Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
462
datasets available to search
ShareScore release 0.7.1
Dataset results
462 results for “Volcano”
Three Kings Volcano 1940
Three Kings or Te Tatua-a-Riukiuta, a group of scoria cones and Maori hillfort in 1940. One of the three main hills was left unquarried. Auckland, New Zealand. Aerial photos from retrolens.nz . Reuploaded better version of model. My 3D model generated with photogrammetry software 3DF Zephyr v4.350 processing 4 images Source: Objaverse 1.0 / Sketchfab
Cabo Verde Fogo Volcano Interferogram November 2014
<p>A volcano eruption in Fogo Island, Cabo Verde, began on 23 Nov 2014, affecting the people living in Chã das Caldeiras, the volcano crater area. An estimated 1,000 people have been evacuated from the area, of which 838 have been relocated in temporary accommodation centres and in houses built in the aftermath of the 1995 eruption.</p>
PSI Santorini Volcano Unrest (Greece)
<p>Persistent Scatterer Interferometry (PSI) dataset over Santorini volcano (Greece) for the unrest period of March 2011 - March 2012 (ESA ENVISAT mission).</p> <p>Foumelis, M., Trasatti, E., Papageorgiou, E., Stramondo, S. & Parcharidis, I., 2013. Monitoring Santorini volcano (Greece) breathing from space. Geophysical Journal International 193 (1), 161-170, doi: 10.1093/gji/ggs135.</p> <p> </p>
Puyehue Volcano Sin-eruptive SAR deformation
<p>On June 4, 2011, Puyehue-Cordon Caulle complex began its eruptive activity. This intense eruption lasted for several months and was characterized by both effusive and explosive activities. ENVISAT ASAR sensor imaged the eruption of the volcano, and the sin-eruptive surface deformation was estimated by using Differential SAR Interferometry (DinSAR). The present dataset is the result of such estimation, and reports the SAR Line of Sight (LoS) displacement, in metres, related to the first phase of the eruption. In particular, the ASAR images used for DinSAR processing are dated May 08, 2011 and June 07, 2011. The interferogram shows a large deflating area in the Cordon Caulle section of the volcanic complex that reaches a value of -90 cm. Moreover, few centimetres of deflation are also present in the west flank of Puyehue stratocone.</p>
Data: Muon Tomography sites for Colombia volcanoes for generate muon flux trought volcanic structures (arXiv:1705.09884v1)
<p><strong>Data: Muon Tomography sites for Colombia volcanoes (arXiv:1705.09884v1)</strong><br> <strong>The MuTe Collaboration</strong><br> <em>Data for generating figure 6<br> Muon Tomography sites for Colombia volcanoes (arXiv:1705.09884v1)</em></p> <p>The files in this record contain data from Extensive Atmospheric Shower simulations made by CORSIKA and Magnetocosmic codes, in a muography of Machin Volcano (Colombia) [https://volcano.si.edu/volcano.cfm?vn=351040] for a particular observation point. The objective was to count muons crossing the volcanic structure for a fixed observation point. Muon transport through the volcanic edifice is calculated by using an algorithm taken Corsika-Magnetocosmic output and taking into account the energy losses with the muon stopping power tables given by Particle Data Group (PDG).</p> <p>This dataset contains:</p> <ul> <li>Six (6) Corsika output files of 4 hours of simulation each using a flat detector (equivalent to 12 hours of simulated cosmic rays).</li> <li>One (1) Corsika output file of 12 hours of simulation using flat detector (equivalent to 6 hours of simulated cosmic rays).</li> <li>One (1) Corsika output file of 48 hours of simulation using flat detector (equivalent to 24 hours of simulated cosmic rays).</li> <li>Two (2) Corsika output files of 24 hours of simulation each using volumetric detector (equivalent to 48 hours of simulated cosmic rays).</li> <li>Everything makes a total simulated time of 3.75 days.</li> </ul> <p>The output files necessary for the determination of the muon flux through the volcanic structure are obtained through the following process:</p> <ul> <li>From the .shw.bz2 files it is possible to obtain an output file with the momentum information of the particle in the x, y, and z directions, and also the total momentum of the muons, essentially a formatted file (px, py, pz, p). This file can be built by typing in a terminal shell (bash code):</li> </ul> <p><em><strong>> </strong></em><strong>bzcat *.shw.bz2 | awk '{if($1==0006 ||$1==0005){j=sqrt(($2*$2)+($3*$3)+($4*$4));printf "%s %s %s %.s\n",$2, $3, $4, j }}' | sort -n > salida.out</strong></p> <ul> <li>Metadata in the showers file is as this type (for example):</li> </ul> <p># # # shw</p> <p># # CURVED mode is ENABLED and observation level is 2750 m a.s.l.