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2,359 results for “Online”
Back to the edge: relative coordinate system for use-wear analysis [complement to Online Resource 3]
<p>3D micro surface data processed in ConfoMap v7.4.8633 (a derivative of MountainsMap Imaging Topography developed by Digital Surf, Besançon, France).</p> <p>Instructions to download all files at once are given here: <a href="https://doi.org/10.5281/zenodo.4011952">https://doi.org/10.5281/zenodo.4011952</a></p>
The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews (data repository)
<p>These are the data we generated in our evaluation of the graphical user interface.</p> <p>Please see our publication on Wellcome Open Research for information about the evaluations.</p>
Online Public Shaming on Twitter- Dataset
<p>This dataset contains about 870k unlabelled and 1227 labelled collection of tweet ids of several public shaming events in Twitter. Go through the included README file.</p> <p>Refer to the paper below for more details.</p> <p>Basak, Rajesh, Shamik Sural, Niloy Ganguly, and Soumya K. Ghosh. "Online Public Shaming on Twitter: Detection, Analysis, and Mitigation." IEEE Transactions on Computational Social Systems (2019)</p>
Bibliographic dataset characterizing studies that use online biodiversity databases
<p>This dataset includes bibliographic information for 501 papers that were published from 2010-April 2017 (time of search) and use online biodiversity databases for research purposes. Our overarching goal in this study is to determine how research uses of biodiversity data developed during a time of unprecedented growth of online data resources. We also determine uses with the highest number of citations, how online occurrence data are linked to other data types, and if/how data quality is addressed. Specifically, we address the following questions:</p> <p>1.) What primary biodiversity databases have been cited in published research, and which</p> <p> databases have been cited most often?</p> <p>2.) Is the biodiversity research community citing databases appropriately, and are</p> <p> the cited databases currently accessible online?</p> <p>3.) What are the most common uses, general taxa addressed, and data linkages, and how </p> <p> have they changed over time?</p> <p>4.) What uses have the highest impact, as measured through the mean number of citations</p> <p> per year?</p> <p>5.) Are certain uses applied more often for plants/invertebrates/vertebrates?</p> <p>6.) Are links to specific data types associated more often with particular uses?</p> <p>7.) How often are major data quality issues addressed?</p> <p>8.) What data quality issues tend to be addressed for the top uses? </p> <p>Relevant papers for this analysis include those that use online and openly accessible primary occurrence records, or those that add data to an online database. Google Scholar (GS) provides full-text indexing, which was important to identify data sources that often appear buried in the methods section of a paper. Our search was therefore restricted to GS. All authors discussed and agreed upon representative search terms, which were relatively broad to capture a variety of databases hosting primary occurrence records. The terms included: “species occurrence” database (8,800 results), “natural history collection” database (634 results), herbarium database (16,500 results), “biodiversity database” (3,350 results), “primary biodiversity data” database (483 results), “museum collection” database (4,480 results), “digital accessible information” database (10 results), and “digital accessible knowledge” database (52 results)--note that quotations are used as part of the search terms where specific phrases are needed in whole. We downloaded all records returned by each search (or the first 500 if there were more) into a Zotero reference management database. About one third of the 2500 papers in the final dataset were relevant. Three of the authors with specialized knowledge of the field characterized relevant papers using a standardized tagging protocol based on a series of key topics of interest. We developed a list of potential tags and descriptions for each topic, including: database(s) used, database accessibility, scale of study, region of study, taxa addressed, research use of data, other data types linked to species occurrence data, data quality issues addressed, authors, institutions, and funding sources. Each tagged paper was thoroughly checked by a second tagger.</p> <p>The final dataset of tagged papers allow us to quantify general areas of research made possible by the expansion of online species occurrence databases, and trends over time. Analyses of this data will be published in a separate quantitative review.</p>
