3D pointclouds and orthophotos derived from historical aerial images are important sources for quantifying landscape changes used by various resaerchers (e.g. Glaciologists, Geomorphologists, Hydrologists, Botanists). Within the SEHAG project, funded by fhe FWF, we derived several historical snapshots for selected study areas in Austria and Italy. This dataset contains a pointcloud (1_Pointcloud), digital surface model (2_DSM) and orthophoto (3_OP) of the Kaunertal (Austria) derived from historical nadir images from 1970 and 1971 (originial image data (c) 1970/71 BEV and Land Tirol). The photogrammetric processing (i.e. orientation, 3D reconstruction) was done in Match-AT. All raster products (e.g. OP, DSM) were derived using OPALS. The OP has a resolution of 0.5m x 0.5m and the DSM a resolution of 2.5m x 2.5m.
\nCoordinate system and projection: UTM 32N (EPSG:25832) with ellipsoidal heights (ETRS89/GRS80)
\n1_Pointcloud:
\nKT_7071_v1.las: Original pointcloud from the featured based matching of the nadir images.
\nKT_7071_v1_pdens1.tif: Density of the feature based points per square meter. Low density regions corresponds to areas with poor image texture (e.g. shadow, snow).
\n2_DSM:
\nKT_7071_v1.tif: Interpolated surface model with a grid size of 2.5m. Moving planes interpolation using the 8 nearest neighbours and a maximum search radius of 16m. Holes were filled through triangular meshing.
\nKT_7071_v1_shd.tif: Shading of the interpolated surface model.
\nKT_7071_v1_sigma0map.tif: Variance of the 8 points from the best fitting plane per grid point.
\n3_OP: Orthophoto with a pixel size of 50cm.
\n4_QLT:
\nKT_7071_v1_dif2ref_zco_1m.tif: Colour coded differences to the used reference surface model.
KT_7071_v1_dif2ref_zco_1mLegend.svg
3D pointclouds and orthophotos derived from historical aerial images are important sources for quantifying landscape changes used by various resaerchers (e.g. Glaciologists, Geomorphologists, Hydrologists, Botanists). Within the SEHAG project, funded by fhe FWF, we derived several historical snapshots for selected study areas in Austria and Italy. This dataset contains a pointcloud (1_Pointcloud), digital surface model (2_DSM) and orthophoto (3_OP) of the Kaunertal (Austria) derived from historical nadir images from 1969 (originial image data (c) 1969 BEV and Land Tirol). The photogrammetric processing (i.e. orientation, 3D reconstruction) was done in Match-AT. All raster products (e.g. OP, DSM) were derived using OPALS. The OP has a resolution of 0.5m x 0.5m and the DSM a resolution of 2.5m x 2.5m.
\nCoordinate system and projection: UTM 32N (EPSG:25832) with ellipsoidal heights (ETRS89/GRS80)
\n1_Pointcloud:
\nKT_69_v2.las: Original pointcloud from the featured based matching of the nadir images.
\nKT_69_v2_pdens1.tif: Density of the feature based points per square meter. Low density regions corresponds to areas with poor image texture (e.g. shadow, snow).
\n2_DSM:
\nKT_69_v2.tif: Interpolated surface model with a grid size of 2.5m. Moving planes interpolation using the 8 nearest neighbours and a maximum search radius of 16m. Holes were filled through triangular meshing.
\nKT_69_v2_shd.tif: Shading of the interpolated surface model.
\nKT_69_v2_sigma0map.tif: Variance of the 8 points from the best fitting plane per grid point.
\n3_OP: Orthophoto with a pixel size of 50cm.
\n4_QLT:
\nKT_69_v2_dif2ref_zco_1m.tif: Colour coded differences to the used reference surface model.
KT_69_v2_dif2ref_zco_1mLegend.svg
3D pointclouds and orthophotos derived from historical aerial images are important sources for quantifying landscape changes used by various resaerchers (e.g. Glaciologists, Geomorphologists, Hydrologists, Botanists). Within the SEHAG project, funded by fhe FWF, we derived several historical snapshots for selected study areas in Austria and Italy. This dataset contains a pointcloud (1_Pointcloud), digital surface model (2_DSM) and orthophoto (3_OP) of the Kaunertal (Austria) derived from historical nadir images from 1953 (originial image data (c) 1953 BEV and Land Tirol). The photogrammetric processing (i.e. orientation, 3D reconstruction) was done in Match-AT. All raster products (e.g. OP, DSM) were derived using OPALS. The OP has a resolution of 0.5m x 0.5m and the DSM a resolution of 2.5m x 2.5m.
\nCoordinate system and projection: UTM 32N (EPSG:25832) with ellipsoidal heights (ETRS89/GRS80)
\n1_Pointcloud:
\nKT_53_v2.las: Original pointcloud from the featured based matching of the nadir images.
\nKT_53_v2_pdens1.tif: Density of the feature based points per square meter. Low density regions corresponds to areas with poor image texture (e.g. shadow, snow).
\n2_DSM:
\nKT_53_v2.tif: Interpolated surface model with a grid size of 2.5m. Moving planes interpolation using the 8 nearest neighbours and a maximum search radius of 16m. Holes were filled through triangular meshing.
\nKT_53_v2_shd.tif: Shading of the interpolated surface model.
\nKT_53_v2_sigma0map.tif: Variance of the 8 points from the best fitting plane per grid point.
\n3_OP: Orthophoto with a pixel size of 50cm.
\n4_QLT:
\nKT_53_v2_dif2ref_zco_1m.tif: Colour coded differences to the used reference surface model.
KT_53_v2_dif2ref_zco_1mLegend.svg
3D pointclouds and orthophotos derived from historical aerial images are important sources for quantifying landscape changes used by various resaerchers (e.g. Glaciologists, Geomorphologists, Hydrologists, Botanists). Within the SEHAG project, funded by fhe FWF, we derived several historical snapshots for selected study areas in Austria and Italy. This dataset contains a pointcloud (1_Pointcloud), digital surface model (2_DSM) and orthophoto (3_OP) of the Kaunertal (Austria) derived from historical nadir images from 1982 (originial image data (c) 1982 BEV and Land Tirol). The photogrammetric processing (i.e. orientation, 3D reconstruction) was done in Match-AT. All raster products (e.g. OP, DSM) were derived using OPALS. The OP has a resolution of 0.5m x 0.5m and the DSM a resolution of 2.5m x 2.5m.
\nCoordinate system and projection: UTM 32N (EPSG:25832) with ellipsoidal heights (ETRS89/GRS80)
\n1_Pointcloud:
\nKT_82_v1.las: Original pointcloud from the featured based matching of the nadir images.
\nKT_82_v1_pdens1.tif: Density of the feature based points per square meter. Low density regions corresponds to areas with poor image texture (e.g. shadow, snow).
