cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6085/aa/ybhx00_xxxibtnxtsr01_20170524.50.1
title: PISCO: Intertidal: site temperature data: Yachats Beach, Oregon, USA (YBHX00)

description: This metadata record describes air temperature data collected at Yachats Beach, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2017-05-24. Site temperature loggers are bolted down in a wire cage at various locations within each site. Mussel growth temperature loggers are bolted down in a wire cage at high, mid, or low positions within a mussel bed. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/ybhx00_xxxibtnxtsr01_20170623.40.1
title: (:unkn)
DOI: 10.6085/aa/ybhx00_xxxibtnxtsr01_20170623.50.1
title: PISCO: Intertidal: site temperature data: Yachats Beach, Oregon, USA (YBHX00)

description: This metadata record describes air temperature data collected at Yachats Beach, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2017-06-23. Site temperature loggers are bolted down in a wire cage at various locations within each site. Mussel growth temperature loggers are bolted down in a wire cage at high, mid, or low positions within a mussel bed. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/ybhx00_xxxibtnxtsr01_20170721.40.1
title: (:unkn)
DOI: 10.6085/aa/ybhx00_xxxibtnxtsr01_20170721.50.1
title: PISCO: Intertidal: site temperature data: Yachats Beach, Oregon, USA (YBHX00)

description: This metadata record describes air temperature data collected at Yachats Beach, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2017-07-21. Site temperature loggers are bolted down in a wire cage at various locations within each site. Mussel growth temperature loggers are bolted down in a wire cage at high, mid, or low positions within a mussel bed. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/ybhx00_xxxibtnxtsr01_20170824.40.1
title: (:unkn)
DOI: 10.6085/aa/ybhx00_xxxibtnxtsr01_20170824.50.1
title: PISCO: Intertidal: site temperature data: Yachats Beach, Oregon, USA (YBHX00)

description: This metadata record describes air temperature data collected at Yachats Beach, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2017-08-24. Site temperature loggers are bolted down in a wire cage at various locations within each site. Mussel growth temperature loggers are bolted down in a wire cage at high, mid, or low positions within a mussel bed. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/ybhx00_xxxibtnxtsr01_20170908.40.1
title: (:unkn)
DOI: 10.6085/aa/ybhx00_xxxibtnxtsr01_20170908.50.1
title: PISCO: Intertidal: site temperature data: Yachats Beach, Oregon, USA (YBHX00)

description: This metadata record describes air temperature data collected at Yachats Beach, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2017-09-08. Site temperature loggers are bolted down in a wire cage at various locations within each site. Mussel growth temperature loggers are bolted down in a wire cage at high, mid, or low positions within a mussel bed. Temperature is recorded at 60.0 minute intervals.
DOI: 10.14469/hpc/4802
title: peracid epoxidation of trans-dicyanopropene, Def2-TZVPPD/DCM/M062X TS -606.463114

description: Gaussian Calculation
DOI: 10.5281/zenodo.1491190
title: Supplemental material to 'Evaluation of force-based and displacement-based out-of-plane seismic assessment methods for unreinforced masonry walls through refined model simulations'

description: This repository contains the results of discrete element simulations used to study the response of vertically-spanning unreinforced masonry walls under different wall configurations. The simulations are run using the software package UDEC 6.0 (Itasca). The dataset has served as basis for the study conducted in the following paper:


Godio M, Beyer K. Evaluation of force-based and displacement-based out-of-plane seismic assessmentmethods for unreinforced masonrywalls through refined model simulations. Earthquake Engng Struct Dyn. 2019;48:454-475. DOI:10.1002/eqe.3144


