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zenodo52/100

MiRoR15-P1-Tools used to assess the quality of peer review reports: a methodological systematic review

<p>Database, data extraction form, R codes and protocol related to: Superchi C, Gonz&aacute;lez JA, Sol&agrave; I, Cobo E, Hren D, Boutron I.&nbsp;<em>Tools used to assess the quality of peer review reports: a methodological systematic review</em>. BMC Med Res Methodol. 2019;19(48):1&ndash;14. DOI:&nbsp;<a href="https://doi.org/10.1186/s12874-019-0688-x">https://doi.org/10.1186/s12874-019-0688-x</a></p> <p>&nbsp;</p>

opencc-by-4.0Jan 2020View details →
zenodo52/100

Dataset related to the manuscript: "An open-source integrated framework for the automation of citation collection and screening in systematic reviews"

<p>Dataset related to the manuscript: &ldquo;An open-source integrated framework for the automation of citation collection and screening in systematic reviews&rdquo;, to be used together with the code stored at&nbsp;https://github.com/AD-Papers-Material/BART_SystReviewClassifier to reproduce the results.</p> <p>There are three datasets:<br> - The Record data collected from the online scientific databases;<br> - The session journal which describes the search session, i.e., how many records were collected and from which source, for each query/session pairs.<br> - The session data which is the outcome of the classification and review tasks;</p>

opencc-by-4.0Mar 2022View details →
zenodo52/100

Word Embedding of Amazon Product Review Corpus

<p>A word embedding of the <a href="https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html#datasets">Amazon Product Review Corpus</a> (<a href="https://www.doi.org/10.1145/1341531.1341560">Jindal and Liu, 2008</a>).</p> <p>Created using <a href="https://code.google.com/archive/p/word2vec/">Word2Vec</a> in CBOW mode, 500 dimensions and window size 5.</p> <p>Words have been lemmatised and particle verbs have been merged into a single token (e.g. <code>calm_down</code>).</p> <ul> </ul> <p>&nbsp;</p> <p><strong>Attribution</strong></p> <p>This dataset was created as part of the following publication:</p> <p>Marc Schulder,&nbsp;Michael Wiegand,&nbsp;Josef Ruppenhofer&nbsp;and&nbsp;Benjamin Roth&nbsp;(2017).&nbsp;<strong>&quot;Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features&quot;</strong>. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP). Taipei, Taiwan, November 27 - December 3, 2017.&nbsp;<a href="https://doi.org/10.5281/zenodo.3365609">DOI: 10.5281/zenodo.3365609</a>.</p> <p>If you use the data in your research or work, please cite the publication.</p>

opencc-by-4.0Nov 2017View details →
zenodo52/100

A Global Review of Long-range Transported Lead Concentration and Isotopic Ratio Records in Snow and Ice (Supplementary Data)

