cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25502/ntdn-xt14/d
title: CIALCA-Base

description: The Consortium for Improving Agriculture-based Livelihoods in Central Africa (CIALCA) is an innovative research-for-development partnership operating in Burundi, eastern DR Congo and Rwanda. CIALCA is led by IITA, Bioversity International and FAO/IAEA and has a 12-year legacy of conducting agricultural research for development in Central Africa. Since its initial establishment in 2006 the Consortium has been supported by the Belgian Directorate General for Development Cooperation and Humanitarian Aid (DGD). Since its establishment in 2006, CIALCA has been operating along 3 integrated Pillars. They form the foundation of CIALCA and the basis for the success of CIALCA in the Great Lakes Region. In operationalizing its strategy, CIALCA works with government, public and private partners on three cross-cutting themes: entrepreneurial farming, ICT for Agriculture, and integrated agricultural systems for nutrition. 

CIALCA invests heavily in developing smart ICT4Ag decision support tools, and training colleagues, students and decision-makers in using the tools to develop and implement more impactful agricultural development strategies. All CIALCA data is collected using Open Data Kit (ODK) systems that feed into a centralised database that is freely accessible for our CIALCA network and partners. CIALCA collaborates with other CGIAR Big Data initiatives such as RHoMIS and African Cassava Agronomy Initiative (ACAI) to ensure that CIALCA data can be integrated at regional and global level. It allows for the development and implementation of agricultural strategies that respond to the needs of different types of farmers in the Great Lakes Region. One of the outputs of the collaborative work of CIALCA and the move towards wholly digital data collection is CIALCA-Base.

CIALCA-Base has been developed as a repository of all household surveying performed historically, presently, and part of future of CIALCA work. CIALCA-Base brings together from within the consortium, PhD and master students, and CIALCA co-funded research. CIALCABase is a collaborative resource for CIALCA researchers, students, and partners to be understanding the minutiae and diversity of farming households across central Africa. 

CIALCA-Base currently includes household survey data from more than 3500 households collected from two countries. This data has been collected from the current phase of the consortium (2017-2020). However, CIALCA researchers are working hard to bring data online from surveys performed for developing an initial baseline in 2006 and follow up data collected in 2014. This will allow CIALCA to develop panel analyses and begin to get an understanding of how farms across Burundi, DR Congo, and Rwanda have changed over the past 13 years.
DOI: 10.25810/fx6e-r462.8
title: European Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - November 2019

description: The Media and Climate Change Observatory Data monitors 113 sources (across newspapers, radio and TV) in 55 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/media_coverage.
DOI: 10.25810/rxtv-eb29.20
title: German Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - November 2019

description: The Media and Climate Change Observatory Data monitors 113 sources (across newspapers, radio and TV) in 55 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/media_coverage.
DOI: 10.5517/ccdc.csd.cc233drd
title: CCDC 1939693: Experimental Crystal Structure Determination

description: Related Article: Arron C. Deacy, Christopher B. Durr, Charlotte K. Williams|2020|Dalton Trans.|49|223|doi:10.1039/C9DT02918D
DOI: 10.5517/ccdc.csd.cc23kj3b
title: CCDC 1953251: Experimental Crystal Structure Determination

description: Related Article: Yannic Heider,  Philipp Willmes,  Volker Huch,  Michael Zimmer,  David Scheschkewitz|2019|J.Am.Chem.Soc.|141|19498|doi:10.1021/jacs.9b11181
DOI: 10.5517/ccdc.csd.cc23n857
title: CCDC 1955888: Experimental Crystal Structure Determination

description: Related Article: Yan Guo,  Zhengqiang Xia,  Jingjing Liu,  Jiaxiu Yu,  Shenglai Yao,  Weiqun Shi,  Kongqiu Hu,  Sanping Chen,  Yaoyu Wang,  Anyang Li,  Matthias Driess,  Wenyuan Wang|2019|J.Am.Chem.Soc.|141|19252|doi:10.1021/jacs.9b10946
DOI: 10.5517/ccdc.csd.cc23p88c
title: CCDC 1956852: Experimental Crystal Structure Determination

description: Related Article: Stephan Hagspiel, Merle Arrowsmith, Felipe Fantuzzi, Alexander Hermann, Valerie Paprocki, Regina Drescher, Ivo Krummenacher, Holger Braunschweig|2020|Chemical Science|11|551|doi:10.1039/C9SC05026D
DOI: 10.5517/ccdc.csd.cc23p89d
title: CCDC 1956853: Experimental Crystal Structure Determination

description: Related Article: Stephan Hagspiel, Merle Arrowsmith, Felipe Fantuzzi, Alexander Hermann, Valerie Paprocki, Regina Drescher, Ivo Krummenacher, Holger Braunschweig|2020|Chemical Science|11|551|doi:10.1039/C9SC05026D
DOI: 10.5517/ccdc.csd.cc23r1zx
title: CCDC 1958579: Experimental Crystal Structure Determination

