cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/9df301adbfd619fa474e1041f0070c05
title: Settlement-Era Tree Composition, Ohio: Level 1

description: Ohio Township Surveys (OTS) provide spatially aggregated witness tree counts within the town/township polygons that were tallied from early land survey records of town outlines and lotting subdivisions. Overall dates ranged from 1623 to 1870, but varied by town and were recorded about the time of first settlement of the town. A myriad of archived sources were tapped from town, state and national repositories, historical societies and private collections. The SetTreeComp_Ohio_Level1_v1.0 database includes records throughout the domain from the Connecticut Western Reserve at the Connecticut State Archives and various records in the Ohio State Archives collated by Charles Cogbill, the collections of the Ohio Biological Survey through the efforts of Ronald Stuckey and the McLachlan lab at Notre Dame University, and records of the Ohio Land Company by James Dyer and the Marietta College Archives. Every effort was used to avoid duplication of trees. The taxa classes were generally genera or unambiguous categories based on the vernacular names used by the surveyors. In several cases (black gum/sweet gum, ironwood, poplar/tulip poplar, cedar/juniper), because of ambiguity in the common tree names used by surveyors, a group represents trees from different families and even orders. This material is based upon work supported by the National Science Foundation under grants #DEB-1241874, 1241868, 1241870, 1241851, 1241891, 1241846, 1241856, 1241930.
DOI: 10.6073/pasta/aa0ef9828d41569a96651b056ad89fb3
title: Settlement-Era Gridded Tree Composition, Midwestern US: Level 1

description: Gridded forest composition data for Minnesota, Wisconsin, Michigan, and portions of Illinois and Indiana from survey notes from the Public Land Survey System (PLSS), prior to widespread land use conversion by EuroAmerican settlers. The Public Land Survey System in this region was carried out from approx. 1800 - 1904, in a time transgressive manner from east to west. Trees identified at section and quartersection points within the PLSS are aggregated to a regular 8km grid on a Great Lakes St. Lawrence Albers projection (EPSG:3175). For all points only the closest two trees are used in estimating composition and then summed within the 8km grid cell. The raw count of trees is reported, including "No trees" where surveyors found no trees within 300 links of the point. Methods and data are described in Goring et al., 2015 (http://biorxiv.org/content/early/2015/10/24/026575), except for data from Illinois and Indiana which are described in the methods below. This material is based upon work supported by the National Science Foundation under grants #DEB-1241874, 1241868, 1241870, 1241851, 1241891, 1241846, 1241856, 1241930.
DOI: 10.5517/ccdc.csd.cc28qghz
title: CCDC 2106961: Experimental Crystal Structure Determination

description: Related Article: Richard Staples, Joel Dopke|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28rv41
title: CCDC 2108283: Experimental Crystal Structure Determination

description: Related Article: James Kaduk|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc28swwv
title: CCDC 2109298: Experimental Crystal Structure Determination

description: Related Article: Riku Enomoto, Megumi Hoshi, Hironaga Oyama, Hideki Agata, Shinichi Kurokawa, Hitoshi Kuma, Hidehiro Uekusa, Yoichi Murakami|2021|Materials Horizons|8|3449|doi:10.1039/D1MH01542G
DOI: 10.5517/ccdc.csd.cc28swxw
title: CCDC 2109299: Experimental Crystal Structure Determination

description: Related Article: Riku Enomoto, Megumi Hoshi, Hironaga Oyama, Hideki Agata, Shinichi Kurokawa, Hitoshi Kuma, Hidehiro Uekusa, Yoichi Murakami|2021|Materials Horizons|8|3449|doi:10.1039/D1MH01542G
DOI: 10.5517/ccdc.csd.cc28swyx
title: CCDC 2109300: Experimental Crystal Structure Determination

