cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24431/rw1k58m
title: Size-fractionated chlorophyll collected from CTD samples in Chukchi Seas during Arctic Integrated Ecosystem Research Program 2019

description: These data are part of the Arctic IES component of the Arctic Integrated Ecosystem Research Program (IERP), sponsored by the North Pacific Research Board (NPRB), Collaborative Alaskan Arctic Studies Program (formerly the North Slope Borough/Shell Baseline Studies Program), Bureau of Ocean Energy Management (BOEM), and the Office of Naval Research Marine Mammals and Biology Program. These data are discrete samples for size-fractionated chlorophyll analysis. Samples were collected on the Arctic EIS cruise in late summer 2019 in the Chukchi Sea. Samples were collected directly from Niskin bottles, filtered through a sequential filter setup to create 3 size fractions. The entire data fileis presented as a comma separated value file. The file"Variable definitions_chlorophyll.docx" is a reference for the variable titles used as headers in the csv.
DOI: 10.24431/rw1k58n
title: Pico- and Nanoplankton in the Chukchi Sea, quantified by flow cytometry, Arctic Integrated Ecosystem Research Program 2019

description: These data are part of the Arctic IES component of the Arctic Integrated Ecosystem Research Program (IERP), sponsored by the North Pacific Research Board (NPRB), Collaborative Alaskan Arctic Studies Program (formerly the North Slope Borough/Shell Baseline Studies Program), Bureau of Ocean Energy Management (BOEM), and the Office of Naval Research Marine Mammals and Biology Program. This dataset is presented as a single comma separated values file. It includes discrete samples collected from niskin bottles for analysis of pico- and nanoplankton abundance by flow cytometry. Specifically population abundances for Synechococcus, picoeukaryotes (&lt;3um), nanoeukaryotes (3-10um) and cryptophytes were quantified. Based upon the average size of cells in each of the identified populations, carbon per cell and carbon per population were estimated. Samples were collected in the Chukchi Sea during late summer. The file "Variable definitions_flow_cytometry_phytoplankton.docx" is a reference for the variable titles used as headers in the csv.
DOI: 10.24431/rw1k58o
title: Phytoplankton cell counts in the Chukchi Sea, quantified by flow cytometry, Arctic Integrated Ecosystem Research Program ASGARD 2017

description: These data are part of the ASGARD component of the Arctic Integrated Ecosystem Research Program (IERP), sponsored by the North Pacific Research Board (NPRB), Collaborative Alaskan Arctic Studies Program (formerly the North Slope Borough/Shell Baseline Studies Program), Bureau of Ocean Energy Management (BOEM), and the Office of Naval Research Marine Mammals and Biology Program. These data were collected during the ASGARD 2017 cruise during June 2017. Data were collected throughout the water column on all the 'core' stations, as well as several other stations to fill in the spatial gaps. Samples were analyzed by flow cytometry to quantify the abundance of the smaller phytoplankton cells present as described in Moran et al. 2012. Cell abundances of Synechococcus, picoeukaryotes, nanoeukaryotes and the specific eukaryotic group cryptophytes are provided, as well as their conversion to carbon per cell as in Casey et al. 2013, and then in carbon per population (product of cell carbon and cell number). In addition to these data are relevant sampling metadata: Station, location, CTD bottle fire data, etc. The data format is a csv file. If there was a bottle fire and no sample was taken, it is represented by '-999'.
DOI: 10.24431/rw1k58p
title: Particulate Phosphorus concentrations from North Bering and Chukchi Seas Arctic Integrated Ecosystem Research Program, ASGARD 2017

description: These data are part of the ASGARD component of the Arctic Integrated Ecosystem Research Program (IERP), sponsored by the North Pacific Research Board (NPRB), Collaborative Alaskan Arctic Studies Program (formerly the North Slope Borough/Shell Baseline Studies Program), Bureau of Ocean Energy Management (BOEM), and the Office of Naval Research Marine Mammals and Biology Program. Samples were collected on the ASGARD 2017 cruise at the 10 core process stations, plus several to fill in spatial gaps. Samples were drawn from the Niskin at several depths through the entire water column and filtered on precombusted GFF filters. Data are presented in units of nmol/L. The entire data file contains other CTD bottle fire metadata for interpretation of the particulate phosphorus data.
DOI: 10.24431/rw1k58q
title: Phytoplankton cell counts in the Chukchi Sea, quantified by flow cytometry, Arctic Integrated Ecosystem Research Program, ASGARD 2018

