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Diversity in citations to a single study: Supplementary data set for citation context network analysis
<p><strong>Introduction</strong></p> <p>This document describes the data set used for all analyses in 'Diversity in citations to a single study: A citation context network analysis of how evidence from a prospective cohort study was cited' accepted for publication in <em>Quantitative Science Studies</em> [1].</p> <p><strong>Data Collection</strong></p> <p>The data collection procedure has been fully described [1]. Concisely, the data set contains bibliometric data collected from Web of Science Core Collection via the University of Edinburgh’s Library subscription concerning all papers that cited a cohort study, Paul <em>et al.</em> [2], in the period <1985. This includes a full list of citing papers, and the citations between these papers. Additionally, it includes textual passages (citation contexts) from 343 citing papers, which were manually recovered from the full-text documents accessible via the University of Edinburgh’s Library subscription. These data have been cleaned, converted into network readable datasets, and are coded into particular classifications reflecting content, which are described fully in the supplied code book and within the manuscript [1]. </p> <p><strong>Data description</strong></p> <p>All relevant data can be found in the attached file 'Supplementary_material_Leng_QSS_2021.xlsx', which contains the following five workbooks:</p> <ul> <li><strong>“Overview”</strong> includes a list of the content of the workbooks.</li> <li><strong>“Code Book”</strong> contains the coding rules and definitions used for the classification of findings and paper titles.</li> <li><strong>“Node attribute list”</strong> includes a workbook containing all node attributes for the citation network, which includes Paul et al. [2] and its citing papers as of 1984. Highlighted in yellow at the bottom of this workbook is two papers that were discarded due to duplication - remove these if analysing this dataset in a network analysis. The columns refer to:</li> </ul> <ol> <li><em>Id</em>, the node identifier</li> <li><em>Label</em>, the formal citation of the paper to which data within this row corresponds. Citation is in the following format: last name of first author, year of publication, journal of publication, volume number, start page, and DOI (if available). </li> <li><em>Title</em>, the paper title for the paper in question.</li> <li><em>Publication_year</em>, the year of publication.</li> <li><em>Document_type, </em>the document type (e.g. review, article)</li> <li><em>WoS_ID</em>, the paper’s unique Web of Science accession number.</li> <li><em>Citation_context</em>, a column specifying whether citation context data is available from that paper</li> <li><em>Explanans</em>, the title explanans terms for that paper;</li> <li><em>Explanandum</em>, the explanandum terms for that paper.</li> <li><em>Combined_Title_Classification</em>, the combined terms used for fig 2 of the published manuscript.</li> <li><em>Serum_cholesterol_(SC)</em>, a column identifying papers that cited the serum cholesterol findings.</li> <li><em>Blood_Pressure_(BP), </em>a column identifying papers that cited the blood pressure findings.</li> <li><em>Coffee_(C),</em> a column identifying papers that cited the coffee findings.</li> <li><em>Diet_(D), </em>a column identifying papers that cited the dietary findings.</li> <li><em>Smoking_(S), </em>a column identifying papers that cited the smoking findings.</li> <li><em>Alcohol_(A), </em>a column identifying papers that cited the alcohol findings.</li> <li><em>Physical_Activity_(PA),</em> a column identifying papers that cited the physical activity findings.</li> <li><em>Body_Fatness (BF), </em>a column identifying papers that cited the body fatness findings.</li> <li><em>Indegree,</em> the number of within network citations to that paper, calculated for the network shown in Fig 4 of the manuscript.</li> <li><em>Outdegree</em>, the number of within network references of that paper as calculated for the network in Fig 4.</li> <li><em>Main_component</em>, a column specifying whether a node is contained in the largest weakly connect component as shown in Fig 4 of the manuscript.