\n2_DSM:
\nKT_82_v1.tif: Interpolated surface model with a grid size of 2.5m. Moving planes interpolation using the 8 nearest neighbours and a maximum search radius of 16m. Holes were filled through triangular meshing.
\nKT_82_v1_shd.tif: Shading of the interpolated surface model.
\nKT_82_v1_sigma0map.tif: Variance of the 8 points from the best fitting plane per grid point.
\n3_OP: Orthophoto with a pixel size of 50cm.
\n4_QLT:
\nKT_82_v1_dif2ref_zco_1m.tif: Colour coded differences to the used reference surface model.
KT_82_v1_dif2ref_zco_1mLegend.svg
3D pointclouds and orthophotos derived from historical aerial images are important sources for quantifying landscape changes used by various resaerchers (e.g. Glaciologists, Geomorphologists, Hydrologists, Botanists). Within the SEHAG project, funded by fhe FWF, we derived several historical snapshots for selected study areas in Austria and Italy. This dataset contains a pointcloud (1_Pointcloud), digital surface model (2_DSM) and orthophoto (3_OP) of the Kaunertal (Austria) derived from historical nadir images from 2003 (originial image data (c) 2003 BEV and Land Tirol). The photogrammetric processing (i.e. orientation, 3D reconstruction) was done in Match-AT. All raster products (e.g. OP, DSM) were derived using OPALS. The OP has a resolution of 0.5m x 0.5m and the DSM a resolution of 2.5m x 2.5m.
\nCoordinate system and projection: UTM 32N (EPSG:25832) with ellipsoidal heights (ETRS89/GRS80)
\n1_Pointcloud:
\nKT_03_v1.las: Original pointcloud from the featured based matching of the nadir images.
\nKT_03_v1_pdens1.tif: Density of the feature based points per square meter. Low density regions corresponds to areas with poor image texture (e.g. shadow, snow).
\n2_DSM:
\nKT_03_v1.tif: Interpolated surface model with a grid size of 2.5m. Moving planes interpolation using the 8 nearest neighbours and a maximum search radius of 16m. Holes were filled through triangular meshing.
\nKT_03_v1_shd.tif: Shading of the interpolated surface model.
\nKT_03_v1_sigma0map.tif: Variance of the 8 points from the best fitting plane per grid point.
\n3_OP: Orthophoto with a pixel size of 50cm.
\n4_QLT:
\nKT_03_v1_dif2ref_zco_1m.tif: Colour coded differences to the used reference surface model.
KT_03_v1_dif2ref_zco_1mLegend.svg
3D pointclouds and orthophotos derived from historical aerial images are important sources for quantifying landscape changes used by various resaerchers (e.g. Glaciologists, Geomorphologists, Hydrologists, Botanists). Within the SEHAG project, funded by fhe FWF, we derived several historical snapshots for selected study areas in Austria and Italy. This dataset contains a pointcloud (1_Pointcloud), digital surface model (2_DSM) and orthophoto (3_OP) of the Kaunertal (Austria) derived from historical nadir images from 1953 and 1954 (originial image data (c) 1953/54 BEV and Land Tirol). The photogrammetric processing (i.e. orientation, 3D reconstruction) was done in Match-AT. All raster products (e.g. OP, DSM) were derived using OPALS. The OP has a resolution of 0.5m x 0.5m and the DSM a resolution of 2.5m x 2.5m.
\nCoordinate system and projection: UTM 32N (EPSG:25832) with ellipsoidal heights (ETRS89/GRS80)
\n1_Pointcloud:
\nHT_5354_v2.las: Original pointcloud from the featured based matching of the nadir images.
\nHT_5354_v2_pdens1.tif: Density of the feature based points per square meter. Low density regions corresponds to areas with poor image texture (e.g. shadow, snow).
\n2_DSM:
\nHT_5354_v2.tif: Interpolated surface model with a grid size of 2.5m. Moving planes interpolation using the 8 nearest neighbours and a maximum search radius of 16m. Holes were filled through triangular meshing.
\nHT_5354_v2_shd.tif: Shading of the interpolated surface model.
\nHT_5354_v2_sigma0map.tif: Variance of the 8 points from the best fitting plane per grid point.
\n3_OP: Orthophoto with a pixel size of 50cm.
\n4_QLT:
\nHT_5354_v2_dif2ref_zco_1m.tif: Colour coded differences to the used reference surface model.
HT_5354_v2_dif2ref_zco_1mLegend.svg
3D pointclouds and orthophotos derived from historical aerial images are important sources for quantifying landscape changes used by various resaerchers (e.g. Glaciologists, Geomorphologists, Hydrologists, Botanists). Within the SEHAG project, funded by fhe FWF, we derived several historical snapshots for selected study areas in Austria and Italy. This dataset contains a pointcloud (1_Pointcloud), digital surface model (2_DSM) and orthophoto (3_OP) of the Kaunertal (Austria) derived from historical nadir images from 1970 and 1973 (originial image data (c) 1970/1973 BEV and Land Tirol). The photogrammetric processing (i.e. orientation, 3D reconstruction) was done in Match-AT. All raster products (e.g. OP, DSM) were derived using OPALS. The OP has a resolution of 0.5m x 0.5m and the DSM a resolution of 2.5m x 2.5m.
\nCoordinate system and projection: UTM 32N (EPSG:25832) with ellipsoidal heights (ETRS89/GRS80)
\n1_Pointcloud:
\nHT_7073_v2.las: Original pointcloud from the featured based matching of the nadir images.
\nHT_7073_v2_pdens1.tif: Density of the feature based points per square meter. Low density regions corresponds to areas with poor image texture (e.g. shadow, snow).
\n2_DSM:
\nHT_7073_v2.tif: Interpolated surface model with a grid size of 2.5m. Moving planes interpolation using the 8 nearest neighbours and a maximum search radius of 16m. Holes were filled through triangular meshing.
\nHT_7073_v2_shd.tif: Shading of the interpolated surface model.
\nHT_7073_v2_sigma0map.tif: Variance of the 8 points from the best fitting plane per grid point.
\n3_OP: Orthophoto with a pixel size of 50cm.
\n4_QLT:
\nHT_7073_v2_dif2ref_zco_1m.tif: Colour coded differences to the used reference surface model.
HT_7073_v2_dif2ref_zco_1mLegend.svg
3D pointclouds and orthophotos derived from historical aerial images are important sources for quantifying landscape changes used by various resaerchers (e.g. Glaciologists, Geomorphologists, Hydrologists, Botanists). Within the SEHAG project, funded by fhe FWF, we derived several historical snapshots for selected study areas in Austria and Italy. This dataset contains a pointcloud (1_Pointcloud), digital surface model (2_DSM) and orthophoto (3_OP) of the Kaunertal (Austria) derived from historical nadir images from 1990 (originial image data (c) 1990 BEV and Land Tirol). The photogrammetric processing (i.e. orientation, 3D reconstruction) was done in Match-AT. All raster products (e.g. OP, DSM) were derived using OPALS. The OP has a resolution of 0.5m x 0.5m and the DSM a resolution of 2.5m x 2.5m.