<p><strong>This is the supplemental material for:</strong></p> <p>Brooks, H.L., Miner, K.R., Kreutz, K.J., Winski, D.A., (in review). A Global Review of Long-range Transported Lead Concentration and Isotopic Ratio Records in Snow and Ice.&nbsp;</p> <p><strong>Purpose:</strong></p> <p>This systematic literature review contextualizes current data availability and examines spatial and temporal gaps in the long-range transported Pb analyses (concentration and isotope ratios) in ice and snow samples. Additionally, we note areas of needed community improvement. It is our hope that researchers will also benefit from a queryable set of references, allowing for quick access to the records appropriate to address multiple research questions.&nbsp;</p> <p><strong>Available Files:</strong></p> <p><em><strong>Table A1:</strong></em> Metadata for Pb records -- Individual sample sites</p> <p><em><strong>Table A2:</strong></em> Metadata for Pb records -- Transect sample sites</p> <p><em><strong>Table A3:</strong></em> Records grouped into 23 regions</p> <p><em><strong>Supplement_fig_25Aug2024: </strong></em>Additional figures supporting main manuscript</p> <p><em><strong>Supplement_method_25Aug2024: </strong></em>Methodology used for the systematic literature review</p> <p><em><strong>Supplement_citations_25Aug2024:</strong></em> Citations for all records included in the systematic literature review</p> <p><em><strong>citations_export.bib:</strong></em> Export of all systematic literature review citation data as bibtex format. Easy import to citation managers (Zotero, Mendley, Endnote, etc)</p> <p><em><strong>indexedReferences.csv:</strong></em> CSV dump of citations_export.bib indexed with citation keys used in TableA.3</p> <p><em><strong>tables.RDS:&nbsp;</strong></em>TableA.1, TableA.2, and indexed References formatted for easy import into R</p> <p><em><strong>tables.sqlite: </strong></em>TableA.1, TableA.2, and indexed References formatted for SQL queries in SQLite</p> <p><em><strong>readme_tables_sqlite.md:</strong></em> Examples of SQLite queries</p> <p>&nbsp;</p> <p><strong>Systematic Literature Review Methodology:</strong></p> <p>To address the current spatial and temporal distribution of long-range transported Pb deposited in the cryosphere (snow-pits and ice cores), we completed a systematic literature review, following the methodology outlined by Booth et al (2016). We completed an &ldquo;exhaustive coverage [search], citing all relevant literature" (Booth et al., 2016), using the search terms &ldquo;Lead (Pb) isotopes and concentration in surface snow, snow pits, and ice cores&rdquo;. We performed an initial comprehensive literature search on these search terms on Web of Science Collection databases in September 2020 and May 2023. Records evaluated for relevance using the title and abstract. Removal of clearly off-topic papers (e.g., the chemistry of penguin feces) gathered in the search due to the dual meaning of &ldquo;lead&rdquo; reduced the paper count to 326 titles. The full text of the remaining publications was evaluated with clear explicit criteria for inclusion and exclusion, based on the following criteria.</p> <ol> <li> <ol> <li>Only studies examining long-traveled background atmospheric lead signals were considered. All point source pollution studies examining the localized effects of traffic, road salt, mines, industry, power plants, human activity at base camp stations, etc, were excluded. An exception was made for samples which were taken at sufficient depths in the analyzed record to predate the pollution source or where wind trajectory did not transport pollution to the collection site regardless of close geographic proximity.</li> <li> <p>Only studies of natural, undisturbed snowpacks and ice cores were examined. Studies which sampled snow from urban structures were excluded. Point source studies of emissions detail the localized effects of traffic, road salt, mines, industry, power plants, and human activity at base camp stations. While meaningful for understanding the direct emissions from various sources and developing new technology aimed at reducing source emissions, point source emission studies do not contribute to the understanding of regional and global signals. Additionally, studies examining the volcanic signal in snow following major modern eruptions were excluded, as this was classified as disturbed snow.</p> </li> <li>Studies must specify the sampling localities by providing a minimum of latitude and longitude. Where sampling locations are only referenced by colloquial names, the distance from point source pollution cannot be verified. Therefore, such studies were excluded.</li> <li> <p>Records of&nbsp;<sup>210</sup>Pb in snow and ice were excluded.&nbsp;<sup>210</sup>Pb is useful for establishing chronology in young snow and ice due to its small half life (~ 22.3 years). But it is not useful for consideration of old records and the source constraint of <sup>210</sup>Pb into the atmosphere is poorly constrained over time (Nijampurkar &amp; Clausen, 1990). Therefore, it cannot be considered in conjunction with Pb isotopes and concentrations. Records of <sup>210</sup>Pb in snow and ice were excluded.</p> </li> <li> <p>Pb isotopes and concentrations taken from cryoconites (soil-like composites of dust, industrial soot, and microbial mats of photosynthetic bacteria) were excluded from this literature review. Cryoconites are important to glacial systems as they alter the albedo of the glacier surface, and therefore affect the glacier melt rate (Fountain et al., 2004). However, they must be considered separately from surface snow, snow pits, and ice cores due to the drastic differences in formation and biologic nature.</p> </li> <li> <p>The publication must be available to the author (<em>e.g.,</em> through the University Library, from collaborators)</p> </li> </ol> </li> </ol> <p>To ensure that the literature search conducted on the Web of Science was robust and complete, citations were checked to ensure inclusion in the literature search results and included when missing. Publications were indexed into Table A.1 and Table A.2. Following the completion of publication indexing, Table A.1 and Table A.2 were evaluated against the 23 regions (Table A.3) -- 20 from RGI 7.0 (RGI 7.0 Consortium, 2023) and 3 author defined regions -- to identify areas/papers that may have been missed in the initial search. Areas with few or no results were searched again using Google Scholar and Web of Science.</p> <p>Based on these searches, we sought to understand the current spatial and temporal coverage of these records, shed light on gaps in the previous research and make recommendations on mitigating these gaps going forward. We used tables and graphics, included in the main text and the supplement, to summarize the characteristics of the compiled records. In the main text, we discuss the limitations and gaps within the current long-range transported Pb literature, and recommend paths to mitigate these gaps. Finally, in the main text, we illustrate an example of how researchers can query this record compilation, allowing for quick access to the records appropriate to address their research questions.</p> <p><strong>Methodology Bibliography:</strong></p> <p>Booth, A., Sutton, A., &amp; Papaioannou, D. (2016). Systematic approaches to a successful literature review (Second edition). Sage.</p> <p>Fountain, A. G., Tranter, M., Nylen, T. H., Lewis, K. J., &amp; Mueller, D. R. (2004). Evolution of cryoconite holes and their contribution to meltwater runoff from glaciers in the McMurdo dry valleys, Antarctica. Journal of Glaciology, 50(168), 35&ndash;45. https://doi.org/10.3189/172756504781830312</p> <p>Nijampurkar, V. N., &amp; Clausen, H. B. (1990). A century old record of lead-210 fallout on the greenland ice sheet. Tellus Series B Chemical and Physical Meteorology, 42(1), 29&ndash;38. https://doi.org/10.1034/j.1600-0889.1990.00005.</p> <p>RGI 7.0 Consortium. (2023). Randolph glacier inventory&mdash;A dataset of global glacier outlines, version 7.0. (Version 7.0) [Dataset]. NSIDC: National Snow and Ice Data Center. https://doi.org/doi:10.5067/f6jmovy5navz</p>

opencc-by-4.0Sep 2022View details →
zenodo52/100

Methane concentrations and oxidation rates in land-terminating glacial runoff: measurements from three glacial rivers and a paraglacial lake in Iceland and a literature review

