Find research datasets worth reusing

mDRONES4rivers-project: UAV-imagery of the project area Niederwerth at the Rhine River, Germany

Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project &bdquo;Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices.  Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘.  In this dataset, the following UAS data and metadata of the project site ‘Niederwerth’ (center coordinates [WGS84]: 50.386326°N, 7.613847°E; area: 27 ha) at the Rhine River in Germany is available for download: •             Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW) •             RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO) •             Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation : PH_DEM) •             associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model) The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NW_2019_01_Winter.zip = projectname_projectsite_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are additionally provided:  •             Overview table and metadata of the above-mentioned data (xlsx) •             Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models) Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.

mDRONES4rivers-project: UAV-imagery of the project area Kuehkopf Knoblochsaue at the Rhine River, Germany

Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project &bdquo;Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices.  Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘.  In this dataset, the following UAS data and metadata of the project site ‘Kuehkopf Knoblochsaue’ (center coordinates [WGS84]: 49.830564°N, 8.383341°E; area: 48 ha) at the Rhine River in Germany is available for download: •             Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW) •             RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO) •             Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation : PH_DEM) •             associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model) The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NW_2019_01_Winter.zip = projectname_projectsite_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder:  •             Overview table and metadata of the above-mentioned data (xlsx) •             Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models) Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.

mDRONES4rivers-project: UAV-imagery of the project area Laubenheim at the Rhine River, Germany

Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project &bdquo;Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices.  Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘.  In this dataset, the following UAS data and metadata of the project site ‘Laubenheim’ (center coordinates [WGS84]: 49.960007°N, 8.331229°E; area: 11 ha) at the Rhine River in Germany is available for download: •             Multispectral orthophotos (GeoTiff; 6 bands: B, G, R, Red-Edge, NIR, Flag; camera: Micasense; resolution: 25 cm; abbreviation: MS_RAW) •             RGB-orthophotos (GeoTiff; 3 bands: R, G, B; camera: Phantom; resolution: 25 cm; abbreviation: PH_ORTHO) •             Digital Surface Models (GeoTiff; 1 band; camera: Phantom; resolution: ca. 5 cm; abbreviation: PH_DEM) •             associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface model) The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NW_UAV_2019_01_Winter.zip = projectname_projectsite_platform_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder:  •             Overview table and metadata of the above-mentioned data (xlsx) •             Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos, 1x for RGB-orthophotos + digital surface models) Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.

mDRONES4rivers-project: Gyrocopter-imagery of the project area Emmericher Ward at the Rhine River, Germany

Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project &bdquo;Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices.  Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘.  In this dataset, the following UAS data and metadata of the project site ‘Emmericher Ward’ (center coordinates [WGS84]: 50.385264°N, 6.198692°E; area: 900 ha) at the Rhine River in Germany is available for download: •             Multispectral orthophotos (GeoTiff; 5 bands: B, G, R, NIR, Flag; camera system: PanX 2.0 and PanX 3.0; resolution: ca. 30 cm/ca. 16 cm; abbreviation: PanX2_ORTHO/PanX3_ORTHO) •             Digital Surface Models (GeoTiff; 1 band; camera system: PanX 2.0 and PanX 3.0; resolution: ca. 30 cm; abbreviation: PanX_DEM) •             associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos + digital surface model) The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NW_GYRO_2019_01_Winter.zip = projectname_projectsite_platform_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder:  •             Overview table and metadata of the above-mentioned data (xlsx) •             Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos + digital surface models) Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.

mDRONES4rivers-project: Gyrocopter-imagery of the project area Nonnenwerth at the Rhine River, Germany

Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project &bdquo;Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices.  Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘.  In this dataset, the following UAS data and metadata of the project site ‘Nonnenwerth’ (center coordinates [WGS84]: 50.637541°N, 7.208834°E; area: 45 ha) at the Rhine River in Germany is available for download: •             Multispectral orthophotos (GeoTiff; 5 bands: B, G, R, NIR, Flag; camera system: PanX 2.0 and PanX 3.0; resolution: ca. 30 cm/ca. 16 cm; abbreviation: PanX2_ORTHO/PanX3_ORTHO) •             Digital Surface Models (GeoTiff; 1 band; camera system: PanX 2.0 and PanX 3.0; resolution: ca. 30 cm; abbreviation: PanX_DEM) •             associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos + digital surface model) The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NW_GYRO_2019_01_Winter.zip = projectname_projectsite_platform_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder:  •             Overview table and metadata of the above-mentioned data (xlsx) •             Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos + digital surface models) Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.

