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.
10
datasets available to search
ShareScore release 0.7.1
Dataset results
10 results for “Geodesy”
Elucidating the Magma Plumbing System of Ol Doinyo Lengai (Natron Rift, Tanzania) Using Satellite Geodesy and Numerical Modeling; Model input and output files
<p>These are the model input and output associated with the manuscript "Elucidating the Magma Plumbing System of Ol Doinyo Lengai (Natron Rift, Tanzania) Using Satellite Geodesy and Numerical Modeling" in consideration for publication in the Journal of Volcanology and Geothermal Research.</p>
Supplementary material: Accuracy of finite fault slip estimates in subduction zone regions with topographic Green's functions and seafloor geodesy
<p># Code attached to the manuscript entitled "Accuracy of finite fault slip estimates in subduction zone regions with topographic Green's functions and seafloor geodesy"</p> <p>These python scripts are for producing Figure 1 (trench-perpendicular topographic profile for regions where some megathrust earthquakes occurred) and the average topographic profile that is used in the paper.</p> <p> </p>
Decadal seafloor geodesy constrains frictionally locked areas along the Nankai Trough
Open the record for dataset details and reuse information.
Elucidating the Magma Plumbing System of Ol Doinyo Lengai (Natron Rift, Tanzania) Using Satellite Geodesy and Numerical Modeling: Supplementary Model Files
<p>Supplementary code and model files for the manuscript entitled "Elucidating the Magma Plumbing System of Ol Doinyo Lengai (Natron Rift, Tanzania) Using Satellite Geodesy and Numerical Modeling". OlDoinyoLengai_code_and_models.zip contains all necessary Matlab code, functions, input and output files for the GNSS, InSAR, and joint inversions presented in our manuscript necessary to reproduce the results. dMODELS is an open source code developed by the United States Geological Survey. The originally published program is available here: https://pubs.usgs.gov/tm/13/b1/ and the revised software archived here will also be available through the USGS website code.usgs.gov/vsc/publications/OlDoinyoLengai or by contacting Maurizio Battaglia. With this manuscript we are providing an update to dMODELS that includes improved graphics and joint inversion capabilities for both InSAR and GNSS data. </p>
Datasets, scripts and Jupyter Notebook for "Two distinct magma storage regions at Ambrym volcano detected by satellite geodesy", Geophysical Research Letters
<p>This repository includes scripts and files necessary to create Figure 1 (<strong>S1.zip </strong>and <strong>plot_TS_Ambrym_2019_2022.py</strong>) in "Two distinct magma storage regions at Ambrym volcano detected by satellite geodesy", <em>Geophysical Research Letters</em>. We also include the Jupyter Notebook used to run the EnKF data assimilation (<strong>enkf_notebook.zip) </strong>and produce Figures 2 and 3. The Jupyter Notebook and files used to produce Figure 4b,c can be found on <a href="http://github.com/tshreve/jupyterNBs/">GitHub</a>.</p> <p>This version corrects a bug in the code used to plot the cross-sections in Figure 3 with <strong>enkf_notebook.zip</strong>.</p>
SPARQLing Geodesy for Cultural Heritage – New Opportunities for Publishing and Analysing Volunteered Linked (Geo-)Data
<p><strong>SUMMARY</strong></p> <p>Geodesists are working in Industry 4.0 and Spatial Information Management by using cross linked machines, people and data. Moreover, open source software, open geodata and open access are becoming increasingly important. As part of the Semantic Web, Linked Open Data (LOD) must be created and published in order to provide free open geodata in interoperable formats. With this semantically structured and standardised data it is easy to implement tools for GIS applications e.g. QGIS. In these days, the world’s Cultural Heritage (CH) is being destroyed as a result of wars, sea-level rise, floods and other natural disasters by climate change. Several transnational initiatives try to preserve our CH via digitisation initiatives. As best practice for preserving CH data serves the Ogi Ogam Project with the aim to show an easy volunteered approach to modelling Irish `Ogam Stones` containing Ogham inscriptions in Wikidata and interlinking them with spatial information in OpenStreetMap and (geo)resources on the web.