cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5676224
title: Campus Pond data from 2021-09-07 to 2021-09-28

description: General Metadata for Campus Pond Sampling Station Files Specific metadata for each deployment and sensor can be found as text files with the file format of: <pre><code>LP_CampusPond_DO_YYYY-MM-DD_metadata.txt LP_CampusPond_Depth_YYYY-MM-DD_metadata.txt LP_CampusPond_CT_YYYY-MM-DD_metadata.txt</code></pre> Where YYYY-MM-DD is the date that the sampling period ended. NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts. File Created 2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md File Modified Description These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702). All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ Station Specifics The specific sensors at the site are: <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> The sensors are sampled every 15 minutes Measurement Parameters, units, and Variable Names <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT, .press, or .BP - the temperature (dC) from the DO, conductivity, water pressure, or barometric pressure sensor. * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
DOI: 10.5281/zenodo.5676223
title: Campus Pond data from 2021-09-07 to 2021-09-28

description: General Metadata for Campus Pond Sampling Station Files Specific metadata for each deployment and sensor can be found as text files with the file format of: <pre><code>LP_CampusPond_DO_YYYY-MM-DD_metadata.txt LP_CampusPond_Depth_YYYY-MM-DD_metadata.txt LP_CampusPond_CT_YYYY-MM-DD_metadata.txt</code></pre> Where YYYY-MM-DD is the date that the sampling period ended. NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts. File Created 2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md File Modified Description These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702). All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ Station Specifics The specific sensors at the site are: <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> The sensors are sampled every 15 minutes Measurement Parameters, units, and Variable Names <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT, .press, or .BP - the temperature (dC) from the DO, conductivity, water pressure, or barometric pressure sensor. * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
DOI: 10.5281/zenodo.5676056
title: Social Media Tweets Pro and Anti Bolsonaro

description: <strong>Overview</strong> Social media platforms have an important role in Brazilian society's polarization. Especially during the COVID-19 pandemic (2020-2021), these platforms have a peak of posts about President Bolsonaro's speech and behavior during this period. On the one hand, millions of people support Bolsonaro's attitudes and follow his controversial guidances. On the other hand, a vast number of social media users accuse Bolsonaro of acting against democracy and science. In this context, this dataset presents the collection of tweets posts and its linked news articles (including all related media) covering two Brazilians’ demonstrations events PRO and AGAINST President Bolsonaro government, during September 7th and October 2nd of 2021.<br> The dataset contains 4.7M tweets. <strong>Data Collection</strong><br> We use the library Fake-News Crawler (https://github.com/phillipecardenuto/fakenews-crawler) to collect the tweet posts and related media. For this, we provided keywords related to both events to receive the data during events and following days. For instance, some of the keywords used were ‘<em>7deSet</em>’, ‘<em>BolsonaroAte2026</em>’, ‘<em>VemParaRua</em>’, ‘<em>EleNao</em>’, ‘<em>07EuVou</em>’, ‘<em>SupremoÉOPovo</em>’, '<em>aculpaédobolsonaro</em>’, ‘<em>2outeuvou</em>’.<br> <br> <strong>Disclaimer</strong>: We did not perform any filtering or procedure to assert that all collected data is, in fact, related to the demonstrations; therefore, some of the content of the dataset might not be related to these events. <strong>Content</strong><br> brazilian_demonstration_events.json: It contains the tweet posts, their metadata (e.g., post time, language), and all related media content URLs (i.e., news article link and media links).<br> <br> <strong>Media Content</strong><br> Due to the terms of use from the social networks, we do not make publicly available the images and videos that were collected. However, we can provide some extra pieces of media content related to one (or more) events by contacting the authors.<br> <br> <strong>Funding</strong><br> DéjàVu thematic project, São Paulo Research Foundation (grants 2017/12646-3, 2020/02241-9 and 2020/02211-2)<br>
DOI: 10.5281/zenodo.5676055
title: Social Media Tweets Pro and Anti Bolsonaro