</li> <li><em>Cluster</em>, provides the cluster membership number as discussed within the manuscript (Fig 5).</li> </ol> <ul> <li><strong>“Edge list”</strong> includes a workbook including the edges for the network. The columns refer to:</li> </ul> <ol> <li><em>Source</em>, contains the node identifier of the citing paper.</li> <li><em>Target,</em> contains the node identifier of the cited paper.</li> </ol> <ul> <li><strong>“Citation context classification</strong>” includes a workbook containing the WoS accession number for the paper analysed, and any finding category discussed in that paper established via context analysis (see the code book for definitions). The columns refer to:</li> </ul> <ol> <li><em>Id</em>, the node identifier</li> <li><em>Finding_Class, </em>the findings discussed from Paul et al. within the body of the citing paper. </li> </ol> <ul> <li><strong> “Citation context data”</strong> includes a workbook containing the WoS accession number for papers in which citation context data was available, the citation context passages, the reference number or format of Paul et al. within the citing paper, and the finding categories discussed in those contexts (see code book for definitions). The columns refer to:</li> </ul> <ol> <li><em>Id</em>, the node identifier</li> <li><em>Citation_context</em>, the passage copied from the full text of the citing paper containing discussion of the findings of Paul et al.</li> <li><em>Reference_in_citing_article</em>, the reference number or format of Paul et al. within the citing paper.</li> <li><em>Finding_class, </em>the findings discussed from Paul et al. within the body of the citing paper. </li> </ol> <p><strong>Software recommended for analysis</strong></p> <p>For the analyses performed within the manuscript, Gephi version 0.9.2 was used [3], and both the edge and node lists are in a format that is easily read into this software. The Sci2 tool was used to parse data initially [4].</p> <p><strong>Notes</strong></p> <ol> <li>Leng, R. I. (Forthcoming). Diversity in citations to a single study: A citation context network analysis of how evidence from a prospective cohort study was cited. Quantitative Science Studies.</li> <li>Paul, O., Lepper, M. H., Phelan, W. H., Dupertuis, G. W., Macmillan, A., McKean, H., <em>et al.</em> (1963). A longitudinal study of coronary heart disease. <em>Circulation, </em><strong>28</strong>, 20-31. <a href="https://doi.org/10.1161/01.cir.28.1.20">https://doi.org/10.1161/01.cir.28.1.20</a>.</li> <li>Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media.</li> <li>Sci2 Team. (2009). Science of Science (Sci2) Tool. Indiana University and SciTech Strategies. Stable URL: <a href="https://sci2.cns.iu.edu">https://sci2.cns.iu.edu</a></li> </ol>
Surface electromyography data set of knee osteoarthritis patients undergoing hydrotherapy and physiotherapy rehabilitation routines
<p>Osteoarthritis is one of the most prevalent degenerative diseases in the elderly that affects the structural and functional integrity of the musculoskeletal system. Currently, hydrotherapy is taking relevance for osteoarthritis treatment due to its possible efficacy on pain relief and functionality. This therapy can be evaluated by means of an electromyographic analysis. The objective is to show a database of lower limbs muscles electrical activity in charge of postural stability, comparing the difference between hydrotherapy and conventional therapy through surface electromyography. A signal acquisition methodology was developed measuring electromyographic activity of the Tibialis Anterior, Soleus, Vastus Medialis, Biceps Femoris, Medial Gastrocnemius and Lateral Gastrocnemius muscles, before and after applying a specific exercise routine for knee osteoarthritis. This routine consisted of 12 therapy sessions spread over 4 weeks and could be done in water and on land. </p> <p>The data is organized according to the attendance of 28 patients to the therapy sessions. There are two records per person, before and after each hydrotherapy or physiotherapy session, obtaining a total of 1344 records at the end of the 12 sessions, and 56 data for each session. However, a total of 864 complete records were obtained for both therapies, withdrawing those who missed any of the sessions. There is a personal information database in .CSV format and electromyographic records with a .MAT extension.</p>