<div> <p>This dataset contains methane measurements from Icelandic lakes and rivers during the summer of 2018 and 2019. This includes data from net methane oxidation assays with sediment and overlying water from one paraglacial lake and one glacial river, and surface methane concentration data from grab samples in 3 glacial streams and 15 Icelandic lakes (1 of which is paraglacial).&nbsp; The dataset also contains methane concentration data from a synthesis of relevant aquatic ecosystems, used to compare against the original measurements collected.&nbsp;</p> </div> <div> <p>Data and Literature Review Synthesis is supplement to Strock et al. 2024 <em>Oxidation is a potentially significant methane sink in land-terminating glacial runoff</em> published in Nature Scientific Reports.&nbsp;</p> <div> <p>This study was funded by: National Geographic Society Changing Polar Systems grant (CP4-162R-18); In-kind support from the U.S. Geological Survey; Dickinson College Research and Development; Churchill Exploration Fund at Dickinson College&nbsp;</p> </div> </div>

opencc-by-4.0Aug 2024View details →
zenodo48/100

MiRoR2 - P1 - Shortcomings in the evaluation of biomarkers in ovarian cancer: a systematic review

<p>Data set for the study &ldquo;Shortcomings in the evaluation of biomarkers in ovarian cancer: a systematic review&rdquo;, including search strategy, extraction form, extracted data with summary of results, and protocol</p>

opencc-by-4.0Oct 2019View details →
zenodo48/100

MiRoR15-P2-Development of ARCADIA: a tool for assessing the quality of peer-review reports in biomedical research

<p>Survey questionnaire, anonymised survey data, and codebook related to: Superchi C, Hren D, Blanco D, Rius R, Recchioni A, Boutron I, Gonz&aacute;lez JA. Development of ARCADIA: a tool for assessing the quality of peer-review reports in biomedical research. BMJ Open 2020;0:e035604. doi:10.1136/bmjopen-2019-035604</p>

opencc-by-4.0Aug 2020View details →
zenodo48/100

CETAF-DiSSCo/COVID19-TAF biodiversity-related knowledge hub working group: indexed biotic interactions and review summary