\nCoordinate system and projection: UTM 32N (EPSG:25832) with ellipsoidal heights (ETRS89/GRS80)
\n1_Pointcloud:
\nKT_90_v1.las: Original pointcloud from the featured based matching of the nadir images.
\nKT_90_v1_pdens1.tif: Density of the feature based points per square meter. Low density regions corresponds to areas with poor image texture (e.g. shadow, snow).
\n2_DSM:
\nKT_90_v1.tif: Interpolated surface model with a grid size of 2.5m. Moving planes interpolation using the 8 nearest neighbours and a maximum search radius of 16m. Holes were filled through triangular meshing.
\nKT_90_v1_sigma0map.tif: Variance of the 8 points from the best fitting plane per grid point.
\n3_OP: Orthophoto with a pixel size of 50cm.
\n4_QLT:
\n3D pointclouds and orthophotos derived from historical aerial images are important sources for quantifying landscape changes used by various resaerchers (e.g. Glaciologists, Geomorphologists, Hydrologists, Botanists). Within the SEHAG project, funded by fhe FWF, we derived several historical snapshots for selected study areas in Austria and Italy. This dataset contains a pointcloud (1_Pointcloud), digital surface model (2_DSM) and orthophoto (3_OP) of the Kaunertal (Austria) derived from historical nadir images from 1997 (originial image data (c) 1997 BEV and Land Tirol). The photogrammetric processing (i.e. orientation, 3D reconstruction) was done in Match-AT. All raster products (e.g. OP, DSM) were derived using OPALS. The OP has a resolution of 0.5m x 0.5m and the DSM a resolution of 2.5m x 2.5m.
\nCoordinate system and projection: UTM 32N (EPSG:25832) with ellipsoidal heights (ETRS89/GRS80)
\n1_Pointcloud:
\nKT_97_v1.las: Original pointcloud from the featured based matching of the nadir images.
\nKT_97_v1_pdens1.tif: Density of the feature based points per square meter. Low density regions corresponds to areas with poor image texture (e.g. shadow, snow).
\n2_DSM:
\nKT_97_v1.tif: Interpolated surface model with a grid size of 2.5m. Moving planes interpolation using the 8 nearest neighbours and a maximum search radius of 16m. Holes were filled through triangular meshing.
\nKT_97_v1_sigma0map.tif: Variance of the 8 points from the best fitting plane per grid point.
\n3_OP: Orthophoto with a pixel size of 50cm.
\n4_QLT:
\nThe biosynthetic gene cluster (BGC) responsible for producing diaporthinic acid has remained genetically unassigned despite repeated isolation of this metabolite from several fungal species. In this study, we activated the dia BGC in Trichoderma reesei by overexpressing the cluster-associated zinc-cluster protein DiaR1 to identify the BGC’s in vivo metabolic output and reconstruct the corresponding biosynthetic pathway. Metabolite production was analyzed by HPLC-MS/MS, and the major product was isolated and structurally confirmed by NMR spectroscopy. Individual genes of the dia cluster were deleted in the activated background to assess their functional roles, and transcript levels were quantified by RT-qPCR. Activation of the cluster resulted in the predominant accumulation of diaporthinic acid, accompanied by several related isocoumarin derivatives, while antibacterial and antifungal assays showed no detectable activity of diaporthinic acid under the tested conditions. Deletion analyses demonstrated that the polyketide synthase Dia1, the bifunctional halogenase/methyltransferase Dia5, and the FAD-dependent oxidoreductase Dia4 are essential for diaporthinic acid formation, whereas Dia2 and Dia3 are dispensable in vivo despite the previously proposed roles of their Aspergillus oryzae homologs based on in vitro studies. On the basis of intermediate accumulation patterns, we propose that Dia4 catalyzes the oxidation of dichlorodiaporthin to diaporthinic acid. Together, these results genetically link diaporthinic acid to the dia BGC and refine the previously proposed biosynthetic model derived from A. oryzae.
", "additional_descriptions": [{"description": "HPLC-MS/MS analysis
LC-MS grade acetonitrile (ACN) and LC-MS grade formic acid were acquired from VWR chemicals (Radnor, PA, USA). Water (H2O) was purified in-house using a Barnstead™ Smart2Pure™ Water Purification System from Thermo Fisher Scientific (Waltham, MA, USA). Alternariol (CAS # 641-38-3) standard, Catalog # C5061 (Batch No. 1), was purchased from APExBIO (Houston, TX, USA).
The frozen culture media were thawed, vortexed, and 2 mL of each strain and quadruplicate were transferred into fresh Eppendorf tubes. These tubes were spun down for 2 minutes at 20,000 g at room temperature. From the supernatant, 10 μL were taken out and diluted 1:10 in 2 % ACN + 0.1 % FA. The injection volume was 1 μL.
For analysis of the NMR-confirmed diaporthinic acid standard, a stock solution of the compound in DMSO was diluted 1:10 in 2 % ACN + 0.1 % FA. The commercial alternariol standard (1 mg) was dissolved in 1 mL of 50% ACN (with two drops of NH4OH) and further diluted 1:100 in 2 % ACN + 0.1 % FA (c = 10 ng μL-1). The injection volume for both standards was 1 μL.
After dilution of the culture media and the reference standards, the samples were measured employing an untargeted metabolomics workflow in positive ionization mode on a Bruker timsTOF Pro equipped with a VIP-HESI source (Bruker Corporation, Billerica, MA, USA). The frontend was a Thermo Fisher Scientific Vanquish H UHPLC with a Waters Acquity BEH C18 column (150 mm × 1 mm ID, 1.7 μm; Waters Corporation, Milford, MA, USA). Mobile phase A was 0.1 % formic acid in water and solvent B acetonitrile containing 0.1 % formic acid. The following gradient was employed at 40 °C and a constant flow rate of 100 μL min-1: 0 min, 2 % B; 9 min, 98 %; 12 min, 98 % B; 12 min, 2 % B, followed by 4 min re-equilibration. The timsTOF Pro mass spectrometer was operated without trapped ion mobility spectrometry (TIMS off). For positive ionization mode, source capillary voltage was set to 4500 V and dry gas flow to 8 L min-1 at 230 °C. Sheath Gas Flow was set to 4.0 L min-1 at a temperature of 200 °C, with active exhaust being activated. Scan mode was set to Auto MS/MS with 12 Hz MS spectra rate and 16 Hz MS/MS spectra rate, resulting in a total cycle time of 0.5 s. Scan range was set from 20 to 800 m/z.
