Find research datasets worth reusing

opencc-by-4.0Apr 2024View details →

Questionnaire for the self-assessment of digital preservation activities in institutional research repositories

This dataset includes a questionnaire designed to enable institutional repository managers to conduct a self-assessment of their digital preservation strategies and activities. It consists of 46 evaluation criteria extracted and modified from the NDSA Levels of Digital Preservation and ISO 16363:2017 standards. The questionnaire is provided in queXML format, facilitating its import into various survey applications

opencc-by-4.0Nov 2024View details →

Digital Elevation Model (DEM) of northern Brøggerhalvøya (Svalbard, Norway) with Ground Sampling Distance (GSD) of 50 cm

HRSC is a multisensor pushbroom instrument with 9 CCD line sensors mounted in parallel that has been in orbit around Mars since January 2004 on ESA’s Mars Express spacecraft (Gwinner et al., 2016). It simultaneously obtains high-resolution stereo, multicolor, and multiphase images. Digital photogrammetric techniques are used to reconstruct the topography on the basis of five stereo channels, which provide five different views of the ground. An airborne version of the HRSC was used for the acquisition of stereo and color images in Svalbard. Since 1997, different airborne versions of HRSC have been developed. The principles of HRSC-AX data processing are described by Gwinner et al. (2006). The orientation data of the camera are reconstructed from a global positioning system inertial navigation system (GPS INS). HRSC-AX has been applied in diverse technical and scientific applications (e.g., Gwinner et al., 1999, 2000; Hauber et al., 2001; Otto et al., 2007) and has also been successfully used to investigate rock glacier activity (Roer and Nyenhuis, 2007). The flight campaign in July–August 2008 covered a total of seven regions in Svalbard: (1) Longyearbyen and the surroundings of Adventfjorden, (2) large parts of Adventdalen, (3) large parts of the Brøggerhalvøya (halvøya = peninsula) in western Spitsbergen (this dataset), (4) the Bockfjorden area in northern Spitsbergen, (5) the northeastern shore of the Palanderbukta and the margin of the adjacent ice cap in Nordaustlandet, (6) an area on Prins Karls Forland, and (7) the area of the abandoned Russian mining settlement of Pyramiden together with the nearby Ebbedalen.   This dataset is a Digital Elevation Model (DEM) derived from HRSC-AX stereo images. The elevations recorded in the DEM are ellipsoid heights; i.e., they are not computed with respect to a geoid but to a mathematically defined reference surface, which is a rotational ellipsoid with the equatorial A and B axes both having a radius of 6378.14 km and the polar C axis having a radius of 6356.75 km. This results in an offset of about 36.5m with respect to geoid heights; i.e., sea level in the HRSC-AX DEM is not at 0 m, but at ~36.5 m. References Gwinner, K., Hauber, E., Hoffmann, H., Scholten, F., Jaumann, R., Neukum, G., Coltelli, M., and Puglisi, G., 1999, The HRSC-A experiment on high reso- lution imaging and DEM generation at the Aeolian Islands, in Proceedings of the 13th International Conference on Applied Geologic Remote Sens- ing: Ann Arbor, Michigan, ERIM International, v. I, p. 560–569. Gwinner, K., Hauber, E., Jaumann, R., and Neukum, G., 2000, High-resolution, digital photogrammetric mapping: A tool for earth science: Eos (Transactions, American Geophysical Union), v. 81, no. 44, p. 513–520, doi:10.1029/00EO00364. Gwinner, K., Coltelli, M., Flohrer, J., Jaumann, R., Matz, K.-D., Marsella, M., Roatsch, T., Scholten, F., and Trauthan, F., 2006, The HRSC-AX Mt. Etna Project: High-Resolution Orthoimages and 1 m DEM at Regional Scale: International Archives of Photogrammetry and Remote Sensing, v. XXXVI, Part 1, http://isprs.free.fr/documents/Papers/T05-23.pdf. Gwinner, K., Scholten, F., Spiegel, M., Schmidt, R., Giese, B., Oberst, J., Heipke, C., Jaumann, R., and Neukum, G., 2009, Derivation and validation of high-resolution digital elevation models from Mars Express HRSC data: Photogrammetric Engineering and Remote Sensing, v. 75, no. 9, p. 1127–1142. Gwinner, K., Jaumann, R., Hauber, E., et al., 2016, The High Resolution Stereo Camera (HRSC) of Mars Express and its approach to science analysis and mapping for Mars and its satellites: Planetary and Space Science, v. 126, p. 93–138. http://dx.doi.org/10.1016/j.pss.2016.02.014 Hauber, E., Slupetzky, H., Jaumann, R., Wewel, F., Gwinner, K., and Neukum, G., 2001, Digital and automated high resolution stereo mapping of the Sonnblick glacier: EARSeL eProceedings, v. 1, no. 1, p. 246–254. Jaumann, R., Neukum, G., Behnke, T., Duxbury, T.C., Eichentopf, K., Flohrer, J., van Gasselt, S., Giese, B., Gwinner, K., Hauber, E., Hoffmann, H., Hoff- meister, A., Köhler, U., Matz, K.-D., McCord, T.B., Mertens, V., Oberst, J., Pischel, R., Reiss, D., Ress, E., Roatsch, T., Saiger, P., Scholten, F., Schwarz, G., Stephan, K., Wählisch, M., and the HRSC Co-Investigator Team, 2007, The high-resolution stereo camera (HRSC) experiment on Mars Express: instrument aspects and experiment conduct from interplan- etary cruise through the nominal mission: Planetary and Space Science, v. 55, p. 928–952, doi:10.1016/j.pss.2006.12.003. Otto, J.-C., Kleinod, K., König, O., Krautblatter, M., Nyenhuis, M., Roer, I., Schneider, M., Schreiner, B., and Dikau, R., 2007, HRSC-A data: A new high-resolution data set with multipurpose applications in physi- cal geography: Progress in Physical Geography, v. 31, no. 2, p. 179–197, doi:10.1177/0309133307076479. Roer, I., and Nyenhuis, M., 2007, Rockglacier activity studies on a regional scale: Comparison of geomorphological mapping and photogrammetric monitoring: Earth Surface Processes and Landforms, v. 32, p. 1747–1758, doi:10.1002/esp.1496.