<p>This data publication originated as part of developing a biodiversity-related knowledge hub on COVID-19 via COVID19-TAF - Communities Taking Action (https://cetaf.org/covid19-taf-communities-taking-action), a community-rooted initiative raised jointly by the Consortium of European Taxonomic Facilitaties (CETAF, https://cetaf.org) and Distributed Systems of Scientific Collections (DiSSCo, https://www.dissco.eu/).</p> <p>This archive contains the biodiversity datasets of interest identified in period 14 April-6 October 2020 through COVID19-TAF activities and subsequently indexed by Global Biotic Interactions (GloBI, https://globalbioticinteractions.org).&nbsp; GloBI provides open access to finding species interaction data (e.g., predator-prey, pollinator-plant, virus-host, parasite-host) by combining existing open datasets using open source software.</p> <p>These identified datasets (see references and reviews below) add to a growing collection of open species interaction datasets already indexed by GloBI. So, this data publication only includes a small subset of indexed datasets and include only datasets that were added as a direct consequence of COVID19-TAF activities of the biodiversity-related knowledge hub working group.</p> <p>If you have questions or comments about this publication, please open an issue at https://github.com/ParasiteTracker/tpt-reporting or contact the authors by email.</p> <p>Funding:<br> The creation of this archive was made possible in part by reporting software developed as part of the National Science Foundation award &quot;Collaborative Research: Digitization TCN: Digitizing collections to trace parasite-host associations and predict the spread of vector-borne disease,&quot; Award numbers DBI:1901932 and DBI:1901926 . Also, this material is based upon work supported by the National Science Foundation under Grant No. DGE-1545433 .</p> <p>References:<br> Jorrit H. Poelen, James D. Simons and Chris J. Mungall. (2014). Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2014.08.005.</p> <p>GloBI Data Review Report</p> <p>Datasets under review:<br> &nbsp;- Geiselman, Cullen K. &amp; Sarah Younger. 2020. Bat Eco-Interactions Database. www.batbase.org accessed via https://github.com/globalbioticinteractions/batbase/archive/9c65cfeee1a054f9db8cd8bf6892017fd1b3c840.zip on 2020-10-04T22:53:45.576Z<br> &nbsp;- Geiselman, Cullen K. and Tuli I. Defex. 2015. Bat Eco-Interactions Database. www.batplant.org accessed via https://github.com/globalbioticinteractions/batplant/archive/a2e1b57052244d5251d17e96ea61f58bea88975e.zip on 2020-10-04T22:54:28.727Z<br> &nbsp;- Daniel Becker, Gregory F Albery, Anna R Sjodin, Timothee Poisot, Tad Dallas, Evan A. Eskew, Maxwell J. Farrell, Sarah Guth, Barbara A Han, Nancy B Simmons, Colin J Carlson. 2020. Predicting wildlife hosts of betacoronaviruses for SARS-CoV-2 sampling prioritization. bioRxiv 2020.05.22.111344; doi: https://doi.org/10.1101/2020.05.22.111344 accessed via https://github.com/globalbioticinteractions/becker2020/archive/47c6ad28e1c5058f3c13ca69a59fdf21229e8d7f.zip on 2020-10-04T22:54:46.723Z<br> &nbsp;- Chen L, Liu B, Yang J, Jin Q, 2014. DBatVir: the database of bat-associated viruses. Database (Oxford). 2014:bau021. doi:10.1093/database/bau021 accessed via https://github.com/globalbioticinteractions/dbatvir/archive/a906d76e362484d3ca1edbe9683f672838ab70b0.zip on 2020-10-04T22:56:13.913Z<br> &nbsp;- Chen L, Liu B, Wu Z, Jin Q, Yang J, 2017. DRodVir: A resource for exploring the virome diversity in rodents. J Genet Genomics. 44(5):259-264. accessed via https://github.com/globalbioticinteractions/drodvir/archive/0346c0e8d4d66c6400e9965bd6a6aeed24cd7586.zip on 2020-10-04T23:06:04.368Z<br> &nbsp;- Agosti, Donat. 2020. Transcription of Linn&eacute;, C. von, 1758. Systema naturae per regna tria naturae secundum classes, ordines, genera, species, cum characteribus, differentiis, synonymis, locis. Available at: http://dx.doi.org/10.5962/bhl.title.542 . accessed via https://github.com/globalbioticinteractions/linnaeus1758/archive/a818060080fa04a88dac6df1ae5b897304ae8877.zip on 2020-10-05T00:46:04.852Z<br> &nbsp;- Mollentze, Nardus, &amp; Streicker, Daniel G. (2019). Viral zoonotic risk is homogenous among taxonomic orders of mammalian and avian reservoir hosts (Version 1.0.0) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3516613 accessed via https://github.com/globalbioticinteractions/mollentze2019/archive/ad12dc74d03c3d992618f16c37cafb7f7ffd9d01.zip on 2020-10-05T00:50:55.878Z<br> &nbsp;- Eneida L. Hatcher, Sergey A. Zhdanov, Yiming Bao, Olga