description: These data are part of the ASGARD component of the Arctic Integrated Ecosystem Research Program (IERP), sponsored by the North Pacific Research Board (NPRB), Collaborative Alaskan Arctic Studies Program (formerly the North Slope Borough/Shell Baseline Studies Program), Bureau of Ocean Energy Management (BOEM), and the Office of Naval Research Marine Mammals and Biology Program. These data were collected during the ASGARD 2017 cruise during June 2018. Data were collected throughout the water column on all the 'core' stations, as well as several other stations to fill in the spatial gaps. Samples were analyzed by flow cytometry to quantify the abundance of the smaller phytoplankton cells present as described in Moran et al. 2012. Cell abundances of Synechococcus, picoeukaryotes, nanoeukaryotes and the specific eukaryotic group cryptophytes are provided, as well as their conversion to carbon per cell as in Casey et al. 2013, and then in carbon per population (product of cell carbon and cell number). In addition to these data are relevant sampling metadata: Station, location, CTD bottle fire data, etc. The data format is a csv file. If there was a bottle fire and no sample was taken, it is represented by '-999'.
DOI: 10.5281/zenodo.4926921
title: Broad-band spectroscopy of a vanadyl porphyrin: a model electronuclear spin qudit. Open data sets.

description: Data sets supporting all figures in the publication plus a data sheet with details about how these data were obtained and processed. It also includes a Phyton script to evaluate the universality plots for molecular spin processors.
DOI: 10.5281/zenodo.4926920
title: Broad-band spectroscopy of a vanadyl porphyrin: a model electronuclear spin qudit. Open data sets.

description: Data sets supporting all figures in the publication plus a data sheet with details about how these data were obtained and processed. It also includes a Phyton script to evaluate the universality plots for molecular spin processors.
DOI: 10.24431/rw1k58r
title: Particulate Phosphorus concentrations from North Bering and Chukchi Seas Arctic Integrated Ecosystem Research Program, ASGARD 2018

description: These data are part of the ASGARD component of the Arctic Integrated Ecosystem Research Program (IERP), sponsored by the North Pacific Research Board (NPRB), Collaborative Alaskan Arctic Studies Program (formerly the North Slope Borough/Shell Baseline Studies Program), Bureau of Ocean Energy Management (BOEM), and the Office of Naval Research Marine Mammals and Biology Program. These data are derived from particulate phosphorus samples collected on the Sikuliaq 2018 cruise through the north Bering and Chukchi seas, taken at all process stations, plus several other stations to fill in spatial gaps. Samples were drawn from the Niskin at several depths through the entire water column and filtered on precombusted GFF filters. Data are presented in a comma separated values file, in units of nanomoles per liter. The entire data file contains other CTD bottle fire metadata for interpretation of the particulate phosphorus data. The file"Variable definitions_particulate matter.docx" is a reference for the variable titles used as headers in the csv.
DOI: 10.5066/p95euzio
title: Wilcox Group Apparent Thickness, Gulf Coast (wlcxthkg)

description: The Apparent Wilcox Group thickness maps are contoured from location and top information derived from the Petroleum Information (PI) Wells database. The Wilcox apparent thickness map was constructed by searching for Wilcox and Midway Group tops. Apparent thickness is computed by subtracting Midway top from the Wilcox top. Geographic control is superimposed on the maps from USGS state line, county, elevation and other data files. The veracity of the PI Wells database is being checked by comparison to published cross sections and geologic maps. Interpretation of the depth to Wilcox and apparent thickness maps along with published measured sections and cross sections indicates that portions of Texas, Louisiana, Mississippi and Alabama contain broad areas where a 20 to 40 foot net thickness of lignite and coal occur at shallow depths. The thicker coal zones are attributed to growth faulting or rift zones influencing peat deposition. The depth to Wilcox map shows several areas where dome-like uplifts and bench-like coal-bearing rock are buried to depths less than 5,000 ft.
DOI: 10.15468/8rwpsn
title: A new species of Melampyrum (Orobanchaceae) from Southern Korea

description: This dataset contains the digitized treatments in Plazi based on the original journal article Kim, Ki-Joong, Yun, Seok-Min (2012): A new species of Melampyrum (Orobanchaceae) from Southern Korea. Phytotaxa 42: 48-50, DOI: 10.11646/phytotaxa.42.1.6, URL: http://biotaxa.org/Phytotaxa/article/view/phytotaxa.42.1.6
DOI: 10.5281/zenodo.4928103
title: CCMiResearch/DEMOCaseStudies: Procedural Law Case Studies