description: Related Article: Shanwen Zhang,  Qing Xie,  Changli Sun,  Xin-Peng Tian,  Chun Gui,  Xiangjing Qin,  Hua Zhang,  Jianhua Ju|2019|J.Nat.Prod.|82|3366|doi:10.1021/acs.jnatprod.9b00654
DOI: 10.5517/ccdc.csd.cc23sj2j
title: CCDC 1959977: Experimental Crystal Structure Determination

description: Related Article: Liu Ye, Yu Tian, Xiang Meng, Qiang-Shuai Gu, Xin-Yuan Liu|2020|Angew.Chem.,Int.Ed.|59|1129|doi:10.1002/anie.201911742
DOI: 10.25318/1310003401-eng
title: Low birth weight babies (less than 2,500 grams), by sex, three-year average, Canada, provinces, territories, health regions and peer groups

description: This table contains 3006 series, with data for years 1997 - 2001 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (167 items: Canada; Health and Community Services Eastern Region; Newfoundland and Labrador; Health and Community Services St. John's Region; Newfoundland and Labrador; Newfoundland and Labrador ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (6 items: Number of low birth weight babies; Low 95% confidence interval; number of low birth weight babies; High 95% confidence interval; number of low birth weight babies; Proportion of low birth weight babies ...).
DOI: 10.25318/2410002601-eng
title: Travel price index, quarterly

description: This table contains 1 series, with data for years 1980 - 2006 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Price index (1 item: Travel price index).
DOI: 10.25318/2410002601-fra
title: Indice de prix des voyage, trimestriel

description: Ce tableau contient 1 séries, avec des données pour les années 1980 - 2006 (il n'y a pas nécessairement de données pour toutes les années pour l'ensemble des combinaisons), et sa mise à jour n'a plus lieu. Ce tableau contient des données telles que décrites par les dimensions suivantes (Les combinaisons ne sont pas toutes disponibles) : Géographie (1 élément : Canada), Indice de prix (1 élément : Indice des prix des voyages).
DOI: 10.25318/2410002701-fra
title: Nombre de voyages domestiques faits par les résidents du Canada, par caractéristiques des voyages, inactif

description: Enquête sur les voyages des résidents du Canada, voyages domestiques, dépenses, et nuitées, au Canada, selon les caractéristiques des voyages et la durée du voyage annuel (voyages-personnes sauf indication contraire x 1 000).
DOI: 10.25810/558f-c477.20
title: Australian Newspaper Coverage of Climate Change or Global Warming, 2000-2019 - November 2019

description: The Media and Climate Change Observatory Data monitors 113 sources (across newspapers, radio and TV) in 55 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/media_coverage.
DOI: 10.25810/es52-xr23.20
title: Canadian Newspaper Coverage of Climate Change or Global Warming, 2000-2019 - November 2019

description: The Media and Climate Change Observatory Data monitors 113 sources (across newspapers, radio and TV) in 55 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/media_coverage.
DOI: 10.5517/ccdc.csd.cc1pmrgj
title: CCDC 1568118: Experimental Crystal Structure Determination

description: Related Article: Hai-Ling Chen, Rong-Tian Li, Ke-Yang Wu, Pei-Pei Hu, Zhe Zhang, Nai-Han Huang, Wen-Hua Zhang, Jin-Xiang Chen|2019|Talanta|210|120596|doi:10.1016/j.talanta.2019.120596
DOI: 10.5517/ccdc.csd.cc1q5zjd
title: CCDC 1584674: Experimental Crystal Structure Determination

description: Related Article: Hao-Zhao Wei, Liu-Zhu Yu, Min Shi|2020|Org.Biomol.Chem.|18|135|doi:10.1039/C9OB02211B
DOI: 10.5517/ccdc.csd.cc1z4k9z
title: CCDC 1821631: Experimental Crystal Structure Determination

description: Related Article: Marta Falcone, Luciano Barluzzi, Julie Andrez, Farzaneh Fadaei Tirani, Ivica Zivkovic, Alberto Fabrizio, Clemence Corminboeuf, Kay Severin, Marinella Mazzanti|2019|Nature Chemistry|11|154|doi:10.1038/s41557-018-0167-8
DOI: 10.5517/ccdc.csd.cc21vc6h
title: CCDC 1902166: Experimental Crystal Structure Determination

description: Related Article: Meixia Zhou, Xizhou Zheng, Yaorong Wang, Dan Yuan, Yingming Yao|2019|ChemCatChem|11|5783|doi:10.1002/cctc.201900221
DOI: 10.6084/m9.figshare.22266097.v1
title: Response to drift kelp is modified by both substratum and season: green sea urchin foraging behaviour in subsidized habitats