description: Related Article: Riku Enomoto, Megumi Hoshi, Hironaga Oyama, Hideki Agata, Shinichi Kurokawa, Hitoshi Kuma, Hidehiro Uekusa, Yoichi Murakami|2021|Materials Horizons|8|3449|doi:10.1039/D1MH01542G
DOI: 10.5517/ccdc.csd.cc28thwh
title: CCDC 2109887: Experimental Crystal Structure Determination

description: Related Article: Dan Luo, Yanlei He, Jinya Tian, Jonathan L. Sessler, Xiaodong Chi|2021|J.Am.Chem.Soc.|144|113|doi:10.1021/jacs.1c11731
DOI: 10.5517/ccdc.csd.cc28thzl
title: CCDC 2109890: Experimental Crystal Structure Determination

description: Related Article: Dan Luo, Yanlei He, Jinya Tian, Jonathan L. Sessler, Xiaodong Chi|2021|J.Am.Chem.Soc.|144|113|doi:10.1021/jacs.1c11731
DOI: 10.5517/ccdc.csd.cc28tj3r
title: CCDC 2109894: Experimental Crystal Structure Determination

description: Related Article: Dan Luo, Yanlei He, Jinya Tian, Jonathan L. Sessler, Xiaodong Chi|2021|J.Am.Chem.Soc.|144|113|doi:10.1021/jacs.1c11731
DOI: 10.5517/ccdc.csd.cc28xnql
title: CCDC 2112920: Experimental Crystal Structure Determination

description: Related Article: Takuma Kato, Saki Matsukura, Akiko Asano, Mitsunobu Doi|2021|CSD Communication|||
DOI: 10.5281/zenodo.5714446
title: RICCH: An Interactive Analysis Tool for Risk and Impacts of Climate Change on Hydropower Database

description: The "RICCH: An Interactive Analysis Tool for Risk and Impacts of Climate Change on Hydropower" Database, referred to as the RICCH Database, includes a "Hydropower Plants Database" and the incorporation of future hydropower usable capacity for 542 hydropower plants in the Global South. The "Hydropower Plants Database" includes the main design and location characteristics of 542 hydropower plants across 52 countries. Additionally, we incorporate the results of future usable capacity simulations using a multi-model ensemble of 21 Global Climate Models (GCMs) and two representative concentration pathways (RCPs). We use a multi-model ensemble of 21 GCMs from NASA's NEX GDDP dataset RCP 4.5 and RCP 8.5. We aggregate the mean monthly usable capacity (MW) for each model and scenario, for the early century (2010-2039), mid-century (2040-2069), and the end-of-the-century (2070-2099). We include these results for every power plant in the RICCH database. <em>Example: Itaipu (power plant in Brazil) has a record for its simulated mean monthly usable capacity for January (1) in the early century (2010-2039), under GCM ACCESS1_0 and RCP 4.5.</em>
DOI: 10.5281/zenodo.5714445
title: RICCH: An Interactive Analysis Tool for Risk and Impacts of Climate Change on Hydropower Database

description: The "RICCH: An Interactive Analysis Tool for Risk and Impacts of Climate Change on Hydropower" Database, referred to as the RICCH Database, includes a "Hydropower Plants Database" and the incorporation of future hydropower usable capacity for 542 hydropower plants in the Global South. The "Hydropower Plants Database" includes the main design and location characteristics of 542 hydropower plants across 52 countries. Additionally, we incorporate the results of future usable capacity simulations using a multi-model ensemble of 21 Global Climate Models (GCMs) and two representative concentration pathways (RCPs). We use a multi-model ensemble of 21 GCMs from NASA's NEX GDDP dataset RCP 4.5 and RCP 8.5. We aggregate the mean monthly usable capacity (MW) for each model and scenario, for the early century (2010-2039), mid-century (2040-2069), and the end-of-the-century (2070-2099). We include these results for every power plant in the RICCH database. <em>Example: Itaipu (power plant in Brazil) has a record for its simulated mean monthly usable capacity for January (1) in the early century (2010-2039), under GCM ACCESS1_0 and RCP 4.5.</em>
DOI: 10.5281/zenodo.5851109
title: maDLC Parenting Benchmark Dataset - Training