opencc-by-4.0Jul 2024View details →

PEATGRIDS: Mapping global peat thickness and carbon stock via digital soil mapping approach, dataset

PEATGRIDS: a dataset containing the first peat thickness and carbon stock maps estimated over peatlands area across the globe at ~1 km x ~1 km resolution. Carbon stock was calculated across all depths of the predicted peat thickness, multiplied by peat bulk density (BD) and carbon content (CC) across five depths: 0-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm. Mapping effort was performed using quantile random forest regression based on remotely sensed data and environmental covariates, including topography, climate, soil properties, and land cover. The maps cover areas potentially as peatlands according to the UNEP's global peatland map obtained from the <a title="Global Peat Database" href="https://greifswaldmoor.de/global-peatland-database-en.html" target="_blank" rel="noopener">Global Peat Database</a>. We may update this dataset in the future, please consider using the latest version.  Note: This version (2.0.1) clarifies the metric units for carbon stock per area in the previous version (2.0).

opencc-by-4.0Nov 2024View details →

Supplementary Table 1 and data from the workshop on Digital Building Logbooks and Permit Processes for Sustainability in Sustainable Places 24.9.2024 in Luxembourg

This repository contains the supplementary Table 1 and data collected during a workshop on Digital Building Logbooks and Permit Processes for Sustainability. The workshop was held in Sustainable Places on the 24th of September 2024 in Luxembourg.

opencc-by-4.0Nov 2021View details →

Underlying data - Digital Twin for Rainbow Trout (Oncorhynchus mykiss) land-based aquaculture

Datasets for replicating Figures 5, 6, 7 and 8 of the article "Digital twins for land-based aquaculture: a case study for rainbow trout (Oncorhynchus mykiss)", by Adriano C. Lima, Edouard Royer, Matteo Bolzonella, and Roberto Pastres.

Lago Argentino digital core scans and stratigraphic logs

This dataset includes full resolution (20 micron per pixel) digital core scans of all lake cores collected during the 2019 GCO project coring of Lago Argentino. A second folder includes a stratigraphic log and description of each core, created in PSICAT. This dataset is uploaded alongside the submission "Physical limnology and sediment dynamics of Lago Argentino, the world’s largest ice-contact lake" to JGR: Earth Surface. All analyses were conducted at the Continental Scientific Drilling Facility at the University of Minnesota. For any questions about this dataset, please contact vanwy048@umn.edu .

[[Deprecated]] DIGITAL SOIL TEXTURE MAPS OF ARGENTINA

A new version has been uploaded by Guillermo Schulz.