Sensor data set of one electromechanical cylinder at ZeMA testbed (ZeMA DAQ and Smart-Up Unit)
<p><strong>General information on the data set</strong></p> <p>The dataset was generated with two different measurement systems at the ZeMA testbed for electromechanical cylinders.</p> <p> </p> <p><strong>All relevant information can be found within the hdf5 file.</strong></p> <p> </p> <p><strong>Example for reading out the metadata of the hdf5 file in MATLAB:</strong></p> <pre><code># available structures inside file dataset = 'axis11_2kHz_ZeMA_PTB_SI.h5'; h5disp(dataset) % general attributes about file attr = h5info(dataset).Attributes; project = jsondecode(attr(1,1).Value) person = jsondecode(attr(2,1).Value) publication = jsondecode(attr(3,1).Value) experiment = jsondecode(attr(4,1).Value)</code></pre> <p> </p> <p><strong>Example for reading out the metadata of the hdf5 file in Python:</strong></p> <pre><code>import h5py import json # open file h5file = h5py.File("axis11_2kHz_ZeMA_PTB_SI.h5", "r") # general attributes about file for key in h5file.attrs: print(key) val = json.loads(h5file.attrs[key]) for subkey, subval in val.items(): print(" ", subkey, " : ", subval) # available structures inside file h5file.visit(print) # proper exit h5file.close()</code></pre> <p> </p> <p><strong>Metadata output of the hdf5 file:</strong></p> <ul> <li><strong>For the dataset:</strong> <pre><code>HDF5 axis11_2kHz_ZeMA_PTB_SI.h5 Group '/' Attributes: 'Project': '{ "fullTitle":"Metrology for the Factory of the Future", "acronym":"Met4FoF", "websiteLink":"www.met4fof.eu", "fundingSource":"European Commission (EC)", "fundingAdministrator":"EURAMET", "funding programme":"EMPIR", "fundingNumber":"17IND12", "acknowledgementText":"This work has received funding within the project 17IND12 Met4FoF from the EMPIR program co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation program. The authors want to thank Clifford Brown, Daniel Hutzschenreuter, Holger Israel, Giacomo Lanza, Bj\u00f6rn Ludwig, and Julia Neumann fromPhysikalisch-Technische Bundesanstalt (PTB) for their helpful suggestions and support." }' 'Person': '{ "dc:author":[ "Tanja Dorst", "Maximilian Gruber", "Anupam Prasad Vedurmudi" ], "e-mail":[ "t.dorst@zema.de", "maximilian.gruber@ptb.de", "anupam.vedurmudi@ptb.de" ], "affiliation":[ "ZeMA gGmbH", "Physikalisch-Technische Bundesanstalt", "Physikalisch-Technische Bundesanstalt" ] }' 'Publication': '{ "dc:identifier":"10.5281/zenodo.5185953", "dc:license":"Creative Commons Attribution 4.0 International (CC-BY-4.0)", "dc:title":"Sensor data set of one electromechanical cylinder at ZeMA testbed (ZeMA DAQ and Smart-Up Unit)", "dc:description":"The data set was generated with two different measurement systems at the ZeMA testbed. The ZeMA DAQ unit consists of 11 sensors and the SmartUp-Unit has 13 differentsignals. A typical working cycle lasts 2.8s and consists of a forward stroke, a waiting time and a return stroke of the electromechanical cylinder. The data set does not consist of the entire working cycles. Only one second of the return stroke of every 100rd working cycle is included. The dataset consists of 4776 cycles. One row represents one second of the return stroke of one working cycle.", "dc:subject":[ "dynamic measurement", "measurement uncertainty", "sensor network", "digital sensors", "MEMS", "machine learning", "European Union (EU)", "Horizon 2020", "EMPIR" ], "dc:SizeOrDuration":"24 sensors, 4776 cycles and 2000 datapoints each", "dc:type":"Dataset", "dc:issued":"2021-09-10", "dc:bibliographicCitation":"T. Dorst, M. Gruber and A. P. Vedurmudi : Sensor data set of one electromechanical cylinder at ZeMA testbed (ZeMA DAQ and Smart-Up Unit), Zenodo [data set], https://doi.org/10.5281/zenodo.5185953, 2021." }' 'Experiment': '{ "date":"2021-03-29/2021-04-15", "DUT":"Festo ESBF cylinder", "identifier":"axis11", "label":"Electromechanical cylinder no. 11" }'</code></pre> <p> </p> </li> <li><strong>Example for one sensor (BMA 280, acceleration) of the PTB SmartUp Unit (SUU) and one sensor