cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2bkb08
title: CCDC 2161599: Experimental Crystal Structure Determination

description: Related Article: Zhi-Mei Yang, Yu-Yang Li, Xiao-Cheng Zhou, Yi-Fan Liu, Jia-Qian Li, Jian Su, Jing-Lin Zuo|2022|Cryst.Growth Des.|22|4941|doi:10.1021/acs.cgd.2c00490
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bldhv
title: CCDC 2162637: Experimental Crystal Structure Determination

description: Related Article: Soumyadip Basu, Soumitra Rana, Pinaki Saha, Prasanta Ghosh, Chhanda Mukhopadhyay|2022|J.Org.Chem.|87|9755|doi:10.1021/acs.joc.2c00788
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bmm7v
title: CCDC 2163807: Experimental Crystal Structure Determination

description: Related Article: Huai-Wei Wang, Jia-Xue Wu, Xian-Qiang Huang, Da-Cheng Li, Su-Na Wang, Yi Lu, Jian-Min Dou|2022|Org.Lett.|24|5704|doi:10.1021/acs.orglett.2c02075
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bnvtp
title: CCDC 2165003: Experimental Crystal Structure Determination

description: Related Article: Tingzheng Hou, Wentao Xu, Xiaokun Pei, Lu Jiang, Omar M. Yaghi, Kristin A. Persson|2022|J.Am.Chem.Soc.|144|13446|doi:10.1021/jacs.2c03710
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bs24c
title: CCDC 2168082: Experimental Crystal Structure Determination

description: Related Article: Zhi-Mei Yang, Yu-Yang Li, Xiao-Cheng Zhou, Yi-Fan Liu, Jia-Qian Li, Jian Su, Jing-Lin Zuo|2022|Cryst.Growth Des.|22|4941|doi:10.1021/acs.cgd.2c00490
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2btcn6
title: CCDC 2169338: Experimental Crystal Structure Determination

description: Related Article: Hongtai Chen, Tao Zhang, Shurong Liu, Hongxiao Lv, Liming Fan, Xiutang Zhang|2022|Inorg.Chem.|61|11949|doi:10.1021/acs.inorgchem.2c01686
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bxpnm
title: CCDC 2172531: Experimental Crystal Structure Determination

description: Related Article: Yankun Li, Chen-Ho Tung, Zhenghu Xu|2022|Org.Lett.|24|5829|doi:10.1021/acs.orglett.2c02388
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.26180/20486919.v1
title: Finding Wonderful_Bridges.xlsx

description: This dataset is taken from instagram account @wonderful.indonesia which is managed by Ministry of Tourism, Republic of Indonesia. The data covered 2 years of Instagram posts during COVID-19.
DOI: 10.26180/20486919
title: Finding Wonderful_Bridges.xlsx

description: This dataset is taken from instagram account @wonderful.indonesia which is managed by Ministry of Tourism, Republic of Indonesia. The data covered 2 years of Instagram posts during COVID-19.
DOI: 10.34740/kaggle/dsv/4072760
title: Russian Invasion of Ukraine
DOI: 10.6084/m9.figshare.20445300
title: P arrival time and temporary station info

description: 1. Temporary_Sta_Weiyuan includes the station info of the dense seismic network in the Weiyuan region，which is deployed by the Institute of Geophysics, CEA. This network consisted of 33 broadband stations with an average spacing of ~10 km. 2. P_arrival_time_weiyuan_temporary_v2.dat includes the P-wave picks, which are measured using the STA/LTA method.
DOI: 10.6084/m9.figshare.20445300.v3
title: P arrival time and temporary station info

description: 1. Temporary_Sta_Weiyuan includes the station info of the dense seismic network in the Weiyuan region，which is deployed by the Institute of Geophysics, CEA. This network consisted of 33 broadband stations with an average spacing of ~10 km. 2. P_arrival_time_weiyuan_temporary_v2.dat includes the P-wave picks, which are measured using the STA/LTA method.
DOI: 10.6084/m9.figshare.20445300.v2
title: P arrival time and temporary station info in weiyuan region

description: 1. Temporary_Sta_Weiyuan includes the station info of the dense seismic network in the Weiyuan region，which is deployed by the Institute of Geophysics, CEA. This network consisted of 33 broadband stations with an average spacing of ~10 km. 2. P_arrival_time_weiyuan_temporary_v2.dat includes the P-wave picks, which are measured using the STA/LTA method.
DOI: 10.21227/95n2-y902
title: Generated and Validated Invariants of EPIC Smart Grid

