cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26093/cds/vizier.22620027
title: Abundances in inner, outer & FOV of 18 clusters

description: VizieR online Data Catalogue associated with article published in journal Astronomical Journal (AAS) with title 'Ranking theoretical supernovae explosion models from observations of the intracluster gas.' (bibcode: 2022ApJS..262...27B)
DOI: 10.26093/cds/vizier.22620042
title: VLBA obs. of masers in the Scutum Spiral Arm

description: VizieR online Data Catalogue associated with article published in journal Astronomical Journal (AAS) with title 'Accurate distances of massive young stars in the Scutum Spiral Arm.' (bibcode: 2022ApJS..262...42L)
DOI: 10.26093/cds/vizier.22630014
title: Dipper stars from TESS & Gaia

description: VizieR online Data Catalogue associated with article published in journal Astronomical Journal (AAS) with title 'A population of dipper stars from the Transiting Exoplanet Survey Satellite mission.' (bibcode: 2022ApJS..263...14C)
DOI: 10.5281/zenodo.4652796
title: CCG Starter Data Kit: Uganda

description: A starter data kit for Uganda
DOI: 10.5281/zenodo.4756657
title: CCG Starter Data Kit: Uganda

description: A starter data kit for Uganda
DOI: 10.5281/zenodo.4652795
title: CCG Starter Data Kit: Uganda

description: A starter data kit for Uganda
DOI: 10.5281/zenodo.5733333
title: CCG Starter Data Kit: Uganda

description: A starter data kit for Uganda
DOI: 10.5281/zenodo.5751729
title: CCG Starter Data Kit: Uganda

description: A starter data kit for Uganda
DOI: 10.5281/zenodo.7542330
title: CCG Starter Data Kit: Uganda

description: A starter data kit for Uganda
DOI: 10.6073/pasta/d81b100b0737880b7950ec0d93625da9
title: APT02 Monthly temperature and precipitation records from Manhattan, KS

description: Data set contains the monthly values of maximum, minimum and average temperatures and monthly total precipitation for Manhattan, KS since 1891. Data are in three separate files, one for each measurement. Data comes from the Weather Data Library (https://www.ncdc.noaa.gov/cdo-web/search?datasetid=GHCND) in the computer system office of the Cooperative Extension Service of Kansas State University, Manhattan Kansas. 211 Umberger Hall, (785) 532-6270.
DOI: 10.6084/m9.figshare.21905682
title: Dataset of the energy performance of synthetic residential buildings in Iran under climate change

description: This dataset consists of synthetic buiilding data generated using EPSA algorithm and simulated in EnergyPlus under climate change scenario SSP5-8.5 (timeframes 2050 and 2080) for 21 locations in Ira. <br> Each location has data on the buildings' geometry, energy performance, and construction system. The locations are on the coast of the Caspian Sea (Rasht, Ramsar, Nowshahr, and Sari), on the coast of the Persian Gulf (Bandar Mahshahr, Bandar Bushehr, Dayyer, Assaluyeh, Bandar Abaass, Bandar Lengeh, and Chabahar), and in the inner land (Tabriz, Karaj, Hamedan, Tehran, Semnan, Kashan, Yazd Sadooghi, Shiraz, Sirjan, and Fasa). <br> The present-day weather data was retrieved from climate.onebuilding.org. The future weather was morphed using 'Future Weather Generator' software, available at http://www.adai.pt/future-weather-generator/.
DOI: 10.6084/m9.figshare.21905697
title: Data_Sheet_1_Madison_et al_2022_Increasing in situ bioremediation effectiveness through field-scale application of molecular biological tools

description: Data supporting Madison et al. 2022, Increasing in situ bioremediation effectiveness through field-scale application of molecular biological tools. Frontiers in Microbiology.
DOI: 10.6084/m9.figshare.21905697.v1
title: Data_Sheet_1_Madison_et al_2022_Increasing in situ bioremediation effectiveness through field-scale application of molecular biological tools

description: Data supporting Madison et al. 2022, Increasing in situ bioremediation effectiveness through field-scale application of molecular biological tools. Frontiers in Microbiology.
DOI: 10.5519/qd.w0aahg89
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (752 records)
DOI: 10.6084/m9.figshare.20321670
title: Ensemble Modeling of Radiation Belt Electron Acceleration by Chorus Waves: Dependence on Key Input Parameters