of ZeMA DAQ (pressure):</strong> <pre><code>HDF5 axis11_2kHz_ZeMA_PTB_SI.h5 Group '/PTB_SUU' Group '/PTB_SUU/BMA_280' Group '/PTB_SUU/BMA_280/Acceleration' Attributes: 'qudt:hasQuantityKind': '[ "qudt:Acceleration", "qudt:Acceleration", "qudt:Acceleration" ]' 'misc': '{ "interpolation_scheme":"cubic" }' 'si:unit': '"\\metre\\second\\tothe{-2}"' 'sosa:madeBySensor': '"BMA 280"' 'rdf:type': '"qudt:Quantity"' Dataset 'qudt:standardUncertainty' Size: 4766x1000x3 MaxSize: 4766x1000x3 Datatype: H5T_IEEE_F64LE (double) ChunkSize: [] Filters: none FillValue: 0.000000 Attributes: 'si:label': '[ "X acceleration uncertainty", "Y acceleration uncertainty", "Z acceleration uncertainty" ]' Dataset 'qudt:value' Size: 4766x1000x3 MaxSize: 4766x1000x3 Datatype: H5T_IEEE_F64LE (double) ChunkSize: [] Filters: none FillValue: 0.000000 Attributes: 'si:label': '[ "X acceleration", "Y acceleration", "Z acceleration" ]' Group '/ZeMA_DAQ' Group '/ZeMA_DAQ/Pressure' Attributes: 'qudt:hasQuantityKind': '"qudt:Pressure"' 'sosa:madeBySensor': '"Festo VPPM"' 'si:unit': '"\\pascal"' 'rdf:type': '"qudt:Quantity"' Dataset 'qudt:standardUncertainty' Size: 4766x2000 MaxSize: 4766x2000 Datatype: H5T_IEEE_F64LE (double) ChunkSize: [] Filters: none FillValue: 0.000000 Attributes: 'si:label': '"Pneumatic pressure uncertainty"' Dataset 'qudt:value' Size: 4766x2000 MaxSize: 4766x2000 Datatype: H5T_IEEE_F64LE (double) ChunkSize: [] Filters: none FillValue: 0.000000 Attributes: 'si:label': '"Pneumatic pressure"' 'misc': '{ "raw_data":false, "comment":"Converted from ADC values based on appropriate conversion." }'</code></pre> </li> </ul>
data sets for the article Short‑term impact of crop diversifcation on soil carbon fuxes and balance in rainfed and irrigated woody cropping systems under semiarid Mediterranean conditions
<p>Diversifcation practices such as intercropping in woody cropping systems have recently been proposed as a promising management strategy for addressing problems related to soil degradation, climate change mitigation and food security. In this study, we assess the impact of several diversifcation practices in diferent management regimes on the main carbon fuxes regulating the soil carbon balance under semiarid Mediterranean conditions.</p>
Data set of paper Model-Driven System-Performance Engineering for Cyber-Physical Systems
<p>This data set contains the raw and processed data of the paper <em>Model-Driven System-Performance Engineering for Cyber-Physical Systems</em>, published in the proceedings of ESWEEK’21.</p>
Faithful Transcriptions Data Set: TEI/XML-encoded Transcriptions of Medieval Theological Manuscripts
<p>From May to July 2021, the Berlin State Library and the Leipzig University Library jointly organized the Transcribathon <a href="https://lab.sbb.berlin/events/faithful-transcriptions/">“Faithful Transcriptions”</a>, a digital crowd souring project on medieval theological manuscripts. During the project, over 100 participants produced TEI/XML-encoded transcriptions in the IIIF workspace of the <a href="https://handschriftenportal.de/">Handschriftenportal</a>, which is currently being developed.</p> <p>The <a href="https://lab.sbb.berlin/datensets-transkribathon/">Faithful Transcriptions Data Set</a> contains 181 pages with 8.952 text lines from 12 manuscripts in German, Dutch, and Latin. The medieval scripts include Textura, Textualis, Gothic Cursiva, and Bastarda. The transcriptions are linked to the coordinates of the digitized manuscript image on text line level.</p> <p>--------------------------------------------</p> <p>Von Mai bis Juli 2021 richtete die Staatsbibliothek zu Berlin in Kooperation mit der Universitätsbibliothek Leipzig den Transkribathon <a href="https://lab.sbb.berlin/events/faithful-transcriptions/">„Faithful Transcriptions“</a> aus, ein digitales Crowd-Sourcing-Projekt zu theologischen Handschriften des Mittelalters. Über 100 Teilnehmende fertigten dabei TEI/XML-codierte Transkriptionen in der IIIF-basierten Arbeitsumgebung des aktuell in Entwicklung befindlichen <a href="https://handschriftenportal.de/">Handschriftenportals</a> an. </p> <p>Das <a href="https://lab.sbb.berlin/datensets-transkribathon/">Faithful Transcriptions-Datenset</a> enthält 181 Seiten mit 8.952 Textzeilen aus 12 Handschriften in deutscher, niederländischer und lateinischer Sprache. Die mittelalterlichen Schriften reichen von Textura über Textualis und Gotische Kursive bis hin zur Bastarda. Die Transkriptionen sind mit den Bildkoordinaten des Handschriftendigitalisats auf Textzeilenebene verknüpft. </p>