Blinkova, Eric P. Nawrocki, Yuri Ostapchuck, Alejandro A. Sch&auml;ffer, J. Rodney Brister, Virus Variation Resource &ndash; improved response to emergent viral outbreaks, Nucleic Acids Research, Volume 45, Issue D1, January 2017, Pages D482&ndash;D490, https://doi.org/10.1093/nar/gkw1065 . accessed via https://github.com/globalbioticinteractions/ncbi-virus/archive/531a8d743d7adcf1153a19087e5d3c5b76750e3e.zip on 2020-10-05T00:53:53.646Z<br> &nbsp;- Olival, K. J., Hosseini, P. R., Zambrana-Torrelio, C., Ross, N., Bogich, T. L., &amp; Daszak, P. (2017). Host and viral traits predict zoonotic spillover from mammals. Nature, 546(7660), 646&ndash;650. doi:10.1038/nature22975 accessed via https://github.com/globalbioticinteractions/olival2017/archive/f61070a5339d0e6c6e76d7eb4e2102decb52317d.zip on 2020-10-05T00:56:43.356Z<br> &nbsp;- Pensoft Darwin Core Archives with associateTaxa columns accessed via https://github.com/globalbioticinteractions/pensoft-dwca/archive/ee8831a2a391203f4fa8c05a0ddd927202b234bf.zip on 2020-10-05T00:56:51.868Z<br> &nbsp;- Pensoft Darwin Core Archives available via Integrated Publication Toolkit accessed via https://github.com/globalbioticinteractions/pensoft-ipt/archive/4ad4b47978324681289e36f8c2b247b1bcc97b1a.zip on 2020-10-05T00:58:01.912Z<br> &nbsp;- De Rojas M, Do&ntilde;a J, Dimov I (2020) A comprehensive survey of Rhinonyssid mites (Mesostigmata: Rhinonyssidae) in Northwest Russia: New mite-host associations and prevalence data. Biodiversity Data Journal 8: e49535. https://doi.org/10.3897/BDJ.8.e49535 accessed via https://github.com/globalbioticinteractions/pensoft-table/archive/3488e0397ca4e083d5eca6949951e426a75713e3.zip on 2020-10-05T00:58:03.647Z<br> &nbsp;- Marcus Guidoti, Tatiana Ruschel, Donat Agosti. 2020. Corona virus related biotic associations manually extracted from literature. Plazi. accessed via https://github.com/globalbioticinteractions/plazi-covid19/archive/326578b0d9f974760dcd2e962d86636a6487a6c0.zip on 2020-10-05T00:58:08.025Z<br> &nbsp;- Shaw, LP, Wang, AD, Dylus, D, et al. The phylogenetic range of bacterial and viral pathogens of vertebrates. Mol Ecol. 2020; 29: 3361&ndash; 3379. https://doi.org/10.1111/mec.15463 accessed via https://github.com/globalbioticinteractions/shaw2020/archive/bb9ab857b7fdbb4e931752d01b43d37b3ada77cf.zip on 2020-10-05T01:05:23.554Z<br> &nbsp;- OpenBiodiv. 2020. Annotated biotic interaction tables from Pensoft publications. accessed via https://github.com/pensoft/pensoft-interaction-tables/archive/bb7d1dc9f2eba220a61502e06e6114053fd30788.zip on 2020-10-05T03:03:23.372Z<br> &nbsp;- Quentin J. Groom. 2020. Bat interation data manually extracted from literature. accessed via https://github.com/qgroom/batinterations/archive/70108945f9014aa0ac1db920191867f7e151c793.zip on 2020-10-05T03:04:11.533Z</p> <p>Generated on:<br> 2020-10-06</p> <p>by:<br> GloBI&#39;s Elton 0.10.2<br> (see https://github.com/globalbioticinteractions/elton).</p> <p>&nbsp;</p> <p>Note that all files ending with .tsv are files formatted<br> as UTF8 encoded tab-separated values files.</p> <p>https://www.iana.org/assignments/media-types/text/tab-separated-values</p> <p><br> Included in this review archive are:</p> <p>README:<br> &nbsp; This file.</p> <p>review_summary.tsv:<br> &nbsp; Summary across all reviewed collections of total number of distinct review comments.</p> <p>review_summary_by_collection.tsv:<br> &nbsp; Summary by reviewed collection of total number of distinct review comments.</p> <p>indexed_interactions_by_collection.tsv:<br> &nbsp; Summary of number of indexed interaction records by institutionCode and collectionCode.</p> <p>review_comments.tsv.gz:<br> &nbsp; All review comments by collection.</p> <p>indexed_interactions_full.tsv.gz:<br> &nbsp; All indexed interactions for all reviewed collections.</p> <p>indexed_interactions_simple.tsv.gz:<br> &nbsp; All indexed interactions for all reviewed collections selecting only sourceInstitutionCode, sourceCollectionCode, sourceCatalogNumber, sourceTaxonName, interactionTypeName and targetTaxonName.</p> <p>datasets_under_review.tsv:<br> &nbsp; Details on the datasets under review.</p> <p>elton.jar:<br> &nbsp; Program used to update datasets and generate the review reports and associated indexed interactions.</p> <p><br> datasets.zip:<br> &nbsp; source datasets collected by elton in process of executing the generate_report.sh script.</p> <p>generate_report.sh:<br> &nbsp; program used to generate the report</p> <p>generate_report.log:<br> &nbsp; log file generated as part of running the generate_report.sh script</p>