description: Procedural law case studies including: Czech Arbitration Court Code of Civil Procedure
DOI: 10.5281/zenodo.4928097
title: Datasets for Study on Cold Temperature Limitation on GPP in an Evergreen Forest

description: Data used in publication "Resolving temperature limitations on spring productivity in an evergreen conifer forest using a model-data fusion framework" <strong>MonthlyTowerData.nc </strong> Monthly averaged meteorological and GPP data from AmeriFlux US-NR1 tower (January 2000 - December 2018). <strong>CARDAMOMoutputs.nc</strong> CARDAMOM model GPP outputs for four experiments. Dimensions are 228 months (Jan 2000 through December 2018) by 4000 ensemble members for each experiment. <strong>TBM-MIPoutputs.nc</strong> TBM-MIP model GPP outputs (January 2000-December 2018).
DOI: 10.5281/zenodo.4928096
title: Datasets for Study on Cold Temperature Limitation on GPP in an Evergreen Forest

description: Data used in publication "Resolving temperature limitations on spring productivity in an evergreen conifer forest using a model-data fusion framework" <strong>MonthlyTowerData.nc </strong> Monthly averaged meteorological and GPP data from AmeriFlux US-NR1 tower (January 2000 - December 2018). <strong>CARDAMOMoutputs.nc</strong> CARDAMOM model GPP outputs for four experiments. Dimensions are 228 months (Jan 2000 through December 2018) by 4000 ensemble members for each experiment. <strong>TBM-MIPoutputs.nc</strong> TBM-MIP model GPP outputs (January 2000-December 2018).
DOI: 10.15468/6sc2c2
title: Valve morphology of four species of Frustulia (Bacillariophyta), including two described as new

description: This dataset contains the digitized treatments in Plazi based on the original journal article Graeff, Carrie, Kociolek, John Patrick, Burliga, Ana Luiza (2012): Valve morphology of four species of Frustulia (Bacillariophyta), including two described as new. Phytotaxa 42: 62-76, DOI: 10.11646/phytotaxa.42.1.8, URL: http://biotaxa.org/Phytotaxa/article/view/phytotaxa.42.1.8
DOI: 10.6084/m9.figshare.14770935
title: Chandler et al. (2021) - MetaData

description: MetaData from Chandler et al. (2021) including descriptions of all associated data files and R scripts.
DOI: 10.6084/m9.figshare.14770635
title: EIS_Regions_WGS84

description: Shapefiles for the U.S. Fish and Wildlife Service's Eastern Indigo Snake conservation regions. Used in a cross-validation analysis to evaluate the performance of our model in different regions (Table 3 in our manuscript).
DOI: 10.6084/m9.figshare.14770392.v1
title: East_West_Bins_5k_WGS84

description: The shapefile of the spatial cross-validation bins from east to west across our study area. The bins themselves are longest north to southand were manually drawn to allow each bin to approximate the range of environmental conditions across our study area. Bin numbersfor each background/used point are denoted by column "NS_Bin" in the CSV data file but correspond to "EW Bins" in Table 2 andEast-West Bins in Table 3 of our manuscript.
DOI: 10.6084/m9.figshare.14766189.v1
title: Indigo_snake_uniform_random_background_points_with_covariates

description: The files contains the covariate values for 337,952 points sampled randomly across our study area without regards to distance from nearest road to be used in calibrating our models. All column names are the same as described for "Indigo_snake_HSM_data_with_covariates". <br>
DOI: 10.6084/m9.figshare.14763258
title: Indigo_snake_HSM_data_with_covariates

description: This file contains covariate values for the 497,649 background points and 1215 indigo snake presence (used) points used to develop our model. We have withheld specific locations of snake observations, but they are available on request, either from the authors or from the U.S. Fish and Wildlife Service. Briefly, each covariate layer was measured at several spatial scales that are denoted by the number in the column name. Base scales are the individual pixel values (30 m pixels) for that layer and numbers 250, 500, 1000, 2500, or 5000 represent the radii of a circular buffer (in meters) used to calculate a mean value around each point. Secific details reguarding data sources are provided in the full publication but a list of layers.
DOI: 10.6084/m9.figshare.14770392
title: East_West_Bins_5k_WGS84

