cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5255/ukda-sn-854954
title: School Segregation Data Linked to Next Steps, Sweeps 1 to 8, 2003-2006

description: The authors of the dataset used the publicly available school level data from the NPD and identified relevant data on the composition of the disadvantaged groups in the school population of full-time equivalent student. In particular, they used six common indicators of disadvantage in schooling that have been identified as potential factors of school stratification by social group: 1) the number of pupils taking free school meals (FSMt), 2) the number known to be eligible for free school meals (FSMe), 3) the number known to have a statement of special educational needs (SENs), 4) the number known to have special needs without a statement (SENn), 5) the number known to have English as a second or additional language (ESL/EAL), and 6) the number classified as white British ethnic origin (NW) The relevant figures for each indicator per school in each year were converted into what has been termed the Gorard Segregation Index (GS) and the Dissimilarity Index (D) at a national level in order to probe into the main characteristics of school segregation: The Gorard Segregation Index (GS) is an index of segregation between schools that refers to “the proportion of potentially disadvantaged students in a school system who would have to exchange schools with another (non-disadvantaged) student for there to be no segregation by disadvantage between schools in that school system (or the area under consideration)” It has the same basis as the disparity ratio used in studies of health. The Dissimilarity Index (D): the residual for D is the absolute value of the result of subtracting the population proportion of non-FSM pupils in each school from the population proportion of FSM pupils in each school; D itself is the sum of these residuals for all schools, then divided by two.
DOI: 10.23698/aida/lnco2
title: Regional lymph node metastasis in colon adenocarcinoma, second collection series

description: Whole slide pathology images from regional lymph node metastasis in colon adenocarcinoma produced at Region Gävleborg Clinical Pathology and Cytology department. Consists of fifty chronologically consecutive cases. This dataset represents a second collection series in connection to the LNCO dataset using different collection and annotation parameters.
DOI: 10.23698/aida/lnco
title: Regional lymph node metastasis in colon adenocarcinoma

description: Whole slide pathology images from regional lymph node metastasis in colon adenocarcinoma produced at Region Gävleborg Clinical Pathology and Cytology department and Region Östergötland Clinical Pathology department. Annotations for AI training produced as part of AIDA clinical fellowship project investigating AI decision support in metastasis detection. This dataset has been extended with a second collection series in the LNCO2 dataset using different collection and annotation parameters.
DOI: 10.34740/kaggle/dsv/2366092
title: Digital Science and Knowledge Transfer Survey 2020
DOI: 10.5281/zenodo.5025868
title: Figure data of 'Epitaxy of advanced nanowire quantum devices'

description: Data belonging to 'Epitaxy of advanced nanowire quantum devices' including metadata files are in this ZIP folder
DOI: 10.5281/zenodo.4572619
title: Figure data of 'Epitaxy of advanced nanowire quantum devices'

description: Data belonging to 'Epitaxy of advanced nanowire quantum devices' including metadata files are in this ZIP folder
DOI: 10.5281/zenodo.5026298
title: Enchelyopus cimbrius SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5026297
title: Enchelyopus cimbrius SPAdes preassembly

description: .
DOI: 10.17030/uclan.data.00000294
title: FrEd Dataset
DOI: 10.18430/m36xep
title: X-ray diffraction data for the crystal structure of Thiamine-monophosphate kinase from Stenotrophomonas maltophilia K279a (6XEP)
DOI: 10.34740/kaggle/dsv/2366192
title: COVID Vaccination in World (updated daily)
DOI: 10.3886/e143142
title: Replication Data for: An Employment Guarantee as Risk Insurance? Assessing the Effects of the NREGS on Agricultural Production Decisions

description: Uninsured risk constrains households in their production decisions in many developing countries. Similarly to crop insurance, employment guarantees can support farmers in managing agricultural production risks. Evidence from representative panel data of Andhra Pradesh, India, suggests that the National Rural Employment Guarantee Scheme (NREGS) reduces households’ uncertainty about future income streams because it provides employment opportunities in rural areas independently of weather shocks and crop failure. Therewith the NREGS makes an ex-post labor supply response to agricultural shocks more efficient. Households with access to the NREGS are found to shift their production toward riskier but also more profitable crops. The observed shifts in agricultural production do considerably raise the profitability of agricultural production and hence the incomes of smallholder farmers. The findings are not driven by changes in the labor or cost intensity of those crops, which supports the idea that the causal mechanism underlying the observed changes is indeed aninsurance effect.
DOI: 10.3886/e143142v1
title: Replication Data for: An Employment Guarantee as Risk Insurance? Assessing the Effects of the NREGS on Agricultural Production Decisions