Data Set of Public Procurement in México (2013-2020)
<p>This repository contains all data sets, manuals, and codes to reproduce the main results shown in the paper "A machine learning model to identify corruption in México's public procurement contracts (on revision in the <em>Journal of Quantitative Criminology</em> - Springer.) (arxive:)</p>
Ray Tracing-Based Delay Model for Compensating Gravitational Deformations of VLBI Radio Telescopes (Data Set)
<p>The precision and the reliability of very long baseline interferometry (VLBI) depend on several factors. Apart from fabrication discrepancies or meteorological effects, gravity-induced deformations of the receiving unit of VLBI radio telescopes are identified as a crucial error source biasing VLBI products and obtained results such as the scale of a realized global geodetic reference frame. Gravity-induced deformations are systematical errors and yield signal path variations (SPVs). In 1988, Clark and Thomsen derived a VLBI delay model, which was adopted by the International VLBI Service for Geodesy and Astrometry (IVS) to reduce these systematic errors. However, the model parametrizes the SPV by a linear substitute function and considers only deformations acting rotationally symmetrically. The aim of this investigation is to derive the signal path variations of a legacy radio telescope and a modern broadband VGOS-specified radio telescope and to study the effect of nonrotationally symmetric deformation patterns. For that purpose, SPVs are obtained from a nonlinear spatial ray tracing approach. For the first time, a tilt and a displacement of the subreflector perpendicular to the optical axis of the feed unit is taken into account. The results prove the commonly used VLBI delay model as a suitable first-order delay model to reduce gravity-induced deformations.</p>
Data set: Europeana Metadata to Analyse The EU's Policy Effectiveness in Digitising European Heritage
<p>This dataset was produced as a part of a research MSc thesis project, “<em>Using Europeana Metadata to Analyse The EU’s Policy Effectiveness in Digitising European Heritage</em><em>” </em>published by the KU Leuven in joint cooperation with Europeana.</p> <p>The dataset contains the data from the Europeana API call, graphs created form the data and the code needed to collect the CH metadata from Europeana digital collections which was used to evaluate the policy aims used in the study. Within this repository one will find the code scripts used to make the API calls, three Raw data files and two cleaned data spreadsheets with graphs used in the published revised research thesis</p> <p>Links to the research produced with this dataset and the Original Thesis published by the KU Leuven can be found below.</p> <p>Research Report: Morgenstern, Paul Simon. (2022). Using Europeana Metadata to Analyse The EU's Policy Effectiveness in Digitising European Heritage. Zenodo. https://doi.org/10.5281/zenodo.7278645</p> <p> </p> <p>Thesis: Morgenstern, P., Truyen, F., & Nyi Nyi Htun, ’. (2022). Using Europeana Metadata to Analyse The EU’s Policy Effectiveness in Digitising European Heritage. KU Leuven. Faculteit Wetenschappen.</p>
Slightly widely sliced cubic insulin data sets for Diamond / CCP4 workshop tutorials
<p>A 450 x 0.2° image data set from a cubic insulin crystal recorded at Diamond Light Source beamline i03 for the 2022 CCP4 workshop. This is to accompany tutorials so that students can download data and work through tutorials at home</p> <p> </p> <p>Tutorial home space is https://github.com/graeme-winter/dials_tutorials</p> <p> </p>
correctKin PLINK data sets
<p>The PLINK data set of archaic mediveal family and the public 1KG individuals used in our manuscript: An optimized method to infer relatedness up to the 4th degree from low coverage ancient human genomes (BMC Genome Biology).</p> <p>The public sample IDs are equivalent with the 1KG phase III IDs. For archaic data: FTH (Father - tooth sample - high coverage); FPM (father - pars petrosa - medium coverage); FPL (father - parse petrosa - low coverage); CPH (Son - pars petrosa - high coverage); FPL (Son - pars petrosa - low coverage).</p> <p> </p>