description: This dataset belongs to the generated and validated list of invariants of EPIC smart grid
DOI: 10.6084/m9.figshare.20486913
title: F1000_survival_table1_narisara_ranee

description: Survival_Cannabis
DOI: 10.6084/m9.figshare.20486925
title: Argyrosomus japonicus Genome assembly and annotation

description: Argyrosomus japonicus Genome assembly and annotation
DOI: 10.6084/m9.figshare.20486925.v1
title: Argyrosomus japonicus Genome assembly and annotation

description: Argyrosomus japonicus Genome assembly and annotation
DOI: 10.6084/m9.figshare.20486910.v1
title: Tweet IDs + Botometer results

description: We used the Twitter API (V2) to collect all tweets, retweets, quotes and replies containing case-insensitive versions of the hashtags: #(I)StandWithPutin, #(I)StandWithRussia, #(I)SupportRussia, #(I)StandWithUkraine, #(I)StandWithZelenskyy and #(I)SupportUkraine. These were obtained from February 23rd 2022 00:00:00 UTC until March 8th 2022 23:59:59 UTC, the fortnight after Russia invaded Ukraine. We queried the hashtags with and without the `I', a total of 12 query hashtags, collecting 5,203,746 tweets. The data collected predates the beginning of the Russian invasion by one day. These hashtags were chosen as they were found to be the most trending hashtags related to the Russia/Ukraine war which could be easily identified with a particular side in the conflict. <br> We calculated Botometer results on 483,100 (26.5%) of accounts. These accounts were randomly sampled from a list of all unique users in our dataset which posted in English. This random sample leads to an approximately uniform frequency of Tweets from accounts with Botometer labels across the time frame we considered. We include the language dependent and language independent results from Botometer, including the Complete Automation Probabilities (CAP) and each of the sub-category scores for different bot types. Moreoever, we include the display scores and raw scores from Botometer for each account. More information about the Botometer scores can be found at this link: https://rapidapi.com/OSoMe/api/botometer-pro/details
DOI: 10.14458/siam.res.2022.2
title: An Investigation into the Social Determinants ofCrowdfunding Effectiveness in Developing, non-Westerncontexts: Some Evidence from Thailand
DOI: 10.14458/siam.res.2022.3
title: Application of Good Governance for Implementing the United Nations' Sustainable Development Goals: SDG Goal#16 in Afghanistan
DOI: 10.14458/siam.res.2022.4
title: Cashless Payment Acceptance among Consumers in Thailand: A Case Study on Digital Wallets
DOI: 10.14458/siam.res.2022.5
title: Consideration of Influencer Marketing on Social Media to Influence Generation Z's Purchase Intention
DOI: 10.14458/siam.res.2022.6
title: COVID-19 Vaccine Hesitancy among International University Students: An Empirical Study at Siam University
DOI: 10.14458/siam.res.2022.7
title: Curriculum Development of the Master of Arts in Peace Studies and Diplomacy (MAPD) Program and Program Learning Outcomes (PLOs)
DOI: 10.14458/siam.res.2022.8
title: Digital Transformation of Next Normal Education in the Post Covid Pandemic
DOI: 10.14458/siam.res.2022.9
title: Effect of Mandatory Sit-at-Home Order by The Indigenous People of Biafra on the Socio-Economic Activities in South-Eastern Region, Nigeria
DOI: 10.14458/siam.res.2022.10
title: Empirical Study on the Determinants of Financial Literacy and Association with Financial Well-Being During the Pandemic Among Thai Tertiary Students
DOI: 10.14458/siam.res.2022.11
title: Factor Affecting Online Shopping Behavior in Cambodia
DOI: 10.14458/siam.res.2022.12
title: Online Shopping Intention among the International Students in Thailand An Empirical Study
DOI: 10.14458/siam.res.2022.13
title: Online-Purchasing Behavior of Thai-Millennials for Preschool-aged Toys in Bangkok
DOI: 10.14458/siam.res.2022.14
title: Review on Students Engagement: The Factor Influencing Online Learning
DOI: 10.14458/siam.res.2022.15
title: The Agitation of the Indigenous People of Biafra (IPOB) And its Impact on Nigeria's National Development
DOI: 10.14458/siam.res.2022.16
title: The Impact of COVID-19 Regulations on Supply Chains in the Automotive Industry
DOI: 10.14458/siam.res.2022.17
title: The New World Order under the New Balance of Powerbetween the United States, China and Russiain the Post-Cold War Era
DOI: 10.14458/siam.res.2022.18
title: The Role of Management Information Systems Towards Maritime Logistics Management in Myanmar
DOI: 10.14458/siam.res.2022.19
title: The Strategic Management on Tourism Industry in Vietnam in the Next Normal
DOI: 10.14458/siam.res.2022.20
title: The Sustainable Strategies for Luxury Product During COVID19 Pandemic Situation
DOI: 10.14458/siam.res.2022.21
title: Voters' Preferences during the 2011 General Election in Nigeria: A Study of Oyi Local Government Area of Anambra State
DOI: 10.6084/m9.figshare.20486910.v2
title: Tweets discussing the Russia/Ukraine war