description: This is the dataset used to produce figures for the paper under review with the title of "Ensemble Modeling of Radiation Belt Electron Acceleration by Chorus Waves: Dependence on Key Input Parameters". The ensemble simulation results are also provided.
DOI: 10.5281/zenodo.7541976
title: The state of Diversity and Inclusion in Apache: A Pulse Check

description: The state of Diversity and Inclusion in Apache: A Pulse Check --- Supplementary materials
DOI: 10.5281/zenodo.7541975
title: The state of Diversity and Inclusion in Apache: A Pulse Check

description: The state of Diversity and Inclusion in Apache: A Pulse Check --- Supplementary materials
DOI: 10.5281/zenodo.7542415
title: The state of Diversity and Inclusion in Apache: A Pulse Check

description: The state of Diversity and Inclusion in Apache: A Pulse Check --- Supplementary materials
DOI: 10.5281/zenodo.5498104
title: CCG Starter Data Kit: Uruguay

description: A starter data kit for Uruguay
DOI: 10.5281/zenodo.7542364
title: CCG Starter Data Kit: Uruguay

description: A starter data kit for Uruguay
DOI: 10.5281/zenodo.5498103
title: CCG Starter Data Kit: Uruguay

description: A starter data kit for Uruguay
DOI: 10.6073/pasta/76bf6d37d8774f5e84a2246e6cf9f236
title: Soil and microbial N data for Saddle, South of saddle, and North of saddle, 1991 - 1992.

description: Net nitrogen mineralization, nitrification, and microbial nitrogen were measured in dry, moist, and wet meadow plots in 3 different locations on Niwot Ridge: a south-facing slope in the Boulder watershed, across the Saddle, and a north-facing slope. Measurements were made on a monthly basis while soils were unfrozen and once over the period of frozen soil conditions. Associated soil measurements included moisture, temperature, organic N and C, total P, and texture.
DOI: 10.6073/pasta/b39ae766102bd17856d1935ad1b81f67
title: Soil and microbial N data for Saddle and South of saddle, 1992.

description: Net nitrogen mineralization, nitrification, and microbial nitrogen were measured in dry and moist meadow plots on Niwot Ridge from early June to mid-October 1992. Dry meadow plots in the City of Boulder Watershed had been fertilized with N during the two years prior to measurements, and both dry and moist meadow plots in the Saddle were being watered and fertilized concurrent to measurements.
DOI: 10.6073/pasta/7f181f4b59bf7874dc5bf5ae829083d6
title: Soil net nitrogen transformation rates for Saddle Catchment, 2017

description: In Spring/Summer 2017, Youchao Chen conducted three in-field soil core incubations (24-30 days each) to determine soil net N mineralization and net nitrification rates. He determined net N rates across 6 plant community types within the Niwot Ridge LTER Saddle Catchment: dry meadow, moist meadow, wet meadow, shrub, krummholz, and subalpine forest. These data are reported with soil moisture and bulk density.
DOI: 10.6084/m9.figshare.21902133
title: Data for: Disentangling the causes of temporal variation in the opportunity for sexual selection

description: This dataset contains the following files: 1) Opportunity for precopulatory sexual selection (all species) 2) Opportunities for selection (red junglefowl) 3) Red junglefowl raw mating data 4) Random mating simulation with worked example (R code) 5) Shuffle the day order (R code) <br> Columns: groupID = identity of the mating group MaleID = identity of the male FemaleID = identity of the female Copulation = mating event (each row identifies 1 copulation) Day_order = day of the observation period Im = opportunity for precopulatory sexual selection It = opportunity for total selection In = opportunity for partner fecundity Method = method of mating/reproductive success calculation (cumulative vs daily) Sex = male/female Species = species scientific name
DOI: 10.6084/m9.figshare.21902133.v1
title: Data for: Disentangling the causes of temporal variation in the opportunity for sexual selection

description: This dataset contains the following files: 1) Opportunity for precopulatory sexual selection (all species) 2) Opportunities for selection (red junglefowl) 3) Red junglefowl raw mating data 4) Random mating simulation with worked example (R code) 5) Shuffle the day order (R code) <br> Columns: groupID = identity of the mating group MaleID = identity of the male FemaleID = identity of the female Copulation = mating event (each row identifies 1 copulation) Day_order = day of the observation period Im = opportunity for precopulatory sexual selection It = opportunity for total selection In = opportunity for partner fecundity Method = method of mating/reproductive success calculation (cumulative vs daily) Sex = male/female Species = species scientific name
DOI: 10.5281/zenodo.7542458
title: Machine Learning approach to Classification of Resting-State EEG Microstates in stroke survivors

