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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Fernandez-Turiel, J. L.; Perez-Torrado, F. J.; Rodriguez-Gonzalez, A.; Saavedra, J.; +8 Authors

    This dataset compiles SEM images, modelled isopach map and topographic profiles, and data of radiocarbon ages, parameters of Tephra2 and AshCalc codes of Holocene volcanic ashes of of Southern Puna and neighbouring areas (NW Argentina). SEM images detail differences among the Bolsón de Fiambalá, Cerro Blanco and Cueros de Purulla fallout ash deposits. Tephra2 code was used to simulate the ash fallout, and the AshCalc code to compare different methods for ash volume estimates associated with the 4.2 ka cal BP eruption of the Cerro Blanco Volcanic Complex. Topographic profiles are used to explain the secondary thickening of fallout ash deposits. Material suplementario (Figuras S1-S4 y Tablas S1-S4 del artículo Fernandez-Turiel, J.-L.; Perez-Torrado, F. J.; Rodriguez-Gonzalez, A.; Saavedra, J.; Carracedo, J. C., Rejas, M.; Lobo, A.; Osterrieth, M.; Carrizo, J. I.; Esteban, G.; Gallardo, J.; Ratto, N. (2019). The large eruption 4.2 ka cal BP in Cerro Blanco, Central Volcanic Zone, Andes: Insights to the Holocene eruptive deposits in the southern Puna and adjacent regions. Estudios Geológicos 75(1): e088. https://doi.org/10.3989/egeol.43438.515 MINECO, CGL2011-23307, Proyecto QUECA Peer reviewed

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Recolector de Cienci...arrow_drop_down
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    DIGITAL.CSIC
    Dataset . 2019
    Data sources: Datacite; Sygma
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Recolector de Cienci...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DIGITAL.CSIC
      Dataset . 2019
      Data sources: Datacite; Sygma
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: von der Linden, Jens; Kimblin, Clare; McKenna, Ian; Bagley, Skyler; +10 Authors

    Background This data is camera images and nozzle pressure gauge voltage traces from rapid decompression shots at the LMU shock tube facility. This data is discussed in the "Materials and Methods" section of the paper "Standing Shock Prevents Propagation of Sparks in Supersonic Explosive Flows". Electric sparks and explosive flows have long been associated with each other. Flowing dust particles originate charge through contact and separate based on inertia, resulting in strong electric fields supporting sparks. These sparks can cause explosions in dusty environments, especially those rich in carbon, such as coal mines and grain elevators. Recent observations of explosive events in nature and decompression experiments indicate that supersonic flows of explosions may alter the electrical discharge process. Shocks may suppress parts of the hierarchy of the discharge phenomena, such as leaders. In our decompression experiments, a shock tube ejects a flow of gas and particles into an expansion chamber. We imaged an illuminated plume from the decompression of a mixture of argon and <100 mg of diamond particles and observe sparks occurring below the sharp boundary of a condensation cloud. We also performed hydrodynamics simulations of the decompression event that provide insight into the conditions supporting the observed behavior. Simulation results agree closely with the experimentally observed Mach disk shock shape and height. This represents direct evidence that the sparks are sculpted by the outflow. The spatial and temporal scale of the sparks transmit an impression of the shock tube flow, a connection that could enable novel instrumentation to diagnose currently inaccessible supersonic granular phenomena. Accessing Data The prefixes of the filenames correspond to the shot dates and times listed in table S1 of the paper. The "_camera.zip" files contains tiff images of the camera frames. The ".ixc" file in each zip lists camera settings in plain text. The ".dat" file contains the voltage measurement of the nozzle pressure gauge. Row 1 is the header, row 2 is the time in seconds, and row 3 is the voltage of the pressure gauge in Volts. The peak pressure in the header can be used to relate the voltage to pressure. This work was performed in part under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344, and Mission Support and Test Services, LLC, under Contract No. DE-NA0003624 with support from the Site-Directed Research and Development program, DOE/NV/03624--0956, and in part by the European Plate Observing Systems Transnational Access program of the European Community HORIZON 2020 research and innovation program under grant N 676564. CC acknowledges the support from the DFG grant CI 25/2-1 and from the European Community HORIZON 2020 research and innovation programme under the Marie Sklodowska Curie grant nr. 705619. LLNL-MI-817289. This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, complete- ness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific com- mercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes. {"references": ["C. Cimarelli, M. Alatorre-Ibargengoitia, U. Kueppers, B. Scheu, D. Dingwell, Experimen- tal generation of volcanic lightning. Geology 42, 79\u201382 (2014)"]}