Version history:<br>
V1: datasets '01_UDEC_VALIDATION' and '02_UDEC_RESULTS are added<br>
V2: minor modifications to the datasets: deletion of unwanted temporary files from the datasets<br>
V3: '00_CONTENT' PDF-file is added
DOI: 10.14469/hpc/4805
title: Test dataset

description: A test dataset of nonsense to test repository functionality
DOI: 10.5281/zenodo.1492219
title: IT-VaLex: Index Thomisticus Valency Lexicon

description: IT-VaLex: <em>Index Thomisticus</em> Valency Lexicon. Website: https://itreebank.marginalia.it/itvalex/
description: {"references": ["McGillivray, B., Passarotti, M., Ruffolo, P. (2009) 'The Index Thomisticus Treebank Project: Annotation, Parsing and Valency Lexicon', TAL 50(2): 103-127. http://www.atala.org/sites/default/files/TAL-2009-50-2-04-McGillivray.pdf", "McGillivray, B., Passarotti, M. (2009) 'The development of the Index Thomisticus Treebank valency lexicon', LaTeCH-SHELT&R '09 Proceedings of the EACL 2009 Workshop on Language Technology and Resources for Cultural Heritage, Social Sciences, Humanities, and Education. ACL, pp. 43-50. https://dl.acm.org/citation.cfm?id=1642055"]}
DOI: 10.15787/vtt1/s4hl3q
title: Factors Impacting the Likelihood of Near-Crashes and Crashes

description: Project Description This study will build a nested logit model for predicting the likelihood near-crashes and crashes by incident type. The upper-level nest will comprise three alternatives (a) no-risky event, (b) near-crash, and (c) crash. The NDS dataset classifies the trips into finer categories but we choose this aggregate three-way classification for our study. Based on preliminary analysis of InSight data, there are over 28,000 trips (including only the "balanced sample baseline trips") with about 1800 crashes and 6600 near-crashes. The lower-level nest, defined only for near-crash and crash events, will include various incident types such as rear-end, road departure, and turn-into-path (the raw data has more than 16 categories, these will be aggregated into a reasonable number of groups for modeling). Road-departure appears to be dominant incident type for crashes while rear-end and side-swipe are dominant incident types for near-crashes. Data Request Scope Selected variables within the Event detail table, Trip, Participant and Vehicle data sets are being requested. The event detail table holds information about near-crashes, crashes etc. which allows for performing nested structures for in the prediction model. The remaining datasets,Trip, Participant and Vehicle data sets provides additional but important information about the event characteristics, information about persons involved in the event (demographics, cognitive and medical conditions etc.) and lastly the vehicle characteristics pertaining to the event occurrence. Data Specification Trip Summary Table Event Detail Table Participant Driver Demographics Questionnaire Driving History Questionnaire Medical Conditions Medications Barkley's ADHD Screening Test Visual and Cognitive Test Sleep Habit Questionnaire Clock Drawing Assessment Sensation Seeking Scale Risk Taking Questionnaire Driver Behavior Questionnaire Vehicle Detail
DOI: 10.5281/zenodo.1492607
title: On the role of eye contact in gaze cueing

description: The data presented here are reported in Kompatsiari et al. 2018<br> Please refer to that paper for context and method.
DOI: 10.14469/hpc/4806
title: peracid epoxidation of aminoethene, TS -438.044292 Activation free energy 22.1 kcal/mol

description: Gaussian Calculation
DOI: 10.17632/wy343nk8nt.1
title: Data for: Adaptation action and research in glaciated mountain systems: Are they enough to meet the challenge of climate change?

description: This Excel file contains three pages of data: 1. Data for all documents reviewed. 2. Data for documents that were explicitly framed as mountain and adaptation focused. 3. Summary statistics for both sets of documents. For pages 1 and 2, columns represent questions asked about each document. See the Questionnaire and Codebook in the article’s Supplementary Materials for details about questions as well as descriptions for possible response options. For pages 1 and 2, values in Column A “PR” and “GL” stand for per-reviewed and grey literature, respectively. For pages 1 and 2, each row represents a ‘discrete adaptation initiative’. Discrete adaptation initiatives are defined as actions that are distinct in their timing, form, intent, or scope. One document may report several discrete adaptation initiatives. For pages 1 and 2, raw data is disaggregated in columns AO - GF to facilitate analysis.
DOI: 10.5063/f13t9ff8
title: Alaska Board of Fisheries Meetings