description: Uninsured risk constrains households in their production decisions in many developing countries. Similarly to crop insurance, employment guarantees can support farmers in managing agricultural production risks. Evidence from representative panel data of Andhra Pradesh, India, suggests that the National Rural Employment Guarantee Scheme (NREGS) reduces households’ uncertainty about future income streams because it provides employment opportunities in rural areas independently of weather shocks and crop failure. Therewith the NREGS makes an ex-post labor supply response to agricultural shocks more efficient. Households with access to the NREGS are found to shift their production toward riskier but also more profitable crops. The observed shifts in agricultural production do considerably raise the profitability of agricultural production and hence the incomes of smallholder farmers. The findings are not driven by changes in the labor or cost intensity of those crops, which supports the idea that the causal mechanism underlying the observed changes is indeed aninsurance effect.
DOI: 10.5255/ukda-sn-854969
title: End Line Evaluation of the Project Sister for Sister's Education-II, 2021

description: Sisters for Sisters' Education II (SfSE-II) project is funded by Foreign Commonwealth and Development Office’s Girls’ Education Challenge Transition Window (GEC T) and builds on the achievements of phase I (2013 – 2017). The project was implemented by the VSO in Nepal with the British Council as resource partner and Mercy Corp as the technical partner in four districts of Nepal: Dhading, Lamjung, Parsa, and Surkhet. Foundation of Development Management (FDM) conducted a longitudinal evaluation of the project, of which FDM was part of the midline and endline evaluation. Here, the FDM is submitting the quantitative data of the end-line evaluation gathered through the Household and Girls’ Survey. The project stands on three major components: learning, transition, and sustainability. To supplement these outcomes, five intermediate outcomes, namely, attendance, self-esteem and empowerment of the girls, parental engagement in girl’s education, teaching quality and gender-responsive school management and governance, were developed. In addition to these pre-developed components, inquiry on the impact of COVID-19 was carried out among the girls. Data concerning these outcomes, intermediate outcomes and the impact of the pandemic were collected through girls’ and household surveys. Due to the limitation posed by the pandemic, data were collected only from the treatment schools. The dataset of the girls and households survey has been attached herein along with a codebook to ensure further clarity on the dataset.
DOI: 10.5066/p9bszm8r
title: Integrated modeling of climate and land change impacts on future dynamic wetland habitat ? a case study from California?s Central Valley

description: This dataset consists of raster geotiff and tabular outputs of annual map projections of land use and land cover for the California Central Valley for the period 2011-2101 across 5 future scenarios. Four of the scenarios were developed as part of the Central Valley Landscape Conservation Project. The 4 original scenarios include a Bad-Business-As-Usual (BBAU; high water, poor management), California Dreamin? (DREAM; high water, good management), Central Valley Dustbowl (DUST; low water, poor management), and Everyone Equally Miserable (EEM; low water, good management). These scenarios represent alternative plausible futures, capturing a range of climate variability, land management activities, and habitat restoration goals. We parameterized our models based on close interpretation of these four scenario narratives to best reflect stakeholder interests, adding a baseline Historical Business-As-Usual scenario (HBAU) for comparison. For these future map projections, the model was initialized in 2011 and run forward on an annual time step to 2101. There are 5 datasets included in this Data Release summarizing data across the 5 scenarios including: 1) State Class Rasters = maps of annual LULC, 2) State Class Spreadsheet = tabular output of annual LULC by region and WEAP zone, 3) State Class Transition Spreadsheet = annual tabular output of changes in LULC, 4) TGAP Class Transition Rasters = annual raster maps by specific LULC transition type, and 5) TGAP Flooding Probability Rasters = maps of 30-year average annual transition probabilties across 32 different flooding classes. The datasets were generated from the LUCAS ST-SIM model as described in the parent manuscript. The data can be used to visualize annual land-use and land-cover (LULC), LULC transitions, probability of fallowing, and probability of flooding across the region for each modeled year and scenario, highlighting the spatial and temporal distribution of potential future ecological and waterbird habitat. The full methods and results of this research are described in detail in the parent manuscript "Integrated modeling of climate and land change impacts on future dynamic wetland habitat ? a case study from California?s Central Valley" (2021).
DOI: 10.5281/zenodo.5026440
title: Merluccius paradoxus SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5026439
title: Merluccius paradoxus SPAdes preassembly