</p> <p># # This is the Secondaries file - CrkTools v3r0</p> <p># # 12 column format is:</p> <p># # CorsikaId px py pz x y z shower_id prm_id prm_energy prm_theta prm_phi</p> <p>0001 +1.42146e-04 -3.96008e-05 +1.60247e-04 -1.31716e+03 -6.10051e+01 +2.44986e+03 00000001 0703 +1.25065e+02 +43.016 +021.768</p> <p>0003 +1.80713e-04 +1.89560e-03 +4.49373e-03 -1.32279e+03 -5.62869e+01 +2.44986e+03 00000001 0703 +1.25065e+02 +43.016 +021.768</p> <p>0003 +9.41713e-03 +2.38845e-03 +1.10020e-02 -1.32098e+03 -5.68323e+01 +2.44986e+03 00000001 0703 +1.25065e+02 +43.016 +021.768</p> <ul> <li>Concatenate all output files.</li> <li>Then, the muon flux trought rock can be calculated from two python codes, available in https://github.com/AstroparticulasBucaramanga/Propagacion-Muones-en-Roca. This step generates the final files to be graphed with any plotter, in our case, also using python.</li> </ul>
Dataset for: "Gas buffering of magma chamber contraction during persistent explosive activity at Mt. Etna volcano"
<p>Data used for generating the figures in the paper "Gas buffering of magma chamber contraction during persistent explosive activity at Mt. Etna volcano", accepted for publication in Nature Communications Earth & Environment.</p>
Dataset: Very-small-aperture 3-D infrasonic array for volcanic jet observation at Stromboli Volcano, Geophysical Journal International, Volume 229, Issue 1, Pages 459–471, https://doi.org/10.1093/gji/ggab487
<p>This is the dataset of the infrasound observation of Yamakawa et al. (GJI, 2022).</p>
Waitomokia volcano 1939
Waitomokia or Mt Gabriel volcanic scoria cone in 1939 before it was quarried. Auckland, New Zealand. Aerial photos from retrolens.nz. My 3D reconstruction generated with photogrammetry software 3DF Zephyr v4.009 processing 3 images Source: Objaverse 1.0 / Sketchfab
Mt Richmond and McLennan Hills volcanoes 2 1940
Mt Richmond or Otahuhu, and McLennan Hills, volcanic scoria cones and Maori hillforts, in 1940 before McLennan Hills was quarried away. Otahuhu is named after Maori chief Tahuhu who founded a settlement there in the 14th century. The local scoria cones were used as defendable hillforts, had fertile soil for growing crops and were next to a canoe portage route across the narrowest part of the Auckland isthmus. Auckland, New Zealand. Aerial photos from retrolens.nz . This version covers a wider area, showing both coastlines. My 3D model from photos generated with photogrammetry software 3DF Zephyr v4.351 processing 5 images Source: Objaverse 1.0 / Sketchfab
"Volcanoes and Seismic Activity Dataset"
<p>El datset “Volcanoes and Seismic Activity Dataset” és el resultat de la PRA1 de l'assignatura de Tipologia i Cicle de Vida de les Dades, del Màster de Ciència de Dades de la UOC.</p> <p>El conjut de dades s'ha generat en aplicació de técniques de web scraping a la pàgina web https://www.volcanodiscovery.com/volcanoes.html, completant el registre de tots els volcans de la pàgina web, certes caracteristiques com d'ubicació, estat i morfologia bàsica i els darrers sísmes asociats a cadascún d'ells a la data dels raspat. </p> <p>El total de volcans únics registrats és de 2.070.</p> <p>El total de registres del dataset és de 3.416. Cada volcà pot tenir diferents sísme associats. </p> <p>El total de camps del dataset és de 10.</p> <p>Descripció dels camps:</p> <ul> <li> <p>Name (nom): Inclou el nom del volcà.</p> </li> <li> <p>URL (enllaç): Inclou els enllaços a la pàgina de cada volcà.</p> </li> <li> <p>Type/Height (tipus i altura): Inclou el tipus de volcà (segons morfologia) i la seva altura en metres (m) i peus (ft).</p> </li> <li> <p>Status (estat): Inclou l’estat del volcà, és a dir, si és un volcà actiu, extingit, i el seu grau d’activació en escala Likert del 0 (extingit) al 5 (actiu).</p> </li> <li> <p>Territory/Geolocation (Territori/coordenades geolocalització): Inclou la regió on es troba el volcà i les coordenades de localització.</p> </li> <li> <p>Eruption style (tipus d’erupcions): Inclou el tipus d’erupció observada per cada volcà. En alguns casos, pot incloure més d’un estil d’erupció.</p> </li> <li> <p>Earthquake date (data del terratrèmol): Si el volcà té un terratrèmol associat, la data i l’hora en què va passar el terratrèmol. En alguns casos, indica també els dies que fa des de la seva ocurrència prenent com a referència el moment en què es va realitzar l’scraping.</p> </li> <li> <p>Magnitude/Depth (magnitud/profunditat): Inclou la magnitud i la profunditat del terratrèmol. Cal separar els dos valors en una posterior neteja de les dades: les dues primeres xifres, normalment separades per un punt, fan referència a la magnitud i les últimes xifres, a la profunditat (ex. 3.4205 km es correspondria a una magnitud de 3.4 i una profunditat de 205 km).</p> </li> <li> <p>Distance (distància): Inclou la distància del terratrèmol respecte del volcà i la direcció.</p> </li> <li> <p>Earthquake location (ubicació del terratrèmol): Inclou el país/estat i l’àrea o regió on s’ha donat el terratrèmol.</p> </li> </ul>