description: <strong>Overview</strong> Social media platforms have an important role in Brazilian society's polarization. Especially during the COVID-19 pandemic (2020-2021), these platforms have a peak of posts about President Bolsonaro's speech and behavior during this period. On the one hand, millions of people support Bolsonaro's attitudes and follow his controversial guidances. On the other hand, a vast number of social media users accuse Bolsonaro of acting against democracy and science. In this context, this dataset presents the collection of tweets posts and its linked news articles (including all related media) covering two Brazilians’ demonstrations events PRO and AGAINST President Bolsonaro government, during September 7th and October 2nd of 2021.<br> The dataset contains 4.7M tweets. <strong>Data Collection</strong><br> We use the library Fake-News Crawler (https://github.com/phillipecardenuto/fakenews-crawler) to collect the tweet posts and related media. For this, we provided keywords related to both events to receive the data during events and following days. For instance, some of the keywords used were ‘<em>7deSet</em>’, ‘<em>BolsonaroAte2026</em>’, ‘<em>VemParaRua</em>’, ‘<em>EleNao</em>’, ‘<em>07EuVou</em>’, ‘<em>SupremoÉOPovo</em>’, '<em>aculpaédobolsonaro</em>’, ‘<em>2outeuvou</em>’.<br> <br> <strong>Disclaimer</strong>: We did not perform any filtering or procedure to assert that all collected data is, in fact, related to the demonstrations; therefore, some of the content of the dataset might not be related to these events. <strong>Content</strong><br> brazilian_demonstration_events.json: It contains the tweet posts, their metadata (e.g., post time, language), and all related media content URLs (i.e., news article link and media links).<br> <br> <strong>Media Content</strong><br> Due to the terms of use from the social networks, we do not make publicly available the images and videos that were collected. However, we can provide some extra pieces of media content related to one (or more) events by contacting the authors.<br> <br> <strong>Funding</strong><br> DéjàVu thematic project, São Paulo Research Foundation (grants 2017/12646-3, 2020/02241-9 and 2020/02211-2)<br>
DOI: 10.14457/cu.the.2005.1936
title: การเปลี่ยนแปลงสมบัติทางเคมีกายภาพของข้าวสารในระหว่างการเก็บที่มีผลต่อลักษณะเนื้อสัมผัสของข้าวสุก
DOI: 10.5517/ccdc.csd.cc25grm1
title: CCDC 2010183: Experimental Crystal Structure Determination

description: Related Article: Pablo Redero, Thierry Hartung, Jianwei Zhang, Leo D. M. Nicholls, Guo Zichen, Martin Simon, Christopher Golz, Manuel Alcarazo|2020|Angew.Chem.,Int.Ed.|59|23527|doi:10.1002/anie.202010021
DOI: 10.5281/zenodo.5676240
title: Campus Pond Data from 2021-09-29 to 2021-11-02

description: General Metadata for Campus Pond Sampling Station Files Specific metadata for each deployment and sensor can be found as text files with the file format of: <pre><code>LP_CampusPond_DO_YYYY-MM-DD_metadata.txt LP_CampusPond_Depth_YYYY-MM-DD_metadata.txt LP_CampusPond_CT_YYYY-MM-DD_metadata.txt</code></pre> Where YYYY-MM-DD is the date that the sampling period ended. NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts. File Created 2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md File Modified Description These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702). All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ Station Specifics The specific sensors at the site are: <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> The sensors are sampled every 15 minutes Measurement Parameters, units, and Variable Names <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT, .press, or .BP - the temperature (dC) from the DO, conductivity, water pressure, or barometric pressure sensor. * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
DOI: 10.5281/zenodo.5676239
title: Campus Pond Data from 2021-09-29 to 2021-11-02

description: General Metadata for Campus Pond Sampling Station Files Specific metadata for each deployment and sensor can be found as text files with the file format of: <pre><code>LP_CampusPond_DO_YYYY-MM-DD_metadata.txt LP_CampusPond_Depth_YYYY-MM-DD_metadata.txt LP_CampusPond_CT_YYYY-MM-DD_metadata.txt</code></pre> Where YYYY-MM-DD is the date that the sampling period ended. NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts. File Created 2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md File Modified Description These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702). All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ Station Specifics The specific sensors at the site are: <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> The sensors are sampled every 15 minutes Measurement Parameters, units, and Variable Names <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT, .press, or .BP - the temperature (dC) from the DO, conductivity, water pressure, or barometric pressure sensor. * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
DOI: 10.6084/m9.figshare.16943812.v2
title: Data&ScriptsFigure3

description: Data and scripts to generate Figure 3<br>
DOI: 10.5281/zenodo.5676252
title: Data from Italian cities for the SDGs

description: The aggregation of data concerned 103 Italian cities and for each city 45 indicators were considered
DOI: 10.5281/zenodo.5557210
title: Data from Italian cities for the SDGs

description: The aggregation of data concerned 103 Italian cities and for each city 45 indicators were considered
DOI: 10.5281/zenodo.5676213
title: Dataset used in "Balloons in the Sky: Unveiling the Characteristics and Trade-offs of the Google Loon Service"

description: This dataset was used for the paper "Balloons in the Sky: Unveiling the Characteristics and Trade-offs of the Google Loon Service" It is composed of three different files, identifying three different case studies Peru, Puerto Rico, and Kenya Once uncompressed, the files are stored in parquet format. They can be analyzed using e.g. pyspark with the following code <pre><code class="language-python">df = spark.read.parquet('dataset.parquet') </code></pre> Each scenario is composed of two tables. The file dataset.parquet contains the measured bandwidth in the analyzed area for a period of approximately three months. Its columns are: ts: the timestamp of the measurement, as UNIX timestamp h3: the id of the H3 hexagon (aka <em>pixel</em>) of the measurement nloons: the number of balloons that provided coverage to the pixel at the given timestamp thr: the available bandwith serviceDuration: the duration of the service on the given pixel, starting from ts The file serving_loons.parquet contain the information about the available balloons flying over the area under study. Its columns are ts: the timestamp of the measurement, as UNIX timestamp serving_loons: the number of ballons flying over the area
DOI: 10.5281/zenodo.5676212
title: Dataset used in "Balloons in the Sky: Unveiling the Characteristics and Trade-offs of the Google Loon Service"