Data set for "Axonal and dendritic morphology of excitatory neurons in layer 2/3 mouse barrel cortex imaged through whole-brain two-photon tomography and registered to a digital brain atlas"

Data set for: Liu Y, Foustoukos G, Crochet S and Petersen CCH (2022) Axonal and dendritic morphology of excitatory neurons in layer 2/3 mouse barrel cortex imaged through whole-brain two-photon tomography and registered to a digital brain atlas. Front Neuroanat  15: 791015. https://doi.org/10.3389/fnana.2021.791015 There are 2 files in this upload: 1. The file named "2022_Liu_FrontNeuroanat.pdf" is the Open Access pdf of the online publication in Frontiers in Neuroanatomy. 2. The file named "Liu_data_code.zip" (~1 GB) is a zipped version of a folder ‘Liu_data_code’, which contains the data analyzed in the study along with the Python codes used to generate the published figures. The original high resolution image stacks obtained through whole-brain two-photon serial tomography are unfortunately too large for Zenodo, and only highly-downsampled data are included in this upload, which were used for registration with the Allen CCFv3. Instructions on how to view and analyse the anatomical data are provided in the 'README.docx' file, which you will find upon unzipping the folder.

Multi-temporal digital terrain models of the NBS experiment in OAL-Austria

Multi-temporal digital terrain models of the NBS experiment in OAL-Austria with a spatial resolution of 10cm, derived from 3D point clouds acquired with a terrestrial laser scanner (Riegl-VZ2000i); Projection: EPSG 31254 The TLS-monitoring is intended for assessing the stability of the embankment at the NBS field demonstrator in OAL-Austria. The digital terrain models were acquired after applying the ground classification filter proposed by Axelsson (2000)

Copernicus Digital Elevation Model (DEM) for Europe at 3 arc seconds (ca. 90 meter) resolution derived from Copernicus Global 30 meter DEM dataset

Overview: The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters. The Copernicus DEM for Europe at 3 arcsec (0:00:03 = 0.00083333333 ~ 90 meter) in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/). Processing steps: The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in <a href="https://gdal.org/drivers/raster/vrt.html">VRT</a> format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized: <code>gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt </code> In order to reduce the spatial resolution to 3 arc seconds, weighted resampling was performed in GRASS GIS (using <code>r.resamp.stats -w</code> and the pixel values were scaled with 1000 (storing the pixels as integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using <code>r.relief</code>, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files. Projection + EPSG code: Latitude-Longitude/WGS84 (EPSG: 4326) Spatial extent: north: 82:00:30N south: 18N west: 32:00:30W east: 70E Spatial resolution: 3 arc seconds (approx. 90 m) Pixel values: meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.) Software used: GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief) Original dataset license: <a href="https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf">https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf</a> Processed by: mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)

Copernicus Digital Elevation Model (DEM) for Europe at 30 arc seconds (ca. 1000 meter) resolution derived from Copernicus Global 30 meter DEM dataset

Overview: The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters. The Copernicus DEM for Europe at 30 arcsec (0:00:30 = 0.0083333333 ~ 1000 meter) in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/). Processing steps: The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in <a href="https://gdal.org/drivers/raster/vrt.html">VRT</a> format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized: <code>gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt </code> In order to reduce the spatial resolution to 30 arc seconds, weighted resampling was performed in GRASS GIS (using <code>r.resamp.stats -w</code> and the pixel values were scaled with 1000 (storing the pixels as integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using <code>r.relief</code>, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files. Projection + EPSG code: Latitude-Longitude/WGS84 (EPSG: 4326) Spatial extent: north: 82:00:30N south: 18N west: 32:00:30W east: 70E Spatial resolution: 30 arc seconds (approx. 1000 m) Pixel values: meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.) Software used: GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief) Original dataset license: <a href="https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf">https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf</a> Processed by: mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)

Copernicus Digital Elevation Model (DEM) for Europe at 1000 meter resolution (EU-LAEA) derived from Copernicus Global 30 meter DEM dataset