description: We used the Twitter API (V2) to collect all tweets, retweets, quotes and replies containing case-insensitive versions of the hashtags: #(I)StandWithPutin, #(I)StandWithRussia, #(I)SupportRussia, #(I)StandWithUkraine, #(I)StandWithZelenskyy and #(I)SupportUkraine. These were obtained from February 23rd 2022 00:00:00 UTC until March 8th 2022 23:59:59 UTC, the fortnight after Russia invaded Ukraine. We queried the hashtags with and without the `I', a total of 12 query hashtags, collecting 5,203,746 tweets. The data collected predates the beginning of the Russian invasion by one day. These hashtags were chosen as they were found to be the most trending hashtags related to the Russia/Ukraine war which could be easily identified with a particular side in the conflict. <br> We calculated Botometer results on 483,100 (26.5%) of accounts. These accounts were randomly sampled from a list of all unique users in our dataset which posted in English. This random sample leads to an approximately uniform frequency of Tweets from accounts with Botometer labels across the time frame we considered. We include the language dependent and language independent results from Botometer, including the Complete Automation Probabilities (CAP) and each of the sub-category scores for different bot types. Moreoever, we include the display scores and raw scores from Botometer for each account. More information about the Botometer scores can be found at this link: https://rapidapi.com/OSoMe/api/botometer-pro/details
DOI: 10.5281/zenodo.6837711
title: The Good First Issue Recommendation Dataset from "GFI-Bot: Automated Good First Issue Recommendation on GitHub"

description: This is a good first issue (GFI) recommendation dataset created from the GFI-Bot project (https://github.com/osslab-pku/gfi-bot). For more information about the GFI recommendation problem and GFI-Bot, please check our publications: Wenxin Xiao, Hao He, Weiwei Xu, Xin Tan, Jinhao Dong, and Minghui Zhou. 2022. Recommending Good First Issues in GitHub OSS Projects. In Proceedings of the 44th International Conference on Software Engineering, ICSE 2022, Pittsburgh, PA, USA, May 21–29, 2022. ACM. https://hehao98.github.io/files/2022-recgfi.pdf Hao He, Haonan Su, Wenxin Xiao, Runzhi He, and Minghui Zhou. 2022. GFI-Bot: Automated Good First Issue Recommendation on GitHub. In Proceedings of the 2022 ACM 30th Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022, Singapore, November 14-16, 2022. ACM. https://hehao98.github.io/files/2022-gfibot.pdf The dataset is a MongoDB dump and needs to be restored to a MongoDB instance before use. This can be done via the official <code>mongorestore</code> tool by running a command like this in the <code>dataset/</code> folder: <pre><code class="language-bash">mongorestore --uri={{ your mongodb url }} --gzip </code></pre> In the <code>gfibot.dataset</code> collection, each document describes the state of an issue at a certain time (either at the time of issue creation or at the time of issue resolution). The <code>resolver_commit_num</code> is the ground truth label (i.e., # of commits the issue resolver has made in the repository before issue resolution, excluding commits for resolving the issue itself; <code>resolver_commit_num = 0</code> means the resolver is someone completely new to the repository). The remaining fields can be used as features or further analyzed to derive new features. The <code>gfibot.resolved_issue</code> collection additionally provides information about which GitHub user resolved this issue and in what commit or pull request. This information can be used to study problems like, e.g., personalized good first issue recommendation or newcomer retention mechanisms. This dataset can be used to evaluate new GFI recommendation approaches. We hope it will be helpful in advancing GFI recommendation research and other future studies on open-source software onboarding.
DOI: 10.5281/zenodo.6665931
title: The Good First Issue Recommendation Dataset from "GFI-Bot: Automated Good First Issue Recommendation on GitHub"

