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Figure 2 in The Simulium vernum group (Diptera: Simuliidae) in Europe: multiple character sets for assessing species status
Figure 2. Base of a typical gill of a Finnish pupa of Simulium juxtacrenobium Bass & Brockhouse, 1990.
Figure 3 in The Simulium vernum group (Diptera: Simuliidae) in Europe: multiple character sets for assessing species status
Figure 3. Cephalic cuticle of pupae, showing the location of the cross-sections for counting microtubercles (100¥), and sections of the surface sculpture (200¥) of (A) S. juxtacrenobium Bass & Brock., (B) Simulium crenobium (Knoz, 1961), and variations (C, D) of Simulium vernum s.s. Macquart, 1826 across the right-hand side of the middle transect. Scale bars: 0.1 mm.
Figure 1 in The Simulium vernum group (Diptera: Simuliidae) in Europe: multiple character sets for assessing species status
Figure 1. Ventral plate (vp; ventral view), left gonostylus (gl; posteromedial view), and gonostyli (gst; posterior view) of (A) Simulium crenobium (Knoz, 1961), (B) Simulium juxtacrenobium Bass & Brockhouse, 1990, and (C) Simulium vernum s.s. Macquart, 1826. Length and width measurements of basal arms (al, aw) and body (bl, bw) indicated in (b). Scale bar: 0.1 mm.
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>
TaqMan array sequence set for 52-target respiratory pathogen array
<p>Sequence list for probes and primers used in the respiratory Taqman array card investigated in project, protocol 10.5281/zenodo.5081880</p>
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>
Full maize tassel image set in the study of Tasselyzer version 1
<p>Male fertility in maize is controlled by development and genetic programming and is directly impacted by environmental factors such as light, temperature, water, and nutrient availability; the control of this trait has substantial agronomic utility. Maize anthers emerge from male florets, which are clustered to form the tassel at the top of the plant separated from the female ear. Quantification of anther extrusion is one important aspect in the determination of male fertility. To address the lack of an automated method to measure anther extrusion on a large scale, we developed “Tasselyzer'', a quantitative, image-based color trait analysis pipeline for tassel image segmentation, based on the existing PlantCV platform, and we applied it to determine the proportion of anther extrusion. We evaluated Tasselyzer in maize during the seven-day period of pollen shedding as well as in the temperature-sensitive male sterile mutant <em>dcl5</em>. With tassel images obtained with a smart phone camera, we show that the anther scores positively correlate with anther extrusion, and such methods can be used to measure environmental impacts on the <em>dcl5</em> mutant. Altogether, this work establishes an automated and inexpensive method to quantify anther extrusion in maize, which would be useful for research and breeding. </p> <p>Here is the full image set was used in Tasselyzer version 1. </p>
Setting files from: Simulated patterns of mitochondrial diversity are consistent with partial population turnover in Bronze Age Central Europe
<p><strong>Simulated Data and Simulation Program</strong></p> <p>This dataset release permits to simulate the scenarios investigated in the article entitled "Simulated patterns of mitochondrial diversity are consistent with partial population turnover in Bronze Age Central Europe" by Broccard et al, using the program SPLATCHE3, which is included.</p> <p>There is a zipped folder "Broccard_et_al_SimulationData.zip" that contains i) a "ReadMe.txt" file with the instructions to launch the simulations; ii) the executable called "SPLATCHE3-Linux-64b"; iii) the input settings file for the various scenarios.</p> <p>See Broccard, N, Silva, NM and & Currat M., American Journal of Biological Anthropology (2021), for background and http://www.splatche.com/splatche3 for more information about the simulation program.</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>
Set of cross sections presented in "Electronic excitation of benzene by low energy electron impact and the role of higher lying Rydberg states"
<p>Contents:</p> <p>117_ch_thresholds.txt: TCIS excitation energies obtained from the 117CH-B1 calculation.</p> <p>305_ch_thresholds.txt: TCIS excitation energies obtained from the 305CH-B2 calculation.</p> <p>117_ch_DCS.tar.gz: differential cross sections obtained from the 117CH-B1 calculation.</p> <p>305_ch_DCS.tar.gz: differential cross sections obtained from the 305CH-B2 calculation.</p> <p>305_ch_DCS_BC.tar.gz: differential cross sections obtained from the 305CH-B2 calculation with the Born-Closure procedure for the dipole-allowed transitions of band V.</p> <p>305_ch_ICS_and_ICS_BC.tar.gz: elastic and summed electronic excitation integral cross sections and total cross sections, obtained from the 305CH-B2 calculation, with and without the Born-Closure procedure for the dipole-allowed transitions of band V.</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>
Selection function for spectroscopic surveys (main set).