description: The ability of organisms to detect, locate and navigate to resource patches is modified by the surrounding landscape. Green sea urchins (<em>Strongylocentrotus droebachiensis</em>) in barren grounds exist in a food-limited state and are subject to intense competition. Rapid detection and consumption of resource patches, particularly pieces of macroalgae from adjacent algal beds, are key in determining individual growth, survival and reproductive success. Detection and movement to resource patches requires moving through a heterogeneous benthic seascape composed of rocky and sandy patches, presenting different degrees of resistance to movement. We used time-lapse photography to describe the foraging behaviour of urchins in relation to the presence of a key resource subsidy (drift kelp) and different benthic seascapes. We demonstrated that urchins could detect the presence of drift kelp in barren ground habitats and alter their movement behaviour in response, but did not exhibit the ability to directionally navigate towards kelp in field conditions. Seascapes with increased proportions of rocky substrata facilitated increased movement in response to the presence of drift. Moreover, urchin foraging behaviour was temporally variable, with no response to the presence of drift in early spring (May). This indicates not only that interpretations of observations of urchin behaviour must take intrinsic and extrinsic seasonal dynamics into account, but that extrapolating results to explain larger-scale patterns and processes must include both spatially explicit subtidal seascapes and temporal dynamics. In many temperate and boreal regions, this indicates the need for increased subtidal benthic research in the fall and winter. <br> All data used for analysis and presentation of the results are included here, along with R scripts used for analysis. Datasets include original points extracted from photo sequences, images, a track-level dataset combined with both spatial and current information, a step-level dataset combined with both spatial and current information, urchin density data per sequence, spatial information per time-lapse sequence, and metadata per time-lapse sequence. R scripts include the files for analyses, including a R script detailing the preprocessing and order of scripts used in data treatment and analysis and creation of figures presented the published manuscript.
DOI: 10.3886/icpsr24057.v2
title: Federal Justice Statistics Program: Defendants in Federal Criminal Cases Filed in District Court, 1998 [United States]
title: Version 2

description: The data contain records of defendants in criminal cases filed in United States District Court during fiscal year 1998. The data were constructed from the Administrative Office of the United States District Courts' (AOUSC) criminal file. Defendants in criminal cases may be either individuals or corporations. There is one record for each defendant in each case filed. Included in the records are data from court proceedings and offense codes for up to five offenses charged at the time the case was filed. (The most serious charge at termination may differ from the most serious charge at case filing, due to plea bargaining or action of the judge or jury.) In a case with multiple charges against the defendant, a "most serious" offense charge is determined by a hierarchy of offenses based on statutory maximum penalties associated with the charges. The data file contains variables from the original AOUSC files as well as additional analysis variables, or "SAF variables," that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 4.1-4.5 and 5.1-5.6. Variables containing information (e.g., name, Social Security number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.
description: Datasets: DS1: Federal Justice Statistics Program: Defendants in Federal Criminal Cases Filed in District Court, 1998 [United States]
description: Criminal cases filed in United States District Court during fiscal year 1998.
DOI: 10.3886/icpsr24057
title: Federal Justice Statistics Program: Defendants in Federal Criminal Cases Filed in District Court, 1998 [United States]
title: Archival Version

description: The data contain records of defendants in criminal cases filed in United States District Court during fiscal year 1998. The data were constructed from the Administrative Office of the United States District Courts' (AOUSC) criminal file. Defendants in criminal cases may be either individuals or corporations. There is one record for each defendant in each case filed. Included in the records are data from court proceedings and offense codes for up to five offenses charged at the time the case was filed. (The most serious charge at termination may differ from the most serious charge at case filing, due to plea bargaining or action of the judge or jury.) In a case with multiple charges against the defendant, a "most serious" offense charge is determined by a hierarchy of offenses based on statutory maximum penalties associated with the charges. The data file contains variables from the original AOUSC files as well as additional analysis variables, or "SAF variables," that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 4.1-4.5 and 5.1-5.6. Variables containing information (e.g., name, Social Security number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.
description: Datasets: DS1: Federal Justice Statistics Program: Defendants in Federal Criminal Cases Filed in District Court, 1998 [United States]
description: Criminal cases filed in United States District Court during fiscal year 1998.
DOI: 10.3886/icpsr24059.v2
title: Federal Justice Statistics Program: Defendants in Federal Criminal Cases in District Court -- Pending, 1998 [United States]
title: Version 2