Drumbeat and low frequency catalogue for 2022 unrest at Ruapehu volcano, New Zealand
<p>This data set contains csv files for different types of seismic signal observed at Ruapehu volcano during the unrest event of 2022.</p> <p>This data is associated with the following paper, if you are using it please cite appropriately:</p> <p>Bramwell, L.A., Illsley-Kemp, F., Hughes, E.C., Butcher, S., Lamb, O.D. and Behr, Y., 2025. Source dynamics of Ruapehu’s 2022 volcanic unrest: insights from drumbeat seismicity, tremor, and crater lake signals. <em>Bulletin of Volcanology</em>, <em>87</em>(6), p.44.</p>
Dataset for "Unraveling the underlying hydrous plume geometry and its resulting topography of intraplate volcanoes"
<p>These data files include the raw data for the production of the figures in Dasgupta and Lee, titled "Unraveling the underlying hydrous plume geometry and its resulting topography of intraplate volcanoes".</p>
Tracking magma spine extrusion from space: Implications for conduit and topography complexity at Shiveluch volcano, Kamchatka - Webcam data repository
<p>Webcam data showing the growth of a spine at Shieveluch volcano.</p> <p>The data is provided in three formats.</p> <p>First the original images with clear visibility are provided.</p> <p>Second a time lapse movie is provided with images co-aligned to reduce shaking of the camera.</p> <p>Third, a zoom in of the time lapse movie is provided.</p> <p>For more information we refer to the publication with the title "Tracking magma spine extrusion from space: Implications for conduit and topography complexity at Shiveluch volcano, Kamchatka" published in Nature Communications E Env</p>
Elevational patterns in tropical bryophyte diversity differ among substrates: a case study on Baru volcano, Panama
<p><strong>Questions. </strong>Bryophytes attain their highest diversity in tropical mountain forests. Although distribution patterns have been described, little emphasis has been placed on comparing patterns among substrates (e.g., terrestrial, epiphytic). Understanding these patterns is important, because they determine not only the pool of genetic resources, but also the functioning of these forest ecosystems. Therefore, we studied how bryophyte species diversity changes with elevation, how elevational patterns differ between substrate types, and how elevational trends relate to environmental drivers.</p> <p><strong>Location. </strong>Baru Volcano, Panama.</p> <p><strong>Methods. </strong>At each of eight elevations, between 1900 and 3300 m, bryophytes were collected in 600-cm<sup>2</sup> plots from six substrate types with four replicates. Species cover was registered as a measure of relative abundance. Species richness and community structure were determined and related to elevation, substrate types, and environmental drivers at three scales (plots, sets of four replicate plots per substrate per elevation, and all plots at each elevation).</p> <p><strong>Results. </strong>Bryophyte species richness decreased towards higher elevations, at all three scales and on all substrates except bryophytes on soil, for which, at the plot scale, richness peaked at higher elevations than on the other substrates. Relative humidity explained richness slightly better than elevation. Communities at the lowest elevations had the most uneven compositions, due to the presence of many small species with low abundance.</p> <p><strong>Conclusions. </strong>In studies on the spatial distribution of bryophyte diversity, it is essential to consider different substrates and spatial scales separately. If substrates differ in their elevational species-richness patterns, climate and land-use change may affect bryophyte diversity patterns not only directly, but also indirectly via changes in substrate availability. Therefore, a better understanding of the spatial variation in bryophyte diversity in mountains is essential to elucidate the effects of environmental change on this important group of plants and their implications for ecosystem functioning.