description: see https://benchmark.deeplabcut.org/ for more information.
DOI: 10.5281/zenodo.5851108
title: maDLC Parenting Benchmark Dataset - Training

description: see https://benchmark.deeplabcut.org/ for more information.
DOI: 10.5281/zenodo.5851157
title: maDLC Tri-Mouse Benchmark Dataset - Training

description: see https://benchmark.deeplabcut.org/ for more information.
DOI: 10.5281/zenodo.5851156
title: maDLC Tri-Mouse Benchmark Dataset - Training

description: see https://benchmark.deeplabcut.org/ for more information.
DOI: 10.6073/pasta/1d1d319ca13c351c483bdcede22e557f
title: Florida Bay Stable Isotope Data Everglades National Park (FCE LTER), South Florida, USA, ongoing since January 2005

description: 13C and 15N stable isotope data from seagrasses collected during visits to FCE LTER core research sites TS/Ph 7a, TS/Ph8, TS/Ph9, TS/Ph10 and TS/Ph11.
DOI: 10.5281/zenodo.5851205
title: CLNews19-20: A new dataset for rumor detection in Spanish

description: We create CLNews, a dataset for rumor detection in Spanish. Based on fact-checking agencies' data, we mapped related tweets to verify news into four categories: non-rumor, true rumor, false rumor, and unverified rumors. Mapping these news to Twitter, we collected data, including tweet timelines and conversational threads. We release this dataset to promote research in this area in Spanish.
DOI: 10.5281/zenodo.5851204
title: CLNews19-20: A new dataset for rumor detection in Spanish

description: We create CLNews, a dataset for rumor detection in Spanish. Based on fact-checking agencies' data, we mapped related tweets to verify news into four categories: non-rumor, true rumor, false rumor, and unverified rumors. Mapping these news to Twitter, we collected data, including tweet timelines and conversational threads. We release this dataset to promote research in this area in Spanish.
DOI: 10.34740/kaggle/dsv/3044266
title: Vietnam SARS-CoV-2 | COVID-19 Data
DOI: 10.5281/zenodo.5851209
title: Snappable Meshes Performance Dataset

description: <strong>Overview</strong> This dataset contains performance and navigation benchmarks obtained by generating eight maps with the snappable meshes algorithm multiple times. Data in columns is organized as follows: <code>run</code> - Number of generation run. <code>genset</code> - Generated map (maps "(a)" to "(h)" from the Benchmark scene. <code>navset</code>- Number of navigation points used to generate the navigation metrics. <code>tg</code> - Duration of the map generation process, in milliseconds. <code>tv</code> - Duration of the map validation process, in milliseconds. <code>c</code> - Average percentage of valid connections between navigation points. <code>ar</code> - Relative area of the largest fully-connected (i.e., fully-navigable) region. <code>nclu</code> - Number of isolated regions, i.e., of regions which are not connected to any another. <code>genseed</code> - Seed used for the generation process. <code>navseed</code> - Seed used for determining the validation metrics. A number of results presented in the research paper "Procedural Generation of 3D Maps with Snappable Meshes" are obtained from this dataset. <strong>Reproducibility of results</strong> The results presented in the research paper "Procedural Generation of 3D Maps with Snappable Meshes", namely in Figure 8 and Figure 10, can be reproduced with the Jupyter notebook included with this dataset (file <code>analysis.ipynb</code>). <strong>Licenses</strong> The dataset is made available under a CC-BY 4.0 license (see <code>LICENSE_DATA.txt</code>). The code in the Jupyter Notebook is made available under the MIT license (see <code>LICENSE_CODE.txt</code>).
DOI: 10.5281/zenodo.5851208
title: Snappable Meshes Performance Dataset