description: The data contain records of defendants in criminal cases filed in United States District Court before or during fiscal year 1998 and still pending as of year-end. The data were constructed from the Administrative Office of the United States District Courts' (AOUSC) criminal file. Defendants in criminal cases may be either individuals or corporations. There is one record for each defendant in each case filed. Included in the records are data from court proceedings and offense codes for up to five offenses charged at the time the case was filed. (The most serious charge at termination may differ from the most serious charge at case filing, due to plea bargaining or action of the judge or jury.) In a case with multiple charges against the defendant, a "most serious" offense charge is determined by a hierarchy of offenses based on statutory maximum penalties associated with the charges. The data file contains variables from the original AOUSC files as well as additional analysis variables, or "SAF" variables, that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 4.1-4.5 and 5.1-5.6. Variables containing identifying information (e.g., name, Social Security number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.
description: Datasets: DS1: Federal Justice Statistics Program: Defendants in Federal Criminal Cases in District Court -- Pending, 1998 [United States]
description: Criminal cases filed in United States District Court during fiscal year 1998 and still pending as of year-end.
DOI: 10.5281/zenodo.4416179
title: New England Protected Open Space

description: The New England Protected Open Space dataset maintained by Harvard Forest is a compilation of existing open space datasets in the New England region including The Nature Conservancy's Secured Areas, National Conservation Easement Database, Protected Areas Database of the U.S., and data provided by states and land trusts. Two formats of the data are available here: a file geodatabase feature class (POS.gdb.zip) and a shapefile (POS_shp.zip). It is recommended to use the geodatabase feature class if you have access to Esri products, as the POS field names are all longer than 10 characters and are truncated in the shapefile version. Version 1.1 is a partial update, rather than an exhaustive update using all data sources - please read the metadata for more details!
DOI: 10.5281/zenodo.4688018
title: New England Protected Open Space

description: The New England Protected Open Space dataset maintained by Harvard Forest is a compilation of existing open space datasets in the New England region including The Nature Conservancy's Secured Areas, National Conservation Easement Database, Protected Areas Database of the U.S., and data provided by states and land trusts. Data are provided with the full attribute table and with minimal attribute table that keeps only the most essential fields (these have "_min" in the file name). The data with full and minimal attribute tables are available as file geodatabase feature classes (POS.gdb.zip) and shapefiles (POSv1_1_April2021.zip, POSv1_1_April2021_min.zip). It is recommended to use the geodatabase feature class if you have access to Esri products, as the POS field names are all longer than 10 characters and are truncated in the shapefile versions. Version 1.1 is a partial update, rather than an exhaustive update using all data sources - please read the metadata for more details!
DOI: 10.5281/zenodo.7577253
title: New England Protected Open Space

description: The New England Protected Open Space dataset maintained by Harvard Forest is a compilation of existing open space datasets in the New England region including The Nature Conservancy's Secured Areas, National Conservation Easement Database, Protected Areas Database of the U.S., and data provided by states and land trusts. See metadata for each version for version-specific information and information about fields. <strong>Important note about versions of NE POS: </strong>NE POS is a dataset we maintain for research purposes, and research projects can take varying lengths of time. Versions of NE POS may be uploaded to Zenodo "out of order," meaning older versions of data may be uploaded after more recent versions have been published. Use the version number to identify the recency of the data rather than the date of upload. Version 1.0.1 was uploaded in January 2023 but has the same spatial data as v1.0.0. Version 1.0.1 has an extra column that was used for analysis, and the upload is provided with a subset of all NE POS fields. For the same spatial data with all NE POS fields, or a geodatabase feature class, use v1.0.0.
DOI: 10.5281/zenodo.3606762
title: New England Protected Open Space

description: The New England Protected Open Space dataset maintained by Harvard Forest is a compilation of existing open space datasets in the New England region including The Nature Conservancy's Secured Areas, National Conservation Easement Database, Protected Areas Database of the U.S., and data provided by states and land trusts. See metadata for each version for version-specific information and information about fields. Version 1.2 was developed between May 2021 and March 2022, and was published in March 2023. Version 1.2 has new data from multiple sources added circa May 2021, more complete attribute information, and tribal lands removed. See metadata for more details. File geodatabase and shapefile versions are provided - refer to metadata for full field names if using shapefile version, as names will be truncated. <strong>Important note about versions of NE POS: </strong>NE POS is a dataset we maintain for research purposes, and research projects can take varying lengths of time. Versions of NE POS may be uploaded to Zenodo "out of order," meaning older versions of data may be uploaded after more recent versions have been published. Use the version number to identify the recency of the data rather than the date of upload.
DOI: 10.5281/zenodo.7473982
title: Alignment bHLH domains

description: alignement used to run the phylogenetic analysis concerning bHLH transcription factors of O. minuta
DOI: 10.5281/zenodo.7473983
title: Alignment bHLH domains

description: alignement used to run the phylogenetic analysis concerning bHLH transcription factors of O. minuta