cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/p7yw-9p41
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains the IDs of geo-tagged tweets. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for these keywords - “corona”, "coronavirus", "covid", "pandemic", "lockdown", "quarantine", "hand sanitizer", "ppe", "n95", different possible variants of "sarscov2", "nCov", "covid-19", "ncov2019", "2019ncov", "flatten(ing) the curve", "social distancing", "work(ing) from home" and the respective hashtag of all these keywords. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page).-------------------------------------------------------------------------Coronavirus (COVID-19) Tweets Dataset(190+ Million English Language Tweets; ongoing collection)-------------------------------------------------------------------------Note: I started sharing the IDs of the tweets that had exact 'point' location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs shared in the Coronavirus (COVID-19) Tweets Dataset.Update: I have received a lot of requests, especially from Social Science researchers, to also make the geo-tagged tweets created between March 20, 2020, and April 28, 2020, available in this dataset. Hydrating the millions of tweet IDs may come as a tedious task for people with less technical expertise. Therefore, I have started hydrating the IDs provided in the Coronavirus (COVID-19) Tweets Dataset, and I will be sharing the geo-tagged tweets posted in between these dates as the hydration task goes on. I'll be adding new CSV files, and the naming convention for these newly added files will be day-wise (instead of period-wise). Bookmark this page for further updates.The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-june5.zip will contain tweet ID and sentiment score of the tweets (in CSV and JSON formats) that were created between April 28, 2020, and June 05, 2020.Why are only tweet IDs being shared? Twitter's content redistribution policy restricts the sharing of tweet information other than tweet IDs and/or user IDs. Twitter wants researchers always to pull fresh data. It is because a user might delete a tweet or make their profile protected. If the same tweet has already been pulled and shared on a public domain, it might make the user/community vulnerable to many inferences coming out of the shared data which currently does not exist or is private.
DOI: 10.21227/953q-nz15
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains the IDs of geo-tagged tweets. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for these keywords - “corona”, "coronavirus", "covid", "pandemic", "lockdown", "quarantine", "hand sanitizer", "ppe", "n95", different possible variants of "sarscov2", "nCov", "covid-19", "ncov2019", "2019ncov", "flatten(ing) the curve", "social distancing", "work(ing) from home" and the respective hashtag of all these keywords. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page).-------------------------------------------------------------------------Coronavirus (COVID-19) Tweets Dataset(190+ Million English Language Tweets; ongoing collection)-------------------------------------------------------------------------Note: I started sharing the IDs of the tweets that had exact 'point' location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs shared in the Coronavirus (COVID-19) Tweets Dataset.Update: I have received a lot of requests, especially from Social Science researchers, to also make the geo-tagged tweets created between March 20, 2020, and April 28, 2020, available in this dataset. Hydrating the millions of tweet IDs may come as a tedious task for people with less technical expertise. Therefore, I have started hydrating the IDs provided in the Coronavirus (COVID-19) Tweets Dataset, and I will be sharing the geo-tagged tweets posted in between these dates as the hydration task goes on. I'll be adding new CSV files, and the naming convention for these newly added files will be day-wise (instead of period-wise). Bookmark this page for further updates.The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-june5.zip will contain tweet ID and sentiment score of the tweets (in CSV and JSON formats) that were created between April 28, 2020, and June 05, 2020.Why are only tweet IDs being shared? Twitter's content redistribution policy restricts the sharing of tweet information other than tweet IDs and/or user IDs. Twitter wants researchers always to pull fresh data. It is because a user might delete a tweet or make their profile protected. If the same tweet has already been pulled and shared on a public domain, it might make the user/community vulnerable to many inferences coming out of the shared data which currently does not exist or is private.
