cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13693105.v1
title: A Collection of Building Footprint Data in US Counties_Part 1

description: This figshare repository is a collection of building footprint in US Counties. See the references below for more details.<br>References:Heris, M.P., Foks, N.L., Bagstad, K.J. et al. A rasterized building footprint dataset for the United States. Sci Data 7, 207 (2020). https://doi.org/10.1038/s41597-020-0542-3
DOI: 10.6084/m9.figshare.13693105
title: A Collection of Building Footprint Data in US Counties_Part 1

description: This figshare repository is a collection of building footprint in US Counties. See the references below for more details.<br>References:Heris, M.P., Foks, N.L., Bagstad, K.J. et al. A rasterized building footprint dataset for the United States. Sci Data 7, 207 (2020). https://doi.org/10.1038/s41597-020-0542-3
DOI: 10.5066/p9mnkws4
title: High-resolution maps of big sagebrush plant community biomass using multivariate matching algorithms

description: These GeoTIFF data were compiled to investigate how a new multivariate matching algorithm transfers simulated plant functional biomass of big sagebrush plant communities from 200 sites to a gridded product with 30-arcsec spatial resolution. Objectives of our study were to (1) describe how climate change will alter the biomass and composition of key plant functional types; (2) quantify the impacts of climate change on future functional type biomass and composition along climatic gradients; (3) identify if and which geographic locations will be relatively unaffected by climate change while others experience large effects; and (4) determine if there is consistency in climate change impacts on plant communities among a representative set of climate scenarios. These data represent geographic patterns in simulated plant functional biomass of big sagebrush plant communities (cheatgrass, perennial forbs, C3 perennial grasses, C4 perennial grasses, perennial grasses, big sagebrush) as across-year averages of under historical ("current"; years 1980-2010) climate and differences ("change") between projected future climates (years 2030-2060 and 2070-2100) derived as medians across 13 Global Climate Models (GCMs) that participated in CMIP5 for representative concentration pathways RCP4.5 and RCP8.5 and historical values. These data were created in 2020 and 2021 for the area of the sagebrush region in the western United States to describe geographic patterns in simulated plant functional biomass of big sagebrush plant communities under historical and projected future climate conditions at a 30-arcsec spatial resolution. These data can be used to confirm the results of the study identified as the Larger Work Citation, including the high resolution matching of projected declines in big sagebrush, perennial C3 grass and perennial forb biomass in warm, dry sites; no projected change or increases in functional type biomass in cold, moist sites; and widespread projected increases in perennial C4 grasses across sagebrush plant communities in the sagebrush region of the western United States as defined by Palmquist et al. (2021) and within the scope as defined by the study. These data may also be used to evaluate the potential impact of changing climate conditions on geographic patterns in simulated plant functional biomass of big sagebrush plant communities within the scope defined by the study. In particular, these data can be useful for informing the design of long-term landscape conservation efforts to maintain and expand wildlife habitat across the sagebrush biome.
DOI: 10.6084/m9.figshare.16574594
title: A Collection of Building Footprint Data in US Counties_Part 2

description: This figshare repository is a collection of building footprint in US Counties. See the references below for more details.<br>References:Heris, M.P., Foks, N.L., Bagstad, K.J. et al. A rasterized building footprint dataset for the United States. Sci Data 7, 207 (2020). https://doi.org/10.1038/s41597-020-0542-3
DOI: 10.6084/m9.figshare.16574594.v1
title: A Collection of Building Footprint Data in US Counties_Part 2

description: This figshare repository is a collection of building footprint in US Counties. See the references below for more details.<br>References:Heris, M.P., Foks, N.L., Bagstad, K.J. et al. A rasterized building footprint dataset for the United States. Sci Data 7, 207 (2020). https://doi.org/10.1038/s41597-020-0542-3
DOI: 10.6084/m9.figshare.15138570.v1
title: 14-3-3 proteins promote synaptic localization of N-methyl d-aspartate receptors (NMDARs) in mouse hippocampal and cortical neurons