Data was acquired with Bruker Compass Hystar 6.3. Individual compounds were quantified on MS1 level employing the open-source application Skyline version 23.135,36 normalizing to the TIC, based on exact mass only.
This dataset was produced with funding from the European Space Agency (ESA) Climate Change Initiative (CCI) Plus Soil Moisture (SM) Project (CCN 4 to ESRIN Contract No: 4000126684/19/I-NB \"ESA CCI+ Phase 1 New R&D on CCI ECVS Soil Moisture\"). Project website: https://climate.esa.int/en/projects/soil-moisture/
\nThis dataset contains information on the Surface Soil Moisture content derived from satellite observations in the microwave domain.
\nThe operational (ACTIVE, PASSIVE, COMBINED) ESA CCI SM products are available at https://catalogue.ceda.ac.uk/uuid/c256fcfeef24460ca6eb14bf0fe09572/ (Dorigo et al., 2017; Gruber et al., 2019; Preimesberger et al., 2021).
\nThe ESA CCI SUB-DAILYSM science product is a 12-hourly product that is produced with the same method as the daily ESA CCI COMBINED SM product. For the Sub Daily product, the input data is temporally resampled to 12 hours instead of 24 hours. The temporal window is centred around 0 UTC and 12 UTC. Satellite observations that were taken directly on the border between the two time windows will be added to the previous timestamp to avoid double binning. So observations taken at 6 UTC will be added to 0 UTC, and observations at 18 UTC will be added to 12 UTC.
\nDue to the increased need for temporal coverage for a subdaily product, it has been produced from 2012 on, after the activation of ASCAT-B and AMSR2. The following Sensors are included in the SUB-DAILY product: ASCAT A, ASCAT B, ASCAT C, AMSR2, FY3b, FY3c, FY3d, GPM, SMAP, SMOS and TRMM.
\nYou can use command-line tools such as wget or curl to download (and extract) data for multiple years. The following command will download and extract the complete data set to the local directory ~/Download on Linux or macOS systems.
\n\n\n\n\n#!/bin/bash\n
# Set download directory
DOWNLOAD_DIR=~/Downloads
base_url=\"https://researchdata.tuwien.at/records/939n8-zg244/files\"
# Loop through years 2012 to 2024 and download & extract data
for year in {2012..2024}; do
echo \"Downloading $year.zip...\"
wget -q -P \"$DOWNLOAD_DIR\" \"$base_url/$year.zip\"
unzip -o \"$DOWNLOAD_DIR/$year.zip\" -d $DOWNLOAD_DIR
rm \"$DOWNLOAD_DIR/$year.zip\"
done
The dataset provides global sub-daily (0UTC and 12UTC) estimates for the 2012-2024 period at 0.25° (~25 km) horizontal grid resolution. Daily images are grouped by year (YYYY), each subdirectory containing one netCDF image file for a specific hour (HH), day (DD) and month (MM) of that year in a 2-dimensional (longitude, latitude) grid system (CRS: WGS84). The file name follows the convention:
\n\n\nESACCI-SOILMOISTURE-L3S-SUBDAILY-COMBINED-YYYYMMDDHH0000-fv09.2.nc
\n
Each netCDF file contains 3 coordinate variables
\nand the following data variables
\nAdditional information for each variable are given in the netCDF attributes.
\nThese data can be read by any software that supports Climate and Forecast (CF) conform metadata standards for netCDF files, such as:
\nThis record and all related records are part of the ESA CCI Soil Moisture science data records community.
", "funding": [{"funder": {"id": "03wd9za21", "name": "European Space Agency"}, "award": {"number": "4000126684/19/I-NB"}}]}, "custom_fields": {}, "access": {"record": "public", "files": "public", "embargo": {"active": false, "reason": null}, "status": "open"}, "files": {"enabled": true, "order": [], "count": 13, "total_bytes": 17377440266, "entries": {"2018.zip": {"id": "f85273ba-ae94-4bda-89e3-2250216bbd7b", "checksum": "md5:6df45d6b2ddecfc3a8b2ba29d2b23477", "ext": "zip", "size": 1426404463, "mimetype": "application/zip", "key": "2018.zip", "metadata": {}, "access": {"hidden": false}}, "2012.zip": {"id": "24977f8c-a6b3-4285-8995-12e78bc25031", "checksum": "md5:6f5a9b7711ad661574a208802be92d48", "ext": "zip", "size": 699696856, "mimetype": "application/zip", "key": "2012.zip", "metadata": {}, "access": {"hidden": false}}, "2013.zip": {"id": "5831cb39-9b97-4b45-9c99-618ea31c517f", "checksum": "md5:320c068dd05d6fbcb26571fc9a08738e", "ext": "zip", "size": 1349268295, "mimetype": 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The recording is based on the work with the title \"Madonna tenerina (Madonna tenerina)\" and the id \"A-Wn_Mus.Hs._18827_n08\" in the e-lautedb. It is found on the page(s) or folio(s) 9r-9v in the source \"Lautentabulatur Antonius\" with the source-id \"A-Wn_Mus.Hs._18827\".
The original source and multiple transcriptions of the work can be found on the E-LAUTE platform: https://edition.onb.ac.at/fedora/objects/o:lau.A-Wn_Mus.Hs._18827/methods/sdef:TEI/get?mode=n08.
Links to the source: https://search.onb.ac.at/permalink/f/sb7jht/ONB_alma21308232200003338, https://opac.rism.info/search?id=600141783&View=rism.
This dataset includes:
E-LAUTE: Electronic Linked Annotated Unified Tablature Edition - The Lute in the German-Speaking Area 1450-1550
The E-LAUTE project creates innovative digital editions of lute tablatures from the German-speaking area between 1450 and 1550. This interdisciplinary \"open knowledge platform\" combines musicology, music practice, music informatics, and literary studies to transform traditional editions into collaborative research spaces.