</p> <p><strong>ZUSAMMENFASSUNG</strong> </p> <p>Geodäten arbeiten in der Industrie 4.0 mit vernetzten Maschinen, Menschen und Daten. Zudem werden die Themen Open Source Software, offene Geodaten und Open Access immer wichtiger. Linked Open Data (LOD) müssen erstellt und veröffentlicht werden, um so freie und offene Geodaten in interoperablen Formaten als Teil des Semantic Web zur Verfügung zu stellen. Mit diesen semantisch strukturierten und standardisierten Daten ist es einfach Tools für GIS Applikationen, z.B. QGIS, zu erstellen. Zurzeit werden Kulturgüter (CH) der Welt durch Kriege, Meeresspiegelanstieg, Überflutungen und andere Naturkatastrophen, die durch den Klimawandel verursacht wurden, zerstört. Einige transnationale Initiativen versuchen daher die Kulturgüter durch Digitalisierungs-Initiativen zu erhalten. Als Beispiel dient hier die Digitalisierung im Ogi Ogham Projekt, das zum Ziel hat, einen einfachen auf Freiwilligenbasis fußenden Ansatz zu verfolgen, der irische `Ogham Steine` und deren Ogham Inschriften in Wikidata modelliert und diese mit Geodaten aus OpenStreetMap und deren Geodaten im Web referenziert.</p>
Data from: A geology and geodesy based model of dynamic earthquake rupture on the Rodgers Creek-Hayward-Calaveras fault system, California
<p>The Hayward fault in California's San Francisco Bay area produces large earthquakes, with the last occurring in 1868. We examine how physics-based dynamic rupture modeling can be used to numerically simulate large earthquakes on not only the Hayward fault, but also its connected companions to the north and south, the Rodgers Creek and Calaveras faults. Equipped with a wealth of images of this fault system, including those of its 3D geology and 3D geometry, in addition to inferences about its interseismic creep rate pattern and rock-friction behavior, we use a finite-element computer code to perform 3D dynamic earthquake rupture simulations. We find that the rock properties affect the locations and amount of slip produced in our simulated large earthquakes. Crucial factors that control rupture behavior in our modeling are the earthquake nucleation locations, the fault geometry, and the data that reveal where the fault system is creeping or locked. Our findings suggest that large Rodgers Creek-Hayward-Calaveras-Northern Calaveras (RC-H-C-NC) fault-system earthquakes may result from dynamic rupture that starts in a locked part of the fault system, but is then stopped by the creeping parts, leading to high magnitude-6 earthquakes; or, from dynamic rupture that starts in a locked part of the fault system, then cascades through some of the creeping parts, leading to magnitude-7 earthquakes.</p>
Data from: A geology and geodesy based model of dynamic earthquake rupture on the Rodgers Creek-Hayward-Calaveras fault system, California
Open the record for dataset details and reuse information.
Probing fault frictional properties during afterslip up- and downdip of the 2017 Mw 7.3 Sarpol-e Zahab earthquake with space geodesy
<p>This zip file contains measurements of postseismic surface deformation due to the 2017 Mw 7.3 Sarpol-e Zahab earthquake derived from Sentinel-1 SAR data over a time period of one year after the mainshock. The line-of-sight (LOS) displacements of each satellite track are provided in high-resolution NetCDF file format.</p> <p># data format: NetCDF grid file</p> <p>dlos_yyyymmdd.grd ---- cumulative LOS displacement since the first postseismic acquisition of each track (unit: meters); <br> dates.dat ----- dates of the SAR image acquisitions of each track (ASCII file)<br> look_e/n/u.grd --- East, North, Vertical (Up) components of the line-of-sight direction, so that<br> <br> dlos_displacement = dUe*look_e + dUn*look_n + dUup*look_u</p> <p>where dUe, dUn, and dUup represent the Eastward, Northward, and Upward surface motion.</p> <p>Contact: Kang Wang (kjellywang@gmail.com or kwang@seismo.berkeley.edu)</p> <p>References:</p> <p>Wang, K and R. Bürgmann (2020), Probing fault frictional properties during afterslip up- and downdip of the 2017 Mw 7.3 Sarpol-e Zahab earthquake with space geodesy, Journal of Geophysical Research: Solid Earth<br> </p>
data files for Fonseca et al, Interseismic Strain Accumulation near Lisbon (Portugal) from Space Geodesy, submitted to GRL
<p>Data used to produce the figures of Fonseca et al., Interseismic Strain Accumulation near Lisbon (Portugal) from Space Geodesy (submitted to GRL)</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.