Supporting data for: "Diaphysator: an online application for the exhaustive cartography and user-friendly statistical analysis of long bone diaphyses"
<p>Example of dataset to be used with the R-shiny application “Diaphysator”, composed of right tibiae and femora.</p> <p>These data file have been published in: Lacoste Jeanson, A., Santos, F., Villa, C., Banner, J., & Bruzek, J. (2018). Architecture of the femoral and tibial diaphyses in relation to body mass and composition: Research from whole-body CT. <em>American Journal of Physical Anthropology</em>, 167, 813– 826. doi: <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/ajpa.23713">10.1002/ajpa.23713</a></p> <p>This zip file contains:</p> <ul> <li>an “Information file” in CSV format</li> <li>various data files for human femora and tibiae in CSV format</li> </ul> <p>For all CSV files, the field separator is the comma “,” and the character used for decimal points is the dot “.”</p>
Online Appendix - Scented Since the Beginning: On the Diffuseness of Test Smells in Automatically Generated Test Code
<p>Online appendix for the paper "Scented Since the Beginning: On the Diffuseness of Test Smells in Automatically Generated Test Code".</p> <p>The full description of the content of this appendix can be found in the README file.</p>
Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information and Social Tags on Information Search and Evaluation
<p>ABSTRACT</p> <p>Background: The public typically believes psychotherapy to be more effective than pharmacotherapy for depression treatments. This is not consistent with current scientific evidence, which shows that both types of treatment are about equally effective.</p> <p>Objective: The study investigates whether this bias towards psychotherapy guides online information search and whether the bias can be reduced by explicitly providing expert information (in a blog entry) and by providing tag clouds that implicitly reveal experts’ evaluations.</p> <p>Methods: A total of 174 participants completed a fully automated Web-based study after we invited them via mailing lists. First, participants read two blog posts by experts that either challenged or supported the bias towards psychotherapy. Subsequently, participants searched for information about depression treatment in an online environment that provided more experts’ blog posts about the effectiveness of treatments based on alleged research findings. These blogs were organized in a tag cloud; both psychotherapy tags and pharmacotherapy tags were popular. We measured tag and blog post selection, efficacy ratings of the presented treatments, and participants’ treatment recommendation after information search.</p> <p>Results: Participants demonstrated a clear bias towards psychotherapy (mean 4.53, SD 1.99) compared to pharmacotherapy (mean 2.73, SD 2.41; <em>t</em><sub>173</sub>=7.67, <em>P</em><.001, <em>d</em>=0.81) when rating treatment efficacy prior to the experiment. Accordingly, participants exhibited biased information search and evaluation. This bias was significantly reduced, however, when participants were exposed to tag clouds with challenging popular tags. Participants facing popular tags challenging their bias (n=61) showed significantly less biased tag selection (<em>F</em><sub>2,168</sub>=10.61, <em>P</em><.001, partial eta squared=0.112), blog post selection (<em>F</em><sub>2,168</sub>=6.55, <em>P</em>=.002, partial eta squared=0.072), and treatment efficacy ratings (<em>F</em><sub>2,168</sub>=8.48, <em>P</em><.001, partial eta squared=0.092), compared to bias-supporting tag clouds (n=56) and balanced tag clouds (n=57). Challenging (n=93) explicit expert information as presented in blog posts, compared to supporting expert information (n=81), decreased the bias in information search with regard to blog post selection (<em>F</em><sub>1,168</sub>=4.32, <em>P</em>=.04, partial eta squared=0.025). No significant effects were found for treatment recommendation (<em>P</em>s>.33).</p> <p>Conclusions: We conclude that the psychotherapy bias is most effectively attenuated—and even eliminated—when popular tags implicitly point to blog posts that challenge the widespread view. Explicit expert information (in a blog entry) was less successful in reducing biased information search and evaluation. Since tag clouds have the potential to counter biased information processing, we recommend their insertion.</p>