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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: ZENODO
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    Authors: Lazzeri, Emma; Cocco, Massimo; Bailo, Daniele; Sarretta, Alessandro; +1 Authors

    A cycle of four webinars on Open Science and Open Access for earth and environmental sciences, with discipline-specific tools and practical resources. Course outline: Module 1: - Introduction and motivations - Open Science in Solid Earth Science Module 2: - Research Data Management - OS in solid Earth sciences: the EPOS research infrastructure experience Module 3: - FAIR principles and Open Data - Implementing FAIR. Considerations from the solid Earth domain Module 4: - The Data Management Plan - The adoption of Open Science Paradigm at INGV - Practical Tips Scientific committee: Maria Silvia Giamberini, IGG/CNR Gina Pavone, ISTI/CNR

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    ZENODO
    Other literature type . 2021
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Presentation . 2021
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Other literature type . 2021
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Presentation . 2021
      License: CC BY
      Data sources: Datacite
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    Authors: Bindi, Dino; Zaccarelli, Riccardo; Strollo, Angelo; Di Giacomo, Domenico;

    In Bindi et al. (2019) a harmonized local magnitude scale across Europe has been derived using data disseminated by network operators through the European Integrated Data Archive (EIDA). This data set contains regionalized non-parametric attenuation tables, attenuation corrections to the parametric model and station corrections for both non-parametric and parametric models for more than 2000 stations in Europe. Regionalization has been performed considering six different regions covering Europe and the polygons defining them are also provided. Data are subject to updates that can be triggered by the availability of new and substantial input data (reviewed earthquake catalogues and/or new waveforms). Each update will be released with a new version of the data. The data are provided in ASCII format (.csv).

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    GFZ Data Services
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    GFZ Data Services
    Dataset . 2019
    Data sources: B2FIND
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      GFZ Data Services
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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      GFZ Data Services
      Dataset . 2019
      Data sources: B2FIND
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    Authors: Shevchenko, A.; Dvigalo, V.; Walter, T.; Mania, R.;