</p> <p>FILE: Main data base_JVC.xlsx</p> <p>Sheet=TaxonomicInformation</p> <p>Our database contains taxonomic information on bryophyte species collected along an elevation gradient on the Baru volcano, Panama.</p> <p>Sheet=data</p> <p>The relative abundance of each species or morpho-species is included per 600-cm2 plot in each of the six considered substrates (soil = terricolous, rock = saxicolous, decomposing downed log (i.e. lying on the ground) = lignicolous, tree base = epiphytic on tree base, tree trunk = epiphytic on tree trunk, and understorey branch = epiphytic on branch).</p> <p>Sheet: climatic info<br> In addition, we present the information on the climate recorded between April and December 2017.<br> Acronyms: elev: elevation, tempmean: mean temperature over the measurement period (°C), tempmin: minimum temperature over the measurement period (°C), tempmax: maximum temperature over the measurement period (°C), rhmean: mean relative humidity over the measurement period (%), rhmin: minimum relative humidity over the measurement period (%), rhmax: maximum relative humidity over the measurement period (%), cancov: canopy-cover (%), heican: height of the canopy ( m).</p>
Geochronological and Geochemistry data from BC eruption of Changbaishan-Tianchi volcano
<p>It is raw data of geochronological and geochemistry data of Bingchang eruption of Changbaishan-Tianchi volcano. The geochronological data was determined by the <sup>40</sup>Ar/<sup>39</sup>Ar methods. The geochemistry data were analyzed by Electron Probe Micro-analyzer (EPMA) using a Cameca SX-100 electron microprobe at Oregon State University (OSU), USA. </p>
Supplementary Material 1 : Monitoring Hydrothermal Activity Using Major and Trace Elements in Low-Temperature Fumarolic Condensates, The Case of La Soufriere de Guadeloupe Volcano, by Inostroza et al.
<p>Supplementary Material 1 - Monitoring hydrothermal activity using major and trace elements in low-temperature fumarolic condensates, the case of La Soufriere de Guadeloupe volcano, by Manuel Inostroza, Séverine Moune, Roberto Moretti, Vincent Robert, Magali Bonifacie, Elodie Chilin-Eusebe, Arnaud Burtin, Pierre Burckel</p>
Supporting Information for "Quantifying the statistical relationships between flank eruptions and major earthquakes at Mt. Etna volcano (Italy)". Data Sets S1-S7.
<p>This compressed folder contains supporting information related to the manuscript: "Quantifying the statistical relationships between flank eruptions and major earthquakes at Mt. Etna volcano (Italy)".</p> <p>Data Set S1. Catalog of flank eruptions<br> Historical catalog of flank eruptions of Mt. Etna from 1600 to 2018.</p> <p>Data Set S2. Catalog of major earthquakes<br> Macroseismic catalog of Etnean earthquakes from 1800 to 2018.</p> <p>Data Set S3. GIS dataset of Eruptive fissures<br> GIS shapefiles of eruptive fissures at Mt. Etna from 1800 to 2018. UTM WGS84, Zone 33 N.</p> <p>Data Set S4. Tests with ±2 months maximum inter-event time <br> Histograms of the inter-event time of earthquakes and flank eruptions lesser than ±2 months. Pie charts of the positive values (dark colors), negative values in [-2.5, 0] days (light colors), and lower than -2.5 days (white) are reported.</p> <p>Data Set S5. Tests with dt = 5 days moving window <br> Conditional rates of major earthquakes less than ±4 months from flank eruptions, obtained assuming dt = 5 days instead of dt = 10 days. A solid line marks the average annual rate of the earthquakes, and bold lines threshold rates 2, 5, and 10 times larger than the average value.</p> <p>Data Set S6. Tests on the eruptions end, including earthquakes in ±2.5 days from the onset<br> Conditional rates of major earthquakes less than ±4 months from flank eruptions end, obtained without excluding the earthquakes occurred in ±2.5 days from the onset. A solid line marks the average annual rate of the earthquakes, and bold lines threshold rates 2, 5, and 10 times larger than the average value.</p> <p>Data Set S7. Summary of inter-event time histograms <br> Histograms of the inter-event time of earthquakes and flank eruptions lesser than ±4 months, also decomposed according to spatial groups E1-E4 and fault systems F1-F4. Light-colored bars highlight the eruptions > 2850 m.a.s.l.</p>
Code for noise-based seismic velocity changes estimation with the Bezymianny volcano data set. Journal of Volcanology and Geothermal Research.