single-cell RNAseq data (data set 1) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data
<p>The present dataset (dataset1) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from CRC samples downloaded from the GEO website (<strong>GSE81861). </strong></p> <p>see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data</p> <p>and github: https://github.com/sysbiolux/scFASTCORMICS</p> <p>For more information, version updates of the scFASTCORMICS. </p>
Operator-Software Impact in Local Tie Networks: Case study at Geodetic Observatory Wettzell (Data set)
<p>The operator-software impact describes the differences between results introduced by different operators using identical software packages but applying different analysis strategies to the same data. This contribution studies the operator-software impact in the framework of local tie determination, and compares two different analysis approaches. Both approaches are used in present local tie determinations and mainly differ in the consideration of the vertical deflection within the network adjustment. However, no comparison study has yet been made so far. Selecting a suitable analysis approach is interpreted as a model selection problem, which is addressed by information criteria within this investigation. A suitable model is indicated by a sufficient goodness of fit and an adequate number of model parameters. Moreover, the stiffness of the networks is evaluated by means of principle component analysis. Based on the date of a measurement campaign performed at the Geodetic Observatory Wettzell in 2021, the impact of the analysis approach on local ties is investigated. For that purpose, an innovated procedure is introduced to obtain reference points of space geodetic techniques defining the local ties. Within the procedure, the reference points are defined independently of the used reference frame, and are based on geometrical conditions. Thus, the results depend only on the estimates of the performed network adjustment and, hence, the applied network analysis approach. The comparison of the horizontal coordinates of the determined reference points shows a high agreement. The differences are less than 0.2 mm. However, the vertical components differ by more than 1 mm, and exceed the coverage of the estimated standard deviations. The main reasons for these large discrepancies are a network tilting and a network bending, which is confirmed by a residual analysis.</p>
Data set. Testing Protest Paradigm in Femicide Protests in Mexican Press
<p>his Data set consist of the coding of 865 articles from national Mexican newspapers, from El Universal, Reforma, and Excélsior. It is corresponding to research that analyzes the representation of the protests against femicide in the Mexican press, and the opportunities reached by the social movement in the public discourse. Previous studies found a tendency for negative representations of social movements in the media in the so-called ‘protest paradigm’, this means that the attention obtained does not necessarily guarantee the reproduction of the movement’s discourse. We use the paradigm approach and test the degree of adherence. It registered media attention to the femicide issue for a period of 41 months in three national newspapers. The corpus was examined by using the qualitative content analysis technique, with variables that measure the stories’ emphasis, prominence, legitimation, and tone for social movements and authorities, to compare the two actors.</p>
Data Set on Content Excerpts from Relevant Literature for a Scoping Review of Evacuation Training Methods in Buildings
<p>This Excel-file contains a set of data from a scoping review on methods for fire evacuation training in buildings. The review follows the PRISMA approach (Transparent Reporting of Systematic Reviews and Meta-Analyses) and systematically identifies 73 sources among scientific literature published between 1997 and 2022. The dataset contains information excerpted through a custom template on the employed training methods and technology, study information, participants, and contents of the discussion of the 73 sources of evidence that were identified in the systematic review process.</p>
