Nanopublications LDF server

Matches in Nanopublications for { ?s <http://schema.org/description> ?o ?g. }

• IMD_temperature-rolling-mean.ipynb description "This jupyter notebook uses a rolling mean to show the trend in maximum temperature timeseries from the India Meteorological Department." assertion.
• IMD_temperature-rolling-mean.ipynb description "This jupyter notebook uses a rolling mean to show the trend in maximum temperature timeseries from the India Meteorological Department." assertion.
• Rainfall.ipynb description "This jupyter notebook shows how to read and analyze Rainfall timeseries from the India Meteorological Department." assertion.
• Rainfall.ipynb description "This jupyter notebook shows how to read and analyze Rainfall timeseries from the India Meteorological Department." assertion.
• Tmax.ipynb description "This jupyter notebook shows how to read and analyze maximum temperature timeseries from the India Meteorological Department." assertion.
• Tmax.ipynb description "This jupyter notebook shows how to read and analyze maximum temperature timeseries from the India Meteorological Department." assertion.
• Tmin.ipynb description "This jupyter notebook shows how to read and analyze minimum timeseries from the India Meteorological Department." assertion.
• Tmin.ipynb description "This jupyter notebook shows how to read and analyze minimum timeseries from the India Meteorological Department." assertion.
• Copernicus-Land-analysis.ipynb description "Demonstrate the usage of Copernicus Land NDVI product to assess the changes in the presence of live green vegetation over the region of Mumbai. Methodology approach - Use NDVI data from the Copernicus Global Land Service portal (https://land.copernicus.vgt.vito.be/PDF/portal/Application.html) - Visualize NDVI monthly statistics (long term statistics between 1999 - 2019 and short term statistics 2015-2019 Select a single point and compare NDVI from 2021 with NDVI long term statistics" assertion.
• Copernicus-Land-analysis.ipynb description "Demonstrate the usage of Copernicus Land NDVI product to assess the changes in the presence of live green vegetation over the region of Mumbai. Methodology approach - Use NDVI data from the Copernicus Global Land Service portal (https://land.copernicus.vgt.vito.be/PDF/portal/Application.html) - Visualize NDVI monthly statistics (long term statistics between 1999 - 2019 and short term statistics 2015-2019 Select a single point and compare NDVI from 2021 with NDVI long term statistics" assertion.
• 6942229f-fba8-415d-a326-0ae5fd6360da description "The project aims at establishing the trends of temperature , precipitation and air currents over the city of Mumbai. This will lead to establishment of concrete analysis of Climate Change on a 'local' basis and would help establish a suitable action plan." assertion.
• 6942229f-fba8-415d-a326-0ae5fd6360da description "The project aims at establishing the trends of temperature , precipitation and air currents over the city of Mumbai. This will lead to establishment of concrete analysis of Climate Change on a 'local' basis and would help establish a suitable action plan." assertion.
• cesm-b1850-f19g17 description "This Galaxy history contains all the inputs and generated outputs for this CESM example. If you have an account on Galaxy Europe (if not you can open one), you can import this history and reuse it." assertion.
• cesm-b1850-f19g17 description "This Galaxy history contains all the inputs and generated outputs for this CESM example. If you have an account on Galaxy Europe (if not you can open one), you can import this history and reuse it." assertion.
• display?to_ext=data&hdca_id=8ca88ef64f587a1e&element_identifier=plot description "Plot showing the reference height temperature (Kelvin) for 0001-02-01 00:00:00" assertion.
• display?to_ext=data&hdca_id=8ca88ef64f587a1e&element_identifier=plot description "Plot showing the reference height temperature (Kelvin) for 0001-02-01 00:00:00" assertion.
• display?to_ext=tar description "Tar file containing all the input datasets for running the Community Earth System Modelling in fully coupled mode B1850 f17_g19." assertion.
• display?to_ext=tar description "Tar file containing all the input datasets for running the Community Earth System Modelling in fully coupled mode B1850 f17_g19." assertion.
• display?to_ext=data&hdca_id=bb750a5908336204&element_identifier=atm_log.txt description "Collection containing the logfile for the atmosphere compoment." assertion.