Overview: The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters. The Copernicus DEM for Europe at 1000 meter resolution (EU-LAEA projection) in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/). Processing steps: The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in <a href="https://gdal.org/drivers/raster/vrt.html">VRT</a> format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized: <code>gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt </code> In order to reproject the data to EU-LAEA projection while reducing the spatial resolution to 1000 m, bilinear resampling was performed in GRASS GIS (using <code>r.proj</code> and the pixel values were scaled with 1000 (storing the pixels as Integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using <code>r.relief</code>, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files. Projection + EPSG code: ETRS89-extended / LAEA Europe (EPSG: 3035) Spatial extent: north: 6874000 south: -485000 west: 869000 east: 8712000 Spatial resolution: 1000 m Pixel values: meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.) Software used: GDAL 3.2.2 and GRASS GIS 8.0.0 (r.proj; r.relief) Original dataset license: <a href="https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf">https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf</a> Processed by: mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)

Copernicus Digital Elevation Model (DEM) for Europe at 100 meter resolution (EU-LAEA) derived from Copernicus Global 30 meter DEM dataset

Overview: The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters. The Copernicus DEM for Europe at 100 meter resolution (EU-LAEA projection) in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/). Processing steps: The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in <a href="https://gdal.org/drivers/raster/vrt.html">VRT</a> format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized: <code>gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt </code> In order to reproject the data to EU-LAEA projection while reducing the spatial resolution to 100 m, bilinear resampling was performed in GRASS GIS (using <code>r.proj</code> and the pixel values were scaled with 1000 (storing the pixels as Integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using <code>r.relief</code>, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files. Projection + EPSG code: ETRS89-extended / LAEA Europe (EPSG: 3035) Spatial extent: north: 6874000 south: -485000 west: 869000 east: 8712000 Spatial resolution: 100 m Pixel values: meters * 1000 (scaled to Integer; example: value 23220 = 23.220 m a.s.l.) Software used: GDAL 3.2.2 and GRASS GIS 8.0.0 (r.proj; r.relief) Original dataset license: <a href="https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf">https://spacedata.copernicus.eu/documents/20126/0/CSCDA_ESA_Mission-specific+Annex.pdf</a> Processed by: mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)

opencc-by-4.0Feb 2022View details →

Documentation and digital files in support of "Aftershock regions of Aleutian–Alaska megathrust earthquakes, 1938–2021" by Carl Tape and Anthony Lomax: Parts B, C, and D

These files support a manuscript to be submitted entitled "Aftershock regions of Aleutian–Alaska megathrust earthquakes, 1938-2021," by Carl Tape and Anthony Lomax. This collection contains Parts B, C, and D. A separate collection contains Part A. This research was supported by the U.S. Geological Survey (USGS), Department of the Interior, under USGS award number G19AP00050.

opencc-by-4.0Feb 2022View details →

DIGITAL SOIL TEXTURE MAPS OF ARGENTINA

Soil fractions of Argentina in g/100g, Clay, Silt and Sand, for 4 standard depth intervals (0–15, 15-30, 30–60, 60–100) at 1000 m resolution. Including textural classes for the four standard layers and error estimation using random forest. Global accuracy based on cross-validation <table> <tbody> <tr> <td> sp </td> <td> RMSE </td> <td> Rsquared </td> <td> MAE </td> </tr> <tr> <td> Sand 0-15 cm </td> <td> 16.189 </td> <td> 0.640 </td> <td> 11.069 </td> </tr> <tr> <td> Sand 15-30 cm </td> <td> 16.320 </td> <td> 0.629 </td> <td> 11.213 </td> </tr> <tr> <td> Sand 30-60 cm </td> <td> 16.676 </td> <td> 0.618 </td> <td> 11.364 </td> </tr> <tr> <td> Sand 60-100 cm </td> <td> 16.762 </td> <td> 0.587 </td> <td> 11.472 </td> </tr> <tr> <td> silt 0-15 cm </td> <td> 12.011 </td> <td> 0.638 </td> <td> 8.352 </td> </tr> <tr> <td> silt 15-30 cm </td> <td> 11.807 </td> <td> 0.608 </td> <td> 8.388 </td> </tr> <tr> <td> silt 30-60 cm </td> <td> 11.504 </td> <td> 0.561 </td> <td> 8.168 </td> </tr> <tr> <td> silt 60-100 cm </td> <td> 11.728 </td> <td> 0.583 </td> <td> 8.263 </td> </tr> <tr> <td> clay 0-15 cm </td> <td> 8.766 </td> <td> 0.475 </td> <td> 5.721 </td> </tr> <tr> <td> clay 15-30 cm </td> <td> 10.723 </td> <td> 0.452 </td> <td> 7.432 </td> </tr> <tr> <td> clay 30-60 cm </td> <td> 11.211 </td> <td> 0.557 </td> <td> 7.842 </td> </tr> <tr> <td> clay 60-100 cm </td> <td> 11.005 </td> <td> 0.536 </td> <td> 7.734 </td> </tr> </tbody> </table>