description: .
DOI: 10.5281/zenodo.4897295
title: NMR Spectra (1H and HSQC) of terpenes

description: This repository contains 1D and 2D NMR (Nuclear Magnetic Resonance) spectroscopy data as well as Matlab and Python scripts to load and display these data. Note: the Matlab scripts are compatible with Octave. <strong>Description of the data:</strong> The data made available are Terpenes data (Limonene, Nerol, alpha-Terpinolene, beta-Caryophyllene). Objective: these data have been acquired in order to apply source separation algorithms, that is to say, from the mixture spectra, find the mixture matrix and the pure spectra. These data can be loaded and visualized thanks to the provided scripts (see the following Scripts section). Terpenes_US_1D.mat : this file contains the mixing matrix, the 1D pure spectra (4 components) and the 1D mixture spectra (5 mixtures) Terpenes_US_2D.mat: this file contains the mixing matrix, the 2D pure spectra (4 components) and the 2D mixture spectra (5 mixtures) Ce dépôt contient des données de spectroscopie RMN (Résonance Magnétique Nucléaire) 1D et 2D ainsi que des scripts Matlab et Python afin de charger et afficher ces données. Note : les scripts Matlab sont compatibles avec Octave. <strong>Description des données:</strong> Les données mises à disposition sont des données de Terpènes (Limonène, Nérol, alpha-Terpinolène, beta-Caryophyllène). Objectif : ces données ont été acquises dans le but d'y appliquer des algorithmes de séparation de sources, c'est à dire, à partir des spectres de mélanges, retrouver la matrice de mélange et les spectres des sources pures. Ces données sont chargeables et visualisables grâce aux scripts fournis (voir la section Scripts suivante). Terpenes_US_1D.mat : ce fichier contient la matrice de mélange, les spectres purs 1D (4 composants) et les spectres de mélanges 1D (5 mélanges) Terpenes_US_2D.mat : ce fichier contient la matrice de mélange, les spectres purs 2D (4 composants) et les spectres de mélanges 2D (5 mélanges) <strong>Publication associated to this dataset / Publication associée à ce jeu de données :</strong> Afef Cherni, Elena Piersanti, Sandrine Anthoine, Caroline Chaux, Laetitia Shintu, et al.. Challenges in the decomposition of 2D NMR spectra of mixtures of small molecules. <em>Faraday Discussions</em>, Royal Society of Chemistry, 2019. 〈hal-02146311〉
description: The project leading to this dataset has received funding from the Excellence Initiative of Aix-Marseille University - A*Midex, a French "Investissements d'Avenir" programme. Ce travail a bénéficié d'une aide du gouvernement français au titre du Programme Investissements d'Avenir, Initiative d'Excellence d'Aix-Marseille Université - A*Midex.
DOI: 10.5281/zenodo.4897068
title: NMR Spectra (1H and HSQC) of terpenes

