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This dataset contains sentiment evaluations of weather-related tweets that have been crowd-scored for accuracy. The evaluations were all done by at least 10 different contributors, allowing for a comprehensive overview of sentiment towards the weather across an array of tweets. Data such as the original and trustworthiness of judgments, state of the unit, gold answer, and tweet text are included in this dataset. This remarkable collection is perfect for analyzing trends in sentiment towards the weather within society and can provide insight into how people view changing climate conditions on a global scale. Help us understand more about how people feel about the environment today by exploring this incredible dataset!
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This dataset is composed of sentiment evaluation accuracy data collected from crowd sources on Weather-Related tweets. This dataset can be used to study the accuracy and reliability of sentiment evaluations by crowd sourced workers.
The dataset contains a variety of columns which can be used to analyze the data, such as: - _golden - whether or not the row is a golden row; - _canary - whether or not the row is a canary row; - _unit_state - state of the unit; - _trusted_judgments - number of trusted judgments for this row;
- _last_judgment_at - date & time when last judgment occurred for this row; - orig_unit_state, orig_canary, orig_ies tweasts for correct/incorrect sentiment ratings given by crowd sourced workers. This column also allows to evaluate which criteria was used in assessing which classification was chosen (positive vs negative etc.). All these features will help determine how effective crowd sourcing evaluation really is in terms of generating accurate extracts from natural language sentences.Moreover, you can use this dataset to compare individual contributions from contributors who evaluated the tweet’s text against its category (correct/incorrect). For example: The tweet “It’s going to snow tomorrow!” was classified as positive, checking if 10 contributors found it as correct or incorrect. You can cross check with other factors like gold answers and see how reliable they deemed it on an aggregate basis during their assessment process and compare them with one another too according to their judging protocol established at outset.
In conclusion, this Kaggle Dataset provides you comprehensive crowdsourced assessment results on accuracy attributed towards different weather related topics contained within tweets allowing us to get insights into how reliable are such systems when using them for extracting sentiment information required in natural language processing tasks
- Identifying trends in how people perceive the weather: This dataset can be used to track how different regions of the world view different types of weather. For example, does sunny weather often evoke more positive sentiment than rain? Does the converse hold true?
- Investigating bias in crowd grading: This dataset could be used to examine whether crowd graders tend to grade more positively or negatively for a specific location, depending on their own sentiment about that region.
- Developing better sentiment analysis models: This dataset could be used to train a machine learning model that accurately classifies and outputs sentiment values for tweets relating to the weather. Such a model could potentially even incorporate meta data such as location and time when classifying sentiments related to certain types of climate or seasonal changes
If you use this dataset in your research, please credit the original authors. Data Source
Unknown License - Please check the dataset description for more information.
File: weather-evaluated-agg-DFE.csv | Column name | Description | |:-------------------------------------------|:----------------------------------------------------------------------------------------------------------| | _golden | Indicates whether the row is a golden row or not (Boolean). | | _canary | Indicates whether the row is a canary row or not (Boolean). ...
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The data in this dataset is a spatial inventory of urban agriculture (UA) carried out in the city of Milan (Italy). UA areas where identified with a multi-step and iterative procedure by using different web-mapping tools, especially multitemporal Google Earth images, and ancillary data such as Google Street View and Bing Maps.
License
Creative Commons CC-BY
Disclaimer
Despite our best efforts to validate the data, some information may be incorrect.
Description of the dataset
Typologies of UA
Land use typologies
Credit
Pulighe G., Lupia F. (2019) Multitemporal Geospatial Evaluation of Urban Agriculture and (Non)-Sustainable Food Self-Provisioning in Milan, Italy. Sustainability 2019, 11(7), 1846
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km. Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterMIT Licensehttps://opensource.org/licenses/MIT
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This dataset presents a dual-version representation of employment-related data from India, crafted to highlight the importance of data cleaning and transformation in any real-world data science or analytics project.
It includes two parallel datasets: 1. Messy Dataset (Raw) – Represents a typical unprocessed dataset often encountered in data collection from surveys, databases, or manual entries. 2. Cleaned Dataset – This version demonstrates how proper data preprocessing can significantly enhance the quality and usability of data for analytical and visualization purposes.
Each record captures multiple attributes related to individuals in the Indian job market, including:
- Age Group
- Employment Status (Employed/Unemployed)
- Monthly Salary (INR)
- Education Level
- Industry Sector
- Years of Experience
- Location
- Perceived AI Risk
- Date of Data Recording
The raw dataset underwent comprehensive transformations to convert it into its clean, analysis-ready form: - Missing Values: Identified and handled using either row elimination (where critical data was missing) or imputation techniques. - Duplicate Records: Identified using row comparison and removed to prevent analytical skew. - Inconsistent Formatting: Unified inconsistent naming in columns (like 'monthly_salary_(inr)' → 'Monthly Salary (INR)'), capitalization, and string spacing. - Incorrect Data Types: Converted columns like salary from string/object to float for numerical analysis. - Outliers: Detected and handled based on domain logic and distribution analysis. - Categorization: Converted numeric ages into grouped age categories for comparative analysis. - Standardization: Uniform labels for employment status, industry names, education, and AI risk levels were applied for visualization clarity.