mDRONES4rivers-project: Gyrocopter-imagery of the project area Niederwerth at the Rhine River, Germany

Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project &bdquo;Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices.  Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘.  In this dataset, the following UAS data and metadata of the project site ‘Niederwerth’ (center coordinates [WGS84]: 50.386326°N, 7.613847°E; area: 25 ha) at the Rhine River in Germany is available for download: •               Multispectral orthophotos (GeoTiff; 5 bands: B, G, R, NIR, Flag; camera system: PanX 2.0 and PanX 3.0; resolution: ca. 30 cm/ca. 16 cm; abbreviation: PanX2_ORTHO/PanX3_ORTHO) •             Digital Surface Models (GeoTiff; 1 band; camera system: PanX 2.0 and PanX 3.0; resolution: ca. 30 cm; abbreviation: PanX_DEM) •             associated Technical Reports (PDF; technical metadata concerning data acquisition, and processing using Agisoft Metashape, 1x for multispectral orthophotos + digital surface model) The above-mentioned files are provided for download as dataset stored in one directory per season depending on the date of data acquisition (e.g. mDRONES4rivers_NoW_GYRO_2019_01_Winter.zip = projectname_projectsite_platform_year_no.season_name.season). To provide an overview of all files and general background information plus data preview the following files are stored in the info.zip folder:  •             Overview table and metadata of the above-mentioned data (xlsx) •             Summary (PDF, Detailed description of sensors and data acquisition procedure, 1x for multispectral orthophotos + digital surface models) Note: the data was processed with focus on spectral information and not for geodetic purposes. Georeferencing accuracy has not been checked in detail.

mDRONES4rivers-project: Portfolios of classification results, UAV and gyrocopter data of project sites situated in riparian zones along federal waterways in Germany with focus on the Rhine River, Germany

Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project &bdquo;Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices.  Within the project period (2019-2022) data was collected at different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘.  In this dataset, the following portfolios of classifications, UAS and gyrocopter data of project sites situated in riparian zones along federal waterways in Germany with focus on the Rhine River are available for download: •             Multispectral orthophotos produced with the aid of UAS (PDF, Detailed description of sensors and data acquisition procedure; abbreviation: MS_ORTHO) •             RGB-orthophotos and digital surface models produced with the aid of UAS (PDF, Detailed description of sensors and data acquisition procedure; abbreviation: PH_SR_ORTHO_DSM) •             Multispectral orthophotos and Digital Surface Models produced with the aid of a gyrocopter (PDF, Detailed description of sensors and data acquisition procedure; abbreviation: PANX_ORTHO_DSM) •             Classification results based on UAV- and a gyrocopter data (PDF, Detailed description of processing procedure for different classification levels; abbreviation: CLASSIF_PROD) •             German translated version of all above mentioned product portfolios (PDF, abbreviation: product_portfolio_collection_ger)

mDRONES4rivers-project: Classification results based on UAV data of project sites situated in riparian zones along federal waterways in Germany with focus on the Rhine River, Germany