Need for Explanations - Survey - Online Material
<pre>This dataset contains the results of an online questionnaire to assess the end-users' need for explanations in software systems. The questionnaire was shared in December 2018 and was online until January 2019. 171 participants initiate the survey and 107 completed it. We just analyzed the responses of the participants who completed the survey. This submission contains: The survey raw data in CSV format, separated by comma values; The .xlsx file containing the same raw data; The .pdf file containing the survey questions; A .rtfd version of the survey questions; A .html version of the survey questions; The .xlsx file containing the analyzed data; The .pdf file containing instructions about the coded data. The raw data contains only the responses from the 107 participants who completed the survey. Blank cells indicate that the participant did not provide a response to the corresponding question or answer option. All responses are anonymyzed and identified by an unique ID. _________ Each row is identified by the participant's ID, the date when the questionnaire was submitted, the last page (18 in total) and the language that the participant chose. The subsequent columns contain the questions. We use codes before each question. First, one of the following symbols: (*) as an indication that the question was mandatory; (*+)as an indication that the question was mandatory but was conditionnally shown, depending on previous answers; (+) as an indication that the question was conditionally shown, depending on previous answers; Next, the code of the question as in the questionnaire. And, if multiple choice, the code of the answer option. E.g.: (*+)A2(3) means that the A2 question in the questionnaire was mandatory and conditionally shown, and that this column contains the responses regarding answer option 3. After this code, the question as on the original questionnaire is shown and, when multiple option answer, the corresponding option is shown between [] after the question. E.g.: "In a typical day, which category of software/apps do you use on your digital devices most often? (More than one allowed) [Games]", where Games was one of the optional answers. The questionnaire was available in three languages: Portuguese, German and English. Responses in German and Portuguese were translated to English. These translations are shown in a subsequent column, beside the column with the original responses, and are identified by the word "TRANSLATION" in the title. Responses which were already in English were not translated.</pre>
Final Pool and Online Repository
<p>This file includes all of the classification details of <strong><em>"Quality and Success in Open Source Software: A Systematic Mapping" study.</em></strong></p>
Text-fig. 1. "Plant screen" scheme of complete results of the IPR-vegetation analysis derived from the database. in The Integrated Plant Record Vegetation Analysis: Internet Platform And Online Application
Text-fig. 1. "Plant screen" scheme of complete results of the IPR-vegetation analysis derived from the database.
Figure 1 in EphemBrazil: a curated online database and dashboard to explore the distribution of mayflies (Insecta: Ephemeroptera) from Brazil
Figure 1 General view of the website and interactive map view tab showing filters on the top and family subtitles in the right corner. Note that no filter is applied and all records are shown.
Fig. 2 in Reptiles of Ecuador: a resource-rich online portal, with dynamic checklists and photographic guides
Fig. 2. Biogeographic regions of Ecuador. Source: https://bioweb.bio (modified from Sierra et al. 1999).
Fig. 1 in Reptiles of Ecuador: a resource-rich online portal, with dynamic checklists and photographic guides
Fig. 1. Histogram showing the description of reptile species present in Ecuador through time, from Linnaeuss 10th edition of Systema Naturae to the end of 2018. The number of species described per decade is presented above each bar.