This dataset is ideal for learners and professionals who want to understand: - The impact of messy data on visualization and insights - How transformation steps can dramatically improve data interpretation - Practical examples of preprocessing techniques before feeding into ML models or BI tools
It's also useful for:
- Training ML models with clean inputs
- Data storytelling with visual clarity
- Demonstrating reproducibility in data cleaning pipelines
By examining both the messy and clean datasets, users gain a deeper appreciation for why “garbage in, garbage out” rings true in the world of data science.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These data include all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. IMPORTANT NOTE (Prashanth Dwarakanath 2019-08-30): This only affects the r1i1p1f1 member of the EC-EARTH-CONSORTIUM ensemble (KNMI runs in version v20190711); the historical experiment has accidentally been started with an incorrect initial ocean condition. We will rerun the historical experiment and the scenario experiments, and publish them when they are finalized. The EC Earth 3.3 climate model, released in 2019, includes the following components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 deg with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spain; CNR-ISAC, Italy; DMI, Denmark; ENEA, Italy; FMI, Finland; Geomar, Germany; ICHEC, Ireland; ICTP, Italy; IDL, Portugal; IMAU, The Netherlands; IPMA, Portugal; KIT, Karlsruhe, Germany; KNMI, The Netherlands; Lund University, Sweden; Met Eireann, Ireland; NLeSC, The Netherlands; NTNU, Norway; Oxford University, UK; surfSARA, The Netherlands; SMHI, Sweden; Stockholm University, Sweden; Unite ASTR, Belgium; University College Dublin, Ireland; University of Bergen, Norway; University of Copenhagen, Denmark; University of Helsinki, Finland; University of Santiago de Compostela, Spain; Uppsala University, Sweden; Utrecht University, The Netherlands; Vrije Universiteit Amsterdam, the Netherlands; Wageningen University, The Netherlands. Mailing address: EC-Earth consortium, Rossby Center, Swedish Meteorological and Hydrological Institute/SMHI, SE-601 76 Norrkoping, Sweden (EC-Earth-Consortium) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
Individuals using the data must abide by terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). The original license restrictions on these datasets were recorded as global attributes in the data files, but these may have been subsequently updated.
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TwitterBy CrowdFlower [source]
This dataset contains sentiment evaluations of weather-related tweets that have been crowd-scored for accuracy. The evaluations were all done by at least 10 different contributors, allowing for a comprehensive overview of sentiment towards the weather across an array of tweets. Data such as the original and trustworthiness of judgments, state of the unit, gold answer, and tweet text are included in this dataset. This remarkable collection is perfect for analyzing trends in sentiment towards the weather within society and can provide insight into how people view changing climate conditions on a global scale. Help us understand more about how people feel about the environment today by exploring this incredible dataset!
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
This dataset is composed of sentiment evaluation accuracy data collected from crowd sources on Weather-Related tweets. This dataset can be used to study the accuracy and reliability of sentiment evaluations by crowd sourced workers.
The dataset contains a variety of columns which can be used to analyze the data, such as: - _golden - whether or not the row is a golden row; - _canary - whether or not the row is a canary row; - _unit_state - state of the unit; - _trusted_judgments - number of trusted judgments for this row;
- _last_judgment_at - date & time when last judgment occurred for this row; - orig_unit_state, orig_canary, orig_ies tweasts for correct/incorrect sentiment ratings given by crowd sourced workers. This column also allows to evaluate which criteria was used in assessing which classification was chosen (positive vs negative etc.). All these features will help determine how effective crowd sourcing evaluation really is in terms of generating accurate extracts from natural language sentences.Moreover, you can use this dataset to compare individual contributions from contributors who evaluated the tweet’s text against its category (correct/incorrect). For example: The tweet “It’s going to snow tomorrow!” was classified as positive, checking if 10 contributors found it as correct or incorrect. You can cross check with other factors like gold answers and see how reliable they deemed it on an aggregate basis during their assessment process and compare them with one another too according to their judging protocol established at outset.
In conclusion, this Kaggle Dataset provides you comprehensive crowdsourced assessment results on accuracy attributed towards different weather related topics contained within tweets allowing us to get insights into how reliable are such systems when using them for extracting sentiment information required in natural language processing tasks
- Identifying trends in how people perceive the weather: This dataset can be used to track how different regions of the world view different types of weather. For example, does sunny weather often evoke more positive sentiment than rain? Does the converse hold true?
- Investigating bias in crowd grading: This dataset could be used to examine whether crowd graders tend to grade more positively or negatively for a specific location, depending on their own sentiment about that region.
- Developing better sentiment analysis models: This dataset could be used to train a machine learning model that accurately classifies and outputs sentiment values for tweets relating to the weather. Such a model could potentially even incorporate meta data such as location and time when classifying sentiments related to certain types of climate or seasonal changes
If you use this dataset in your research, please credit the original authors. Data Source
Unknown License - Please check the dataset description for more information.
File: weather-evaluated-agg-DFE.csv | Column name | Description | |:-------------------------------------------|:----------------------------------------------------------------------------------------------------------| | _golden | Indicates whether the row is a golden row or not (Boolean). | | _canary | Indicates whether the row is a canary row or not (Boolean). ...