description: This is a good first issue (GFI) recommendation dataset created from the GFI-Bot project (https://github.com/osslab-pku/gfi-bot). For more information about the GFI recommendation problem and GFI-Bot, please check our publications: Wenxin Xiao, Hao He, Weiwei Xu, Xin Tan, Jinhao Dong, and Minghui Zhou. 2022. Recommending Good First Issues in GitHub OSS Projects. In Proceedings of the 44th International Conference on Software Engineering, ICSE 2022, Pittsburgh, PA, USA, May 21–29, 2022. ACM. https://hehao98.github.io/files/2022-recgfi.pdf Hao He, Haonan Su, Wenxin Xiao, Runzhi He, and Minghui Zhou. 2022. GFI-Bot: Automated Good First Issue Recommendation on GitHub. In Proceedings of the 2022 ACM 30th Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022, Singapore, November 14-16, 2022. ACM. https://hehao98.github.io/files/2022-gfibot.pdf The dataset is a MongoDB dump and needs to be restored to a MongoDB instance before use. This can be done via the official <code>mongorestore</code> tool by running a command like this in the <code>dataset/</code> folder: <pre><code class="language-bash">mongorestore --uri={{ your mongodb url }} --gzip </code></pre> In the <code>gfibot.dataset</code> collection, each document describes the state of an issue at a certain time (either at the time of issue creation or at the time of issue resolution). The <code>resolver_commit_num</code> is the ground truth label (i.e., # of commits the issue resolver has made in the repository before issue resolution, excluding commits for resolving the issue itself; <code>resolver_commit_num = 0</code> means the resolver is someone completely new to the repository). The remaining fields can be used as features or further analyzed to derive new features. The <code>gfibot.resolved_issue</code> collection additionally provides information about which GitHub user resolved this issue and in what commit or pull request. This information can be used to study problems like, e.g., personalized good first issue recommendation or newcomer retention mechanisms. This dataset can be used to evaluate new GFI recommendation approaches. We hope it will be helpful in advancing GFI recommendation research and other future studies on open-source software onboarding.
DOI: 10.57909/planet/planetscope3band.001
title: PlanetScope Satellite Imagery 3 Band Scene
DOI: 10.6084/m9.figshare.20487870
title: Compliance with International Committee of Medical Journal Editors policy on individual participant data sharing in clinical trial registries: an audit. - Supplementaty Data

description: Supplementary Data for : Borana R, Bhaumik S. Compliance with International Committee of Medical Journal Editors policy on individual participant data sharing in clinical trial registries: An audit. Perspect Clin Res 2022.
DOI: 10.34740/kaggle/dsv/4072995
title: WallStreetBets 2022
DOI: 10.6084/m9.figshare.20488176.v1
title: Supplementary Material

description: Supplementary Material S1-S5
DOI: 10.6084/m9.figshare.20488176
title: Supplementary Material

description: Supplementary Material S1-S5
DOI: 10.5281/zenodo.6991805
title: Original data for: Probing luminescence of rare earth ions in natural pink fluorites using Raman microscopes

description: Data for Publication: Probing luminescence of rare earth ions in natural pink fluorites using Raman microscopes<br> Hans Hagemann, Sareh Ayoubipour, Teresa Delgado, Cédric Schnyder, Edwin Gnos Journal of Raman Spectroscopy, 2022;53:1464–1470 https://doi.org/10.1002/jrs.6383
DOI: 10.5281/zenodo.6991804
title: Original data for: Probing luminescence of rare earth ions in natural pink fluorites using Raman microscopes

description: Data for Publication: Probing luminescence of rare earth ions in natural pink fluorites using Raman microscopes<br> Hans Hagemann, Sareh Ayoubipour, Teresa Delgado, Cédric Schnyder, Edwin Gnos Journal of Raman Spectroscopy, 2022;53:1464–1470 https://doi.org/10.1002/jrs.6383
DOI: 10.25442/hku.20480172
title: Geospatial data list