    Decades of photogrammetric records at Bezymianny, one of the most active volcanoes on Earth, allow unveiling morphological changes, eruption and intrusion dynamics, erosion, lava and tephra deposition processes. This data publication releases an almost 7-decade long record, retrieved from airborne, satellite, and UAV platforms. The Kamchatkan Institute of Volcanology and Seismology released archives of high-resolution aerial images acquired in 1967-2013. We complemented the aerial datasets with 2017 Pleiades tri-stereo satellite and UAV images. The images were processed using Erdas Imagine and Photomod software. Here we publish nine quality-controlled point clouds in LAS format referenced to the WGS84 (UTM zone 57N). By comparing the point clouds we were able to describe topographic changes and calculate volumetric differences, details of which were further analyzed in Shevchenko et al. (2020, https://doi.org/...). The ~5-decade-long photogrammetric record was achieved by 8 aerial and 1 satellite-UAV datasets. The 8 sets of near nadir aerial photographs acquired in 1967, 1968, 1976, 1977, 1982, 1994, 2006, and 2013 were taken with various photogrammetry cameras dedicated for topographic analysis, specifically the AFA 41-10 camera (1967, 1968, 1976, and 1977; focal length = 99.086 mm), the TAFA 10 camera (1982 and 1994; focal length = 99.120 mm), and the AFA TE-140 camera (2006 and 2013; focal length = 139.536 mm). These analog cameras have all an 18×18 cm frame size. The acquisition flight altitude above the mean surface of Bezymianny varied from 1,500-2,500 m above mean surface elevation, translating up to >5,000 m above sea level. For photogrammetric processing, we used 3-4 consecutive shots that provided a 60-70% forward overlap. The analog photo negatives were digitized by scanning with Epson Perfection V750 Pro scanner in a resolution of 2,400 pixels/inch (approx. pixel (px) size = 0.01 mm). The mean scale within a single photograph depends on the distance to the surface and corresponds on average to 1:10,000-1:20,000. Thus, each px in the scanned image represents about 10-20 cm resolution on the ground. The coordinates of 12 ground control points were derived from a Theo 010B theodolite dataset collected at geodetic benchmarks during a 1977 fieldwork. These benchmarks were established on the slopes of Bezymianny before the 1977 aerial survey and then captured with the AFA 41-10 aerial camera. The most recent was a satellite dataset acquired on 2017-09-09 by the PHR 1B sensor aboard the Pleiades satellite (AIRBUS Defence & Space) operated by the French space agency (CNES). The forward, nadir and backward camera configuration allows revisiting any point on earth and was tasked for the acquisition of Bezymianny to provide a 0.5 m resolution panchromatic imagery dataset. In order to improve the Pleiades data, we complemented them with UAV data collected on 2017-07-29 with DJI Mavic Pro during fieldwork at Bezymianny. This data publication includes a description of the data (in pdf format) and the nine processed and controlled three-dimensional point clouds (in LAS format). The point clouds can be easily interpolated and imported into most open and commercially available geographic information system (GIS) software. Further details on data and data handling are provided in Shevchenko et al. (2020).

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    Authors: Manunta, Michele; de Luca, Claudio; Zinno, Ivana; Casu, Francesco; +8 Authors

    We present an advanced differential synthetic aperture radar (SAR) interferometry (DInSAR) processing chain, based on the Parallel Small BAseline Subset (P-SBAS) technique, for the efficient generation of deformation time series from Sentinel-1 (S-1) interferometric wide (IW) swath SAR data sets. We first discuss an effective solution for the generation of high-quality interferograms, which properly accounts for the peculiarities of the terrain observation with progressive scans (TOPS) acquisition mode used to collect S-1 IW SAR data. These data characteristics are also properly accounted within the developed processing chain, taking full advantage from the burst partitioning. Indeed, such data structure represents a key element in the proposed P-SBAS implementation of the S-1 IW processing chain, whose migration into a cloud computing (CC) environment is also envisaged. An extensive experimental analysis, which allows us to assess the quality of the obtained interferometric products, is presented. To do this, we apply the developed S-1 IW P-SBAS processing chain to the overall archive acquired from descending orbits during the March 2015-April 2017 time span over the whole Italian territory, consisting in 2740 S-1 slices. In particular, the quality of the final results is assessed through a large-scale comparison with the GPS measurements relevant to nearly 500 stations. The mean standard deviation value of the differences between the DInSAR and the GPS time series (projected in the radar line of sight) is less than 0.5 cm, thus confirming the effectiveness of the implemented solution. Finally, a discussion about the performance achieved by migrating the developed processing chain within the Amazon Web Services CC environment is addressed, highlighting that a two-year data set relevant to a standard S-1 IW slice can be reliably processed in about 30 h.The presented results demonstrate the capability of the implemented P-SBAS approach to efficiently and effectively process large S-1 IW data sets relevant to extended portions of the earth surface, paving the way to the systematic generation of advanced DInSAR products to monitor ground displacements at a very wide spatial scale.