description: Dataset - Machine Learning approach to Classification of Resting-State EEG Microstates in stroke survivors https://docs.google.com/spreadsheets/d/1MeEx9ysEC_tWyohqEmvc8Ey5mc5Z9NV2/edit#gid=160681293
DOI: 10.5281/zenodo.7542457
title: Machine Learning approach to Classification of Resting-State EEG Microstates in stroke survivors

description: Dataset - Machine Learning approach to Classification of Resting-State EEG Microstates in stroke survivors https://docs.google.com/spreadsheets/d/1MeEx9ysEC_tWyohqEmvc8Ey5mc5Z9NV2/edit#gid=160681293
DOI: 10.5281/zenodo.7665
title: Optical spectra of Halpha-bright knots in Stephan's Quintet

description: Optical spectra of Hα-bright knots in the intragroup medium of Stephan's Quintet, an interacting compact galaxy group featuring a string X-ray shock. Provided in HDF5 and FITS, the astronomical FITS file transfer format.
DOI: 10.5281/zenodo.642278
title: Optical spectra of Halpha-bright knots in Stephan's Quintet

description: Optical spectra of Hα-bright knots in the intragroup medium of Stephan's Quintet, an interacting compact galaxy group featuring a string X-ray shock. Provided in HDF5 and FITS, the astronomical FITS file transfer format.
DOI: 10.5281/zenodo.5498105
title: CCG Starter Data Kit: Venezuela

description: A starter data kit for Venezuela
DOI: 10.5281/zenodo.5498106
title: CCG Starter Data Kit: Venezuela

description: A starter data kit for Venezuela
DOI: 10.5281/zenodo.7542423
title: CCG Starter Data Kit: Venezuela

description: A starter data kit for Venezuela
DOI: 10.34740/kaggle/dsv/4861421
title: Fitness tracker data (2016 - present) [2450+days]
DOI: 10.6084/m9.figshare.16653076.v10
title: data_source_codes

description: See README
DOI: 10.6084/m9.figshare.16653079.v8
title: variable_category_codes

description: See README
DOI: 10.6084/m9.figshare.16653064.v5
title: watershed_summaries

description: See README
DOI: 10.6084/m9.figshare.16653067
title: timeseries column descriptions

description: See README
DOI: 10.6084/m9.figshare.16653067.v6
title: timeseries column descriptions

description: See README
DOI: 10.6084/m9.figshare.16653067.v5
title: timeseries column descriptions

description: See README
DOI: 10.6084/m9.figshare.16653070
title: watershed_summary column descriptions

description: See README
DOI: 10.6084/m9.figshare.16653070.v5
title: watershed_summary column descriptions

description: See README
DOI: 10.6084/m9.figshare.16653070.v4
title: watershed_summary column descriptions

description: See README
DOI: 10.6084/m9.figshare.16653073
title: watershed_trait_timeseries column descriptions

description: See README
DOI: 10.6084/m9.figshare.16653073.v5
title: watershed_trait_timeseries column descriptions

description: See README
DOI: 10.6084/m9.figshare.16653073.v4
title: watershed_trait_timeseries column descriptions

description: See README
DOI: 10.6084/m9.figshare.16653076.v11
title: data_source_codes

description: See README
DOI: 10.6084/m9.figshare.16653079
title: variable_category_codes

description: See README
DOI: 10.6084/m9.figshare.16653079.v10
title: variable_category_codes

description: See README
DOI: 10.6084/m9.figshare.16653079.v9
title: variable_category_codes

description: See README
DOI: 10.6084/m9.figshare.16653082.v3
title: README

description: See README
DOI: 10.6084/m9.figshare.19358579.v3
title: data_use_POLICY

description: See README
DOI: 10.6084/m9.figshare.19358582
title: site_metadata

description: See README
DOI: 10.6084/m9.figshare.19358582.v4
title: site_metadata

description: See README
DOI: 10.6084/m9.figshare.19358582.v3
title: site_metadata

description: See README
DOI: 10.6084/m9.figshare.19358585
title: variable_metadata

description: See README
DOI: 10.6084/m9.figshare.19358585.v5
title: variable_metadata

description: See README
DOI: 10.6084/m9.figshare.19358585.v4
title: variable_metadata

description: See README
DOI: 10.6084/m9.figshare.19585810
title: variable_catalog

description: See README
DOI: 10.6084/m9.figshare.19585810.v6
title: variable_catalog

description: See README
DOI: 10.6084/m9.figshare.19585810.v5
title: variable_catalog