opencc-by-4.0May 2020View details →
zenodo48/100

IPBES Data Management Tutorials - Session 6.2: Literature review from the Global Assessment chapter 4

<p>The&nbsp;<em>IPBES data management tutorials</em>&nbsp;are short videos to help experts implement the IPBES data management Policy. They cover topics ranging from data management policy, reports, active research data, tools, and examples.</p> <p>The chapter on<em> Examples of implementing the IPBES data management Policy</em>&nbsp;contains examples of how certain data management tasks and workflows were implemented within IPBES so that they follow the data management policy.&nbsp;<strong>Currently, this chapter contains legacy videos and the most recent examples can be found within the IPBES technical guidelines here:</strong> <a href="https://ict.ipbes.net/ipbes-ict-guide/data-management/technical-guidelines">https://ict.ipbes.net/ipbes-ict-guide/data-management/technical-guidelines</a></p> <p>This session&nbsp;<em>Literature review from the Global Assessment chapter 4 </em>walks you through each step of the data management of the systematic literature review from the Chapter 4 of the Global Assessment.&nbsp;</p>

opencc-by-4.0Dec 2020View details →
zenodo48/100

Data and R code for Tansley review New Phytologist 2021: "An integrated framework of plant form and function: The belowground perspective"

<p>The files in this archive are related to the paper of Weigelt, Mommer, Andraczek et al. (2021) An integrated framework of plant form and function: The belowground perspective. Tansley Review New Phytologist. The paper developed and tested a new conceptual framework of plant form and function linking above and belowground traits of 2510 species. We found that an integrated, whole-plant trait space required as much as four axes. The two main axes represented the fast-slow &lsquo;conservation&rsquo; gradient on which leaf and fine-root traits were well aligned, and the &lsquo;collaboration&rsquo; gradient in roots. The two additional axes were separate, orthogonal plant size axes for height and rooting depth.</p> <p>This archives contains four files:</p> <ol> <li><strong>Weigelt et al.2021RCode.DataCleaning.txt</strong> - &nbsp;RCode for the complete data processing starting with the downloaded database files from the Plant Trait Database version 5.0 (TRY, Kattge et al. 2020), the Global Root Trait database (GRooT, Guerrero-Ramirez et al. 2020) and a small number of additional data files listed in Table S2 of the original paper. Additional information was later incorporated using FungalRoot Database (Soudzilovkaia et al. 2020), nodDB Database (Tedersoo et al. 2018) and a compiled dataset on rooting depth (Fan et al. 2017). The code processes, cleans and merges the data and produces a final table for PCA analysis of species specific mean traits. This final table is provided as a second file in this archive (Weigelt_et_al_2021_Main.PCA.Matrix.xlsx). A second part of the RCode.DataCleaning extracts species-specific individual trait data where root and shoot traits were measured on the same plant individual or plot. This data was compiled from 43 studies identified in Table S2&nbsp; of the original publication. The final table for individual trait data is the third file in this archive (Weigelt_et_al_2021_Individual.PCA.Matrix.xlsx).</li> <li><strong>Weigelt_et_al_2021_Main.PCA.Matrix.xlsx</strong> &ndash; Datafile with species-specific global mean trait data for 17 traits of 2510 species with at least one root and one shoot trait available. Meta-data is provided in the data file.</li> <li><strong>Weigelt_et_al_2021_Individual.PCA.Matrix.xlsx</strong> &ndash; Datafile with species-specific trait data where root and shoot traits were measured on the same individual or plot for 6 traits of 455 species. Meta-data is provided in the data file.</li> <li><strong>Weigelt et al.2021RCode.Analysis.txt &ndash; </strong>RCode for all analyses and figures provided in the paper for both the species mean and individual based dataset. The Code is annotated to help reproducibility of the analysis.</li> </ol>

opencc-by-4.0Dec 2020View details →
zenodo48/100

A Standardized Review of Bat Names Across Multiple Taxonomic Authorities

<p>The Bat Eco-Interactions Working Group, in collaboration with GBatNet and the international Bat Taxonomy Group, developed the <strong>Bat Taxonomic Alignment (BTA)</strong> to reconcile taxonomic discrepancies across currently recognized bat species. As knowledge of bat population structure and evolutionary history advances, taxonomic boundaries and species names are frequently revised. To address these changes, the BTA integrates data from ten leading taxonomic authorities and consolidates relationships, synonyms, and historic combinations for over <strong>1,480 valid bat species</strong> across <strong>1,680 taxonomic treatments</strong>.</p> <p>This open-access, searchable tool provides a time-calibrated inventory of Chiroptera taxonomy, documenting valid names, alternative names, subspecies, and synonymies. By aligning these classifications, the BTA enables users to identify unharmonized binomials and trace nomenclatural changes over time. It promotes taxonomic clarity critical for research, biodiversity assessments, and conservation planning, where misidentified or misaligned taxa can lead to gaps in knowledge, resource misallocation, or overlooked species. The BTA thus represents a foundational advancement in bat biodiversity informatics, emphasizing transparency, data provenance, and interoperability across digital taxonomic frameworks.</p> <p>&nbsp;</p>

opencc-zeroMay 2023View details →
zenodo48/100

D4.1 Review on Accuracy of Proximal Soil Sensors Dataset

<p><span lang="EN-US">The dataset includes the raw data about PSS accuracy based on the root-mean-square error (RMSE) and wet chemistry analytical data on which we based our analysis, organized in a comma-separated value (CSV) file. A table with the metadata of the accuracy dataset is included in this document. A previous version of the dataset present in this supplementary has already been published in the Zenodo repository with the following associated DOI: <a href="https://doi.org/10.5281/zenodo.14035520">https://doi.org/10.5281/zenodo.14035520</a>. The current version updates the previous one due to incongruencies found after the upload. The PDF file contains a table that give information about the fields in the CSV.</span></p>

opencc-by-4.0Nov 2024View details →
zenodo48/100

Supplementary data for the article: Future environmental impacts of metals: a systematic review of impact trends, modelling approaches, and challenges