Spatially and temporally high-resolution data was acquired with the aid of multispectral sensors mounted on UAV and a gyrocopter platform for the purpose of classification. The work was part of the research and development project &bdquo;Modern sensors and airborne remote sensing for the mapping of vegetation and hydromorphology along Federal waterways in Germany“ (mDRONES4rivers) in cooperation of the German Federal Institute of Hydrology (BfG), Geocoptix GmbH, Hochschule Koblenz und JB Hyperspectral Devices.  Within the project period (2019-2022) an object oriented image classification was conducted based on UAV and gyrocopter data for different sites situated in Germany along the Rivers Rhine and Oder. All published data produced within the project can be found by searching for the keyword ‘mDRONES4rivers‘.  In this dataset, the following classification results and metadata of the project sites situated in riparian zones along federal waterways in Germany with focus on the Rhine River, Germany is available for download: •             Basic & Vegetation Classification (ESRI Shapefile; abbreviation: lvl2_vegetation_units) •             Classification of dominant stands (ESRI Shapefile; abbreviation: lvl4_dominant_stands ) •             Classification of substrat types (ESRI Shapefile; abbreviation: lvl4_substrate_types) •             associated reports (PDF; statistical and additional information on the classifiaction results and workflow) The above-mentioned files are provided for download as dataset stored in one directory per projekt site and season (e.g. mDRONES4rivers_Niederwerth_2019_03_Summer_Classification.zip = projectname_projectsite_year_no.season_name.season_product). To provide an overview of all files and general background information plus data preview the following files are additionally provided:  •             Portfolios (PDF, Detailed description of classification products and classification workflow, 1x for basic surface types, 1x for classification of vegetation units, 1x for classification of dominant stands,  1x for classification of substrate types) •            Color Coding table for the visualization of the classifiaction units (.xlsx)

opencc-by-4.0Aug 2021View details →

IPCC AR6 Relative Sea Level Projection P-Boxes

Description This data set contains detailed elements of the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections for all of the p-boxes described in AR6 WG1 9.6.3 (under ar6-regional-pboxes.zip), as well as a variant excluding the AR6 estimates of background sea level change (under ar6-regional_novlm-pboxes.zip). Most users will not want this dataset, but rather the dataset at https://doi.org/10.5281/zenodo.5914709. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. Required Acknowledgements and Citation In order to document the impact of these sea-level rise projections, users of the projections are obligated to cite chapter 9 of Working Group 1 contribution to the the IPCC Sixth Assessment Report, the Framework for Assessment of Changes To Sea-level (FACTS) model description paper, and the version of the data set used: <ul> <li>Fox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1211–1362, <a href="https://doi.org/10.1017/9781009157896.011" rel="nofollow">doi:10.1017/9781009157896.011</a>.</li> <li>Kopp, R. E., Garner, G. G., Hermans, T. H. J., Jha, S., Kumar, P., Reedy, A., Slangen, A. B. A., Turilli, M., Edwards, T. L., Gregory, J. M., Koubbe, G., Levermann, A., Merzky, A., Nowicki, S., Palmer, M. D., & Smith, C. (2023). The Framework for Assessing Changes To Sea-Level (FACTS) v1.0: A platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. Geoscientific Model Development, 16, 7461–7489. <a href="https://doi.org/10.5194/gmd-16-7461-2023" rel="nofollow">https://doi.org/10.5194/gmd-16-7461-2023</a></li> <li>Garner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Sea Level Projections. Version 20210809. Dataset accessed [YYYY-MM-DD] at <a href="https://doi.org/10.5281/zenodo.5914709" rel="nofollow">https://doi.org/10.5281/zenodo.5914709</a>.</li> </ul> Please also include in the acknowledgements of works citing these projections: <blockquote> We thank the projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea-Level Change Team for developing and hosting the IPCC AR6 Sea-Level Projection Tool. </blockquote> IPCC AR6 Licensing The IPCC AR6 Sea-Level Rise Projections are licensed by the authors under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.

Requirements (enhancements) of 64 Mozilla projects mined from Bugzilla

The dataset consists of 4200 enhancements that are in some form of dependency with the others (such as blocks, depends_on etc.)  This data spans from 08/05/2001 to 09/08/2019. This dataset is gathered using Bugzilla's REST API for 64 projects. We have id, summary, priority, severity, type, version, target_milesotne, product, depends_on, blocks fields information for each one of these enhancements.