For more information, visit the project website: https://e-laute.info/
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{"subject": "lute music"}], "contributors": [{"person_or_org": {"type": "personal", "name": "Hulcuva, Barbora", "given_name": "Barbora", "family_name": "Hulcuva"}, "role": {"id": "other", "title": {"en": "Other"}}}, {"person_or_org": {"type": "personal", "name": "Jaklin, Julia Maria", "given_name": "Julia Maria", "family_name": "Jaklin"}, "role": {"id": "contactperson", "title": {"en": "Contact person"}}, "affiliations": [{"id": "04d836q62", "name": "TU Wien", "identifiers": [{"identifier": "04d836q62", "scheme": "ror"}, {"identifier": "grid.5329.d", "scheme": "grid"}, {"identifier": "0000 0004 1937 0669", "scheme": "isni"}]}]}, {"person_or_org": {"type": "personal", "name": "Bischoff, Silas", "given_name": "Silas", "family_name": "Bischoff"}, "role": {"id": "producer", "title": {"en": "Producer"}}}], "dates": [{"date": "2024-12-03", "type": {"id": "created", "title": {"en": "Created"}}, "description": "Recording date"}], "identifiers": [{"identifier": "A-Wn_Mus.Hs._41950_n01, A-Wn_Mus.Hs._41950_n02, A-Wn_Mus.Hs._41950_n03", "scheme": "other"}], "related_identifiers": [{"identifier": "http://data.onb.ac.at/rec/AC14278637", "scheme": "url", "relation_type": {"id": "ispartof", "title": {"en": "Is part of"}}, "resource_type": {"id": "other", "title": {"de": "Anderes", "en": "Other"}}}], "rights": [{"id": "cc-by-sa-4.0", "title": {"en": "Creative Commons Attribution Share Alike 4.0 International"}, "description": {"en": "Permits almost any use subject to providing credit and license notice. 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The recording is based on the work with the title \"preambulum (Pr\u00e4ambulum), Nach lauf (Nachlauf), praem[bulum] (Pr\u00e4ambulum)\" and the id \"A-Wn_Mus.Hs._41950_n01, A-Wn_Mus.Hs._41950_n02, A-Wn_Mus.Hs._41950_n03\" in the e-lautedb. It is found on the page(s) or folio(s) 1r-3r_1-7, 3r_8-11-3v_1, 3v_2 in the source \"Blindhamers Lautentabulatur\" with the source-id \"A-Wn_Mus.Hs._41950\".
The original source and multiple transcriptions of the work can be found on the E-LAUTE platform: https://edition.onb.ac.at/fedora/objects/o:lau.A-Wn_Mus.Hs._41950/methods/sdef:TEI/get?mode=n03.
Links to the source: http://data.onb.ac.at/rec/AC14278637.
This dataset includes:
E-LAUTE: Electronic Linked Annotated Unified Tablature Edition - The Lute in the German-Speaking Area 1450-1550
The E-LAUTE project creates innovative digital editions of lute tablatures from the German-speaking area between 1450 and 1550. This interdisciplinary \"open knowledge platform\" combines musicology, music practice, music informatics, and literary studies to transform traditional editions into collaborative research spaces.
For more information, visit the project website: https://e-laute.info/
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"oai:researchdata.tuwien.ac.at:f8tjt-k8y11", "provider": "oai"}}, "metadata": {"resource_type": {"id": "dataset", "title": {"de": "Datensatz", "en": "Dataset"}}, "creators": [{"person_or_org": {"type": "personal", "name": "Mairinger, Paul Anton", "given_name": "Paul Anton", "family_name": "Mairinger"}, "role": {"id": "contactperson", "title": {"en": "Contact person"}}, "affiliations": [{"id": "04d836q62", "name": "TU Wien", "identifiers": [{"identifier": "04d836q62", "scheme": "ror"}, {"identifier": "grid.5329.d", "scheme": "grid"}, {"identifier": "0000 0004 1937 0669", "scheme": "isni"}]}]}], "title": "Traces in WAN Traffic: Inferring Alarm States and User Activity from Encrypted Smart Home Traffic", "publisher": "TU Wien", "publication_date": "2026-04-21", "dates": [{"date": "2026-04-21", "type": {"id": "created", "title": {"en": "Created"}}}], "rights": [{"id": "cc-by-4.0", "title": {"en": "Creative Commons Attribution 4.0 International"}, "description": {"en": "The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited."}, "icon": "cc-by-icon", "props": {"url": "https://creativecommons.org/licenses/by/4.0/legalcode", "scheme": "spdx"}}], "description": "This repository contains research data for evaluating network-traffic-based classification of Philips Hue smart-home actions. The dataset provides packet-level captures for repeated light on/off commands and labeled packet-burst features for Hue security-state commands. It is intended to support reproducible experiments on IoT traffic analysis, command inference, and device-behavior fingerprinting.
\nResearch dataset of Philips Hue smart-home network traces for IoT traffic analysis. The repository contains 10,000 labeled on/off PCAP captures and labeled packet-burst features for arm/disarm security-state commands.
\nRepository/\n -- armstate_labeled.csv\n -- Left_Spot_device_10ktrial.7z\nOn-Off/Left_Spot_device_10ktrial.7z contains 10,000 PCAP files captured during repeated Philips Hue light-control actions for a smart-light device communicating with a Hue Bridge Pro. The archive contains 5,000 Turn_On captures and 5,000 Turn_Off captures. File names encode the trial number, timestamp, device label and action label.
Arm-Disarm/armstate_labeled.csv contains 100 labeled packet-burst feature records for Hue security-state commands:
arm_home: 25 recordsarm_away: 25 recordsdisarm: 50 recordsThe CSV uses the following columns:
\nlabel: command class label.TO-lengths: ordered packet-length sequence for packets sent to the target device.total-t: total burst duration in seconds.IAT: mean inter-arrival time in seconds.packet-amount: number of packets in the burst.This dataset is structured to support the FAIR principles:
\nOn-Off, Arm-Disarm) and named with explicit device/action labels.If you use this dataset, cite the accompanying paper and the archived dataset release. A final citation will be added once the publication metadata and persistent dataset identifier are available.
\nUntil then, please cite this repository as:
\n\n\nTraces in WAN Traffic: Inferring Alarm States and User Activity from Encrypted Smart Home Traffic
\n
Temporary BibTeX entry:
\n@dataset{hue_research_data_2026,\n title = {Traces in WAN Traffic: Inferring Alarm States and User Activity from Encrypted Smart Home Traffic},\n author = {{Paul Mairinger et al.}},\n year = {2026},\n note = {Dataset repository. Final citation metadata to be added after publication.},\n url = {TODO}\n}Smartphone GNSS and Sensor Data with RTK Reference Trajectory
\nThis dataset was produced with funding from the European Space Agency (ESA) Climate Change Initiative (CCI) Plus Soil Moisture Project (CCN4 to ESRIN Contract No: 4000126684/19/I-NB \"ESA CCI+ Phase 1 New R&D on CCI ECVS Soil Moisture\"). Project website: https://climate.esa.int/en/projects/soil-moisture/
\nThis dataset contains information on the Surface Soil Moisture (SM) content derived from satellite observations in the microwave domain.
\nThe MODEL-INDEPENDENT (or \"modelfree\") product of ESA CCI SM v9.2 provides -- similar to the COMBINED product -- global, harmonized daily satellite soil moisture measurements from both radar and radiometer observations at 0.25-degree spatial grid resolution. It currently covers the period from 2002-2024.