The mOTUs online database provides web-accessible genomic context to taxonomic profiling of microbial communities - Supplementary Tables
<p><strong>Supplementary Table 1:</strong></p> <p>A map between each of the genomes in mOTUs-db (3’747’151), the associated study and its metagenomic sample (in case of MAGs).</p> <p>Columns:</p> <p><code> GENOME → Unique mOTUs-db name of the genome</code><br><code> STUDY → Unique mOTUs-db name of the study</code><br><code> IS_MAG → True if genome is a MAG, otherwise False </code><br><code> METAGENOMIC_SAMPLE → Unique name of the metagenomic sample or NA in case of non-MAG genome</code></p> <p>Example:</p> <p><code> GENOME STUDY IS_MAG METAGENOMIC_SAMPLE</code><br><code> ---------------------------------------------------------------------------------------------</code><br><code> ACIN21-1_SAMN05421555_MAG_00000001 ACIN21-1 True ACIN21-1_SAMN05421555_METAG</code><br><code> RSGB23-1_GCA-006096615-V1_GENO_10000001 RSGB23-1 False NA</code></p> <p><strong>Supplementary Table 2:</strong></p> <p>A map between all non-MAG genomes (919’090) and their source (e.g. Refseq or JGI).</p> <p>Columns:</p> <p><code> GENOME → Unique mOTUs-db name of the genome</code><br><code> SOURCE_SAMPLE_LINK → Link to the original location of this genome</code></p> <p>Example:</p> <p><code> #GENOME SOURCE_SAMPLE_LINK</code><br><code> --------------------------------------------------------------------------------------------------------</code><br><code> JGIG23-1_GA0055041_GENO_10000001 https://gold.jgi.doe.gov/analysis_project?id=Ga0055041</code><br><code> RSGB23-1_GCA-006717865-V1_GENO_10000001 https://www.ncbi.nlm.nih.gov/datasets/genome/GCA_006717865.1</code></p> <p><strong>Supplementary Table 3:</strong></p> <p>A list of all metagenomic studies processed for the mOTUs-db, their number of samples, the number of reconstructed MAGs and the associated publication.</p> <p>Columns:</p> <p><code> STUDY --> Unique mOTUs-db study identifier</code><br><code> BIOPROJECT --> Public identifier (NCBI/JGI) of metagenomic sequencing project</code><br><code> SAMPLES --> Number of metagenomic samples</code><br><code> MAGs --> Number of reconstructed MAGs</code><br><code> PUBLICATION --> Link to publication</code></p> <p>Example:</p> <p><code> STUDY BIOPROJECT SAMPLES MAGs PUBLICATION</code><br><code> -------------------------------------------------------------------------------------------------</code><br><code> ACIN21-1 PRJEB44456 58 1,110 https://www.nature.com/articles/s42003-021-02112-2</code></p> <p><strong>Supplementary Table 4:</strong></p> <p>Mapping between mOTUs-db sample identifier, the associated biosample and the environment.</p> <p>Columns:</p> <p><code> SAMPLE --> Unique mOTUS-db sample identifier</code><br><code> BIOSAMPLE --> Public identifier (NCBI/JGI) of metagenomic sample</code><br><code> STUDY --> Unique mOTUs-db study identifier</code><br><code> ENVIRONMENT --> Environment of metagenomic sample</code><br><code> SOURCE_SAMPLE_LINK --> Link to the original location of this sample</code></p> <p>Example:</p> <p><code> #SAMPLE BIOSAMPLE STUDY ENVIRONMENT SOURCE_SAMPLE_LINK</code><br><code> ---------------------------------------------------------------------------------------------------------------------</code><br><code> ACIN21-1_SAMN05421555_METAG SAMN05421555 ACIN21-1 marine https://www.ncbi.nlm.nih.gov/biosample/SAMN05421555/</code></p> <p><strong>Supplementary Table 5:</strong></p> <p>A list of environments covered in the mOTUs-db mapped to the respective NCBI taxonomy (if possible)</p> <p>Columns:</p> <p><code> TERM --> Unique environment name</code><br><code> NCBI TAXONOMY ID --> Link to the NCBI taxonomy</code></p> <p>Example:</p> <p><code> TERM NCBI TAXONOMY ID</code><br><code> ----------------------------------------------</code><br><code> activated sludge metagenome NCBI:txid942017</code><br><code> air metagenome NCBI:txid655179</code></p>
FIGURE 3 in Twenty Years Online! A brief history of Palaeontologia Electronica
FIGURE 3. Research articles published in Palaeontologia Electronica for each year (2017 exclusive), expressed as a percentage of each palaeontological sub-discipline. This represents a somewhat more arbitrary (compared to Figure 2) assignment of each research article to one of 11 palaeontological sub-disciplines. This assignment is more arbitrary because many articles aren't easily categorised into a single sub-discipline and, depending on subject matter, the sub-disciplines themselves can overlap. Other articles, particularly highly technical articles, don't always fit so neatly within any strictly palaeontological sub-discipline. Nevertheless, primarily on the basis of article title, with reference to the abstract and keywords where necessary, each article has been assigned as Museum/Education, Micropalaeontology, Palaeobotany, Palynology, Invertebrate Palaeontology, Vertebrate Palaeontology, Taphonomy, Ichnology, Palaeoecology, Epistemology/Philosophy, and Stratigraphy/Geology.