description: This dataset was used for the paper "Balloons in the Sky: Unveiling the Characteristics and Trade-offs of the Google Loon Service" It is composed of three different files, identifying three different case studies Peru, Puerto Rico, and Kenya Once uncompressed, the files are stored in parquet format. They can be analyzed using e.g. pyspark with the following code <pre><code class="language-python">df = spark.read.parquet('dataset.parquet') </code></pre> Each scenario is composed of two tables. The file dataset.parquet contains the measured bandwidth in the analyzed area for a period of approximately three months. Its columns are: ts: the timestamp of the measurement, as UNIX timestamp h3: the id of the H3 hexagon (aka <em>pixel</em>) of the measurement nloons: the number of balloons that provided coverage to the pixel at the given timestamp thr: the available bandwith serviceDuration: the duration of the service on the given pixel, starting from ts The file serving_loons.parquet contain the information about the available balloons flying over the area under study. Its columns are ts: the timestamp of the measurement, as UNIX timestamp serving_loons: the number of ballons flying over the area
DOI: 10.5517/ccdc.csd.cc20sqzj
title: CCDC 1870818: Experimental Crystal Structure Determination

description: Related Article: Byung-Chang Oh, Eunyoung Yoon, Jintaek Gong, Jaewook Kim, Russell W. Driver, Yongjun Kim, Woo Youn Kim, Hee-Seung Lee|2021|Small|17|2102525|doi:10.1002/smll.202102525
DOI: 10.5517/ccdc.csd.cc234cbz
title: CCDC 1940610: Experimental Crystal Structure Determination

description: Related Article: Byung-Chang Oh, Eunyoung Yoon, Jintaek Gong, Jaewook Kim, Russell W. Driver, Yongjun Kim, Woo Youn Kim, Hee-Seung Lee|2021|Small|17|2102525|doi:10.1002/smll.202102525
DOI: 10.5281/zenodo.5639616
title: Supplementary Data for the manuscript 'The Rad9-Rad1-Hus1 DNA repair clamp is found in Microsporidia'

description: This dataset contains the supplementary data files for the manuscript titled 'The Rad9-Rad1-Hus1 DNA repair clamp is found in Microsporidia'
DOI: 10.6084/m9.figshare.16992208
title: ActorAttributes

description: Data Frame containing variables for actor-level attributes
DOI: 10.6084/m9.figshare.16992208.v1
title: ActorAttributes

description: Data Frame containing variables for actor-level attributes
DOI: 10.5281/zenodo.5676315
title: Composite Gini Coefficient for Nature-based Solutions (Hydrology, Environment, Society)

description: Composite Gini Coefficient for Nature-based Solutions (Hydrology, Environment, Society)
DOI: 10.5281/zenodo.5676314
title: Composite Gini Coefficient for Nature-based Solutions (Hydrology, Environment, Society)

description: Composite Gini Coefficient for Nature-based Solutions (Hydrology, Environment, Society)
DOI: 10.6084/m9.figshare.16992214
title: Actor-Forum Edgelist

description: Actor-Forum Edgelist
DOI: 10.6084/m9.figshare.16992214.v1
title: Actor-Forum Edgelist

description: Actor-Forum Edgelist
DOI: 10.6084/m9.figshare.16992220
title: Actor-Issue Edgelist

description: Actor-Issue Edgelist
DOI: 10.6084/m9.figshare.16992220.v1
title: Actor-Issue Edgelist

description: Actor-Issue Edgelist
DOI: 10.6084/m9.figshare.16992223.v1
title: Untitled Item

description: All of the data files (.csv) required for the Forum Navigation analysis. Includes an actor-actor edgelist, an actor-forum edgelist, an actor-issue edgelist, a forum-issue edgelist, an issue-issue matrix, an isolates dataset, an actor attributes data frame (actor_orgtype.csv) and a forum attributes data frame (ForumSponsorship.csv).
DOI: 10.15468/jfulra
title: Benthic foraminifera of Laucala Bay, Suva, Fiji

description: This checklist provides the first confirmed species occurrences of benthic foraminifera in Laucala Bay (Suva, Fiji).
DOI: 10.5517/ccdc.csd.cc1jr7q7
title: CCDC 1422519: Experimental Crystal Structure Determination

description: Related Article: Yuji Mikata, Kana Murakami, Ayaka Ochi, Fumie Nakagaki, Kyoko Naito, Arimasa Matsumoto, Ryoji Mitsuhashi, Masahiro Mikuriya|2020|Inorg.Chim.Acta|509|119688|doi:10.1016/j.ica.2020.119688
DOI: 10.5517/ccdc.csd.cc1jr7r8
title: CCDC 1422520: Experimental Crystal Structure Determination

description: Related Article: Yuji Mikata, Kana Murakami, Ayaka Ochi, Fumie Nakagaki, Kyoko Naito, Arimasa Matsumoto, Ryoji Mitsuhashi, Masahiro Mikuriya|2020|Inorg.Chim.Acta|509|119688|doi:10.1016/j.ica.2020.119688