opencc-by-4.0Mar 2022View details →

Digital elevation model mosaic of the Hypanis region, Mars

This dataset accompanies the following papers: Adler et al. (2019) Hypotheses for the origin of the Hypanis fan-shaped deposit at the edge of the Chryse escarpment, Mars: Is it a delta? Icarus, 319, 885-908. doi: https://doi.org/10.1016/j.icarus.2018.05.021 Adler et al. (2022) Regional Geology of the Hypanis Valles System, Mars. JGR: Planets, doi: 10.1029/2021JE006994 Contents: -       DEM mosaic of the Hypanis Valles and deposit region constructed from CTX, HRSC, and MOLA elevation data (geotiff). -       Coverage map of CTX, HRSC, and MOLA footprints used (shapefile). -       Previews of DEM (greyscale and color) and of coverage map (png) Description: We constructed a regional elevation mosaic (~17 m/pixel) in Adler et al. (2019) archived here. This mosaic incorporates 10 CTX digital elevation models (DEMs) of high resolution, 3 HRSC digital elevation models of medium resolution, and 1 MOLA global DEM of low resolution. Individual CTX DEMs were generated from the stereopairs listed below. Some individual products were calibrated and formatted with the USGS Integrated Software for Imagers and Spectrometers (ISIS) and then Ames Stereo Pipeline. Other products were generated with SOCET SET. All products were controlled to MOLA shot elevation data. Data incorporated: CTX stereopairs: ID (nadir-most), ID (resolution [m/pix]) P07_003631_1920, B09_013296_1920 (17.7 m/pixel) B17_016408_1913, G06_020443_1916 (18.5 m/pixel) J03_046104_1918, F05_037783_1918 (24.0 m/pixel) P08_004264_1912, B06_011951_1916 (17.7 m/pixel) G09_021788_1918, G11_022434_1918 (18.4 m/pixel) B17_016474_1915, B19_017186_1915 (20.2 m/pixel) D19_034816_1921, F01_036293_1920 (24.0 m/pixel) P13_006176_1918, F01_036293_1920 (18.2 m/pixel) D07_029845_1921, D07_029990_1921 (20.2 m/pixel) G21_026601_1918, P04_002774_1922 (20.2 m/pixel) HRSC DA4: H2134 (75 m/pixel) H2145 (50 m/pixel) H0894 (75 m/pixel) MOLA Elevation: 128 ppd Elevation (463 m/pixel) Funding: The work to create individual CTX stereopair DEMs was funded by UK Space Agency (UK SA) grants ST/ K502388/1, ST/R002355/1, ST/L00643X/1, and ST/R001413/1. We thank the Science and Technology Facilities Council for supporting science relating to ExoMars Rover landing site selection activities. The work to create a mosaic using these products and others was supported by grants from the NASA Mars Odyssey Project under a subcontract to ASU administered by the Jet Propulsion Laboratory/California Institute of Technology.

opencc-by-4.0Jun 2021View details →

LADDER. Learners' digital communication: a corpus for pragmatic competences in Italian L1/L2