opencc-by-4.0Aug 2021View details →

IPCC AR6 Relative Sea Level Projection Distributions

Description This data set contains detailed elements the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projection distributions for all the workflows described in AR6 WG1 9.6.3.2, as well as distributions for the components contributing to relative sea level change. Most users will not want this dataset, but rather the dataset at https://doi.org/10.5281/zenodo.5914709. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. Required Acknowledgements and Citation In order to document the impact of these sea-level rise projections, users of the projections are obligated to cite chapter 9 of Working Group 1 contribution to the the IPCC Sixth Assessment Report, the Framework for Assessment of Changes To Sea-level (FACTS) model description paper, and the version of the data set used: <ul> <li>Fox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1211–1362, <a href="https://doi.org/10.1017/9781009157896.011" rel="nofollow">doi:10.1017/9781009157896.011</a>.</li> <li>Kopp, R. E., Garner, G. G., Hermans, T. H. J., Jha, S., Kumar, P., Reedy, A., Slangen, A. B. A., Turilli, M., Edwards, T. L., Gregory, J. M., Koubbe, G., Levermann, A., Merzky, A., Nowicki, S., Palmer, M. D., & Smith, C. (2023). The Framework for Assessing Changes To Sea-Level (FACTS) v1.0: A platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. Geoscientific Model Development, 16, 7461–7489. <a href="https://doi.org/10.5194/gmd-16-7461-2023" rel="nofollow">https://doi.org/10.5194/gmd-16-7461-2023</a></li> <li>Garner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Sea Level Projections. Version 20210809. Dataset accessed [YYYY-MM-DD] at <a href="https://doi.org/10.5281/zenodo.5914709" rel="nofollow">https://doi.org/10.5281/zenodo.5914709</a>.</li> </ul> Please also include in the acknowledgements of works citing these projections: <blockquote> We thank the projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea-Level Change Team for developing and hosting the IPCC AR6 Sea-Level Projection Tool. </blockquote> IPCC AR6 Licensing The IPCC AR6 Sea-Level Rise Projections are licensed by the authors under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.

The Transient UV Objects Project

Poster and lightning talk for 'Exploring the Transient Universe with the Nancy Grace Roman Space Telescope': The Transient UV Objects Project, David Modiano. Note: apologies for the incorrect date in the first slide of the presentation!  Abstract: Despite the prevalence of transient-searching facilities operating across most wavelengths, the ultraviolet (UV) transient sky remains to be systematically studied. Therefore, we have recently initiated the Transient Ultraviolet Objects (TUVO) project, with which we search for serendipitous UV transients in data obtained using currently available UV instruments with a strong focus on the UV/Optical (UVOT) telescope aboard the Neil Gehrels Swift Observatory. We constructed a pipeline (named TUVOpipe) in order to find such transients in the UVOT data, using difference image analysis. The pipeline is run daily on all new public UVOT data (which are available 6-8 hours after the observations are performed), so we discover transients in near real-time. Using TUVOpipe we have processed 111 330 individual UVOT images and we currently detect an average rate of &sim;100 transient candidates per day. Of these daily candidates, on average &sim;30% are real transients (separated by human vetting from the remaining ‘bogus’ transients which were not discarded automatically within the pipeline). Most of the real transients correspond to known variable stars, though we also detect a significant number of known active galactic nuclei and accreting white dwarfs. Some of the transients we find represent previously unreported new transients, or undiscovered outbursts of previously known transients, predominantly outbursts from cataclysmic variables. Here we describe TUVOpipe and some of the initial results we have so far obtained.

Viroplant Project - Microcosm studies on the effect of bacteriophages used as plant protection products on soil microbial communities

This file contains the description, data and DNA analyses on the effect of bacteriophages with a potential to be used as plant protecction products on the structure and function of soil microbial communities. The objective was to evaluate two different microcsom incubation systems with phages and microbial cells from soil, or soil itself and to analyses in a time dependent manner how the phages affect the natural soil microbiomes. The microbial communities were quantified with qPCR and their diversity analyzed with PCR amplified 16S rRNA gene sequences. Bioinformatic analyses were used to evaluate microbial community responses