description: Data sets for manuscript, "14-3-3 proteins promote synaptic localization of N-methyl d-aspartate receptors (NMDARs) in mouse hippocampal and cortical neurons"
DOI: 10.6084/m9.figshare.16700041
title: Ch2 Ecotype Project [Data + R code]

description: Grassland restoration unveils phylogenetic signal and community assembly along a longitudinal aridity gradient - raw data and R code archive
DOI: 10.6084/m9.figshare.16700041.v3
title: Ch2 Ecotype Project [Data + R code]

description: Grassland restoration unveils phylogenetic signal and community assembly along a longitudinal aridity gradient - raw data and R code archive
DOI: 10.6084/m9.figshare.16700041.v2
title: Ch2 Ecotype Project [Data + R code]

description: Grassland restoration unveils phylogenetic signal and community assembly along a longitudinal aridity gradient - raw data and R code archive
DOI: 10.5281/zenodo.5097003
title: High-Throughput Screening of Tribological Properties of Monolayer Films using Molecular Dynamics and Machine Learning: Supplemental Repository

description: Supplemental repository for the "High-Throughput Screening of Tribological Properties of Monolayer Films using Molecular Dynamics and Machine Learning" article. Contains calculated tribological properties of dual-monolayer systems from Molecular Dynamics (MD) simulation and Machine Learning (ML).
DOI: 10.34740/kaggle/dsv/2682863
title: US counties COVID 19 dataset
DOI: 10.6084/m9.figshare.16640719
title: SOIL-WATERGRIDS v1, mapping dynamic changes in soil moisture and depth of water table from 1970 to 2014, dataset and modelling

description: SOIL-WATERGRIDS is a comprehensive data product of the monthly estimates of volumetric soil water content at three depths within the root zone and the depth of the water table globally gridded at a resolution of 0.25x025 degree per grid cell from 1970 to 2014. <br>This package includes a Technical Documentation with the details about the use of the data product.
DOI: 10.18739/a20r9m51b
title: Lake basin water level and ground temperature data in Arctic Alaska, 2019-2021

description: Lakes are abundant features on coastal plains of the Arctic and most are termed "thermokarst" because they form in ice-rich permafrost and gradually expand over time. The dynamic nature of thermokarst lakes also makes them prone to catastrophic drainage and abrupt conversion to wetlands, called drained thermokarst lake basins (DTLBs). Together, thermokarst lakes and DTLBs cover up to 80% of arctic lowland regions, making understanding their response to ongoing climate change essential for coastal plain environmental assessment. Datasets presented here document water level and temperature (surface and ground) regimes for a large (38 sites) array of lake with high drainage potential and lake basin (DTLBS), which have already drained, located on differing terrain units of Alaska's Arctic Coastal Plain. Lake data was measured along deep protected shorelines using pressure transducers to record hourly water level and bed temperature. Wetland (DTLB) data was also measured with pressure transducers and ground thermistors at 25 and 100 centimeters (cm) depth. Of special interest at some DTLB sites was the potential occurrence of snow-dam outburst events during the early summer snowmelt periods. In these cases, pressure transducers were set to log at 10 minute intervals for this period. All data archived here are summarized at daily average values.
DOI: 10.6084/m9.figshare.16640719.v1
title: SOIL-WATERGRIDS v1, mapping dynamic changes in soil moisture and depth of water table from 1970 to 2014, dataset and modelling

description: SOIL-WATERGRIDS is a comprehensive data product of the monthly estimates of volumetric soil water content at three depths within the root zone and the depth of the water table globally gridded at a resolution of 0.25x025 degree per grid cell from 1970 to 2014. <br>This package includes a Technical Documentation with the details about the use of the data product.
DOI: 10.6084/m9.figshare.15138570.v2
title: 14-3-3 proteins promote synaptic localization of N-methyl d-aspartate receptors (NMDARs) in mouse hippocampal and cortical neurons