\nSoil moisture is derived from observations of 13 different active and passive satellites operating across various frequency bands (K, C, X, and L-band). Unlike the COMBINED product -- for which all satellite time series are scaled to GLDAS Noah soil moisture simulations before merging, in order to remove biases between them -- the MODEL-INDEPENDENT product utilizes a satellite-only scaling reference dataset. This reference is based on harmonized L-band (SMOS and SMAP) retrievals from 2010 onwards (Madelon et al., 2022), which were extended further back with C-band retrievals from AMSR-E (2002-2010). Gaps in the scaling reference dataset are filled using the algorithm from the GAPFILLED product (Preimesberger et al., 2025). The merging algorithm employed is consistent with that of the v9.2 COMBINED product. The new scaling reference leads to significantly different absolute soil moisture values, especially in latitudes above 60°N. Data from the SMMR, SSMI and ERS missions are not included in this product.
\nThis product is in its early development stage and should be used with caution, as it may contain incomplete or unvalidated data.
\n2002-06-19 to 2024-12-31, global, 0.25 deg. regular grid
\nGLDAS Noah (model) is replaced with a purely satellite-based scaling reference (based on SMOS)
\nDifferent absolute value range compared to the COMBINED product is expected due to the different scaling reference used
\nA temporal inconsistency is observed between the AMSR-E and SMOS period (at 01-2010). This affects mainly data above 60°N and can affect long-term trend detection
\nYou can use command line tools such as wget or curl to download (and extract) data for multiple years. The following command will download and extract the complete data set to the local directory ~/Download on Linux or macOS systems (~15 GB).
\n\n\n\n\n#!/bin/bash\n
# Set download directory
DOWNLOAD_DIR=~/Downloads
base_url=\"https://researchdata.tuwien.at/records/y147y-q6j91/files\"
# Loop through years 2002 to 2024 and download & extract data
for year in {2002..2024}; do
echo \"Downloading $year.zip...\"
wget -q -P \"$DOWNLOAD_DIR\" \"$base_url/$year.zip\"
unzip -o \"$DOWNLOAD_DIR/$year.zip\" -d $DOWNLOAD_DIR
rm \"$DOWNLOAD_DIR/$year.zip\"
done
The dataset provides global daily estimates for the 2002-2024 period at 0.25° (~25 km) horizontal grid resolution. Daily images are grouped by year (YYYY), each subdirectory containing one netCDF image file for a specific day (DD), month (MM) in a 2-dimensional (longitude, latitude) grid system (CRS: WGS84). The file name has the following convention:
\n\n\nESACCI-SOILMOISTURE-L3S-SSMV-COMBINED_MODELFREE-YYYYMMDD000000-fv09.2.nc
\n
Each netCDF file contains 3 coordinate variables (WGS84 longitude, latitude and time stamp), as well as the following data variables:
\nAdditional information for each variable is given in the netCDF attributes.
\nThese data can be read by any software that supports Climate and Forecast (CF) conform metadata standards for netCDF files, such as:
\nR. Madelon et al., “Toward the Removal of Model Dependency in Soil Moisture Climate Data Records by Using an L-Band Scaling Reference,\" in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 831-848, 2022, doi: 10.1109/JSTARS.2021.3137008.
\nThis record and all related records are part of the ESA CCI Soil Moisture science data records community.
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\nThis dataset was created to investigate to support experiment on depth estimation and pose estimation of transparent objects. Diverse objects with varying materials, shape, size and liquid fill level are recorded in scenes with various background, lighting in different organization. The aim of this dataset is to help highlight strengths and weaknesses of different approaches and empirically investigate the reliability of different methods in realistic scenarios. By using glass and plastic objects, filled with liquid and empty, properties like opacity and index of refraction are varied. The selected objects also vary significantly in shape and size, with a mix of transparent and non-transparent materials. Additionally, scene properties, including viewing angle, object arrangements, support plane texture, and lighting are varied to create diverse evaluation scenarios.
\nThe dataset is collected by moving a camera attached to a robot arm around a scene. The same viewpoints are collected for every scene, and the camera poses are obtained through inverse kinematics of the robot arm. We use 3D-DAT (https://github.com/markus-suchi/3D-DAT) for annotation, placing object models in the virtual 3D scene, and manually correcting their poses based on their reprojection error in the different RGB views.
\nTo obtain 3D object models, the physical objects are coated using a mat spray paint after collecting the different scenes. A high-quality depth sensor (Photoneo MotionCam-3D scanner, https://www.photoneo.com/) is used to reconstruct them. The set of 17 objects used in our experiments includes plastics and glass objects, filled or empty with a variety of shapes, and a variety of sizes. The 3D object models of the deformable objects are obtained by first manually estimating the object masks using SegmentAnything2, and using them in a voxel carving procedure, followed by a marching cube step to obtain a final mesh model.
\nA total of 34 scenes is collected using a Intel Realsense D435 (https://www.intelrealsense.com/depth-camera-d435i/), saving both the RGB image and the depth image at a resolution of 1280 × 720 pixels. The robotic arm performs a circular motion around the scene with the camera oriented toward the scene center, placing the camera at four different heights and corresponding polar angles (68°, 60°, 48° and 33°). For each circle, either 16 or 26 views are collecting resulting in a total of 64 or 104 views per scene. The light is uniform and comes from the top of the scene. For seven scenes, we add a strong light projector to the side of the scene, producing caustics and other refraction and reflection effects at the interface of transparent objects. Six scenes also have a textured background instead of an uniform one, and the number of distractors in the scene is varied.
\nFor each scene in the \"scenes/\" folder, the structure is as follow:
\n\n
We complement this dataset with a rendered training set generated using BlenderProc consisting in 148k images featuring high-quality models of the four most represented transparent objects in the real dataset to support training methods as needed. The rendered dataset includes various distractor objects and changing liquid fill levels as well as various liquid properties. As is standard with BlenderProc, the rendered dataset is using the BOP format detailed here. The models used in the renderings are also provided under the models/ folder.
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N\u00e4herungsmodell", "publisher": "TU Wien", "publication_date": "2026-04-15", "subjects": [{"subject": "HPV"}, {"subject": "Modelling and Simulation"}, {"subject": "Medical and health sciences"}, {"subject": "Vaccinations"}, {"subject": "Dashboard"}], "languages": [{"id": "deu", "title": {"en": "German"}}], "rights": [{"id": "cc-by-4.0", "title": {"en": "Creative Commons Attribution 4.0 International"}, "description": {"en": "The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited."}, "icon": "cc-by-icon", "props": {"url": "https://creativecommons.org/licenses/by/4.0/legalcode", "scheme": "spdx"}}], "description": "In Österreich ist die HPV-Impfung seit 2014 Teil des kostenfreien Impfprogramms, parallel gibt es den Privatmarkt für nicht im kostenfreien Programm abgedeckte Personengruppen. In den letzten Jahren wurde auch regelmäßig die Altersgruppe, die von diesem Impfprogramm profitieren kann, vergrößert. Ziel das Projektes war es, zu evaluieren, wie gut die österreichische Bevölkerung gegen HPV geimpft ist. Dabei wurde nicht nur eine Durchimpfungsrate für Gesamtösterreich berechnet, sondern es wurde auch spezifisch auf die Unterschiede in den Bundesländern und den Geschlechtern eingegangen. Die Ergebnisse sollen dazu dienen, etwaige Impflücken zu erkennen und zu evaluieren, wie sich die Erhöhung der Altersgrenze für das kostenfreie Impfprogramm auswirkt.