description: See README
DOI: 10.5281/zenodo.7542277
title: Renta media por persona y nivel de formación en los 21 distritos del Ayuntamiento de Madrid (2016-2019)

description: Este conjunto de datos ha sido utilizado en el proyecto REFOMAD. Incluye información sobre la renta media por persona, el nivel de formación educativa de los residentes mayores de 25 años y el número de centros educativos en cada uno de los 21 distritos del Ayuntamiento de Madrid durante los años 2016-2019. El nivel de formación tiene 6 niveles: no sabe leer ni escribir, bachiller elemental, formación profesional, titulados medios, estudios universitarios y nivel de estudios no consta. Los centros educativos se clasifican también en 6 niveles: escuelas infantiles municipales, escuelas infantiles públicas de la Comunidad Autónoma de Madrid, escuelas infantiles privadas, colegios públicos infantil/primaria, institutos públicos de educación secundaria y colegios privados infantil/primaria. Los datos de renta fueron proporcionados por el INE, los datos sobre la formación fueron obtenidos mediante encuestas propias realizadas por el equipo REFOMAD y los datos de los centros educativos fueron solicitados al portal de datos abiertos del Ayuntamiento de Madrid. Los datos están en formato XLSX y tienen un tamaño de 17 kB. Los datos fueron prepreocesados y curados utilizando herramientas de software libre como NumPy y pandas en Python versión 3.10.6.
DOI: 10.5281/zenodo.7542276
title: Renta media por persona y nivel de formación en los 21 distritos del Ayuntamiento de Madrid (2016-2019)

description: Este conjunto de datos ha sido utilizado en el proyecto REFOMAD. Incluye información sobre la renta media por persona, el nivel de formación educativa de los residentes mayores de 25 años y el número de centros educativos en cada uno de los 21 distritos del Ayuntamiento de Madrid durante los años 2016-2019. El nivel de formación tiene 6 niveles: no sabe leer ni escribir, bachiller elemental, formación profesional, titulados medios, estudios universitarios y nivel de estudios no consta. Los centros educativos se clasifican también en 6 niveles: escuelas infantiles municipales, escuelas infantiles públicas de la Comunidad Autónoma de Madrid, escuelas infantiles privadas, colegios públicos infantil/primaria, institutos públicos de educación secundaria y colegios privados infantil/primaria. Los datos de renta fueron proporcionados por el INE, los datos sobre la formación fueron obtenidos mediante encuestas propias realizadas por el equipo REFOMAD y los datos de los centros educativos fueron solicitados al portal de datos abiertos del Ayuntamiento de Madrid. Los datos están en formato XLSX y tienen un tamaño de 17 kB. Los datos fueron prepreocesados y curados utilizando herramientas de software libre como NumPy y pandas en Python versión 3.10.6.
DOI: 10.5517/ccdc.csd.cc2b95f8
title: CCDC 2153769: Experimental Crystal Structure Determination

description: Related Article: Sareh Paziresh, Reza Babadi Aghakhanpour, Hamid R. Shahsavari, Vahideh Dolatyari, Irene Ara, S. Masoud Nabavizadeh|2022|New J.Chem.|47|1378|doi:10.1039/D2NJ05209A
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.cc2bhgmy
title: CCDC 2159820: Experimental Crystal Structure Determination

description: Related Article: Fan-Zhi Bu, Yue-Ming Yu, Yu Yu, Cui-Wei Yan, Zhi-Yong Wu, Yan-Tuan Li|2022|New J.Chem.|47|1328|doi:10.1039/D2NJ03622C
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.cc2bl4nr
title: CCDC 2162394: Experimental Crystal Structure Determination

description: Related Article: Rafaela M. R. da Silva, Iara M. L. Rosa, Willian X. C. Oliveira, Odivaldo C. Alves, Evelyn C. S. Santos, Flávio Garcia, Henrique C. Silva Junior, Glaucio B. Ferreira, Guilherme P. Guedes, Walace D. do Pim, Miguel Julve, Maria Vanda Marinho|2022|New J.Chem.|47|1066|doi:10.1039/D2NJ05268G
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.cc2bpktf
title: CCDC 2165685: Experimental Crystal Structure Determination

description: Related Article: Zongkang Wang, Yang Yuan, Shuxin Jin, Ye Wang, Yingge Gu, Chengyu Wang, Yanzhong Li|2023|New J.Chem.|47|1055|doi:10.1039/D2NJ05660G
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.cc2btmg8
title: CCDC 2169580: Experimental Crystal Structure Determination