description: This repository contains 1D and 2D NMR (Nuclear Magnetic Resonance) spectroscopy data as well as Matlab and Python scripts to load and display these data. Note: the Matlab scripts are compatible with Octave. <strong>Description of the data:</strong> The data made available are Terpenes data (Limonene, Nerol, alpha-Terpinolene, beta-Caryophyllene). Objective: these data have been acquired in order to apply source separation algorithms, that is to say, from the mixture spectra, find the mixture matrix and the pure spectra. These data can be loaded and visualized thanks to the provided scripts (see the following Scripts section). Terpenes_US_1D.mat : this file contains the mixing matrix, the 1D pure spectra (4 components) and the 1D mixture spectra (5 mixtures) Terpenes_US_2D.mat: this file contains the mixing matrix, the 2D pure spectra (4 components) and the 2D mixture spectra (5 mixtures) Ce dépôt contient des données de spectroscopie RMN (Résonance Magnétique Nucléaire) 1D et 2D ainsi que des scripts Matlab et Python afin de charger et afficher ces données. Note : les scripts Matlab sont compatibles avec Octave. <strong>Description des données:</strong> Les données mises à disposition sont des données de Terpènes (Limonène, Nérol, alpha-Terpinolène, beta-Caryophyllène). Objectif : ces données ont été acquises dans le but d'y appliquer des algorithmes de séparation de sources, c'est à dire, à partir des spectres de mélanges, retrouver la matrice de mélange et les spectres des sources pures. Ces données sont chargeables et visualisables grâce aux scripts fournis (voir la section Scripts suivante). Terpenes_US_1D.mat : ce fichier contient la matrice de mélange, les spectres purs 1D (4 composants) et les spectres de mélanges 1D (5 mélanges) Terpenes_US_2D.mat : ce fichier contient la matrice de mélange, les spectres purs 2D (4 composants) et les spectres de mélanges 2D (5 mélanges) <strong>Publication associated to this dataset / Publication associée à ce jeu de données :</strong> Afef Cherni, Elena Piersanti, Sandrine Anthoine, Caroline Chaux, Laetitia Shintu, et al.. Challenges in the decomposition of 2D NMR spectra of mixtures of small molecules. <em>Faraday Discussions</em>, Royal Society of Chemistry, 2019. 〈hal-02146311〉
description: The project leading to this dataset has received funding from the Excellence Initiative of Aix-Marseille University - A*Midex, a French "Investissements d'Avenir" programme. Ce travail a bénéficié d'une aide du gouvernement français au titre du Programme Investissements d'Avenir, Initiative d'Excellence d'Aix-Marseille Université - A*Midex.
DOI: 10.5519/qd.tgabggpp
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4835102 records)
DOI: 10.5281/zenodo.5025066
title: Data Matrix Theme-Specific Analysis of the Recommendation on Science and Scientific Researchers (RSSR): Public and Stakeholder Engagement

description: This Table sets out findings from the mapping exercise conducted as part of the objectives of subtask 6.1 of the RRING project. Aim: Alignment of RRI to advance the UN SDGs. Objectives: Mapping the RSSR to the SDGs Mapping the RSSR to the SDGs is aimed at providing new perspectives, ideas and approaches that can help to improve the operationalization and implementation of each SDG, <em>by facilitating the integration of RRI (or RRI-like) practices in the SDGs, to make them more achievable.</em> The impact of the new perspectives, ideas and approaches in SDG operationalization and implementation will be aimed at the level of <em>national and international policy (making); future research and innovation projects (in industry and academia); as well as education and training of researchers, policy makers and other stakeholders.</em> Two documents were used for this task: 2017 Recommendation on Science and Scientific Researchers ([RSSR], UNESCO), and the United Nations 2030 Agenda for Sustainable Development with the 17 Sustainable Development Goals (SDGs).
DOI: 10.5281/zenodo.5025065
title: Data Matrix Theme-Specific Analysis of the Recommendation on Science and Scientific Researchers (RSSR): Public and Stakeholder Engagement

description: This Table sets out findings from the mapping exercise conducted as part of the objectives of subtask 6.1 of the RRING project. Aim: Alignment of RRI to advance the UN SDGs. Objectives: Mapping the RSSR to the SDGs Mapping the RSSR to the SDGs is aimed at providing new perspectives, ideas and approaches that can help to improve the operationalization and implementation of each SDG, <em>by facilitating the integration of RRI (or RRI-like) practices in the SDGs, to make them more achievable.</em> The impact of the new perspectives, ideas and approaches in SDG operationalization and implementation will be aimed at the level of <em>national and international policy (making); future research and innovation projects (in industry and academia); as well as education and training of researchers, policy makers and other stakeholders.</em> Two documents were used for this task: 2017 Recommendation on Science and Scientific Researchers ([RSSR], UNESCO), and the United Nations 2030 Agenda for Sustainable Development with the 17 Sustainable Development Goals (SDGs).
DOI: 10.5281/zenodo.5025032
title: Data Matrix Theme-Specific Analysis of the Recommendation on Science and Scientific Researchers (RSSR): Ethics and Ethical Governance

description: This Table sets out findings from the mapping exercise conducted as part of the objectives of subtask 6.1 of the RRING project. Aim: Alignment of RRI to advance the UN SDGs. Objectives: Mapping the RSSR to the SDGs Mapping the RSSR to the SDGs is aimed at providing new perspectives, ideas and approaches that can help to improve the operationalization and implementation of each SDG, <em>by facilitating the integration of RRI (or RRI-like) practices in the SDGs, to make them more achievable.</em> The impact of the new perspectives, ideas and approaches in SDG operationalization and implementation will be aimed at the level of <em>national and international policy (making); future research and innovation projects (in industry and academia); as well as education and training of researchers, policy makers and other stakeholders.</em> Two documents were used for this task: 2017 Recommendation on Science and Scientific Researchers ([RSSR], UNESCO), and the United Nations 2030 Agenda for Sustainable Development with the 17 Sustainable Development Goals (SDGs).
DOI: 10.5281/zenodo.5025031
title: Data Matrix Theme-Specific Analysis of the Recommendation on Science and Scientific Researchers (RSSR): Ethics and Ethical Governance