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    ZENODO
    Article . 2019
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Article . 2019
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Article . 2019
    License: CC BY
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    CNR ExploRA
    Article . 2019
    Data sources: CNR ExploRA
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      ZENODO
      Article . 2019
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      ZENODO
      Article . 2019
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Article . 2019
      License: CC BY
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      CNR ExploRA
      Article . 2019
      Data sources: CNR ExploRA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Theodoridou, Maria; Ivanovic, Dragan; Martin, Paul; Remy, Laurent; +1 Authors

    This archive contains a set of mappings in X3ML format between a number of metadata record schemes and CERIF RDF (based on CERIF 1.6). These mapping files were created during the EU Horizon 2020 VRE4EIC project as part of the development of a joint catalogue for resources hosted by various European research infrastructures serving the environmental and earth sciences. The following source metadata schemes are supported: Dublin Core DCAT-AP EPOS DCAT-AP (extension of DCAT-AP used within the EPOS research infrastructure) ISO 19139 OIL-E (Open Information Linking for Environmental research infrastructures) The scheme used by EUDAT's B2FIND service (based on CKAN) The scheme used within the D4Science platform (based on CKAN) In addition, test mappings have been developed for the transformation of RBAC data, WADL specifications, and WSDL (both 1.1 and 2.0), transformation of CERIF and VRE4EIC classification schemes into CERIF RDF, and generation of additional provenance data for data originating from EPOS or the ENVRI environmental research infrastructure cluster. To make use of these mappings, it is necessary to have a means of interpreting X3ML documents. See: https://github.com/isl/x3ml To directly view and edit these mappings, as well as to test them, it is best to use the 3M editor (which interprets X3ML). See: https://github.com/isl/Mapping-Memory-Manager 3M can be set up and run as an online service in Apache Tomcat (version 8 or higher). These mappings are provided to interested parties who wish to replicate or build upon the metadata mapping activity of the VRE4EIC project, or wish to import metadata records from external sources into a single RDF triple store structured according to the CERIF 1.6 standard. They represent the best state of mappings as of the end of the VRE4EIC project, in October 2018, but are provided as-is, with no assertion of completeness, soundness or fitness-for-purpose out of the box. For queries regarding the mappings in this archive, or for information about the VRE4EIC project in general, email vre4eic-contact at ercim dot eu.

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    ZENODO
    Other ORP type . 2019
    Data sources: ZENODO
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      Other ORP type . 2019
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Fernandez-Turiel, J. L.; Perez-Torrado, F. J.; Rodriguez-Gonzalez, A.; Saavedra, J.; +8 Authors

    This dataset compiles SEM images, modelled isopach map and topographic profiles, and data of radiocarbon ages, parameters of Tephra2 and AshCalc codes of Holocene volcanic ashes of of Southern Puna and neighbouring areas (NW Argentina). SEM images detail differences among the Bolsón de Fiambalá, Cerro Blanco and Cueros de Purulla fallout ash deposits. Tephra2 code was used to simulate the ash fallout, and the AshCalc code to compare different methods for ash volume estimates associated with the 4.2 ka cal BP eruption of the Cerro Blanco Volcanic Complex. Topographic profiles are used to explain the secondary thickening of fallout ash deposits. Material suplementario (Figuras S1-S4 y Tablas S1-S4 del artículo Fernandez-Turiel, J.-L.; Perez-Torrado, F. J.; Rodriguez-Gonzalez, A.; Saavedra, J.; Carracedo, J. C., Rejas, M.; Lobo, A.; Osterrieth, M.; Carrizo, J. I.; Esteban, G.; Gallardo, J.; Ratto, N. (2019). The large eruption 4.2 ka cal BP in Cerro Blanco, Central Volcanic Zone, Andes: Insights to the Holocene eruptive deposits in the southern Puna and adjacent regions. Estudios Geológicos 75(1): e088. https://doi.org/10.3989/egeol.43438.515 MINECO, CGL2011-23307, Proyecto QUECA Peer reviewed