DOI: 10.21227/39he-c847
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains the IDs of geo-tagged tweets. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for these keywords - “corona”, "coronavirus", "covid", "pandemic", "lockdown", "quarantine", "hand sanitizer", "ppe", "n95", different possible variants of "sarscov2", "nCov", "covid-19", "ncov2019", "2019ncov", "flatten(ing) the curve", "social distancing", "work(ing) from home" and the respective hashtag of all these keywords. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page).-------------------------------------------------------------------------Coronavirus (COVID-19) Tweets Dataset(190+ Million English Language Tweets; ongoing collection)-------------------------------------------------------------------------Note: I started sharing the IDs of the tweets that had exact 'point' location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs shared in the Coronavirus (COVID-19) Tweets Dataset.Update: I have received a lot of requests, especially from Social Science researchers, to also make the geo-tagged tweets created between March 20, 2020, and April 28, 2020, available in this dataset. Hydrating the millions of tweet IDs may come as a tedious task for people with less technical expertise. Therefore, I have started hydrating the IDs provided in the Coronavirus (COVID-19) Tweets Dataset, and I will be sharing the geo-tagged tweets posted in between these dates as the hydration task goes on. I'll be adding new CSV files, and the naming convention for these newly added files will be day-wise (instead of period-wise). Bookmark this page for further updates.The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-june5.zip will contain tweet ID and sentiment score of the tweets (in CSV and JSON formats) that were created between April 28, 2020, and June 05, 2020.Why are only tweet IDs being shared? Twitter's content redistribution policy restricts the sharing of tweet information other than tweet IDs and/or user IDs. Twitter wants researchers always to pull fresh data. It is because a user might delete a tweet or make their profile protected. If the same tweet has already been pulled and shared on a public domain, it might make the user/community vulnerable to many inferences coming out of the shared data which currently does not exist or is private.
DOI: 10.5281/zenodo.3827445
title: Sky images recorded during the austral summer of 2016/17 as part of the Antarctic Circumnavigation Expedition (ACE).

description: <strong>Dataset abstract</strong> Scattered sunlight measurements can be strongly affected by clouds, mainly due to multiple scattering effects that give rise to large uncertainties in the light path retrieval. In order to estimate cloud cover, we recorded images of the sky every 5 minutes to evaluate a cloud index, from 0 (clear sky) to 10 (completely overcast). This dataset presents the sky images in PNG (Portable Network Graphics) format recorded on board the R/V Akademik Tryoshnikov during the austral summer of 2016/17 as part of the circumnavigation expedition (ACE). Data coverage is from December 2016 until April 2017. These images form a supporting dataset to optical spectroscopy data (Benavent et al., 2020; DOI 10.5281/zenodo.3827443). The ship’s position can be matched with these images using the corrected cruise track (Thomas and Pina Estany, 2019; DOI: 10.5281/zenodo.3483166) or the GPS data provided with the spectroscopy data set (Benavent et al., 2020; DOI 10.5281/zenodo.3827443). <strong>Dataset contents</strong> YYYY-MM-DD_hh.mm.ss.png, data file, portable network graphics README.txt, metadata, text where YYYY-MM-DD_hh.mm.ss is the date and time at which the file was saved in UTC. <strong>Dataset license</strong> This dataset of raw optical sky images from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/
description: The Antarctic Circumnavigation Expedition (ACE) was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals. Support for the MAX-DOAS installation and data collection was provided by the SORPASSO project (also part of ACE) led by Prof. Rafel Simó.
description: {"references": ["Cl\u00e9mer, K., Van Roozendael, M., Fayt, C., Hendrick, F., Hermans, C., Pinardi, G., Spurr, R., Wang, P., De Mazi\u00e8re,M., 2010.Multiple wavelength retrieval of tropospheric aerosol optical properties from MAX-DOAS measurements in Beijing. Atmos. Meas. Tech. 3 (4), 863.", "Plane, J.M.C., Saiz-Lopez, A., 2006. UV-Visible Differential Optical Absorption Spectroscopy (DOAS). In: Heard, D.E. (Ed.), Analytical Techniques for Atmospheric Measurement. Blackwell Publishing, Oxford.", "Platt, U., Stutz, J. (2008). Differential Optical Absorption Spectroscopy: Principles and Applications. Springer Berlin Heidelberg, Berlin, Heidelberg, Berlin, Heidelberg.", "Rodgers, C.D. 2000, \"Inverse Methods for Atmospheric Sounding: Theory and Practice\", Singapore: World Scientific Publishing, Singapore.", "Saiz-Lopez, A., & von Glasow, R. (2012). Reactive halogen chemistry in the troposphere. Chemical Society Reviews. https://doi.org/10.1039/c2cs35208g"]}
DOI: 10.5281/zenodo.3827444
title: Sky images recorded during the austral summer of 2016/17 as part of the Antarctic Circumnavigation Expedition (ACE).