description: A list of geospatial data contained in this collection and their respective descriptions.
DOI: 10.5281/zenodo.6991850
title: Original data for publications: Synthesis, Characterization, and Crystal Structures of Two New Manganese Aceto EMIM Ionic Compounds with Chains of Mn2+ Ions Coordinated Exclusively by Acetate, and: Fe4(OAc)10[EMIM]2: Novel Iron-Based Acetate EMIM Ionic Compound

description: Origianl data for publications (Part of University of Geneva only): Synthesis, Characterization, and Crystal Structures of Two New Manganese Aceto EMIM Ionic Compounds with Chains of Mn2+ Ions Coordinated Exclusively by Acetate<br> Przemyslaw Dera, Edward Bruffey III, Gregory J. Finkelstein, Colleen Kelly, Angelina Gigante, Hans Hagemann, and Godwin Severa<br> ACS Omega 2020, 5, 25, 15592-15600 Fe4(OAc)10[EMIM]2: Novel Iron-Based Acetate EMIM Ionic Compound<br> Godwin Severa, Edward Bruffey, Phuong Q. H. Nguyen, Angelina Gigante, Noemi Leick, Colleen Kelly, Gregory J. Finkelstein, Hans Hagemann, Thomas Gennett, Richard E. Rocheleau, and Przemyslaw Dera,<br> ACS Omega 2021, 6, 31907-31918.
DOI: 10.5281/zenodo.6991849
title: Original data for publications: Synthesis, Characterization, and Crystal Structures of Two New Manganese Aceto EMIM Ionic Compounds with Chains of Mn2+ Ions Coordinated Exclusively by Acetate, and: Fe4(OAc)10[EMIM]2: Novel Iron-Based Acetate EMIM Ionic Compound

description: Origianl data for publications (Part of University of Geneva only): Synthesis, Characterization, and Crystal Structures of Two New Manganese Aceto EMIM Ionic Compounds with Chains of Mn2+ Ions Coordinated Exclusively by Acetate<br> Przemyslaw Dera, Edward Bruffey III, Gregory J. Finkelstein, Colleen Kelly, Angelina Gigante, Hans Hagemann, and Godwin Severa<br> ACS Omega 2020, 5, 25, 15592-15600 Fe4(OAc)10[EMIM]2: Novel Iron-Based Acetate EMIM Ionic Compound<br> Godwin Severa, Edward Bruffey, Phuong Q. H. Nguyen, Angelina Gigante, Noemi Leick, Colleen Kelly, Gregory J. Finkelstein, Hans Hagemann, Thomas Gennett, Richard E. Rocheleau, and Przemyslaw Dera,<br> ACS Omega 2021, 6, 31907-31918.
DOI: 10.25442/hku.20472162
title: The North Atlantic Treaty Organization (NATO)

description: Description The geometry of 30 member countries, which have joined NATO, an intergovernmental military alliance, up until August 2022. According to the official website of NATO, it aims to guarantee the freedom and security of its members through political and military means. An interactive view of this dataset: Link Source Data were collected from the official website of NATO. The geospatial features, including polygons and boundaries of regions, are sourced from Natural Earth, Admin 0 – Countries version 5.1.1 (Published on 12 May 2022). For metadata, such as data description and available methods for geospatial data processing, please read the readme.pdf. Terms of use This dataset features in a collection of geospatial data "Geo-mapping databases for the Belt and Road Initiative". To cite this work, available citation styles can be found here: https://doi.org/10.6084/m9.figshare.c.6076193
DOI: 10.25442/hku.20472162.v1
title: The North Atlantic Treaty Organization (NATO)

description: Description The geometry of 30 member countries, which have joined NATO, an intergovernmental military alliance, up until August 2022. According to the official website of NATO, it aims to guarantee the freedom and security of its members through political and military means. An interactive view of this dataset: Link Source Data were collected from the official website of NATO. The geospatial features, including polygons and boundaries of regions, are sourced from Natural Earth, Admin 0 – Countries version 5.1.1 (Published on 12 May 2022). For metadata, such as data description and available methods for geospatial data processing, please read the readme.pdf. Terms of use This dataset features in a collection of geospatial data "Geo-mapping databases for the Belt and Road Initiative". To cite this work, available citation styles can be found here: https://doi.org/10.6084/m9.figshare.c.6076193