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    DIGITAL.CSIC
    Dataset . 2019
    Data sources: Datacite; Sygma
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      DIGITAL.CSIC
      Dataset . 2019
      Data sources: Datacite; Sygma
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: von der Linden, Jens; Kimblin, Clare; McKenna, Ian; Bagley, Skyler; +10 Authors

    Background This data is camera images and nozzle pressure gauge voltage traces from rapid decompression shots at the LMU shock tube facility. This data is discussed in the "Materials and Methods" section of the paper "Standing Shock Prevents Propagation of Sparks in Supersonic Explosive Flows". Electric sparks and explosive flows have long been associated with each other. Flowing dust particles originate charge through contact and separate based on inertia, resulting in strong electric fields supporting sparks. These sparks can cause explosions in dusty environments, especially those rich in carbon, such as coal mines and grain elevators. Recent observations of explosive events in nature and decompression experiments indicate that supersonic flows of explosions may alter the electrical discharge process. Shocks may suppress parts of the hierarchy of the discharge phenomena, such as leaders. In our decompression experiments, a shock tube ejects a flow of gas and particles into an expansion chamber. We imaged an illuminated plume from the decompression of a mixture of argon and <100 mg of diamond particles and observe sparks occurring below the sharp boundary of a condensation cloud. We also performed hydrodynamics simulations of the decompression event that provide insight into the conditions supporting the observed behavior. Simulation results agree closely with the experimentally observed Mach disk shock shape and height. This represents direct evidence that the sparks are sculpted by the outflow. The spatial and temporal scale of the sparks transmit an impression of the shock tube flow, a connection that could enable novel instrumentation to diagnose currently inaccessible supersonic granular phenomena. Accessing Data The prefixes of the filenames correspond to the shot dates and times listed in table S1 of the paper. The "_camera.zip" files contains tiff images of the camera frames. The ".ixc" file in each zip lists camera settings in plain text. The ".dat" file contains the voltage measurement of the nozzle pressure gauge. Row 1 is the header, row 2 is the time in seconds, and row 3 is the voltage of the pressure gauge in Volts. The peak pressure in the header can be used to relate the voltage to pressure. This work was performed in part under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344, and Mission Support and Test Services, LLC, under Contract No. DE-NA0003624 with support from the Site-Directed Research and Development program, DOE/NV/03624--0956, and in part by the European Plate Observing Systems Transnational Access program of the European Community HORIZON 2020 research and innovation program under grant N 676564. CC acknowledges the support from the DFG grant CI 25/2-1 and from the European Community HORIZON 2020 research and innovation programme under the Marie Sklodowska Curie grant nr. 705619. LLNL-MI-817289. This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, complete- ness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific com- mercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes. {"references": ["C. Cimarelli, M. Alatorre-Ibargengoitia, U. Kueppers, B. Scheu, D. Dingwell, Experimen- tal generation of volcanic lightning. Geology 42, 79\u201382 (2014)"]}

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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2020
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2020
      License: CC BY
      Data sources: ZENODO
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    Authors: Lazzeri, Emma; Cocco, Massimo; Bailo, Daniele; Sarretta, Alessandro; +1 Authors

    A cycle of four webinars on Open Science and Open Access for earth and environmental sciences, with discipline-specific tools and practical resources. Course outline: Module 1: - Introduction and motivations - Open Science in Solid Earth Science Module 2: - Research Data Management - OS in solid Earth sciences: the EPOS research infrastructure experience Module 3: - FAIR principles and Open Data - Implementing FAIR. Considerations from the solid Earth domain Module 4: - The Data Management Plan - The adoption of Open Science Paradigm at INGV - Practical Tips Scientific committee: Maria Silvia Giamberini, IGG/CNR Gina Pavone, ISTI/CNR

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    Authors: Bindi, Dino; Zaccarelli, Riccardo; Strollo, Angelo; Di Giacomo, Domenico;