description: The shapefile of the spatial cross-validation bins from east to west across our study area. The bins themselves are longest north to southand were manually drawn to allow each bin to approximate the range of environmental conditions across our study area. Bin numbersfor each background/used point are denoted by column "NS_Bin" in the CSV data file but correspond to "EW Bins" in Table 2 andEast-West Bins in Table 3 of our manuscript.
DOI: 10.6084/m9.figshare.14770635.v1
title: EIS_Regions_WGS84

description: Shapefiles for the U.S. Fish and Wildlife Service's Eastern Indigo Snake conservation regions. Used in a cross-validation analysis to evaluate the performance of our model in different regions (Table 3 in our manuscript).
DOI: 10.6084/m9.figshare.14771139
title: USFWS_Region_Numbers_for_all_points

description: USFWS_Region_all_data.rdsUSFWS_Region_back.rdsVectors containing the region number from U.S. Fish and Wildlife Service Eastern Indigo Snake conservation regions. Used forcalculating model performance metrics by region.
DOI: 10.6084/m9.figshare.14771139.v1
title: USFWS_Region_Numbers_for_all_points

description: USFWS_Region_all_data.rdsUSFWS_Region_back.rdsVectors containing the region number from U.S. Fish and Wildlife Service Eastern Indigo Snake conservation regions. Used forcalculating model performance metrics by region.
DOI: 10.5066/p9lb9lvc
title: Apparent Depth to the Wilcox Group, Gulf Coast (wlcxdpthg)

description: The depth to top of the Wilcox Group is contoured from location and top information derived from the Petroleum Information (PI) Wells database. The depth to Wilcox map represents the tops found in the database with the addition of surface geology from USGS maps and field data. The veracity of the PI Wells database is being checked by comparison to published cross sections and geologic maps. Interpretation of the depth to Wilcox and apparent thickness maps along with published measured sections and cross sections indicates that portions of Texas, Louisiana, Mississippi and Alabama contain broad areas where a 20 to 40 foot net thickness of lignite and coal occur at shallow depths. The thicker coal zones are attributed to growth faulting or rift zones influencing peat deposition. The depth to Wilcox map shows several areas where dome-like uplifts and bench-like coal-bearing rock are buried to depths less than 5,000 ft.
DOI: 10.6084/m9.figshare.14766189
title: Indigo_snake_uniform_random_background_points_with_covariates

description: The files contains the covariate values for 337,952 points sampled randomly across our study area without regards to distance from nearest road to be used in calibrating our models. All column names are the same as described for "Indigo_snake_HSM_data_with_covariates". <br>
DOI: 10.5281/zenodo.4928225
title: CCMiResearch/DEMOCaseStudies: Procedural Law Case Studies

description: Procedural law case studies including: Czech Arbitration Court Code of Civil Procedure
DOI: 10.5281/zenodo.4928102
title: CCMiResearch/DEMOCaseStudies: Procedural Law Case Studies

description: Procedural law case studies including: Czech Arbitration Court Code of Civil Procedure
DOI: 10.5066/p97lo22q
title: Oil and gas wells of Afghanistan with well logs (welllogafg.shp)

description: This shapefile contains points that describe the location of hydrocarbon exploration and production wells drilled in Afghanistan; and hyperlinks to scanned images of well logs that can be viewed in an ArcReader project.
DOI: 10.6084/m9.figshare.14770671
title: Social Media Viewing - Shout Trout Workout Thomas et al. 2021

description: Data on the views, likes, and comments (YouTube) or retweets (Twitter) associated with Shout Trout Workout (STW), downloaded 17/05/2021. Views on ConnectedWaters Twitter account is up to the date the account was closed on 22nd December 2020. Thomas et al. 2021 (in press) People and Nature (to be updated with DOI). These data are presented in Figure 3 of the manuscript.
DOI: 10.6084/m9.figshare.14770671.v2
title: Social Media Viewing - Shout Trout Workout Thomas et al. 2021

description: Data on the views, likes, and comments (YouTube) or retweets (Twitter) associated with Shout Trout Workout (STW), downloaded 17/05/2021. Views on ConnectedWaters Twitter account is up to the date the account was closed on 22nd December 2020. Thomas et al. 2021 (in press) People and Nature (to be updated with DOI). These data are presented in Figure 3 of the manuscript.
DOI: 10.5066/p918nwu5
title: Structure Contour of the Top of the Upper Miocene Sequence, Gulf Coast