opencc-by-4.0Aug 2021View details →

IPCC AR6 Relative Sea Level Projections without Background Component

Description This data set contains detailed elements the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections that exclude the background term (representing primarily land subsidence or uplift). It includes probability distributions for all the workflows described in AR6 WG1 9.6.3.2, as well as p-boxes derived from these distributions. Most users will not want this dataset, but rather the dataset at https://doi.org/10.5281/zenodo.5914709. These data may be of use for users who want to substitute their own estimates of the background term. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. Required Acknowledgements and Citation In order to document the impact of these sea-level rise projections, users of the projections are obligated to cite chapter 9 of Working Group 1 contribution to the the IPCC Sixth Assessment Report, the Framework for Assessment of Changes To Sea-level (FACTS) model description paper, and the version of the data set used: <ul> <li>Fox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1211–1362, <a href="https://doi.org/10.1017/9781009157896.011" rel="nofollow">doi:10.1017/9781009157896.011</a>.</li> <li>Kopp, R. E., Garner, G. G., Hermans, T. H. J., Jha, S., Kumar, P., Reedy, A., Slangen, A. B. A., Turilli, M., Edwards, T. L., Gregory, J. M., Koubbe, G., Levermann, A., Merzky, A., Nowicki, S., Palmer, M. D., & Smith, C. (2023). The Framework for Assessing Changes To Sea-Level (FACTS) v1.0: A platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. Geoscientific Model Development, 16, 7461–7489. <a href="https://doi.org/10.5194/gmd-16-7461-2023" rel="nofollow">https://doi.org/10.5194/gmd-16-7461-2023</a></li> <li>Garner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Sea Level Projections. Version 20210809. Dataset accessed [YYYY-MM-DD] at <a href="https://doi.org/10.5281/zenodo.5914709" rel="nofollow">https://doi.org/10.5281/zenodo.5914709</a>.</li> </ul> Please also include in the acknowledgements of works citing these projections: <blockquote> We thank the projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea-Level Change Team for developing and hosting the IPCC AR6 Sea-Level Projection Tool. </blockquote> IPCC AR6 Licensing The IPCC AR6 Sea-Level Rise Projections are licensed by the authors under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.

Dataset created in the context of the project "Stable methodologies to evaluate and measure quality, interoperability, blockchain and reuse of open data in the agricultural field"

The project "Stable methodologies to evaluate and measure quality, interoperability, blockchain and reuse of open data in the agricultural field", whose website is https://datause.es/, is a project funded by the Ministry of Science and Innovation - State Research Agency, with reference PID2019-105708RB-C22. Within the framework of the project, a bibliographic search is carried out in all thematic categories of the Web of Science (WoS) related to agriculture and related areas. The search equation included the following categories: WC = (FOOD SCIENCE TECHNOLOGY OR PLANT SCIENCES OR FORESTRY OR AGRICULTURAL ENGINEERING OR AGRONOMY OR HORTICULTURE OR AGRICULTURE DAIRY ANIMAL SCIENCE OR AGRICULTURE MULTIDISCIPLINARY OR AGRICULTURAL ECONOMICS POLICY)  This data set shows the distribution of journals and the quartile they occupy in each of the thematic categories in 2019, with the aim of serving researchers in this area and for future data mining.

opencc-by-4.0Apr 2021View details →

Supplementary data to The vegetation of Chile and the EcoVeg approach in the context of the International Vegetation Classification project

The rar file contains a map of Macrogroups of Chile in ESRI shapefile format. Macrogroups are hierarchically included in the categories of division and formation of IVC classification. These categories can also be displayed using the table associated with the shapefile. Likewise, Chilean zonal vegetation units of Luebert & Pliscoff (2017) are included, so the crosswalk for generating the map of Macrogroups based on the Chilean zonal vegetation units is fully documented.

CoCryM project - Datasets - 01

Source datasets for CoCryM project, more info on: https://sites.google.com/view/makhansary/publications

CoCryM project - Datasets - 04

Source datasets for CoCryM project, more info on: https://sites.google.com/view/makhansary/publications

CoCryM project - Datasets - 02

Source datasets for CoCryM project, more info on: https://sites.google.com/view/makhansary/publications

CoCryM project - Datasets - 03

Source datasets for CoCryM project, more info on: https://sites.google.com/view/makhansary/publications