description: <strong>Overview</strong> This dataset contains performance and navigation benchmarks obtained by generating eight maps with the snappable meshes algorithm multiple times. Data in columns is organized as follows: <code>run</code> - Number of generation run. <code>genset</code> - Generated map (maps "(a)" to "(h)" from the Benchmark scene. <code>navset</code>- Number of navigation points used to generate the navigation metrics. <code>tg</code> - Duration of the map generation process, in milliseconds. <code>tv</code> - Duration of the map validation process, in milliseconds. <code>c</code> - Average percentage of valid connections between navigation points. <code>ar</code> - Relative area of the largest fully-connected (i.e., fully-navigable) region. <code>nclu</code> - Number of isolated regions, i.e., of regions which are not connected to any another. <code>genseed</code> - Seed used for the generation process. <code>navseed</code> - Seed used for determining the validation metrics. A number of results presented in the research paper "Procedural Generation of 3D Maps with Snappable Meshes" are obtained from this dataset. <strong>Reproducibility of results</strong> The results presented in the research paper "Procedural Generation of 3D Maps with Snappable Meshes", namely in Figure 8 and Figure 10, can be reproduced with the Jupyter notebook included with this dataset (file <code>analysis.ipynb</code>). <strong>Licenses</strong> The dataset is made available under a CC-BY 4.0 license (see <code>LICENSE_DATA.txt</code>). The code in the Jupyter Notebook is made available under the MIT license (see <code>LICENSE_CODE.txt</code>).
DOI: 10.25423/cmcc/medsea_multiyear_wav_006_012_medwam3i
title: Mediterranean Sea Waves Reanalysis INTERIM (CMEMS Med-Waves, MEDWAM3i system)
title: MEDSEA_MULTIYEAR_WAV_006_012-INTERIM

description: The INTERIM wave reanalysis for the Mediterranean Sea is a dataset of the MEDSEA_MULTIYEAR_WAV_006_012 multi-year (reanalysis) product of the Mediterranean Sea Waves forecasting system (WAM 4.6.2). It is composed by hourly wave parameters at 1/24° horizontal resolution covering the Mediterranean Sea and extending up to 18.125W into the Atlantic Ocean. It includes an optimal interpolation assimilation scheme assimilating significant wave height along track satellite observations available through CMEMS and it is forced with daily averaged surface currents from the CMEMS Med-physics reanalysis and with 1-h, 0.25° horizontal-resolution ERA5/ERA5T reanalysis 10m-above-sea-surface winds from ECMWF.
DOI: 10.5281/zenodo.4311546
title: Expert system for automatic classification of European bog vegetation plots

description: <strong>EUR_OXY_SPH_Expert_system_file</strong> is an expert system for automatic classification of European bog vegetation plots of <em>Oxycocco-Sphagnetea </em>class. The expert system allows classification of new vegetation plots to a hierarchical phytosociological system of syntaxa, a class (<em>Oxycocco-Sphagnetea</em>), orders (<em>Erico-Ledetalia</em>, <em>Sphagnetalia medii</em>), and alliances (<em>Erico mackaianae-Sphagnion papillosi,</em> <em>Ericion tetralicis, </em><em>Oxycocco-Ericion tetralicis,</em> <em>Sphagnion medii</em>, <em>Oxycocco microcarpi-Empetrion hermaphroditi</em>, <em>Rubo chamaemori-Dicranion elongati</em>)<em>.</em> The class is defined on the basis of the ratio between the sum of square-root transformed percentage covers of 'Bog species' (groups ##D +01 Bog-diagnostic-vascular, ##D +02 Bog-diagnostic-bryophytes), and the sum of square-root transformed percentage covers of species occurring in bog hollows and species occurring out of the bog habitat (groups ##D +01 Vascular_negative, ##D +02 Bryophytes_negative). For classification of a plot to an alliance, the conditions for class and order must be fulfilled, and additionally, the plot must contain a greater proportion of discriminating species group of a certain alliance than that of other alliances of the same order. Each of the three conditions must be fulfilled independently. In addition, the presence of a minimum number of diagnostic species might be required in the definition of alliances. If the discriminating species groups of the orders have the same representation in a plot or the discriminating species are absent, this plot is classified only at the class level. Similarly, if the discriminating species groups of different alliances have the same representation in a plot or the discriminating species are absent, this plot is classified only at the order level. The use of discriminating species groups excludes the possibility of classifying a vegetation-plot record in more than one group at the same hierarchical level. The principles of the expert system follow the methods described by Chytrý et al. (2020) The classification of a set of vegetation plots can be run in the JUICE program (Tichý 2002; https://www.sci.muni.cz/botany/juice/), TURBOVEG 3 program (Hennekens 2015) and an R script developed by H. Bruelheide et al. (submitted).
DOI: 10.5287/bodleian:qmqq0nm8r
title: Persistence Diagrams to Visualise Damage to Biological Networks: Supplementary Dataset
DOI: 10.25390/caryinstitute.11561448.v2
title: Cary Environmental Monitoring Program Stream Hydrology Data: 1993-2020