Data set for "The interfacial structure of InP(100) in contact with HCl and H2SO4 studied by reflection anisotropy spectroscopy"
<p>This is the experimental raw data set associated with the following publication: M. Löw, M. Guidat, J. Kim, and MM May, <em>The interfacial structure of InP(100) in contact with HCl and H<sub>2</sub>SO<sub>4</sub> studied by reflection anisotropy spectroscopy</em>, RSC Advances 12 (2022), 32756-32764. <a href="https://doi.org/10.1039/D2RA05159A">DOI:10.1039/D2RA05159A</a></p> <p>The data set is organised along the figures of the publication. '.ers', '.erc', and '.ert' are spectra, colour plots, and transients, respectively, in the native format of Laytec's EpiRAS. '.par' files are in the data format from the Princeton Applied Research VersaSTAT 3F potentiostat. Spectra files containing the name 'Si100' are from Si(100) wafers with native oxide, used for zero-line correction as described in the paper.</p>
Data_set_regionalization
<p>This base-set contain the information for climatic and socio-ecomic variables for Mexico and a factor of severity drought to 2003-2022. The data contain the spatialized variables.</p>
Online appendix and simulated data sets for assesment of Birth-Death Exposed-Infectious (BDEI) phylodynamic model estimators
<p>The birth-death exposed-infectious (BDEI) phylodynamic model describes the transmission of pathogens featuring an incubation period (when there is a delay between the moment of infection and becoming infectious, as for Ebola and SARS-CoV-2), and permits its estimation along with other parameters, from time-scaled phylogenetic trees.</p> <p>We implemented a highly parallelizable estimator for the BDEI model in a maximum likelihood framework (<a href="https://github.com/evolbioinfo/bdei">PyBDEI</a>) using a combination of numerical analysis methods for efficient equation resolution. This dataset contains the assessment of PyBDEI in comparison with a Bayesian implementation in <a href="http://www.beast2.org/">BEAST2</a> (mtbd package) and a deep learning estimator <a href="https://github.com/evolbioinfo/phylodeep">PhyloDeep</a>: the parameter values estimated by the 3 tools.<br><br>The PyBDEI and the theoretical findings behind it are described in A Zhukova, F Hecht, Y Maday, and O Gascuel. Fast and Accurate Maximum-Likelihood Estimation of Multi-Type Birth-Death Epidemiological Models from Phylogenetic Trees Syst Biol 2023. This dataset contains the online Appendix (Fig S1-S3 and Table S1).</p>
Data set accompanying the paper "Effective cell membrane tension is independent of polyacrylamide substrate stiffness"
<p>This data set contains the data presented in the publication "Effective cell membrane tension is independent of polyacrylamide substrate stiffness". It consists of optical tweezers data and traction force microscopy data of 3T3 fibroblasts and Xenopus retinal ganglion cells on several different substrates.</p>
Meteorological responses of carbon dioxide and methane fluxes in the terrestrial and aquatic ecosystems of a subarctic landscape [Data set]
<p>The data set contains carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) fluxes of boreal subarctic landscape and its ecosystems and ecotones, and ancillary meteorological and environmental data, measured at Kaamanen, northern Finland (69°8’ N, 27°16’ E; 155 m a.s.l.), during June 2017 - June 2019. The studied ecosystems and ecotones include: upland pine forest, fen, treed pine bog, sparsely treed pine bog, lakes and string top fen plant community.</p> <p>C_fluxes1b_Heiskanen_et_al_2022.csv includes quality screened, u* filtered and gap-filled eddy covariance ecosystem flux data and modelled pine bog and string top time series utilising eddy covariance and manual flux chamber measurements.</p> <p>C_fluxes2_Heiskanen_et_al_2022.csv includes quality screened daily average lake fluxes from mineral and organic sediment lakes.</p> <p>environmental_data_Heiskanen_et_al_2022.xlsx includes ancillary meteorological and environmental data.</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.