing terminology applied by authors and database producers to informatics literature on consumer engagement with wearable devices
<p><span>To recommend strategies to improve discoverability of consumer health informatics (CHI) literature, we aimed to characterize controlled vocabulary and author terminology applied to a subset of CHI literature on wearable technologies. </span>A descriptive analysis of articles (N=2,522) from 2019 identified 308 (12.2%) CHI-related articles for which the citations with PubMed identifiers for the included and excluded studies are provided. The 308 articles were published in 181 journals which we classified by type of journal—health, informatics, technology and other—as shown in the third file. We provide an aggregated file of the author-assigned keywords as they appeared in the PubMed records of the included studies along with our decision about whether they represented consumer engagement. We also included an aggregated file of the Medical Subject Headings assigned to the included studies. The top 100 terms and their frequency scores for the title and abstracts are also included. We did not include any of the terminology from CINAHL, and Engineering Databases (Compendex and Inspec together) due to copyright concerns.</p>
Data from: Characterizing terminology applied by authors and database producers to informatics literature on consumer engagement with wearable devices
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Dataset of biofouling epibionts on microalgae compiled from literature and environmental variables from open access databases
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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.