description: The Cary Institute of Ecosystem Studies Environmental Monitoring Program is a long-term data collection program designed to understand how the environment changes over time. The program includes monitoring of climate including temperature and precipitation, as well as variables related to air pollution, such as acid deposition and ozone, and water pollution and streamwater hydrology. The Cary Institute of Ecosystem Studies, Environmental Monitoring Program furnishes data under the following conditions: The data have received quality assurance scrutiny by our program, and, although we are confident of the accuracy of these data, the Cary Institute will not be held liable for errors in these data. Data are subject to change resulting from updates in data screening or models used. Data citation: The following is a standard citation for referencing data from the Cary Institute of Ecosystem Studies, Environmental Monitoring Program:<br>Cary Institute of Ecosystem Studies, Environmental Monitoring Program. 2019 (or current year). Cary Institute of Ecosystem Studies, Box AB, Millbrook, NY 12545, www.caryinstitute.org.<br>Those wishing to publish data from the Cary Institute of Ecosystem Studies, Environmental Monitoring Program are encouraged to contact Data Manager Vicky Kelly, kellyv@caryinstitute.org.
DOI: 10.6073/pasta/264b8de260915cebc230673d37dbbad5
title: Rainfall at El Verde Field Station, Rio Grande, Puerto Rico since 1975

description: Rainfall has been measured at the El Verde Field Station since 1964. McDowell and Estrada-Pinto, 1988 presents a description of the collection procedures, raw data from 1964 to 1986, and some summary statistics for this period of record. Precipitation for this period showed some seasonality in monthly means, with a peak in May. Monthly averages for the period of 1975 to current chart can be found at this site. The highest values for the monthly averages for the period of 1975 to 2000 are from August to December with a low in October and November the highest. In this period the highest amount of total annual rainfall was in 1998 with 5293.61 mm and the minimum in 1994 with 1402.87 mm.
DOI: 10.25390/caryinstitute.11561448.v3
title: Cary Environmental Monitoring Program Stream Hydrology Data: 1993-2021

description: The Cary Institute of Ecosystem Studies Environmental Monitoring Program is a long-term data collection program designed to understand how the environment changes over time. The program includes monitoring of climate including temperature and precipitation, as well as variables related to air pollution, such as acid deposition and ozone, and water pollution and streamwater hydrology. The Cary Institute of Ecosystem Studies, Environmental Monitoring Program furnishes data under the following conditions: The data have received quality assurance scrutiny by our program, and, although we are confident of the accuracy of these data, the Cary Institute will not be held liable for errors in these data. Data are subject to change resulting from updates in data screening or models used. Data citation: The following is a standard citation for referencing data from the Cary Institute of Ecosystem Studies, Environmental Monitoring Program:<br>Cary Institute of Ecosystem Studies, Environmental Monitoring Program. 2021 (or current year). Cary Institute of Ecosystem Studies, Box AB, Millbrook, NY 12545, www.caryinstitute.org.<br>Those wishing to publish data from the Cary Institute of Ecosystem Studies, Environmental Monitoring Program are encouraged to contact Data Manager Vicky Kelly, kellyv@caryinstitute.org.
DOI: 10.6073/pasta/d3ee48a53ba9a263544fc6f38b7e9c48
title: Maximum temperature at El Verde Field Station, Rio Grande, Puerto Rico since October 1992