• display?to_ext=data&hdca_id=bb750a5908336204&element_identifier=atm_log.txt description "Collection containing the logfile for the atmosphere compoment." assertion.
• display?to_ext=txt description "Customized user namelist for CAM restart (atmosphere component) to create history files and restart files at the end of the run." assertion.
• display?to_ext=txt description "Customized user namelist for CAM restart (atmosphere component) to create history files and restart files at the end of the run." assertion.
• display?to_ext=netcdf description "History file (1 month) for the atmosphere component (CAM)." assertion.
• display?to_ext=netcdf description "History file (1 month) for the atmosphere component (CAM)." assertion.
• repository?repository_id=7aa3cab2c60dddc0&changeset_revision=7a7ba86e95a4 description "Link to the Galaxy Tool shed for CESM Galaxy Tool repository. This repository is useful whenever you want to install CESM Galaxy Tool in your own Galaxy instance. The version used in this example is revision: 7a7ba86e95a4" assertion.
• repository?repository_id=7aa3cab2c60dddc0&changeset_revision=7a7ba86e95a4 description "Link to the Galaxy Tool shed for CESM Galaxy Tool repository. This repository is useful whenever you want to install CESM Galaxy Tool in your own Galaxy instance. The version used in this example is revision: 7a7ba86e95a4" assertion.
• diagram?version=1 description "Abstract CWL Automatically generated from the Galaxy workflow file: Workflow constructed from history CESM B1850 f19_g17" assertion.
• diagram?version=1 description "Abstract CWL Automatically generated from the Galaxy workflow file: Workflow constructed from history CESM B1850 f19_g17" assertion.
• www.cesm.ucar.edu description "General webpage where the documentation for the Community Earth System Model is available." assertion.
• www.cesm.ucar.edu description "General webpage where the documentation for the Community Earth System Model is available." assertion.
• CESM description "This github repository contains all the versions of the Community Earth System Model (CESM)." assertion.
• CESM description "This github repository contains all the versions of the Community Earth System Model (CESM)." assertion.
• 364 description "This is a link to Workflow Research Object stored in workflowhub.eu. It contains a Galaxy workflow (.ga), abstract CWL (.cwl) and diagram (.png)." assertion.
• 364 description "This is a link to Workflow Research Object stored in workflowhub.eu. It contains a Galaxy workflow (.ga), abstract CWL (.cwl) and diagram (.png)." assertion.
• f99a5c78-6e3d-44a6-a283-3a61e46e249b description "This Research Object aggregates all the resources needed for running a fully coupled CESM B1850 f19_g17 on Galaxy using the CESM Galaxy Tool. i) Examples of input datasets needed for running CESM B1850 f17_g19 on Galaxy; ii) Galaxy Workflow (.ga) and corresponding CWL abstract and diagram; iii) Link to a published Galaxy history." assertion.
• f99a5c78-6e3d-44a6-a283-3a61e46e249b description "This Research Object aggregates all the resources needed for running a fully coupled CESM B1850 f19_g17 on Galaxy using the CESM Galaxy Tool. i) Examples of input datasets needed for running CESM B1850 f17_g19 on Galaxy; ii) Galaxy Workflow (.ga) and corresponding CWL abstract and diagram; iii) Link to a published Galaxy history." assertion.
• 478eb171-62b1-4ca8-9b62-e8528a838e05 description "Folder containing all the logfiles." assertion.
• 478eb171-62b1-4ca8-9b62-e8528a838e05 description "Folder containing all the logfiles." assertion.
• 409b98bf-c76d-4d96-a814-1cbc0a3171e3 description "CAMS European air quality forecasts: NO2 - time range: 2022-05-29T23:00:00Z/2018-07-12T00:00:00Z - min/max Value: 0/0 - DataType: Float32 - Resolution: 0 -" assertion.
• 409b98bf-c76d-4d96-a814-1cbc0a3171e3 description "CAMS European air quality forecasts: NO2 - time range: 2022-05-29T23:00:00Z/2018-07-12T00:00:00Z - min/max Value: 0/0 - DataType: Float32 - Resolution: 0 -" assertion.