<p>This file contains all the data and the python scripts used to estimate seismic velocity changes for the Bezymianny volcano (Klyuchevskoy volcano group). It also includes a guideline README.pdf with the description how to reproduce all the results presented in the paper <strong>Berezhnev Y., Belovezhets N., Shapiro N., Koulakov I. (2022), Temporal changes of seismic velocities below Bezymianny volcano prior to its explosive eruption on 20.12.2017, Journal of Volcanology and Geothermal Research</strong></p>
Infrasound data recording the August 2021 eruption of Fukutoku-Oka-no-Ba submarine volcano, Japan
<p>Infrasound data recorded at Chichijima of Ogasawara Islands, Japan. The data include signals from the Fukutoku-Oka-no-Ba eruption from 13 to 15 of August, 2021 (Maeno, F., T. Kaneko, M. Ichihara, Y.J. Suzuki, A. Yasuda, K. Nishida, and T. Ohminato, submitted to Communications Earth & Environment). The file is in Matlab data format in the following foramt:</p> <p>data.time (matlab date format)</p> <p>data.ph (band-passed data at 5-15 Hz with sampling rate of 100 Hz)</p> <p>data.lat (Station latitude)</p> <p>data.lon (Station longitude)</p> <p>data.elv (Station elevation in meter above sea level)</p> <p>data.sensor (Sensor type)</p> <p>data.unit (Unit of data.ph)</p> <p> </p> <p> </p>
Electronic Distance Measurements (EDM) on active Sicilian Volcanoes (1975-2009).
<p><strong>File descriptions</strong>: This dataset includes ca. 8000 Electronic Distance Measurements (EDM) collected from 1974 to 2009 on several networks installed on Sicilian Volcanoes (Vulcano, Stromboli, Etna and Pantelleria).<br> EDM represent one of the first methods to detect ground deformation on volcanoes having been used since 1964 on Kilauea (Hawaii). It is a precise technique that uses a laser to measure the transit time of light between a base station to the reflecting prisms positioned around the volcano; the repetition of these measurements in time allows one to monitor the slope distance variations.<br> EDM is a powerful tool for volcano monitoring that has been useful to define the features of magmatic and hydrothermal sources as their volume, position, geometry, and dynamics. Moreover, this technique has been largely used on volcanoes in 70th to 90th years until the 2000s when it has been gradually abandoned in favor of GPS.<br> This dataset reports data obtained on several Sicilian volcanoes (Etna, Vulcano, Stromboli and Pantelleria) from the early ’70 to until the 2000s, in which EDM measurements have played a major role in volcanic process knowledge and that make the Sicilian volcanoes among the ones with the longest geodetic record in the World.<br> Database has been organized on Microsoft Excel files and each file reports the network name (the networks list is in Table1.xls).<br> Inside each data file (in “database” directory), there are two sheets with a sheet reporting all measured distances and a table with associated errors. The position of each benchmark is reported on specific coordinate network files in “benchmarks coordinates” directory). All the coordinates have been obtained with GPS technique, except for the Ionica network where they have been derived from paper maps and therefore suffer by a bigger approximation.<br> In the data files, rows show the measurement date, the instrument model and recorded values; in the first column, the pairs of benchmarks considered are reported.<br> The networks Etna S and Etna NE have additional files, reporting the most frequent measurements taken during the eruptive crises of July 2001 (onset of 2001 eruption) and of October 2002 (onset of the 2002-03 eruption).<br> Almost all networks were measured using both the AGA6BL and the AGA 6000 Geodimeters. In the files, the survey in which the transition from one instrument to the other took place is highlighted. In those surveys, measurements were performed with both instruments in order to maintain the time-series continuity. Furthermore, in the tables “double” measurements related also to reflectors changes or new benchmarks have been highlighted.</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.