description: Daily emperature has been measured at the El Verde Field Station since 1975 (see methods). These data was divided into two data set: #16, having data from 1992 to current and #181 which has data from1975 till August 1992. Data-missing gaps where filled in by extrapolated data from other sources, making the subsequent manipulations less valuable for interpreting long term trends. Monthly averages have been calculated. Maximum values for maximum temperature were recorded from May to October with a range from 29 to 30 and peaks of 29.7 Centigrade in October. The months of October through December show the most dramatic increase, specially December (see chart). Highest average maximum temperatures during these years were recorded in 1998 and 1999 (See chart). Max monthly temperatures appear to be increasing from this years on.
DOI: 10.6084/m9.figshare.13224617
title: Systems-informed genome mining for electroautotrophic microbial production

description: Supplementary data for Abel, Hilzinger, Arkin, and Clark 2020.<br><br>Dataset from Comsol model of direct electron uptake-driven electromicrobial production. Compares productivity of O2 and NO3- as terminal electron acceptors, and four carbon fixation pathways. <br><br>Jackhmmer output files, fasta files for trees, marker gene phylogenetic tree files, marker gene presence/absence table, summary phylogenies for paper figures.
DOI: 10.6084/m9.figshare.13224617.v5
title: Systems-informed genome mining for electroautotrophic microbial production

description: Supplementary data for Abel, Hilzinger, Arkin, and Clark 2020.<br><br>Dataset from Comsol model of direct electron uptake-driven electromicrobial production. Compares productivity of O2 and NO3- as terminal electron acceptors, and four carbon fixation pathways. <br><br>Jackhmmer output files, fasta files for trees, marker gene phylogenetic tree files, marker gene presence/absence table, summary phylogenies for paper figures.
DOI: 10.6084/m9.figshare.13224617.v4
title: Systems-informed genome mining for electroautotrophic microbial production

description: Supplementary data for Abel, Hilzinger, Arkin, and Clark 2020.<br><br>Dataset from Comsol model of direct electron uptake-driven electromicrobial production. Compares productivity of O2 and NO3- as terminal electron acceptors, and four carbon fixation pathways. <br><br>Jackhmmer output files, fasta files for trees, marker gene phylogenetic tree files, marker gene presence/absence table, summary phylogenies for paper figures.
DOI: 10.6084/m9.figshare.17062373
title: Microorganismal cues involved in host-location in Asilidae parasitoids-supl.csv

description: raw data from orientation experiments
DOI: 10.6084/m9.figshare.17062373.v2
title: Microorganismal cues involved in host-location in Asilidae parasitoids-supl.csv

description: raw data from orientation experiments
DOI: 10.6084/m9.figshare.17062373.v1
title: Microorganismal cues involved in host-location in Asilidae parasitoids-supl.csv

description: raw data from orientation experiments
DOI: 10.5281/zenodo.5851199
title: Automatic learning of hydrogen-bond fixes in an AMBER RNA force field - dataset

description: Supporting data related to manuscript "Automatic learning of hydrogen-bond fixes in an AMBER RNA force field"
description: {"references": ["https://arxiv.org/abs/2201.04078"]}
DOI: 10.5281/zenodo.5851198
title: Automatic learning of hydrogen-bond fixes in an AMBER RNA force field - dataset

description: Supporting data related to manuscript "Automatic learning of hydrogen-bond fixes in an AMBER RNA force field"
description: {"references": ["https://arxiv.org/abs/2201.04078"]}