FIGURE 2 in Twenty Years Online! A brief history of Palaeontologia Electronica
FIGURE 2. Research articles published in Palaeontologia Electronica for each year (2017 exclusive), expressed as a percentage of each article category. Over the years PE has published research articles in a number of sub-categories: a Critical Review category was used briefly, Technical Articles have been differentiated from Research Articles since 2009, and the Fossil Calibration Articles were introduced in 2015. However, for consistency and in order to examine our 20 year trends, I have gone back through all research articles and retroactively assigned each to one of five categories: Research, Technical, Taxonomic, Review/Atlas/Guide, and Fossil Calibration.
FIGURE 1 in Twenty Years Online! A brief history of Palaeontologia Electronica
FIGURE 1. Numbers of published articles in Palaeontologia Electronica, per year (2017 exclusive). This graph was drawn using PAST ver. 2.17c (Hammer et al. 2001).
Educational data collected from parents - regarding the analysis of online activities in schools in Romania (during the Covid-19 pandemic, March 2020 - April 2020)
<p>The responses of the 784 parents were collected through the questionnaire available at: <a href="https://forms.gle/Km8WE5QamrYYgXJi7" target="_new" rel="noopener"><strong>https://forms.gle/Km8WE5QamrYYgXJi7</strong></a></p> <p>It was designed with various types of responses, including binomial (yes/no), polynomial (multiple options), and open-ended responses, to capture a comprehensive range of data. This combined approach allows for both quantitative analysis of fixed-response questions and qualitative insights from open-ended questions. Patterns, correlations, and differences between various demographic groups and their experiences and attitudes toward online education can be identified.</p> <p>To protect the identity of the respondents and to obtain accurate responses, all data collected from teachers was anonymous. We did not collect any personal information whatsoever. This aspect was made clear to the respondents in the description of the questionnaire.</p>
TRY 6.0 - Species List from Taxonomic Harmonization – Matches with World Flora Online version 2023.12
<p>Standardized names for TRY 6.0 are available from the TRY File Archive (TFA; see here: <a href="https://www.try-db.org/TryWeb/Data.php#100">https://www.try-db.org/TryWeb/Data.php#100</a>); these were created for the following publication:</p> <p>Schellenberger Costa, D., Boehnisch, G., Freiberg, M., Govaerts, R., Grenié, M., Hassler, M., Kattge, J., Muellner-Riehl, A.N., Rojas Andrés, B.M., Winter, M., Watson, M., Zizka, A. and Wirth, C. (2023), The big four of plant taxonomy – a comparison of global checklists of vascular plant names. New Phytol, 240: 1687-1702. <a href="https://doi.org/10.1111/nph.18961">https://doi.org/10.1111/nph.18961</a></p> <p>Here matched records are provided with the taxonomic backbone of World Flora Online (WFO) version 2023.01, obtained from <a href="https://zenodo.org/records/10425161">https://zenodo.org/records/10425161</a>.</p> <p>Matches with WFO are given in the Zenodo archive in the fields for <em>SID</em> (=taxonID in WFO), <em>scientificName</em> (as in WFO) and <em>scientificNameAuthorship</em> (as in WFO). Fields of <em>TRY_SpeciesID</em>, <em>TRY_AccSpeciesNameScientific</em> and <em>RecommendedScientificName</em> were directly obtained from the TFA.</p> <p> </p> <p>Matching was done via following steps:</p> <p>1. Fungi matched in the TFA via the <a href="http://indexfungorum.org">http://indexfungorum.org</a> were excluded (4,099 records).</p> <p>2. The matching record in WFO was obtained by matching the TFA field of <em>TPL_ID</em> with the WFO field of <em>tplID</em>. Successful matches via this method are indicated in this Zenodo archive by the field of <em>MATCH</em> being set to <strong><em>TPL ID</em></strong>.