description: The structure contours were created using biostratigraphic data in the Paleo-Data, Inc., Tenroc Regional Geologic Database. The depths of the microfossil locations were associated with the wells data provided by the Louisiana Department of Natural Resources. Because of the proprietary nature of the Tenroc database, no actual data can be shown and only those data points contained in the Louisiana State wells database are included in the control points layer. Contouring was accomplished in Dynamic Graphics, Inc., EarthVision modeling software (v.5) using minimum tension gridding. Three custom programs were used to convert contour lines generated from grids in EarthVision to Arc/Info coverages and then to shapefiles. The data are provided as both lines and polygons (umtoplg.shp and umtoppg.shp), and the public wells that penetrate the top of the Upper Miocene (UM) sequence are provided in a point shapefile (umtopptg.shp). These datasets contain basic data and interpretations developed and compiled by the U.S. Geological Survey's Framework Studies and Assessment of the Gulf Coast Project. Other major sources of data include publicly available information from state agencies as well as publications of the U.S. Geological Survey and other scientific organizations. In cases where company proprietary data were used to produce various derivatives such as contour surfaces, the source is cited but the data are not displayed.
DOI: 10.25380/iastate.14454753
title: Reliability Data: Laboratory Failure-Time and Single-Time Strength Data

description: Reliability tests are commonly used in product design and manufacturing processes to assure the reliability of components, subsystems, and, in some cases, complete systems. Typical responses are time to failure (either in terms of operating time or number of cycle of operation) or strength or other critical material properties. Virtually alllaboratory reliability tests are accelerated (e.g., by testing at an increases cycling rate or at higher-than-usual levels of temperature or voltage) so that information is obtained in a timely manner. The resulting test data are often censored because not all units fail by the end of the test.
DOI: 10.25380/iastate.14454756
title: Reliability Data: Field Failure-time Data

description: It is sometimes said that reliability field data is the “real reliability data” because they reflect actual reliability performance of a product or system. Reliability field data areobtained, most commonly, from warranty returns (combined with production/sales records to provide information on units that were not returned) and maintenance databases. For some products (e.g., medical devices), careful field tracking is done, providing detailed information about all units deployed into the field. Reliability field data are almost always multiply censored because many units had not failedat the time the data were analyzed. In addition to failure times, sometimes failure mode information is also available for units that have failed. Other complications like truncation also arise in some field reliability data sets.
DOI: 10.25380/iastate.14454762.v1
title: Reliability Data: Destructive Degradation Data

description: In some reliability studies, the natural response is measured degradation. Degradation measurement, for some variables, is a destructive process. For example, to measure the strength of an adhesive, load is increased linearly until the adhesive fails. Adhesive strength is then defined as the applied load when the adhesive failed. Similar tests are done to measure dielectric strength by increasing voltage until the dielectric fails. Destructive degradation tests can be accelerated, for example, by aging units at higher-than-usual temperatures. Statistical methods have been developed to model destructive degradation data and make reliability inferences.
DOI: 10.25380/iastate.14454762
title: Reliability Data: Destructive Degradation Data

description: In some reliability studies, the natural response is measured degradation. Degradation measurement, for some variables, is a destructive process. For example, to measure the strength of an adhesive, load is increased linearly until the adhesive fails. Adhesive strength is then defined as the applied load when the adhesive failed. Similar tests are done to measure dielectric strength by increasing voltage until the dielectric fails. Destructive degradation tests can be accelerated, for example, by aging units at higher-than-usual temperatures. Statistical methods have been developed to model destructive degradation data and make reliability inferences.
DOI: 10.25380/iastate.14454765
title: Reliability Data: Repeated Measured Degradation Data

description: In some reliability studies, the natural response is measured degradation (either performance degradation or physical/chemical degradation), as opposed to the traditional failure-time reliability data. Examples include light output from LEDs and lasers. crack length, and the amount of wear. Laboratory degradation tests are typically accelerated by increasing a variable like temperature to increase the degradation rate. Before statistical methods had been developed for repeated measured degradation data, it was common practice to wait for enough units to actually fail and then use statistical methods for failure-time data (Device-A in Chapter 18 of SMRD2 is such an example). There are, however, important advantages for direct modeling and analysis of repeated measures degradation data. In particular, it is possible to make reliability inferences with few or no observed failures and the degradation data contain useful information for checking important model assumptions.