• cab8eaeb-e22d-4fc7-9999-180d0e179a98 description "CAMS European air quality forecasts: NO2 - time range: 2022-05-29T23:00:00Z/2018-07-12T00:00:00Z - min/max Value: 0/0 - DataType: Float32 - Resolution: 0 -" assertion.
• cab8eaeb-e22d-4fc7-9999-180d0e179a98 description "CAMS European air quality forecasts: NO2 - time range: 2022-05-29T23:00:00Z/2018-07-12T00:00:00Z - min/max Value: 0/0 - DataType: Float32 - Resolution: 0 -" assertion.
• pangeo_CMIP6_masked_and_weighted_average description "This is the rendered Jupyter notebook" assertion.
• pangeo_CMIP6_masked_and_weighted_average description "This is the rendered Jupyter notebook" assertion.
• 03dc6999-4799-4739-b184-0a9d11c50aa4 description "This jupyter notebook demonstrates the usage of masks and shows how to compute a weighted average with Pangeo CMIP6 data" assertion.
• 03dc6999-4799-4739-b184-0a9d11c50aa4 description "This jupyter notebook demonstrates the usage of masks and shows how to compute a weighted average with Pangeo CMIP6 data" assertion.
• 515d1476-eba5-4698-907d-9bc6edc191b2 description "Plot of the global weighted average and unweighted average." assertion.
• 515d1476-eba5-4698-907d-9bc6edc191b2 description "Plot of the global weighted average and unweighted average." assertion.
• masked_and_weighted_average.ipynb description "upyter notebook demonstrating the usage of masks and computing weighted average with Pangeo CMIP6 data." assertion.
• masked_and_weighted_average.ipynb description "upyter notebook demonstrating the usage of masks and computing weighted average with Pangeo CMIP6 data." assertion.
• CAMS-PM2_5-fc-20211224.png description "Jupyter Notebook showing Copernicus Monitoring Service PM2.5 forecasts 24th December 2021 at 12:00 UTC." assertion.
• CAMS-PM2_5-fc-20211224.png description "Jupyter Notebook showing Copernicus Monitoring Service PM2.5 forecasts 24th December 2021 at 12:00 UTC." assertion.
• c3aa751b-c32d-48d2-b781-0ab44bedc252 description "This [tutorial](https://training.galaxyproject.org/training-material/topics/climate/tutorials/pangeo-notebook/tutorial.html) is from the Galaxy Training Network. In this tutorial, we will learn about Xarray, one of the most used Python library from the Pangeo ecosystem. We will be using data from Copernicus Atmosphere Monitoring Service and more precisely PM2.5 (Particle Matter < 2.5 μm) 4 days forecast from December, 22 2021. Parallel data analysis with Pangeo is not covered in this tutorial." assertion.
• c3aa751b-c32d-48d2-b781-0ab44bedc252 description "This [tutorial](https://training.galaxyproject.org/training-material/topics/climate/tutorials/pangeo-notebook/tutorial.html) is from the Galaxy Training Network. In this tutorial, we will learn about Xarray, one of the most used Python library from the Pangeo ecosystem. We will be using data from Copernicus Atmosphere Monitoring Service and more precisely PM2.5 (Particle Matter < 2.5 μm) 4 days forecast from December, 22 2021. Parallel data analysis with Pangeo is not covered in this tutorial." assertion.
• climate-pangeo-notebook.ipynb description "In this tutorial, we will learn about Xarray, one of the most used Python library from the Pangeo ecosystem" assertion.
• climate-pangeo-notebook.ipynb description "In this tutorial, we will learn about Xarray, one of the most used Python library from the Pangeo ecosystem" assertion.
• 192c3541-b61d-4e21-80d5-691d667b44cb description "This Research Object demonstrates how to use CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services and compute monthly map of NO2 over a given geographical area, here Spain" assertion.
• 192c3541-b61d-4e21-80d5-691d667b44cb description "This Research Object demonstrates how to use CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services and compute monthly map of NO2 over a given geographical area, here Spain" assertion.
• 0ba03959-692a-42fc-a073-cb2d5e21328e description "Conda environment used on EGI notebook on 27/05/2022" assertion.
• 0ba03959-692a-42fc-a073-cb2d5e21328e description "Conda environment used on EGI notebook on 27/05/2022" assertion.