</p> <p>3. Where matches in WFO included a non-empty <em>acceptedNameUsageID</em>, the currently accepted name of the taxon was obtained via this ID. Successful matches via this method are indicated in this Zenodo archive by the field of <em>MATCH</em> being set to <strong><em>TPL ID</em></strong> and fields of <em>synonymID, scientificName.synonym</em> and scientificNameAuthorship.synonym showing details for the match with the synonym.</p> <p>4. Taxa that were not matched in previous steps were matched for the TFA field of <em>MatchedName</em>. Matching was done via the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora package</a> version 1.14-5 (<a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">Kindt 2020</a>). Matches expected to be acceptable after visual inspection are indicated in this Zenodo archive by the field of <em>MATCH</em> being set to <strong><em>manual</em></strong><em>.</em> Taxa at specific and infraspecific levels from the TFA where matches had only been achieved at generic levels for the <em>MatchedName</em> were excluded in this step.</p> <p>5. Taxa that were not matched in previous steps were matched for the TFA field of <em>TRY_AccSpeciesName</em>. Matching was done via the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora package</a> version 1.14-5 (<a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">Kindt 2020</a>). Matches expected to be acceptable after visual inspection are indicated in this Zenodo archive by the field of <em>MATCH</em> being set to <strong><em>manual</em></strong><em>.</em></p> <p>6. Taxa that were not matched in previous steps were matched for the TFA field of <em>AlternativeName</em>. Matching was done via the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora package</a> version 1.14-5 (<a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">Kindt 2020</a>). Matches expected to be acceptable after visual inspection are indicated in this Zenodo archive by the field of <em>MATCH</em> being set to <strong><em>manual</em></strong><em>.</em></p> <p>7. Taxa that were not matched in previous steps were matched for the TFA field of <em>MatchedName</em> against <a href="https://sftp.kew.org/pub/data-repositories/WCVP/Archive/">version 11 of the World Checklist of Vascular Plants</a>. Matching was also done via the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora package</a> version 1.14-5 (<a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">Kindt 2020</a>), with similar scripts <a href="https://rpubs.com/Roeland-KINDT/1134151">as shown in this Rpub</a>. Matches expected to be acceptable after visual inspection are indicated in this Zenodo archive by the field of <em>MATCH</em> being set to <strong><em>manual</em></strong><em> </em>and by the field of <em>SID</em> (and possibly <em>synonymID</em>) containing records where the WCVP ID is preceded by WCVP-.</p> <p>8. 836 records where neither the TFA nor the previous steps managed to establish a match were removed.</p> <p>9. Taxa that could not be matched in previous steps are flagged by the field of <em>MATCH</em> being set to <strong><em>NONE - no species MatchedName</em></strong><em> </em>(where TFA also did not achieve a match at the required specific or infraspecific level) or <strong><em>NONE</em></strong> (other records where no match was achieved).</p> <p> </p> <p>The Zenodo archive contains 406,208 records with matches via the TPL, 96,040 records with manual matches, 1,822 records where the TFA also not achieve matches at required (infra-)specific levels and 361 records where no match was achieved (among this latter category were 202 records flagged in TFA as ‘not found in WFO’ and 140 records flagged in TFA as ‘found only here’).