description: <strong>Dataset abstract</strong> Scattered sunlight measurements can be strongly affected by clouds, mainly due to multiple scattering effects that give rise to large uncertainties in the light path retrieval. In order to estimate cloud cover, we recorded images of the sky every 5 minutes to evaluate a cloud index, from 0 (clear sky) to 10 (completely overcast). This dataset presents the sky images in PNG (Portable Network Graphics) format recorded on board the R/V Akademik Tryoshnikov during the austral summer of 2016/17 as part of the circumnavigation expedition (ACE). Data coverage is from December 2016 until April 2017. These images form a supporting dataset to optical spectroscopy data (Benavent et al., 2020; DOI 10.5281/zenodo.3827443). The ship’s position can be matched with these images using the corrected cruise track (Thomas and Pina Estany, 2019; DOI: 10.5281/zenodo.3483166) or the GPS data provided with the spectroscopy data set (Benavent et al., 2020; DOI 10.5281/zenodo.3827443). <strong>Dataset contents</strong> YYYY-MM-DD_hh.mm.ss.png, data file, portable network graphics README.txt, metadata, text where YYYY-MM-DD_hh.mm.ss is the date and time at which the file was saved in UTC. <strong>Dataset license</strong> This dataset of raw optical sky images from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/
description: The Antarctic Circumnavigation Expedition (ACE) was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals. Support for the MAX-DOAS installation and data collection was provided by the SORPASSO project (also part of ACE) led by Prof. Rafel Simó.
description: {"references": ["Cl\u00e9mer, K., Van Roozendael, M., Fayt, C., Hendrick, F., Hermans, C., Pinardi, G., Spurr, R., Wang, P., De Mazi\u00e8re,M., 2010.Multiple wavelength retrieval of tropospheric aerosol optical properties from MAX-DOAS measurements in Beijing. Atmos. Meas. Tech. 3 (4), 863.", "Plane, J.M.C., Saiz-Lopez, A., 2006. UV-Visible Differential Optical Absorption Spectroscopy (DOAS). In: Heard, D.E. (Ed.), Analytical Techniques for Atmospheric Measurement. Blackwell Publishing, Oxford.", "Platt, U., Stutz, J. (2008). Differential Optical Absorption Spectroscopy: Principles and Applications. Springer Berlin Heidelberg, Berlin, Heidelberg, Berlin, Heidelberg.", "Rodgers, C.D. 2000, \"Inverse Methods for Atmospheric Sounding: Theory and Practice\", Singapore: World Scientific Publishing, Singapore.", "Saiz-Lopez, A., & von Glasow, R. (2012). Reactive halogen chemistry in the troposphere. Chemical Society Reviews. https://doi.org/10.1039/c2cs35208g"]}
DOI: 10.21227/j2g8-6q63
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains the IDs of geo-tagged tweets. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for these keywords - “corona”, "coronavirus", "covid", "pandemic", "lockdown", "quarantine", "hand sanitizer", "ppe", "n95", different possible variants of "sarscov2", "nCov", "covid-19", "ncov2019", "2019ncov", "flatten(ing) the curve", "social distancing", "work(ing) from home" and the respective hashtag of all these keywords. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page).-------------------------------------------------------------------------Coronavirus (COVID-19) Tweets Dataset(190+ Million English Language Tweets; ongoing collection)-------------------------------------------------------------------------Note: I started sharing the IDs of the tweets that had exact 'point' location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs shared in the Coronavirus (COVID-19) Tweets Dataset.Update: I have received a lot of requests, especially from Social Science researchers, to also make the geo-tagged tweets created between March 20, 2020, and April 28, 2020, available in this dataset. Hydrating the millions of tweet IDs may come as a tedious task for people with less technical expertise. Therefore, I have started hydrating the IDs provided in the Coronavirus (COVID-19) Tweets Dataset, and I will be sharing the geo-tagged tweets posted in between these dates as the hydration task goes on. I'll be adding new CSV files, and the naming convention for these newly added files will be day-wise (instead of period-wise). Bookmark this page for further updates.The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-june5.zip will contain tweet ID and sentiment score of the tweets (in CSV and JSON formats) that were created between April 28, 2020, and June 05, 2020.Why are only tweet IDs being shared? Twitter's content redistribution policy restricts the sharing of tweet information other than tweet IDs and/or user IDs. Twitter wants researchers always to pull fresh data. It is because a user might delete a tweet or make their profile protected. If the same tweet has already been pulled and shared on a public domain, it might make the user/community vulnerable to many inferences coming out of the shared data which currently does not exist or is private.