• 11d2f3de-d2f1-4584-a0fb-a2b4cd3d1ae7 description "Conda environment generated with conda-lock for linux-64" assertion.
• 11d2f3de-d2f1-4584-a0fb-a2b4cd3d1ae7 description "Conda environment generated with conda-lock for linux-64" assertion.
• 142a28a6-8f93-4307-a216-9e31b413598b description "Conda environment generated with conda-lock for osx-64" assertion.
• 142a28a6-8f93-4307-a216-9e31b413598b description "Conda environment generated with conda-lock for osx-64" assertion.
• 1f385594-7bdd-4b98-88bf-4469e7584f90 description "Monthly average maps of CAMS Nitrogen Dioxide [µg m-3] over Spain in 2019, 2020 and 2021" assertion.
• 1f385594-7bdd-4b98-88bf-4469e7584f90 description "Monthly average maps of CAMS Nitrogen Dioxide [µg m-3] over Spain in 2019, 2020 and 2021" assertion.
• 4e8ee688-dd76-4faa-a088-028fe709bd37 description "This Research Object demonstrates how to use CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services and compute monthly map of NO2 over a given geographical area, here Spain" assertion.
• 4e8ee688-dd76-4faa-a088-028fe709bd37 description "This Research Object demonstrates how to use CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services and compute monthly map of NO2 over a given geographical area, here Spain" assertion.
• b27ea2c2-4d7d-4a61-b25b-8674d1abc30c description "Conda environment generated with conda-lock for linux-64" assertion.
• b27ea2c2-4d7d-4a61-b25b-8674d1abc30c description "Conda environment generated with conda-lock for linux-64" assertion.
• cba6183d-3163-4254-8c11-f973b6b11e7d description "Monthly average maps of CAMS Nitrogen Dioxide [µg m-3] over Spain in 2019, 2020 and 2021" assertion.
• cba6183d-3163-4254-8c11-f973b6b11e7d description "Monthly average maps of CAMS Nitrogen Dioxide [µg m-3] over Spain in 2019, 2020 and 2021" assertion.
• e90c6d17-54b2-47b7-ae75-f0cf7d297b09 description "Conda environment used on EGI notebook on 27/05/2022" assertion.
• e90c6d17-54b2-47b7-ae75-f0cf7d297b09 description "Conda environment used on EGI notebook on 27/05/2022" assertion.
• fa1d2782-8c89-4630-b244-466e03a560a0 description "Conda environment generated with conda-lock for osx-64" assertion.
• fa1d2782-8c89-4630-b244-466e03a560a0 description "Conda environment generated with conda-lock for osx-64" assertion.
• ef5953b8-d6b7-47a2-b115-929ac8179864 description "This Research Object demonstrates how to use CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services and compute monthly map of NO2 over a given geographical area, here Spain" assertion.
• ef5953b8-d6b7-47a2-b115-929ac8179864 description "This Research Object demonstrates how to use CAMS European air quality analysis from Copernicus Atmosphere Monitoring with RELIANCE services and compute monthly map of NO2 over a given geographical area, here Spain" assertion.
• 188552de-76b7-4676-8f24-2aa88950c349 description "Monthly average maps of CAMS Nitrogen Dioxide [µg m-3] over Spain in 2019, 2020 and 2021" assertion.
• 188552de-76b7-4676-8f24-2aa88950c349 description "Monthly average maps of CAMS Nitrogen Dioxide [µg m-3] over Spain in 2019, 2020 and 2021" assertion.
• a825aac5-caf2-42bb-ac4d-d8bef3954f71 description "This is a first test of Research Object (RO) to foster reproducible research." assertion.
• a825aac5-caf2-42bb-ac4d-d8bef3954f71 description "This is a first test of Research Object (RO) to foster reproducible research." assertion.
• 6484f9aa-e4b4-4ef0-b312-2d75224d6447 description "Research object created for the TPDL 2022 Conference." assertion.
• 6484f9aa-e4b4-4ef0-b312-2d75224d6447 description "Research object created for the TPDL 2022 Conference." assertion.
• zenodo.5494629 description "Contains input Datasets of detectreeRGB AI4ER MRes Project used in the Jupyter notebook of Tree crown delineation using detectreeRGB" assertion.