</p> <p> </p> <p>Version 2024.10b was created with added fields from TFA of <em>TRY_SpeciesName</em> and <em>BackboneDatabase</em>. This was done especially to explain different matches for records with the same <em>RecommendedScientificName </em>but with different matches to WFO, as for example for <em>Acacia adunca</em> A.Cunn. & G.Don and <em>Acacia aestivalis</em> E.Pritz.</p> <p> </p> <p><strong>References</strong></p> <ul> <li>Kattge J. 2023. TRY 6.0 - Species List from Taxonomic Harmonization. <a href="https://www.try-db.org/TryWeb/Data.php#100">https://www.try-db.org/TryWeb/Data.php#100</a></li> <li>Schellenberger Costa, D., Boehnisch, G., Freiberg, M., Govaerts, R., Grenié, M., Hassler, M., Kattge, J., Muellner-Riehl, A.N., Rojas Andrés, B.M., Winter, M., Watson, M., Zizka, A. and Wirth, C. (2023), The big four of plant taxonomy – a comparison of global checklists of vascular plant names. New Phytol, 240: 1687-1702. <a href="https://doi.org/10.1111/nph.18961">https://doi.org/10.1111/nph.18961</a></li> <li>The World Flora Online Consortium, Alan Elliott, Roger Hyam, William Ulate, Mark Watson, Gregory Anderson, Giovani carlos Andrella, et al. “World Flora Online Plant List December 2023”. Zenodo, December 22, 2023. <a href="https://doi.org/10.5281/zenodo.10425161" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10425161</a>.</li> <li>Kindt R (2020). “WorldFlora: An R package for exact and fuzzy matching of plant names against the World Flora Online taxonomic backbone data.” <em>Applications in Plant Sciences</em>, <strong>8</strong>(9), e11388. <a href="https://doi.org/10.1002/aps3.11388">https://doi.org/10.1002/aps3.11388</a></li> <li>Borsch, T., Berendsohn, W., Dalcin, E., Delmas, M., Demissew, S., Elliott, A., Fritsch, P., Fuchs, A., Geltman, D., Güner, A., Haevermans, T., Knapp, S., le Roux, M.M., Loizeau, P.-A., Miller, C., Miller, J., Miller, J.T., Palese, R., Paton, A., Parnell, J., Pendry, C., Qin, H.-N., Sosa, V., Sosef, M., von Raab-Straube, E., Ranwashe, F., Raz, L., Salimov, R., Smets, E., Thiers, B., Thomas, W., Tulig, M., Ulate, W., Ung, V., Watson, M., Jackson, P.W. and Zamora, N. (2020), World Flora Online: Placing taxonomists at the heart of a definitive and comprehensive global resource on the world's plants. TAXON, 69: 1311-1341. <a href="https://doi.org/10.1002/tax.12373">https://doi.org/10.1002/tax.12373</a></li> <li>Govaerts, R., Nic Lughadha, E., Black, N. <em>et al.</em> The World Checklist of Vascular Plants, a continuously updated resource for exploring global plant diversity. <em>Sci Data</em> <strong>8</strong>, 215 (2021). <a href="https://doi.org/10.1038/s41597-021-00997-6">https://doi.org/10.1038/s41597-021-00997-6</a></li> </ul> <p> </p> <p>The development of this archive supported by the <strong>Darwin Initiative</strong> to project DAREX001 of <em>Developing a Global Biodiversity Standard certification for tree-planting and restoration</em>, by <strong>Norway’s International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia</strong> to the <em>Provision of Adequate Tree Seed Portfolio</em> project in Ethiopia, by the <strong>Green Climate Fund</strong> through the IUCN-led <em>Transforming the Eastern Province of Rwanda through Adaptation</em> project and through the <em>Readiness proposal on Climate Appropriate Portfolios of Tree Diversity for Burkina Faso</em>, by the <strong>Bezos Earth Fund</strong> to the <em>Bezos Quality Tree Seed for Africa in Kenya and Rwanda</em> project and by the <strong>German International Climate Initiative (IKI)</strong> to the regional tree seed programme on <em>The Right Tree for the Right Place for the Right Purpose in Africa</em>.</p> <p> </p>
Conjunto de dados relacionados á pesquisa sobre a participação e envolvimento de cinco mulheres idosas no processo de codesign online.