    In Bindi et al. (2019) a harmonized local magnitude scale across Europe has been derived using data disseminated by network operators through the European Integrated Data Archive (EIDA). This data set contains regionalized non-parametric attenuation tables, attenuation corrections to the parametric model and station corrections for both non-parametric and parametric models for more than 2000 stations in Europe. Regionalization has been performed considering six different regions covering Europe and the polygons defining them are also provided. Data are subject to updates that can be triggered by the availability of new and substantial input data (reviewed earthquake catalogues and/or new waveforms). Each update will be released with a new version of the data. The data are provided in ASCII format (.csv).

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    GFZ Data Services
    Dataset . 2019
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    Dataset . 2019
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    Authors: Shevchenko, A.; Dvigalo, V.; Walter, T.; Mania, R.;

    Decades of photogrammetric records at Bezymianny, one of the most active volcanoes on Earth, allow unveiling morphological changes, eruption and intrusion dynamics, erosion, lava and tephra deposition processes. This data publication releases an almost 7-decade long record, retrieved from airborne, satellite, and UAV platforms. The Kamchatkan Institute of Volcanology and Seismology released archives of high-resolution aerial images acquired in 1967-2013. We complemented the aerial datasets with 2017 Pleiades tri-stereo satellite and UAV images. The images were processed using Erdas Imagine and Photomod software. Here we publish nine quality-controlled point clouds in LAS format referenced to the WGS84 (UTM zone 57N). By comparing the point clouds we were able to describe topographic changes and calculate volumetric differences, details of which were further analyzed in Shevchenko et al. (2020, https://doi.org/...). The ~5-decade-long photogrammetric record was achieved by 8 aerial and 1 satellite-UAV datasets. The 8 sets of near nadir aerial photographs acquired in 1967, 1968, 1976, 1977, 1982, 1994, 2006, and 2013 were taken with various photogrammetry cameras dedicated for topographic analysis, specifically the AFA 41-10 camera (1967, 1968, 1976, and 1977; focal length = 99.086 mm), the TAFA 10 camera (1982 and 1994; focal length = 99.120 mm), and the AFA TE-140 camera (2006 and 2013; focal length = 139.536 mm). These analog cameras have all an 18×18 cm frame size. The acquisition flight altitude above the mean surface of Bezymianny varied from 1,500-2,500 m above mean surface elevation, translating up to >5,000 m above sea level. For photogrammetric processing, we used 3-4 consecutive shots that provided a 60-70% forward overlap. The analog photo negatives were digitized by scanning with Epson Perfection V750 Pro scanner in a resolution of 2,400 pixels/inch (approx. pixel (px) size = 0.01 mm). The mean scale within a single photograph depends on the distance to the surface and corresponds on average to 1:10,000-1:20,000. Thus, each px in the scanned image represents about 10-20 cm resolution on the ground. The coordinates of 12 ground control points were derived from a Theo 010B theodolite dataset collected at geodetic benchmarks during a 1977 fieldwork. These benchmarks were established on the slopes of Bezymianny before the 1977 aerial survey and then captured with the AFA 41-10 aerial camera. The most recent was a satellite dataset acquired on 2017-09-09 by the PHR 1B sensor aboard the Pleiades satellite (AIRBUS Defence & Space) operated by the French space agency (CNES). The forward, nadir and backward camera configuration allows revisiting any point on earth and was tasked for the acquisition of Bezymianny to provide a 0.5 m resolution panchromatic imagery dataset. In order to improve the Pleiades data, we complemented them with UAV data collected on 2017-07-29 with DJI Mavic Pro during fieldwork at Bezymianny. This data publication includes a description of the data (in pdf format) and the nine processed and controlled three-dimensional point clouds (in LAS format). The point clouds can be easily interpolated and imported into most open and commercially available geographic information system (GIS) software. Further details on data and data handling are provided in Shevchenko et al. (2020).