• zenodo.5494629 description "Contains input Datasets of detectreeRGB AI4ER MRes Project used in the Jupyter notebook of Tree crown delineation using detectreeRGB" assertion.
• zenodo.5494629 description "Contains input Datasets of detectreeRGB AI4ER MRes Project used in the Jupyter notebook of Tree crown delineation using detectreeRGB" assertion.
• zenodo.5494629 description "Contains input Datasets of detectreeRGB AI4ER MRes Project used in the Jupyter notebook of Tree crown delineation using detectreeRGB" assertion.
• zenodo.5494629 description "Contains input Datasets of detectreeRGB AI4ER MRes Project used in the Jupyter notebook of Tree crown delineation using detectreeRGB" assertion.
• zenodo.6387953 description "Contains outputs, (vector, raster and figures), generated in the Jupyter notebook of Tree crown delineation using detectreeRGB" assertion.
• zenodo.6387953 description "Contains outputs, (vector, raster and figures), generated in the Jupyter notebook of Tree crown delineation using detectreeRGB" assertion.
• zenodo.6387953 description "Contains outputs, (vector, raster and figures), generated in the Jupyter notebook of Tree crown delineation using detectreeRGB" assertion.
• zenodo.6387953 description "Contains outputs, (vector, raster and figures), generated in the Jupyter notebook of Tree crown delineation using detectreeRGB" assertion.
• zenodo.6387953 description "Contains outputs, (vector, raster and figures), generated in the Jupyter notebook of Tree crown delineation using detectreeRGB" assertion.
• forest-modelling-treecrown_detectreergb description "Rendered version of the Jupyter Notebook hosted by the Environmental Data Science Book." assertion.
• forest-modelling-treecrown_detectreergb description "Rendered version of the Jupyter Notebook hosted by the Environmental Data Science Book." assertion.
• 6bc62582-2f11-4983-a51c-0af32459eca6 description "The research object refers to the Tree crown delineation using detectreeRGB notebook published in the Environmental Data Science book. Purpose: Accurately delineating trees using detectron2, a library that provides state-of-the-art deep learning detection and segmentation algorithms. Modelling approach: An established deep learning model, Mask R-CNN was deployed from detectron2 library to delineate tree crowns accurately. A pre-trained model, named detectreeRGB, is provided to predict the location and extent of tree crowns from a top-down RGB image, captured by drone, aircraft or satellite. detectreeRGB was implemented in python 3.8 using pytorch v1.7.1 and detectron2 v0.5. Further details can be found in the repository documentation. Highlights: detectreeRGB advances the state-of-the-art in tree identification from RGB images by delineating exactly the extent of the tree crown. We demonstrate how to apply the pretrained model to a sample image fetched from a Zenodo repository. Our pre-trained model was developed using aircraft images of tropical forests in Malaysia. The model can be further trained using the user’s own images" assertion.
• 6bc62582-2f11-4983-a51c-0af32459eca6 description "The research object refers to the Tree crown delineation using detectreeRGB notebook published in the Environmental Data Science book. Purpose: Accurately delineating trees using detectron2, a library that provides state-of-the-art deep learning detection and segmentation algorithms. Modelling approach: An established deep learning model, Mask R-CNN was deployed from detectron2 library to delineate tree crowns accurately. A pre-trained model, named detectreeRGB, is provided to predict the location and extent of tree crowns from a top-down RGB image, captured by drone, aircraft or satellite. detectreeRGB was implemented in python 3.8 using pytorch v1.7.1 and detectron2 v0.5. Further details can be found in the repository documentation. Highlights: detectreeRGB advances the state-of-the-art in tree identification from RGB images by delineating exactly the extent of the tree crown. We demonstrate how to apply the pretrained model to a sample image fetched from a Zenodo repository. Our pre-trained model was developed using aircraft images of tropical forests in Malaysia. The model can be further trained using the user’s own images" assertion.
• conda-linux-64.lock description "Lock conda file for linux-64 OS of the Jupyter notebook hosted by the Environmental Data Science Book" assertion.
• conda-linux-64.lock description "Lock conda file for linux-64 OS of the Jupyter notebook hosted by the Environmental Data Science Book" assertion.

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