<p>Este conjunto de dados faz parte de uma pesquisa mais ampla referente à tese de doutorado, que envolveu dois estudos de caso: um conduzido presencialmente e o outro remotamente. O conjunto de dados atual corresponde ao estudo de caso remoto, com foco em como cinco mulheres idosas participaram e se envolveram no processo de <strong>codesign de interação</strong> realizado remotamente.</p> <p>O conjunto inclui:</p> <ol> <li> <p><strong>Transcrições de Sessões Gravadas e Entrevistas Semiestruturadas</strong></p> <ul> <li>Formato: Arquivos PDF</li> <li>Conteúdo: Transcrições completas das entrevistas semiestruturadas e sessões gravadas com participantes.</li> <li>Exemplos: <ul> <li><em>Transcrições - EntrevistasSemi - IV-ok.pdf</em></li> <li><em>Transcrições - EntrevistasSemi - MN-ok.pdf</em></li> <li><em>Arquivo de áudio - vídeo - 24-08-pdf)</em></li> </ul> </li> </ul> </li> <li> <p><strong>Roda de Conversa</strong></p> <ul> <li>Formato: PDF</li> <li>Conteúdo: Registro de discussões em grupo, com insights sobre o processo de codesign.</li> <li>Exemplo: <em>roda de conversa - letramentodigital-OK.pdf</em></li> </ul> </li> <li> <p><strong>Grelhas de Análise de Conteúdo</strong></p> <ul> <li>Formato: PDF</li> <li>Conteúdo: Grelhas usadas para análise qualitativa de entrevistas e dados de campo.</li> </ul> </li> <li> <p><strong>Diários de Campo</strong></p> <ul> <li>Formato: PDF</li> <li>Conteúdo: Anotações de campo sobre observações durante o processo de coleta de dados, incluindo reflexões sobre os métodos de pesquisa e contextos observados.</li> <li>Exemplos: <ul> <li><em>DIÁRIO DE CAMPO - 12maio.pdf</em></li> <li><em>DIÁRIO DE CAMPO - 08mar.pdf </em></li> <li><em>...</em></li> </ul> </li> </ul> </li> <li> <p><strong>Respostas de Questionários Online</strong></p> <ul> <li>Formato: PDF</li> <li>Conteúdo: Respostas de participantes a questionários online relacionados ao estudo.</li> <li>Exemplos: <ul> <li><em>questionario-online-EI-MN.pdf</em></li> <li><em>...</em></li> </ul> </li> </ul> </li> <li> <p><strong>Modelos de Documentos</strong></p> <ul> <li>Formato: PDF</li> <li>Conteúdo: Modelos de questionários e entrevistas utilizados no estudo.</li> <li>Exemplos: <ul> <li><em>entrevista-semiestruturada-remoto-modelo.pdf</em></li> <li><em>questionario-online-modelo.pdf</em></li> <li><em>formulário online</em></li> </ul> </li> </ul> </li> </ol> <p><strong>Detalhes adicionais:</strong></p> <ul> <li><strong>Período de coleta de dados</strong>: De [junho/2021] a [agosto/2021].</li> <li><strong>Número de participantes</strong>: 5 mulheres idosas.</li> <li><strong>Formato dos dados</strong>: Principalmente PDFs, com transcrições, diários de campo, questionários e grelhas de análise de conteúdo.</li> </ul> <p>Os dados foram coletados conforme as diretrizes éticas estabelecidas pelo Comitê de Ética em Pesquisa da UESB (número de registro 17517019.2.0000.0055), incluindo o consentimento necessário dos participantes para o uso e compartilhamento para fins científicos.</p>
ScienceDex guides
Understand access before you commit
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.