<p>Selection function values for large spectroscopic surveys. Supplementary material for A&A paper Minst&Hekker 2018 (https://ui.adsabs.harvard.edu/#abs/2018arXiv181012296M/abstract). Main set (all stars in each survey)</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>
Additional set of photos for the publication "The oldest case of paedomorphosis in rove beetles: a new genus of Paederinae from Cretaceous amber (Coleoptera: Staphylinidae)"
<p>Additional set of photos of two specimens of extinct <em>Midinudon juvenis</em> Tokareva & Żyła gen. et sp. nov. (Coleoptera: Staphylinidae) in Burmese amber. Accession codes of specimens in the collection of the Leibniz Institute for the Analysis of Biodiversity Change are GPIH05515 and GPIH05516.</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>
Automated Nuclear Pleomorphism Scoring in Breast Cancer: Slide-Study test set
<p>This dataset contains data from the Slide-Study data set used in the paper:</p> <p>[1]<em> C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polonia, H. M. Horlings, W. Weichert, J. M. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J.-M Bokhorst, J. van der Laak, F. Ciompi, Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer. NPJ Breast Cancer, 2022.</em></p> <p>The dataset consists of n=118 digital pathology whole-slide images (WSI) of breast cancer surgical resections, stained with hematoxylin and eosin (H&E) at Radboud University Medical Centers, Nijmegen (The Netherlands).</p> <p>The WSIs were scanned with a 3DHistech P1000 scanners at 0.25 um/px spacing, originally stored in MRXS file format. However, the WSIs made available here have been converted to TIFF format with a maximum spacing of 0.5 um/px. This was done to make slides broadly accessible (since MRXS files are sometimes not compatible with some digital pathology viewers or APIs), and with the same spacing used in the prediction of the pleomorphism score in the NPJ breast cancer paper.</p> <p>Note that we are solely releasing the Slide-Study test set used in [1]. Together with the data, we have released a web-based evaluation platform via the <a href="https://grand-challenge.org/">grand-challenge.org</a> platform, which can be found at this link: <a href="https://breastpleomorphism.grand-challenge.org/">https://breastpleomorphism.grand-challenge.org/</a>. In this way, researchers can download the WSI from Zenodo, process them with their algorithm to predict a single pleomorphism score for each slide, compile the predictions as indicated on the grand-challenge.org page, and submit them, to compare the results with the ones presented in the paper and with the opinion of a panel of four pathologists involved in the study.</p> <p>The data is released under CC BY-NC 4.0 license.</p>
Sappho Fragment 44 Set to Music. Hector and Andromache, A Wedding at Troy
<p>Aliki Markantonatou performs the surviving fragment of the ancient Greek poet Sappho's poem, ‘A Wedding at Troy’. The tune that it is performed to is the tune that would have accompanied the poem when it was sung in ancient Greece. Sappho's poem is a prequel to the Trojan War, recalling the time when Trojan Prince Hector arrived home with his new wife, Andromache.</p> <p>This recording was made to accompany the Panoply Vase Animation Project's vase animation 'Sappho 44: Hector and Andromache – A Wedding at Troy' <a href="https://www.youtube.com/watch?v=ZSn63s88InI&t=0s">https://youtu.be/ZSn63s88InI</a>, and the documentary 'About Sappho' <a href="https://www.youtube.com/watch?v=r_IWSbE1T9o&t=0s">https://youtu.be/r_IWSbE1T9o</a>.</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>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.