description: Related Article: Thiago Anjos, Elba L. Gutterres, Daniela A. Barancelli, Roberta Cargnelutti, Benhur Godoi, Thiago Barcellos, Ricardo F. Schumacher|2022|New J.Chem.|47|1076|doi:10.1039/D2NJ05567H
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: 10.14279/depositonce-16782
title: A deep neural network for molecular wave functions in quasi-atomic minimal basis representation

description: The emergence of machine learning methods in quantum chemistry provides new methods to revisit an old problem: Can the predictive accuracy of electronic structure calculations be decoupled from their numerical bottlenecks? Previous attempts to answer this question have, among other methods, given rise to semi-empirical quantum chemistry in minimal basis representation. We present an adaptation of the recently proposed SchNet for Orbitals (SchNOrb) deep convolutional neural network model [K. T. Schütt et al., Nat. Commun. 10, 5024 (2019)] for electronic wave functions in an optimized quasi-atomic minimal basis representation. For five organic molecules ranging from 5 to 13 heavy atoms, the model accurately predicts molecular orbital energies and wave functions and provides access to derived properties for chemical bonding analysis. Particularly for larger molecules, the model outperforms the original atomic-orbital-based SchNOrb method in terms of accuracy and scaling. We conclude by discussing the future potential of this approach in quantum chemical workflows.
DOI: 10.5519/qd.jyutpqs5
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (714 records)
DOI: 10.6084/m9.figshare.21624156
title: Supplemental Tables

description: Supplemental Tables for Eljalby et al., 2022
DOI: 10.6084/m9.figshare.21624156.v2
title: Supplemental Tables

description: Supplemental Tables for Eljalby et al., 2022
DOI: 10.6084/m9.figshare.21624156.v1
title: eTables.xlsx

description: Supplemental Tables for Eljalby et al., 2022
DOI: 10.34740/kaggle/dsv/4861598
title: BBC News
DOI: 10.6084/m9.figshare.21905898
title: Supplemental Tables

description: Supplemental Tables for Eljalby et al., 2023
DOI: 10.6084/m9.figshare.21905898.v1
title: Supplemental Tables

description: Supplemental Tables for Eljalby et al., 2023
DOI: 10.6084/m9.figshare.21905910
title: Supplemental Tables for Eljalby et al., 2022

description: Supplemental Tables for Eljalby et al., 2022
DOI: 10.6084/m9.figshare.21905910.v2
title: Supplemental Tables for Eljalby et al., 2022

description: Supplemental Tables for Eljalby et al., 2022
DOI: 10.6084/m9.figshare.21905910.v1
title: Supplemental Tables for Eljalby et al., 2022

description: Supplemental Tables for Eljalby et al., 2022
DOI: 10.6084/m9.figshare.21905895.v1
title: Data for the manuscript "Combining paleomagnetic and Re-Os isotope data to quantify the process from hydrocarbon generation to accumulation"

description: The files here include the data of carbonate reservoir rocks in the Longmen Shan belt, South China. In detail, Table S1 is the data of isothermal remanent magnetization component uxmixing analysis (Table S1); Table S2 is the result of Total Organic Content (TOC) and natural remanent magnetism (NRM) values for hydrocarbon-bearing carbonate samples; Table S3 is the result of vitrinite reflectance in oil (Ro) value. Table S4 is the reuslt of Sr isotope values. There are also files, including the raw data for demagnetization, and their directions.
DOI: 10.5517/ccdc.csd.cc2c3mjn
title: CCDC 2178231: Experimental Crystal Structure Determination

description: Related Article: Jakub Orvoš, Róbert Fischer, Barbora Brachňaková, Ján Pavlik, Ján Moncoľ, Alexandra Šagátová, Marek Fronc, Jozef Kožíšek, Lucie Routaboul, Azzedine Bousseksou, Ivan Šalitroš|2022|New J.Chem.|47|1488|doi:10.1039/D2NJ04774H
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.cc2c3mkp
title: CCDC 2178232: Experimental Crystal Structure Determination

description: Related Article: Jakub Orvoš, Róbert Fischer, Barbora Brachňaková, Ján Pavlik, Ján Moncoľ, Alexandra Šagátová, Marek Fronc, Jozef Kožíšek, Lucie Routaboul, Azzedine Bousseksou, Ivan Šalitroš|2022|New J.Chem.|47|1488|doi:10.1039/D2NJ04774H
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.