<p>This repository provides the supplementary data to the paper titled&nbsp;<a href="https://doi.org/10.1016/j.resconrec.2024.107572" target="_blank" rel="noopener"><em>"Future environmental impacts of metals: a systematic review of impact trends, modelling approaches, and challenges"</em></a>, published 2024 in&nbsp;<em>Resources, Conservation and Recycling</em>.</p> <h4><strong>Contents</strong></h4> <p>The repository is split in 3 parts and comprises the following files (more details are provided in the <em>README.md</em>):</p> <p><strong>A_Database of reviewed studies:</strong></p> <ul> <li>contains the detailed review data, meant for readers to use as an overview file to gather studies relevant to them. It also includes an overview of all data sources that the reviewed studies used.</li> </ul> <p><strong>B_Scientific supplement to paper:</strong></p> <ul> <li>Contains all data relevant to the related publication Harpprecht et al. (2024), such as studies screened , FAIR data analysis, or analyzed impact trends.</li> </ul> <p><strong>C_Data for figures in paper:</strong></p> <ul> <li>This file contains all the data for Figures 3, 4 and 5 in tabular form, representing impact trends, scenario variables, scenario modelling approaches and data sources used.</li> </ul> <h4><strong>Summary</strong></h4> <p>These files allow to reproduce the results of our study. In this work, we systematically reviewed studies which assessed future environmental impacts of metal supply chains. Our review yielded 40 publications covering 15 metals: copper, iron, aluminium, nickel, zinc, lead, cobalt, lithium, gold, manganese, neodymium, dysprosium, praseodymium, terbium, and titanium. We evaluated their results regarding future impact trends, and their methods, i.e., modelling approaches, scenario variables, and data sources of scenario variables. We identified 15 scenario variables. The most common variables are background electricity mix, ore grade, recycling shares, demand, and energy efficiency. We identified 229 unique data sources for the reviewed scenario variables.</p> <h4><strong>Related publication</strong></h4> <p>More details on the data and its interpretation as well as the scientific context are provided in the publication itself:</p> <p><a href="https://doi.org/10.1016/j.resconrec.2024.107572" target="_blank" rel="noopener">Harpprecht, C., Miranda Xicotencatl, B., van Nielen, S., van der Meide, M., Li, C. , Li, Z., Tukker, A., Steubing, B. (2024). <em>Future environmental impacts of metals: a systematic review of impact trends, modelling approaches, and challenges.</em> Resources, Conservation and Recycling.</a></p> <h4><strong>Funding&nbsp;</strong></h4> <p>Carina Harpprecht received funding from the Energy Program of the German Aerospace Center in 2022. Zhijie Li received funding from the European Institute of Innovation and Technology (EIT) under the project Valomag (Project No. 14049).</p> <h4><strong>License</strong></h4> <p>CC-BY 4.0 license for DLR (German Aerospace Center)</p>

opencc-by-4.0Nov 2023View details →
zenodo48/100

ZOOOM Literature Review Clean Dataset

<p>The csv file contains the dataset of literature search produced by the ZOOOM EU Funded Project on open software, open hardware, open data business models.</p>

opencc-by-sa-4.0Nov 2023View details →
zenodo48/100

Dataset for: A systematic literature review on user factors to support the sense of presence

<p>This dataset was created for a publication of Wiepke, Axel and Heinemann, Birte called "A systematic literature review on user factors to support the sense of presence". In this paper we used the PRISMA-method to collect Papers via Google Scholar on the third of April 2023 with the search term:<br>(framework OR model OR frameworks OR models OR processes OR ontologies) AND ((&ldquo;personality traits&rdquo; OR &ldquo;personality variables&rdquo; OR &ldquo;personality factors&rdquo;) AND &ldquo;spatial presence&rdquo;) AND (&ldquo;virtual reality&rdquo;) AND (learn OR edu\*)</p> <p>The results were pictured in "agreed" findings, where more than 50% of found studies supported a category of results and in "controversial", where there were significant findings, but less than 50% of the studies reported significance.</p> <p>This dataset contains:</p> <ul> <li>raw data for our literature review in .bib</li> <li>our main findings with categories in .csv</li> <li>a short Jupyter notebook script for one graphic in ipynb</li> <li>other graphics as .png</li> </ul>

opencc-by-4.0Dec 2023View details →
zenodo48/100

Systematic Literature Review on Tourism Marketing in the Metaverse

<p>The aim of this research is to investigate tourist marketing within the embryonic context of the metaverse in order to comprehend the building blocks and the primary technologies employed in the sector. For this purpose, a systematic literature review is conducted. The references are extracted in January 2023. The data in this document correspond to the articles finally included in the systematic literature review after the article screening phase.</p> <p>Keywords: tourism marketing, metaverse, technologies, building blocks, SLR (Systematic Literature Review), PRISMA</p> <p>&nbsp;</p>

opencc-by-4.0Mar 2024View details →
zenodo48/100

New Challenges in Point Cloud Visual Quality Assessment: A Systematic Review (Dataset)