DOI: 10.21227/3ve3-e108
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains the IDs of geo-tagged tweets. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for these keywords - “corona”, "coronavirus", "covid", "pandemic", "lockdown", "quarantine", "hand sanitizer", "ppe", "n95", different possible variants of "sarscov2", "nCov", "covid-19", "ncov2019", "2019ncov", "flatten(ing) the curve", "social distancing", "work(ing) from home" and the respective hashtag of all these keywords. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page).-------------------------------------------------------------------------Coronavirus (COVID-19) Tweets Dataset(190+ Million English Language Tweets; ongoing collection)-------------------------------------------------------------------------Note: I started sharing the IDs of the tweets that had exact 'point' location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs shared in the Coronavirus (COVID-19) Tweets Dataset.Update: I have received a lot of requests, especially from Social Science researchers, to also make the geo-tagged tweets created between March 20, 2020, and April 28, 2020, available in this dataset. Hydrating the millions of tweet IDs may come as a tedious task for people with less technical expertise. Therefore, I have started hydrating the IDs provided in the Coronavirus (COVID-19) Tweets Dataset, and I will be sharing the geo-tagged tweets posted in between these dates as the hydration task goes on. I'll be adding new CSV files, and the naming convention for these newly added files will be day-wise (instead of period-wise). Bookmark this page for further updates.The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-june5.zip will contain tweet ID and sentiment score of the tweets (in CSV and JSON formats) that were created between April 28, 2020, and June 05, 2020.Why are only tweet IDs being shared? Twitter's content redistribution policy restricts the sharing of tweet information other than tweet IDs and/or user IDs. Twitter wants researchers always to pull fresh data. It is because a user might delete a tweet or make their profile protected. If the same tweet has already been pulled and shared on a public domain, it might make the user/community vulnerable to many inferences coming out of the shared data which currently does not exist or is private.
DOI: 10.21227/64v9-ws15
title: Multilayer Wall Correction Factors for Indoor Ray-Tracing Radio Propagation Modeling (Data)

description: This dataset contains supplementary data and information for C. H. Teh, B. K. Chung and E. H. Lim, "Multilayer Wall Correction Factors for Indoor Ray-Tracing Radio Propagation Modeling," in IEEE Transactions on Antennas and Propagation, vol. 68, no. 1, pp. 604-608, Jan. 2020, doi: 10.1109/TAP.2019.2943397.
DOI: 10.21227/yf95-b180
title: Multilayer Wall Correction Factors for Indoor Ray-Tracing Radio Propagation Modeling (Data)

description: This dataset contains supplementary data and information for C. H. Teh, B. K. Chung and E. H. Lim, "Multilayer Wall Correction Factors for Indoor Ray-Tracing Radio Propagation Modeling," in IEEE Transactions on Antennas and Propagation, vol. 68, no. 1, pp. 604-608, Jan. 2020, doi: 10.1109/TAP.2019.2943397.
DOI: 10.5281/zenodo.3900946
title: Pinnacle Test Data

description: Test data for Pinnacle Export Tool in pymedphys repo.
DOI: 10.5281/zenodo.3900945
title: Pinnacle Test Data

description: Test data for Pinnacle Export Tool in pymedphys repo.