description: Data sets for manuscript, "14-3-3 proteins promote synaptic localization of N-methyl d-aspartate receptors (NMDARs) in mouse hippocampal and cortical neurons"
DOI: 10.6084/m9.figshare.14852955.v1
title: Climate velocity and land-use instability 1971-2100

description: Datasets contains <br>(a) Raster layers of climate and land-use velocity during 1971-2000, 2021-2050, and 2071-2100. (see Asamoah et al. Climate and land use changes reduce the benefits of terrestrial protected areas [Nature Climate Change] for detailed methodology). Spatial resolution: 24 km in a Mollweide projection (ESRI: 54009).<br>(b) Microsoft excel spreadsheets and R codes for visualizing some of the plots in Asamoah et al. [Nature Climate Change]
DOI: 10.6084/m9.figshare.16755427.v1
title: Creative performance

description: Data variables are listed in the SPSS files.
DOI: 10.6084/m9.figshare.15138570.v3
title: 14-3-3 proteins promote synaptic localization of N-methyl d-aspartate receptors (NMDARs) in mouse hippocampal and cortical neurons

description: Data sets for manuscript, "14-3-3 proteins promote synaptic localization of N-methyl d-aspartate receptors (NMDARs) in mouse hippocampal and cortical neurons"
DOI: 10.6084/m9.figshare.16592804
title: Building Dataset with bounding boxes

description: The dataset for buildings in MATLAB Version.
DOI: 10.6084/m9.figshare.16592789
title: Raw Images Dataset.rar

description: The dataset consists of 500 aerial satellite images for buildings in Riyadh City, Saudi Arabia.
DOI: 10.6084/m9.figshare.16592804.v1
title: Building Dataset with bounding boxes

description: The dataset for buildings in MATLAB Version.
DOI: 10.18131/g3-2wf8-9s24
title: 10_17_19_LookAt_SentenceDur_Extended.txt
DOI: 10.5517/ccdc.csd.cc27r63b
title: CCDC 2077871: Experimental Crystal Structure Determination

description: Related Article: Petr I. Matveev, Pin-Wen Huang, Anna A. Kirsanova, Ivan V. Ananyev, Tsagana B. Sumyanova, Anastasia V. Kharcheva, Evgenii Yu. Khvorostinin, Vladimir G. Petrov, Wei-Qun Shi, Stepan N. Kalmykov, Nataliya E. Borisova|2021|Inorg.Chem.|60|14563|doi:10.1021/acs.inorgchem.1c01432
DOI: 10.5517/ccdc.csd.cc27r64c
title: CCDC 2077872: Experimental Crystal Structure Determination

description: Related Article: Petr I. Matveev, Pin-Wen Huang, Anna A. Kirsanova, Ivan V. Ananyev, Tsagana B. Sumyanova, Anastasia V. Kharcheva, Evgenii Yu. Khvorostinin, Vladimir G. Petrov, Wei-Qun Shi, Stepan N. Kalmykov, Nataliya E. Borisova|2021|Inorg.Chem.|60|14563|doi:10.1021/acs.inorgchem.1c01432
DOI: 10.5517/ccdc.csd.cc27ybdy
title: CCDC 2083770: Experimental Crystal Structure Determination

description: Related Article: Abdullah Abdulkader, Adelheid Hagenbach, Ulrich Abram|2021|Eur.J.Inorg.Chem.|2021|3812|doi:10.1002/ejic.202100521
DOI: 10.5517/ccdc.csd.cc27ybfz
title: CCDC 2083771: Experimental Crystal Structure Determination

description: Related Article: Abdullah Abdulkader, Adelheid Hagenbach, Ulrich Abram|2021|Eur.J.Inorg.Chem.|2021|3812|doi:10.1002/ejic.202100521
DOI: 10.5517/ccdc.csd.cc27ybg0
title: CCDC 2083772: Experimental Crystal Structure Determination

description: Related Article: Abdullah Abdulkader, Adelheid Hagenbach, Ulrich Abram|2021|Eur.J.Inorg.Chem.|2021|3812|doi:10.1002/ejic.202100521
DOI: 10.5517/ccdc.csd.cc27ybh1
title: CCDC 2083773: Experimental Crystal Structure Determination