\nAls Datengrundlage dient dabei einerseits die Informationen zu den Impfungen des kostenfreien Impfprogramms und des E-Impfpasses (verfügbar seit 2020), die vom BMASGPK zur Verfügung gestellt werden, und andererseits die Verkaufszahlen von Merck Sharp & Dohme Ges.m.b.H (MSD). Alle Datenquellen wurden mittels eines Modells vereint um möglichst valide Durchimpfungsraten zu erhalten. Die Ergebnisse werden anschließend in einem Dashboard aufbereitet, welches von MSD öffentlich zur Verfügung gestellt wird und auf der Impfseite des BMASGPK verlinkt ist (impfen.gv.at).
\nDer vorliegende Bericht wurde durch Vertreter:innen des BMASGPK und von MSD geprüft und freigegeben.
\nDer vorliegende Bericht beschreibt das Modell, das verwendet wurde um die Datenquellen zu verarbeiten. Der Bericht beinhaltet eine Zusammenfassung der an dem Projekt beteiligten Partner und deren Rolle im Projekt, einen detaillierte Beschreibung aller verwendeten Daten, eine Dokumentation des Modells, eine Beschreibung des öffentlichen Cockpits, das die erhalten Durchimpfungsraten darstellt, und einen Ausblick wie die Daten aktuell upgedated werden.
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"orcid"}]}, "role": {"id": "researcher", "title": {"en": "Researcher"}}, "affiliations": [{"id": "04d836q62", "name": "TU Wien", "identifiers": [{"identifier": "04d836q62", "scheme": "ror"}, {"identifier": "grid.5329.d", "scheme": "grid"}, {"identifier": "0000 0004 1937 0669", "scheme": "isni"}]}]}, {"person_or_org": {"type": "personal", "name": "Bauer-Marschallinger, Bernhard", "given_name": "Bernhard", "family_name": "Bauer-Marschallinger", "identifiers": [{"identifier": "0000-0001-7356-7516", "scheme": "orcid"}]}, "role": {"id": "researcher", "title": {"en": "Researcher"}}, "affiliations": [{"name": "TU Wien"}]}, {"person_or_org": {"type": "personal", "name": "Vreugdenhil, Mariette", "given_name": "Mariette", "family_name": "Vreugdenhil", "identifiers": [{"identifier": "0000-0003-4913-0255", "scheme": "orcid"}]}, "role": {"id": "researcher", "title": {"en": "Researcher"}}, "affiliations": [{"id": "04d836q62", "name": "TU Wien", "identifiers": [{"identifier": "04d836q62", "scheme": "ror"}, {"identifier": "grid.5329.d", "scheme": "grid"}, {"identifier": "0000 0004 1937 0669", "scheme": "isni"}]}]}], "title": "Alpine Surface Soil Moisture from Sentinel-1 using 0th-Order Radiative Transfer", "publisher": "TU Wien", "publication_date": "2026-03-26", "subjects": [{"id": "http://www.oecd.org/science/inno/38235147.pdf?1.5", "subject": "Earth and related environmental sciences", "scheme": "FOS"}], "dates": [{"date": "2024-05", "type": {"id": "created", "title": {"en": "Created"}}}], "related_identifiers": [{"identifier": "10.1016/j.rse.2022.113025", "scheme": "doi", "relation_type": {"id": "isderivedfrom", "title": {"en": "Is derived from"}}, "resource_type": {"id": "publication-article", "title": {"de": "Zeitschriftenartikel", "en": "Journal Article"}}}, {"identifier": "10.1016/j.rse.2023.113651", "scheme": "doi", "relation_type": {"id": "isderivedfrom", "title": {"en": "Is derived from"}}, "resource_type": {"id": "publication-article", "title": {"de": 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Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited."}, "icon": "cc-by-icon", "props": {"url": "https://creativecommons.org/licenses/by/4.0/legalcode", "scheme": "spdx"}}], "description": "This dataset contains Sentinel-1 derived Surface Soil Moisture (SSM) estimates for the Alpine region, obtained using a 0th order Radiative Transfer Model (RT0). The RT0 approach, first introduced by Wagner et al. (2022) and building on the work of Quast et al. (2023), addresses the dynamic influence of vegetation on the backscatter signal by modeling the Vegetation Optical Depth (VOD) using a Leaf Area Index (LAI) climatology derived from the CLMS global LAI 300m 10-daily product (Verger et al., 2022) as a proxy, as well as frozen surface conditions by using ERA5-Land data (Munoz-Sabater et al., 2021). Open use is granted under the CC BY 4.0 license. Co-Funded by European Union and Austrian Research Promotion Agency. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.
\nSoil moisture is a critical variable for understanding hydrological processes, land-atmosphere interactions, and climate dynamics. Mountainous regions such as the Alps present unique challenges for soil moisture monitoring due to complex topography, varied land cover, and frequent snow/ice cover. This dataset applies the RT0 retrieval method to Sentinel-1 backscatter observations to derive relative surface soil moisture at 500 m spatial sampling over the Alpine region. The algorithm addresses environmental influences including vegetation dynamics, and frozen/snow-covered surfaces. A detailed description of the RT0 retrieval algorithm and its validation will be provided in a dedicated publication (Raml et al. preprint available soon).
\nThe retrieval algorithm applies a 0th order Radiative Transfer Model (RT0) to derive relative surface soil moisture from Sentinel-1 observations at 500 m resolution. Model parameters are calibrated using ERA5-Land volumetric soil moisture reference data (2016–2020), with frozen soil and snow-affected observations masked during calibration using snow-depth (sd) and soil-temperature level 1(stl1). To optimise soil moisture sensitivity in the complex Alpine terrain, the algorithm incorporates a novel SSM sensitivity map (Raml et. al. 2023) for static masking during resampling of original 20 m Sentinel-1 imagery to the 500 m, selecting only pixels where the SAR signal is most responsive to soil moisture dynamics. Relative SSM is then estimated by directly inverting the RT0 model. For a comprehensive methodological description, including model equations, parameter derivation, and validation results, readers are referred to the planned publication (Raml et al. preprint available soon).
\nThe SSM estimates are representative of the top soil layer (surface moisture) and are provided as relative values.