Ladder. A Corpus of Computer-Mediated Communication for the Analysis of the Acquisition of Pragmalinguistic Competences by German-Speaking Learners of Italian.       Project description: Many recent research projects (Artoni, Benigni, & Nuzzo, 2020; Cortés Velásquez & Nuzzo, 2017; Nuzzo & Cortés Velásquez, 2020) have underlined the usefulness of creating and analyzing corpora for teaching pragmatics, which, unlike other linguistic levels such as syntax, cannot be explained by rules but only by reference to tendential values or more or less appropriate choices in a given context. This is even more true for interactions via digital media, such as email and instant-messaging services, which have little place in manuals or L2 courses and for which learners have few reference models (Brocca, 2021; Trubnikova & Garofolin, 2020). Data collection: Data were collected from April 2020 to April 2021 with the help of a discourse completion task (DCT). The data consists of emails and instant messages. The informants are (i) German learners of Italian between A2-C1 level according to the CEFR and most of them are students living in Tyrol (Austria) and (ii) native speakers of Italian most of whom are students from Rome (Italy). The data of the learners were collected by students of the undergraduate seminar “Insegnare la pragmatica” which is part of the compulsory module 2b for student teachers at the Institute of Didactics of the University of Innsbruck. The data of the native speakers were collected in large part from students in foreign languages at the University RomaTre thanks to the collaboration with Prof. Elena Nuzzo. The DCTs have been conducted with online questionnaires. Along with the texts, metadata were also registered with the help of an online questionnaire giving sociolinguistic information about the informant (age, self-assessed language level, place of residence, native language, etc.). The DCTs aim to elicit linguistic acts of request and refusal in increasing levels of social distance and different media (Taguchi & Roever, 2017, pp. 85, 231; Hinger et al. 2018: 148). The DCTs elicit different speech acts (requests and refusals) with different degrees of formality (study/work or free time), directed at different people (lecturer, friend, boss) and in different media (mail or instant messaging). The scenarios represent authentic circumstances for the students. The following table shows the situations that were studied:   Email high level of social distance between sender and recipient Scenario 1: Sender is asking for something that he/she is not entitled to Scenario 2: Sender is asking for something that he/she is entitled to WhatsApp messages a) low level of social distance between sender and recipient Scenario 1: Request Scenario 2: Rejecting a request Scenario 3: Short-notice cancellation of an invitation b) medium level of social distance between sender and recipient Scenario 4: Request Scenario 5: Rejecting a request Scenario 6: Short-term rejection of an invitation     The WhatsApp messages, which are exemplary of the text type instant messaging, were produced directly with the cell phone. The metadata were subsequently associated with the respective messages in an Excel spreadsheet. All personal data were anonymized. The prompts were presented in Italian, as follows: Mail Mail a) Immagina di star facendo un corso con il Dr. Nicola Brocca. Domani devi fare una presentazione in classe. Non hai avuto tempo per studiare perché dovevi prepararti a un esame di inglese e ti accorgi che il materiale da presentare è più di quello che avevi previsto. Scrivi una mail al professore: la tua speranza è spostare la presentazione. Engl:  Imagine you are taking a course with Dr. Nicola Brocca. Tomorrow you have to give a presentation in class. You had no time to study because you had to prepare for an English exam, and you realize that there is more material to present than you had imagined. You write an email to the professor: your hope is to reschedule the presentation. Mail b) Hai fatto un corso con il Dr. Brocca. Hai consegnato il tuo portfolio il 01.02.2020 adesso è il 01.03.2020 e non hai ancora ricevuto il voto. Ti serve il voto per registrarti per una borsa di studio. Manda una mail al prof.: il tuo obiettivo è ricevere il voto al più presto Engl: You have taken a course with Dr. Brocca. You turned in your portfolio on 02/01/2020, it is now 03/01/2020 and you have not received the grade yet. You need the grade to register for a scholarship. Send an email to the professor: your goal is to receive the grade as soon as possible.   WhatsApp messages 1. Sei in Erasmus in Italia. Avete creato una chat con 10 compagni di corso. Hai perso la tua tessera della biblioteca a vuoi chiedere se qualcuno ti può aiutare perché ti serve un libro entro domani...per esempio prestandoti la sua. Cosa scrivi? Engl: You are taking part in the Erasmus program in Italy. You have created a chat with 10 classmates. You lost your library card and want to ask if someone can help you because you need a book by tomorrow.... E.g. by lending you their card. What do you write? 