description: Related Article: Abdullah Abdulkader, Adelheid Hagenbach, Ulrich Abram|2021|Eur.J.Inorg.Chem.|2021|3812|doi:10.1002/ejic.202100521
DOI: 10.5517/ccdc.csd.cc284m8b
title: CCDC 2089811: Experimental Crystal Structure Determination

description: Related Article: Takashi Komuro, Junpei Asagami, Hironori Higashi, Keita Sato, Hisako Hashimoto, Hiromi Tobita|2021|Organometallics|40|3113|doi:10.1021/acs.organomet.1c00359
DOI: 10.5517/ccdc.csd.cc284m9c
title: CCDC 2089812: Experimental Crystal Structure Determination

description: Related Article: Takashi Komuro, Junpei Asagami, Hironori Higashi, Keita Sato, Hisako Hashimoto, Hiromi Tobita|2021|Organometallics|40|3113|doi:10.1021/acs.organomet.1c00359
DOI: 10.5517/ccdc.csd.cc284mbd
title: CCDC 2089813: Experimental Crystal Structure Determination

description: Related Article: Takashi Komuro, Junpei Asagami, Hironori Higashi, Keita Sato, Hisako Hashimoto, Hiromi Tobita|2021|Organometallics|40|3113|doi:10.1021/acs.organomet.1c00359
DOI: 10.5517/ccdc.csd.cc285nsx
title: CCDC 2090819: Experimental Crystal Structure Determination

description: Related Article: Hong-Quan Du, Xiang-Ping Hu|2021|Org.Lett.|23|7678|doi:10.1021/acs.orglett.1c02978
DOI: 10.5517/ccdc.csd.cc28fy7x
title: CCDC 2098769: Experimental Crystal Structure Determination

description: Related Article: Hong-Quan Du, Xiang-Ping Hu|2021|Org.Lett.|23|7678|doi:10.1021/acs.orglett.1c02978
DOI: 10.5517/ccdc.csd.cc28j847
title: CCDC 2100998: Experimental Crystal Structure Determination

description: Related Article: Qingbao Gong, Qinghua Wu, Xing Guo, Heng Li, Wanwan Li, Changjiang Yu, Erhong Hao, Lijuan Jiao|2021|Org.Lett.|23|7661|doi:10.1021/acs.orglett.1c02926
DOI: 10.6073/pasta/69920636b661dedbed3144f7e5b8992f
title: Data to support "delta13C and delta15N values from a mesocosm experiment showing sea urchins mediate the availability of kelp detritus to benthic consumers"

description: The purple sea urchin Strongylocentrotus purpuratus is an important herbivore and detritivore in southern California giant kelp (Macrocystis pyrifera) forests that grow on shallow rocky reefs (~3-20m depth) off southern California, including Santa Barbara where this study was done. To investigate the shredder activity of purple urchins, we assembled communities of common detritivores and suspension feeders from local reefs in mesocosms. Three species of brittle stars (Ophiopteris papillosa, Ophioplocus esmarki, and Ophiothrix spiculata), one vermetid gastropod (Thylacodes squamigerus), two barnacles (Chthamalus sp. and Megabalanus californicus), one polychaete worm (Chaetopterus sp.), and three sea cucumbers (Cucumaria piperata, Pachythyone rubra, and Cucumaria salma) were collected from the seafloor of local kelp forests at 5-15m depth in the Santa Barbara Channel. Ten of each species were placed in each of six 50 L (51x38x27 cm) flow-through unfiltered seawater tanks, each containing two concrete bricks for hard substrate on top of 3 cm of sand. Because sea urchins are highly mobile, capable of bulldozing other occupants, we isolated them above the experimental communities on plastic mesh (1cm). Mesh dividers were secured horizontally across each mesocosm 16 cm above the bottom. Ten individuals of each consumer species, along with 2-3 blades, totaling 47.3 g (±1.2 SE), of isotopically labeled kelp (see below) were placed on the floor of each tank, below the divider. On top of the mesh divider, we placed an additional 229.8 g (±6.1 SE) of enriched kelp blades, and in half of the tanks, 10 adult urchins (total mass 343.3 g ±1.3 SE) per tank. The kelp below the mesh ensured that the detritivores had direct access to degrading kelp detritus regardless of the urchin treatment, similar to the situation in the kelp forest, allowing us to more clearly ascertain the degree to which the detritivores were dependent on urchins for kelp detritus assimilation. The experiment was run for 28 days (Jul 26 - Aug 24, 2016); above-mesh kelp was removed and replenished once after 13 days.
DOI: 10.6084/m9.figshare.3409927
title: Data used to develop #Polar scores