\nData Limitations: Due to the selection process and the coarse resolution of ERA5-Land used for masking during calibration, the dataset exhibits increased no-data areas in regions challenging for SSM retrieval, including:
\nThese limitations are particularly relevant for the Alpine region and will be addressed in future updates to the RT0 product.
\nThis data set is related to TrackDrone data set - Siegendorf 2024 (10.48436/yzk5x-49910).
\nHowever, it is an independent data set that improves the existing data set. The main improvement is the availability of synchronised image data from the image-assisted total stations (IATSs).
\nThe data set consists of measurements from two total stations and images acquired by those two total stations to a drone/UAS. The UAS itself was equipped with a GNSS antenna, a laser scanner, an IMU, a nadir-looking camera. and four photogrammetric targets to allow the estimation of the UAS orientation based on IATS. The layout is shown in the included image Siegendorf_2026_Layout.jpg. It is complemented by extensive reference data in the study area. The reference data consists of TLS data and about 100 Ground Control Points that can be used for bundle-block adjustment of the camera data.
\nThe specific sensors of this field study are:
\nThe data was acquired to study the full 6-DoF trajectory estimation of airborne platform with IATS. However, the data set can for example also be used for research towards mobile mapping, GNSS processing and decentralized multi-sensor systems using IATS.
\nThe data set consists of Raw Data (e.g. RiNEX files, ASCII observations from the IATS, and images), Processed Data (Cartesian measurements from GNSS and IATS as well as extracted target observations by the IATS), and Reference Data (TLS, Ground Control Points, Coordinates of Fixed Points). The file crs_definitions provides the information to transform into global coordinate system as well as the definitions of the body frame to sensor frame transformation. The Raw Data containts *.rdbx files, the can be read using the RDBLib, but all basic information is also in the .las files.
\nThis dataset was created within a research project on the preparedness for future pandemic crises (see funding information). It is intended to support the reproducibility of scientific results and to enable further research based on the published data.
\nThe dataset was generated using an agent-based simulation model combined with additional outcomes research data on the psychosocial well-being of school children during school closures. It contains simulation results for different school closure scenarios during the COVID-19 pandemic in Austria, each representing a specific intervention configuration and linked to either the 2020 or 2021 time period during the pandemic.
\nThe repository consists of three main files. scenarios.csv provides an overview of all simulation scenarios. description.pdf documents the structure and content of the simulation output files. data.zip contains the simulation output as CSV files, organized in subfolders corresponding to the scenarios listed in scenarios.csv.
The dataset is described in detail in “Balancing epidemic containment and psychosocial effects: integrated outcomes research and simulation reveals the harm-benefit landscape of school closures” (to be submitted for publication). Technical information on the underlying simulation model is provided in Model Documentation.
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"role": {"id": "supervisor", "title": {"en": "Supervisor"}}, "affiliations": [{"id": "03prydq77", "name": "University of Vienna", "identifiers": [{"identifier": "03prydq77", "scheme": "ror"}, {"identifier": "grid.10420.37", "scheme": "grid"}, {"identifier": "0000 0001 2286 1424", "scheme": "isni"}]}]}, {"person_or_org": {"type": "personal", "name": "Valtiner, Markus", "given_name": "Markus", "family_name": "Valtiner", "identifiers": [{"identifier": "0000-0001-5410-1067", "scheme": "orcid"}]}, "role": {"id": "projectleader", "title": {"en": "Project leader"}}, "affiliations": [{"name": "TU Wien"}]}], "title": "Entropic\u2013Dielectric Interplay Governs Ion Adsorption in Inner Electric Double Layers", "publisher": "TU Wien", "publication_date": "2026-03-20", "subjects": [{"id": "http://www.oecd.org/science/inno/38235147.pdf?1.4", "subject": "Chemical sciences", "scheme": "FOS"}, {"id": "http://www.oecd.org/science/inno/38235147.pdf?1.3", "subject": "Physical sciences", "scheme": "FOS"}], "dates": [{"date": "2026-03-20", "type": {"id": "accepted", "title": {"en": "Accepted"}}}], "languages": [{"id": "eng", "title": {"en": "English"}}], "rights": [{"id": "cc-by-4.0", "title": {"en": "Creative Commons Attribution 4.0 International"}, "description": {"en": "The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited."}, "icon": "cc-by-icon", "props": {"url": "https://creativecommons.org/licenses/by/4.0/legalcode", "scheme": "spdx"}}], "description": "Context and methodology
\nThe material contained in this dataset exclusively relates to the data presented and generated for publication in Science Advances with the title \"Entropic–Dielectric Interplay Governs Ion Adsorption in Inner Electric Double Layers\". Please refer to the journal's website for further details (DOI: doi of the article).
\nThe research presented in this article addresses molecular-level characterisation of charged solid-liquid interfaces with a combination of experimental (AFM, SFG, SFA) and theroetical (MD, DFT) methods.
\nTechnical details
\nThe current data repository collects data from each of the above mentioneds, as indicated by the names of the folders. Furthermore, each folder contains a \"README\" file which further provides details on data files, data type and compatibility, directory architecture. Email addresses of the data curators are also indicated in the \"README\" files.
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{"identifier": "10.48436/c4nk9-m2n74", "provider": "datacite", "client": "datacite"}, "oai": {"identifier": "oai:researchdata.tuwien.ac.at:c4nk9-m2n74", "provider": "oai"}}, "metadata": {"resource_type": {"id": "dataset", "title": {"de": "Datensatz", "en": "Dataset"}}, "creators": [{"person_or_org": {"type": "personal", "name": "Giannandrea, Daniele", "given_name": "Daniele", "family_name": "Giannandrea", "identifiers": [{"identifier": "0009-0009-4234-1974", "scheme": "orcid"}]}, "role": {"id": "contactperson", "title": {"en": "Contact person"}}, "affiliations": [{"id": "04d836q62", "name": "TU Wien", "identifiers": [{"identifier": "04d836q62", "scheme": "ror"}, {"identifier": "grid.5329.d", "scheme": "grid"}, {"identifier": "0000 0004 1937 0669", "scheme": "isni"}]}, {"name": "dwh GmbH"}]}], "title": "Austrian Synthetic Population Coordinates by GEPOC ABM", "publisher": "TU Wien", "publication_date": "2026-04-02", "contributors": [{"person_or_org": {"type": "personal", "name": 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\nThe datasets were created in the context of the spatial parametrization of the agent-based population model GEPOC ABM. The sampling of coordinates is done in two stages:
\nThis dataset is part of the digital documentation of the Tomb of Meret Neith, Umm el Qaab, Abydos, Egypt about 3000BC, its artefacts, and the reconstruction of the tomb. For an overview of the related work, please visit https://researchdata.tuwien.at/communities/meretneith/.
\nContains photographic documentation of evidences found supporting the reconstruction.
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