2. Ricevi questo messaggio da un amico/a che fa un seminario con te: "Ciao, sono a corto di tempo. Ho visto che hai preso 30 all'esame. Potresti darmi una mano e restare con me in biblioteca oggi?" Non vuoi aiutare il tuo amico. Come reagisci? Engl: You receive this message from a friend who is attending a seminar with you: "Hello, I'm running out of time. I saw that you got a 30 on the exam. Could you help me and stay with me in the library today?" You don't want to help the friend. How do you respond? 3. Cinque giorni fa hai promesso ad un/a amico/a che questa sera sareste andati al cinema assieme. Però hai cambiato idea. Cosa fai? Cosa scrivi?  Engl:  Five days ago, you promised a friend that tonight you would go to the movies together. But you changed your mind. What would you do? What do you write?   4. Sei al lavoro e hai smarrito il documento elettronico per entrare nel parcheggio. Sei nuovo in questo gruppo di lavoro e hai solo il numero del tuo diretto superiore. Gli mandi un messaggio per chiedergli se ti può aiutare. Engl: You are at work and have lost your electronic badge to enter the parking lot. You are new to this work group and only have the number of your direct supervisor. You send him/her a message and ask if he/she can help you.   5. Ricevi questo messaggio dal/la tuo/a superiore. "Gentile collega, domani c'è una scadenza importante. Per caso sarebbe in grado di restare oggi in ufficio oltre l'orario?" Non vuoi restare in ufficio oltre il normale. Come reagisci? Engl: You receive this message from your supervisor. "Dear colleague, tomorrow is an important appointment. Would you be able to stay in the office after hours today?" You don't want to stay in the office beyond normal working hours. How do you respond?   6. Cinque giorni fa hai promesso al/la tuo/a superiore che oggi saresti andato a una cena di lavoro. Però devi disdire. Cosa fai? Engl: Five days ago, you promised your superior that you would go to a business dinner today. However, you have to cancel. What do you do?   The corpus, which was first collected in .xlsx format, was exported to XML format and CSV format in cooperation with Joseph Wang-Kathrein (Brenner Archive Research Center). It was ensured that the emoticons and special characters were also transferred unchanged in the conversion process. These formats allow long-term archiving and significantly facilitate data exchange. The size of the corpus (as of May 2021, version Ladder 1.0): The LADDER corpus includes emails and instant-messaging messages amounting to 18,935 tokens and 33,966 tokens respectively. The corpus of WhatsApp messages consists of a total of 1,204 messages from 80 native speakers and 114 learners. The corpus of emails consists of a total of 235 emails from 78 native-speaker informants and 38 learners. The amount of data allows a qualitatively relevant comparison in sub-corpora e.g. language levels. The size of the corpus is necessarily limited quantitatively, as data collection must be done manually through individual DCT management and metadata checking. The major bottleneck is currently the annotation of socio-pragmatic aspects, a process that is difficult to automate and that needs to be conducted through cross-annotation by multiple annotators. Some students' works on the corpus have been collected and are accessible via the following link: https://ladder.hypotheses.org/   Bibliography: Artoni, D., Benigni, V., & Nuzzo, E. (2020), "Pragmatic instruction in L2-Russian: a study on requests and advice" in Instructed Second Language Acquisition, 4(1), 62-95. doi:10.1558/isla.39864 Brocca, N. (2021), "LADDER: La costruzione e analisi di un corpus di scritture digitali per l’insegnamento della pragmatica in L2" in Italiano Lingua Due, 13(1 (2021)). Cortés Velásquez, D., & Nuzzo, E. (2017), "Disdire un appuntamento: spunti per la didattica dell'italiano L2 a partire da un corpus di parlanti nativi" in Italiano Lingua Due, 1, 17-36. Hinger, B., Stadler, W., Schmiderer, K., Bauer, M., (Hrg.) (2018). Testen und Bewerten fremdsprachlicher Kompetenzen. Tübingen: Narr Francke Attempto Verlag. Nuzzo, E., & Cortés Velásquez, D. (2020), "Canceling Last Minute in Italian and Colombian Spanish: A Cross-Cultural Account of Pragmalinguistic Strategies" in Corpus Pragmatics, 4, 1-26. doi:10.1007/s41701-020-00084-y Taguchi, N., & Roever, C. (2017), Second language pragmatics: Oxford: Oxford University Press. Trubnikova, V., & Garofolin, B. (2020), Lingua e interazione. Insegnare la pragmatica a scuola. Pisa: ETS.

opencc-by-4.0May 2022View details →

Tarefa de Restauração Digital da Disciplina Tecnologia da Informação

Atividade acadêmica de restauração digital da disciplina Tecnologia da Informação, do curso de Arquivologia - Universidade Federal da Paraíba. Página 28, do livro O espadachim de carvão / Affonso Solano. - Rio de Janeiro : Casa da Palavra, 2013.ISBN 97885773435081. Ficção brasileira. I. Título. 2013.

opencc-by-4.0Jun 2022View details →

Harvesting the Value of Data: A Data Architectural Smart Solutions Approach for Enabling Digital Water - Dataset

This database includes the test data used to produce the results for the following article: Harvesting the Value of Data: A Data Architectural Smart Solutions Approach for Enabling Digital Water  by S. Seshan, D. Vries, M. Zandvoort, A. W. C. van der Helm, J. Poinapen, Smart Water - WaterAge Magazine, February 16-23