<p>This dataset is a collection of annotated information on the scientific papers screened and analyzed for the systematic review of the literature in Point Cloud Visual Quality Assessment.&nbsp;</p> <p>The data is structured as follows:</p> <ul> <li>General information <ul> <li>Document title</li> <li>Authors</li> <li>Year of publication</li> <li>Venue (Conference or Journal title)</li> <li>Citations (number)</li> <li>URL/DOI</li> </ul> </li> </ul> <ul> <li>About the content&nbsp;<br> <ul> <li>Content Type: Point clouds (PC), Colored Point clouds (CPC), Meshes, Dynamic Point Clouds (DPC)</li> <li>Content source: Source of the content used in a subjective QA test or the evaluation of one or more QA metrics</li> </ul> </li> </ul> <ul> <li>About metric benchmarks <ul> <li>Subjective Ground-truth Data: Dataset(s) Source of the subjective scores used as ground-truth in a QA metric benchmark</li> <li>Assessed Metrics: Types of metrics assessed in a benchmark (JPEG standards, IQM, NR, State-of-the-art, others)</li> <li>Performance Measures: PLCC, SROCC, KRCC, RMSE, OR, others</li> </ul> </li> </ul> <ul> <li>About Objective QA metrics <ul> <li>Metric: Name given to the metric introduced in this paper</li> <li>Base: 3D-based or Projection-based</li> <li>Categories: Categories that characterize the approach of the proposed metric (Feature-based, Learning-Based, Perceptual-based, IQM, others)&nbsp;</li> <li>Reference: Full-Reference (FR), Reduced-Reference (RR) or No-Reference (NR)</li> </ul> </li> </ul> <ul> <li>About Subjective QA experiments <ul> <li>Display: Type of display (2D, 3D, AR, MR, VR) and interaction approach (passive, interactive, 3DoF, 6DoF) used in the described experiment.</li> <li>Rendering: Type of rendering used to display the stimuli (Points, Squares, Cubes, Surface)</li> <li>Lab/Remote: The experiment was run in one or more lab environments, or remotely (Lab, Cross-Lab, Remote)</li> <li>Rating: Subjective rating methodology used in the experiment (ACR, DSIS, PWC, others)</li> <li>Dataset: Name of the new subjective dataset if the experiment's results were published.</li> <li>Observers: Number of observers&nbsp;</li> <li>Distortion type: Types of distortions applied to the stimuli and assessed in the experiment</li> </ul> </li> </ul>

opencc-by-4.0Oct 2024View details →
zenodo48/100

Automated Literature Screening for Systematic Reviews: Dataset for Evaluation Against Human Title and Abstract and Full-Text Screening Decisions

<p>This Zenodo entry contains the supplementary material associated with the manuscript titled&nbsp;<em>Automated Literature Screening for Systematic Reviews: A 5-Tier Prompting Approach Meeting Cochrane&rsquo;s Sensitivity Requirement of Greater Than 0.99.</em> The paper will be presented at <a href="https://dbis.rwth-aachen.de/LLMs4MI2024/">LLMsMI 2024</a> in November 2024.</p> <p>A script is provided for replicating the executed experiments, along with a comprehensive evaluation file that reports all the experiment results. Provided data files represent an extension to the original datasets as provided by [1]. For associated systematic review manuscripts and eligibility criteria, please refer to [1] as well.&nbsp;</p> <p>[1] Guo, Eddie; Gupta, Mehul; Deng, Jiawen; Park, Ye-Jean; Paget, Mike; Naugler, Christopher (2023). "Automated Paper Screening for Clinical Reviews Using Large Language Models."&nbsp;<em>Mendeley Data</em>, V1, doi: 10.17632/np79tmhkh5.1. Accessed from: <a href="https://data.mendeley.com/datasets/np79tmhkh5/1" target="_new" rel="noopener">https://data.mendeley.com/datasets/np79tmhkh5/1</a>.</p>

opencc-by-4.0Dec 2023View details →
zenodo48/100

MOBO: The MOvie and BOok reviews dataset

<p>The <strong>MOBO</strong>&nbsp;dataset.</p> <p>The <em><strong>MOvie and BOok reviews dataset</strong></em> is a collection made up of movie and book reviews, paired with their related plots.<br> The reviews come from different publicly available datasets: the Stanford&#39;s IMDB movie reviews [1], the GoodReads [2] and the Amazon reviews dataset [3]. With the help of 15 annotators, we further labeled more than 18,000 reviews&#39; sentences (~6000 per corpus), marking the sentence polarity (<em>Positive</em>,&nbsp;<em>Negative</em>), or whether a sentence describes its corresponding movie/book&nbsp;<em>Plot</em>, or none of the above (<em>None</em>). In the&nbsp;<code>dataset</code>&nbsp;folder, we have shared an excerpt of the annotated sentences for each dataset.</p>

opencc-by-4.0Mar 2022View details →
zenodo48/100

A Review of Transnational Migrant Entrepreneurship

<p>The spatialities of migrant entrepreneurship have changed dynamically in recent decades. Movements and exchanges transcend national borders more than ever, and transnational migrant entrepreneurship has become a burgeoning field of research. Yet, knowledge is dispersed across disciplines, and an understanding of contemporary spatialities is limited. We review 155 articles published in English, French, German, and Spanish since 2009, thereby providing an overview of existing knowledge on transnational migrant entrepreneurship and suggesting avenues for future research. We identify five current topical areas of research: (1) the business advantages of transnational migrant entrepreneurship, (2) the determinants of becoming a transnational migrant entrepreneur, (3) the transnational networks of migrants, (4) the economic impacts of transnational migrant entrepreneurship on home and host countries, and (5) whether local environments enable or deter entrepreneurial success. Building on our synthesis of the most recent literature, we propose three crucial dimensions which have been under-researched in past and current work, and which address the diversity of geographical locations, spatial connections, and spatial mobilities involved in transnational migrant entrepreneurship. Moreover, we put forward a set of questions for future research which will advance a comprehension of unequal opportunities among transnational migrant entrepreneurs.</p>

opencc-by-4.0May 2022View details →

ScienceDex guides

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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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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record