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    Authors: Manunta, Michele; de Luca, Claudio; Zinno, Ivana; Casu, Francesco; +8 Authors

    We present an advanced differential synthetic aperture radar (SAR) interferometry (DInSAR) processing chain, based on the Parallel Small BAseline Subset (P-SBAS) technique, for the efficient generation of deformation time series from Sentinel-1 (S-1) interferometric wide (IW) swath SAR data sets. We first discuss an effective solution for the generation of high-quality interferograms, which properly accounts for the peculiarities of the terrain observation with progressive scans (TOPS) acquisition mode used to collect S-1 IW SAR data. These data characteristics are also properly accounted within the developed processing chain, taking full advantage from the burst partitioning. Indeed, such data structure represents a key element in the proposed P-SBAS implementation of the S-1 IW processing chain, whose migration into a cloud computing (CC) environment is also envisaged. An extensive experimental analysis, which allows us to assess the quality of the obtained interferometric products, is presented. To do this, we apply the developed S-1 IW P-SBAS processing chain to the overall archive acquired from descending orbits during the March 2015-April 2017 time span over the whole Italian territory, consisting in 2740 S-1 slices. In particular, the quality of the final results is assessed through a large-scale comparison with the GPS measurements relevant to nearly 500 stations. The mean standard deviation value of the differences between the DInSAR and the GPS time series (projected in the radar line of sight) is less than 0.5 cm, thus confirming the effectiveness of the implemented solution. Finally, a discussion about the performance achieved by migrating the developed processing chain within the Amazon Web Services CC environment is addressed, highlighting that a two-year data set relevant to a standard S-1 IW slice can be reliably processed in about 30 h.The presented results demonstrate the capability of the implemented P-SBAS approach to efficiently and effectively process large S-1 IW data sets relevant to extended portions of the earth surface, paving the way to the systematic generation of advanced DInSAR products to monitor ground displacements at a very wide spatial scale.

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    Article . 2019
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    Authors: Theodoridou, Maria; Ivanovic, Dragan; Martin, Paul; Remy, Laurent; +1 Authors

    This archive contains a set of mappings in X3ML format between a number of metadata record schemes and CERIF RDF (based on CERIF 1.6). These mapping files were created during the EU Horizon 2020 VRE4EIC project as part of the development of a joint catalogue for resources hosted by various European research infrastructures serving the environmental and earth sciences. The following source metadata schemes are supported: Dublin Core DCAT-AP EPOS DCAT-AP (extension of DCAT-AP used within the EPOS research infrastructure) ISO 19139 OIL-E (Open Information Linking for Environmental research infrastructures) The scheme used by EUDAT's B2FIND service (based on CKAN) The scheme used within the D4Science platform (based on CKAN) In addition, test mappings have been developed for the transformation of RBAC data, WADL specifications, and WSDL (both 1.1 and 2.0), transformation of CERIF and VRE4EIC classification schemes into CERIF RDF, and generation of additional provenance data for data originating from EPOS or the ENVRI environmental research infrastructure cluster. To make use of these mappings, it is necessary to have a means of interpreting X3ML documents. See: https://github.com/isl/x3ml To directly view and edit these mappings, as well as to test them, it is best to use the 3M editor (which interprets X3ML). See: https://github.com/isl/Mapping-Memory-Manager 3M can be set up and run as an online service in Apache Tomcat (version 8 or higher). These mappings are provided to interested parties who wish to replicate or build upon the metadata mapping activity of the VRE4EIC project, or wish to import metadata records from external sources into a single RDF triple store structured according to the CERIF 1.6 standard. They represent the best state of mappings as of the end of the VRE4EIC project, in October 2018, but are provided as-is, with no assertion of completeness, soundness or fitness-for-purpose out of the box. For queries regarding the mappings in this archive, or for information about the VRE4EIC project in general, email vre4eic-contact at ercim dot eu.