description: We present a new approach to measuring political polarization, including a novel algorithm and open source Python code, which leverages Twitter content to produce measures of polarization for both users and hashtags. #Polar scores provide advantages over existing measures because they (1) can be calculated throughout the legislative cycle, (2) allow for easy differentiation between users with similar scores, (3) are chamber-agnostic, and (4) are a generic approach that can be applied beyond the U.S. Congress. #Polar scores leverage available information such as party labels, word frequency, and hashtags to create an accessible, straightforward algorithm for estimating polarity using text. (from the paper: Hemphill, L., Culotta, A., and Heston, M. (forthcoming) #Polar Scores: Measuring partisanship using social media content. <i>Journal of Information Technology & Politics</i>.)<br>The dataset contains one plain text TSV file with the following information for each of the 55,244 tweets used to develop #Polar scores : tweet_id, created_at, user_id, screen_name, tag, shortid, sex, party, state, chamber, name. The file contains one row per hashtag, and therefore tweets may appear more than once. The Python code for calculating #Polar scores is available here: http://doi.org/10.5281/zenodo.53888
DOI: 10.6084/m9.figshare.3409927.v2
title: Data used to develop #Polar scores

description: We present a new approach to measuring political polarization, including a novel algorithm and open source Python code, which leverages Twitter content to produce measures of polarization for both users and hashtags. #Polar scores provide advantages over existing measures because they (1) can be calculated throughout the legislative cycle, (2) allow for easy differentiation between users with similar scores, (3) are chamber-agnostic, and (4) are a generic approach that can be applied beyond the U.S. Congress. #Polar scores leverage available information such as party labels, word frequency, and hashtags to create an accessible, straightforward algorithm for estimating polarity using text. (from the paper: Hemphill, L., Culotta, A., and Heston, M. (forthcoming) #Polar Scores: Measuring partisanship using social media content. <i>Journal of Information Technology & Politics</i>.)<br>The dataset contains one plain text TSV file with the following information for each of the 55,244 tweets used to develop #Polar scores : tweet_id, created_at, user_id, screen_name, tag, shortid, sex, party, state, chamber, name. The file contains one row per hashtag, and therefore tweets may appear more than once. The Python code for calculating #Polar scores is available here: http://doi.org/10.5281/zenodo.53888
DOI: 10.6073/pasta/e0aace9ba6c17e7b69ffde3f26d72a32
title: Data to support "delta13C and delta15N values from a mesocosm experiment showing sea urchins mediate the availability of kelp detritus to benthic consumers"