description: This Table sets out findings from the mapping exercise conducted as part of the objectives of subtask 6.1 of the RRING project. Aim: Alignment of RRI to advance the UN SDGs. Objectives: Mapping the RSSR to the SDGs Mapping the RSSR to the SDGs is aimed at providing new perspectives, ideas and approaches that can help to improve the operationalization and implementation of each SDG, <em>by facilitating the integration of RRI (or RRI-like) practices in the SDGs, to make them more achievable.</em> The impact of the new perspectives, ideas and approaches in SDG operationalization and implementation will be aimed at the level of <em>national and international policy (making); future research and innovation projects (in industry and academia); as well as education and training of researchers, policy makers and other stakeholders.</em> Two documents were used for this task: 2017 Recommendation on Science and Scientific Researchers ([RSSR], UNESCO), and the United Nations 2030 Agenda for Sustainable Development with the 17 Sustainable Development Goals (SDGs).
DOI: 10.5066/p9ttlzal
title: Stillwater Complex, Montana: Logs of core drilled by Cyprus in the Chrome Lake area, 1971 to 1980

description: This dataset includes TIFF (Tagged Image File Format) images of graphic drill core logs showing associated drill core information, a TIFF image of the explanation for the lithology and structure sections of the logs, an Esri shapefile of the locations of the drill holes, and fourteen individual .csv files of tabular data that were compiled from handwritten drill core logs. The drill core is from the Stillwater Complex, Montana and was drilled from 1971 to 1980 by the Cyprus Mines Corporation. The core was logged in 1986. The data shown in the graphic drill logs and contained within the .csv files includes lithologic, structure, core recovery, grain size, chromite, sulfide, copper, and nickel mineralization information. The graphic drill logs were created using Golden software's Strater 5 drill core visualization software and are provided with both logarithmic and linear scales. See USGS SIR 2014-5183 (https://pubs.usgs.gov/sir/2014/5183/) for report and spatial data relating to the Stillwater Complex.
DOI: 10.6084/m9.figshare.14838804
title: Marin_etal_soilecolCL.xlsx

description: Database including coordinates (UTM system) (741 in total), citation, DOI identifier, and soil taxa and ecosystem function investigated in Chile, from a Web of Science (1945-2020) search.
DOI: 10.6084/m9.figshare.14838804.v1
title: Marin_etal_soilecolCL.xlsx

description: Database including coordinates (UTM system) (741 in total), citation, DOI identifier, and soil taxa and ecosystem function investigated in Chile, from a Web of Science (1945-2020) search.
DOI: 10.5281/zenodo.5026617
title: Merluccius productus SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5026616
title: Merluccius productus SPAdes preassembly

description: .
DOI: 10.6084/m9.figshare.14838825.v1
title: Figure data used in the manuscript entitled 'Historical dynamics of landslide risk from population and forest cover changes in the Kivu Rift'

description: This file contains the raw data used for Fig. 3, Fig. 4, and Fig. 5 of the Nature Sustainability manuscript entitled 'Historical dynamics of landslide risk from population and forest cover changes in the Kivu Rift'.
DOI: 10.6084/m9.figshare.14838825
title: Figure data used in the manuscript entitled 'Historical dynamics of landslide risk from population and forest cover changes in the Kivu Rift'

description: This file contains the raw data used for Fig. 3, Fig. 4, and Fig. 5 of the Nature Sustainability manuscript entitled 'Historical dynamics of landslide risk from population and forest cover changes in the Kivu Rift'.
DOI: 10.6084/m9.figshare.14838807.v1
title: µCT series of Mytilus edulis juvenile (252-1)

description: SRµCT scan of a aposymbiotic M<i>ytilus edulis</i> juvenile. The mussel was sampled close to Kiel, Germany (54.394 N; 10.190 E) at 1.5 m water depth in 2018. The mussel was fixed with 2.5% glutaraldehyde stored in PHEM-buffer. The sample was scanned at the DESY in Hamburg Germany.