description: The purple sea urchin Strongylocentrotus purpuratus is an important herbivore and detritivore in southern California giant kelp (Macrocystis pyrifera) forests that grow on shallow rocky reefs (~3-20m depth) off southern California, including Santa Barbara where this study was done. To investigate the shredder activity of purple urchins, we assembled communities of common detritivores and suspension feeders from local reefs in mesocosms. Three species of brittle stars (Ophiopteris papillosa, Ophioplocus esmarki, and Ophiothrix spiculata), one vermetid gastropod (Thylacodes squamigerus), two barnacles (Chthamalus sp. and Megabalanus californicus), one polychaete worm (Chaetopterus sp.), and three sea cucumbers (Cucumaria piperata, Pachythyone rubra, and Cucumaria salma) were collected from the seafloor of local kelp forests at 5-15m depth in the Santa Barbara Channel. Ten of each species were placed in each of six 50 L (51x38x27 cm) flow-through unfiltered seawater tanks, each containing two concrete bricks for hard substrate on top of 3 cm of sand. Because sea urchins are highly mobile, capable of bulldozing other occupants, we isolated them above the experimental communities on plastic mesh (1cm). Mesh dividers were secured horizontally across each mesocosm 16 cm above the bottom. Ten individuals of each consumer species, along with 2-3 blades, totaling 47.3 g (±1.2 SE), of isotopically labeled kelp (see below) were placed on the floor of each tank, below the divider. On top of the mesh divider, we placed an additional 229.8 g (±6.1 SE) of enriched kelp blades, and in half of the tanks, 10 adult urchins (total mass 343.3 g ±1.3 SE) per tank. The kelp below the mesh ensured that the detritivores had direct access to degrading kelp detritus regardless of the urchin treatment, similar to the situation in the kelp forest, allowing us to more clearly ascertain the degree to which the detritivores were dependent on urchins for kelp detritus assimilation. The experiment was run for 28 days (Jul 26 - Aug 24, 2016); above-mesh kelp was removed and replenished once after 13 days. The duplicated data table has been published in Dryad: Yorke, Christie E.; Page, Henry M.; Miller, Robert J. (2019), Data from: Sea urchins mediate the availability of kelp detritus to benthic consumers, Dryad, Dataset, https://doi.org/10.5061/dryad.38m3dc6
DOI: 10.5281/zenodo.5553438
title: Dispersal probabilities and geography input for BioGeoBEARS

description: Dispersal probabilities by assigned geographical time-slice and range data for use in BioGeoBEARS ancestral range reconstruction of Caribbean <em>Micrathena. </em>
DOI: 10.6084/m9.figshare.16614262
title: Text-mined AuNP Synthesis Recipes Dataset

description: This dataset contains protocols for gold nanoparticle synthesis, mined from the literature. The set includes 5,154 data records, each representing a single gold nanoparticle synthesis article. Each record contains codified synthesis protocols and extracted morphological information from a total of 7,608 experimental and 12,519 characterization paragraphs.
DOI: 10.17632/sghssffhd3.1
title: Data for: Chemical structure changes of lacustrine Type-II kerogen under semi-open pyrolysis as investigated by solid-state 13C NMR and FT-IR spectroscopy

description: This is the raw data of my manuscript.
DOI: 10.17632/tjgj87yw78.2
title: Immature instars of three species of Rhodnius (Hemiptera: Re-duviidae: Triatominae): morphological and morphometric studies

description: This data is of geometric mophometric of the  Immature instars of three species of Rhodnius (Hemiptera: Re-duviidae: Triatominae): morphological and morphometric studies
DOI: 10.17632/tjgj87yw78.3
title: Immature instars of three species of Rhodnius (Hemiptera: Re-duviidae: Triatominae): morphological and morphometric studies

description: This data is of geometric mophometric of the  Immature instars of three species of Rhodnius (Hemiptera: Re-duviidae: Triatominae): morphological and morphometric studies
DOI: 10.6084/m9.figshare.16755205
title: Mass Spec enrichment & significance table for OpenCell

description: This dataset is contains pre-calculated statistics (fold enrichment and student's t-test p-value) of bait and prey proteins in immuno-precipitation mass spectrometry (IPMS) experiments. The enrichment and p-value are used by an algorithm to call significant interactions, where we determine that a bait captured significantly enriched quantity of prey during the experiment.Please refer to our GitHub repo (2021-opencell-figures) for usage examples.<br>
DOI: 10.6084/m9.figshare.16755481
title: EC_PDX_figure_data.RData

description: Pre-processed genomic data ready for figure generation using scripts in: https://github.com/okon/EC_PDX_genomics<br>This data was generated for the endometrial cancer PDX genomic characterization paper by Bonazzi, Kondrashova et al. - pre-print https://doi.org/10.1101/2021.03.30.436914<br>