description: The Alaska Board of Fisheries (BOF) provides a local forum for regional opinions on fish and game issues, facilitates resource allocation, and makes regulatory changes. The BOF holds a variety of meetings each year. This dataset includes information about the dates, locations, and meeting descriptions for BOF meetings that occurred or are slated to occur between 2000 and 2019. The original source of these data is the Alaska Department of Fish and Game. Original data dating back to 2003 were extracted from here: http://www.adfg.alaska.gov/index.cfm?adfg=fisheriesboard.meetinginfo. Glenn Haight, BOF Executive Director, provided information about meetings from years prior to 2003. This dataset was modified by separating the start and end dates from the original "Dates" column into two separate columns.
DOI: 10.5063/f17m065j
title: Pink salmon age, sex, and length data from Prince William Sound, Alaska, 1997-2016

description: Age, sex and length (ASL) data provide population dynamics information that can indicate how population trends occur and may be changing. These data can help researchers estimate population growth rates, age-class distribution, and population demographics. Knowing population demographics, growth rates and trends is particularly valuable to fisheries managers who must perform population assessments to inform management decisions. These data are therefore important in valuable fisheries like the salmon fisheries of Alaska. This dataset includes length data on pink salmon from annual sampling of commercial salmon harvests in Prince William Sound from 1997-2016. Length was measured in millimeters, generally from mid-eye to the fork of the tail. Because pink salmon always return after 2 years at sea, the salt water age was set at 2 for all rows of the dataset to enable easier integration with ASL datasets from other species. This data package includes the original data file (PWS Pink_LenWt_Individual Salmon Data_ALLYEARS copy.xls), a script that reformats the original data file into a consistent format (ASL_formatting_PWS_pink.R), and the reformatted dataset as a .csv file (ASL_formatted_PrinceWilliamSoundpinks.csv).
DOI: 10.5063/f1cc0xxx
title: Historic air temperatures in Alaska for 1901-2015, with spatial subsetting by region

description: The purpose of this project is to extract historic average Alaskan air temperatures across different time intervals for periods of interest (e.g. spawning season, growing season, monthly averages) across different regions of Alaska. Details on the extraction can be found in the file "AirTempHistoric.ipynb" within this package. In particular, the data files in this package comprise records for regional and temporal subsets of the original dataset, with the regional divisions determined by the SASAP (State of Alaska's Salmon and People) project. These data were derived from the "Historical Monthly Temperature - 1 km CRU TS" dataset, available at http://ckan.snap.uaf.edu/dataset/historical-monthly-temperature-1-km-cru-ts. The Historical Monthly Temperature - 1 km CRU TS dataset was created by Matthew Leonawicz, Michael Lindgren, Tom Kurkowski (takurkowski@alaska.edu), Scott Rupp, and John Walsh, funded by the Arctic Landscape Conservation Cooperative, Western Alaska Landscape Conservation Cooperative, and Northwest Boreal Landscape Conservation Cooperative (LCCs) and the Alaska Climate Science Center and is licensed under Creative Commons Attribution 4.0 (https://creativecommons.org/licenses/by/4.0/).
DOI: 10.5066/f74748tv
title: Influence of land use in the northern Great Plains on honey bee health and pollination service delivery, NPWRC (2015-2017)

description: Land use within a 4-km radius around 36 apiaries in North Dakota, South Dakota, and Minnesota was quantified over two years, 2015-16 and 2016-17. The area (hectares) of Ag (corn, soy, small grains), Grass (pasture, grassland, fallow land, wildflowers, shrub land, and hay land), Wetlands (herbaceous and woody), and Bee crops (alfalfa, canola, sunflower) were quantified around each apiary in each year. Within each apiary, the average change in frames of adult bees among all colonies from June to September was calculated. Additionally, the average September Varroa mite infestation rate, the average adult population size during almond pollination, the count of colonies exhibiting queen events in September, and the count of colonies exhibiting disease symptoms (Chalkbrood, American Foulbrood) per apiary were calculated.
DOI: 10.5066/p9thsfe0
title: Calibration datasets and model archive summaries for regression models developed to estimate metal concentrations at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah

description: This data release supports the following publication: Mast, M. A., 2018, Estimating metal concentrations with regression analysis and water-quality surrogates at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah: U.S. Geological Survey Scientific Investigations Report 2018-5116. The U.S. Geological Survey (USGS), in cooperation with the U. S. Environmental Protection Agency (EPA), developed site-specific regression models to estimate concentrations of selected metals at nine USGS streamflow-gaging stations along the Animas and San Juan Rivers. Multiple linear-regression models were developed by relating metal concentrations in discrete water-quality samples to continuously monitored streamflow and surrogate parameters including specific conductance, pH, turbidity, and water temperature. Models were developed for dissolved and total concentrations of aluminum, arsenic, cadmium, iron, lead, manganese, and zinc using water-quality samples collected during 2005-17 by several agencies, using different collection methods and analytical laboratories. Calibration datasets in comma-separated format (CSV) include the variables of sampling date and time, metal concentrations (in micrograms per liter), stream discharge (in cubic feet per second), specific conductance (in microsiemens per centimeter at 25 degrees Celsius), pH, water temperature (in degrees Celsius), turbidity (in nephelometric turbidity units), and calculated seasonal terms based on Julian day. Surrogate parameters and discrete water-quality samples were used from nine sites including Cement Creek at Silverton, Colo. (USGS station 09358550); Animas River below Silverton, Colo. (USGS station 09359020); Animas River at Durango, Colo. (USGS station 09361500); Animas River Near Cedar Hill, N. Mex. (USGS station 09363500); Animas River below Aztec, N. Mex. (USGS station 09364010); San Juan River at Farmington, N. Mex. (USGS station 09365000); San Juan River at Shiprock, N. Mex (USGS Station 09368000); San Juan River at Four Corners, Colo. (USGS station 09371010); and San Juan River near Bluff, Utah (USGS station 09379500). Model archive summaries in pdf format include model statistics, data, and plots and were generated using a R script developed by USGS Kansas Water Science Center available at https://patrickeslick.github.io/ModelArchiveSummary/. A description of each USGS streamflow gaging station along with information about the calibration datasets also are provided.
DOI: 10.5063/f1028psr
title: Historic air temperatures in Alaska for 1901-2015, with spatial subsetting by region

description: The purpose of this project is to extract historic average Alaskan air temperatures across different time intervals for periods of interest (e.g. spawning season, growing season, monthly averages) across different regions of Alaska. Details on the extraction can be found in the file "AirTempHistoric.ipynb" within this package. In particular, the data files in this package comprise records for regional and temporal subsets of the original dataset, with the regional divisions determined by the SASAP (State of Alaska's Salmon and People) project. These data were derived from the "Historical Monthly Temperature - 1 km CRU TS" dataset, available at http://ckan.snap.uaf.edu/dataset/historical-monthly-temperature-1-km-cru-ts. The Historical Monthly Temperature - 1 km CRU TS dataset was created by Matthew Leonawicz, Michael Lindgren, Tom Kurkowski (takurkowski@alaska.edu), Scott Rupp, and John Walsh, funded by the Arctic Landscape Conservation Cooperative, Western Alaska Landscape Conservation Cooperative, and Northwest Boreal Landscape Conservation Cooperative (LCCs) and the Alaska Climate Science Center and is licensed under Creative Commons Attribution 4.0 (https://creativecommons.org/licenses/by/4.0/).
DOI: 10.5281/zenodo.1492821
title: Large Language Model

description: One of the large language models trained in this paper: https://arxiv.org/abs/1810.10045
DOI: 10.5281/zenodo.1492892
title: Large Language Model

description: One of the large language models trained in this paper: https://arxiv.org/abs/1810.10045
DOI: 10.14469/hpc/4809
title: 1st attempt NMR

description: Gaussian Calculation
DOI: 10.14469/hpc/4810
title: Fragmentation maps for spatially explicit coalescence methods

description: Random maps generated for coalescence neutral simulations exploring fragmentation
DOI: 10.5066/p9fp632q
title: Topographic Survey and Streambed-Sediment Data of Fountain Creek between Colorado Springs and the Confluence of Fountain Creek at the Arkansas River, Colorado, 2018

description: In 2012, the U.S. Geological Survey (USGS) in cooperation with Colorado Springs Utilities selected 10 study reaches along Fountain Creek between Colorado Springs, Colorado and the confluence of Fountain Creek with the Arkansas River for annual bed and bank characterization and topographic surveys. The 10 study reaches are approximately 5 to 20 bank-full channel widths in length. Data were collected in 2018 that are similar in method and scope as data collected from 2012 to 2017.Topographic survey points were collected using real-time kinematic Global Navigation Satellite Systems (RTK-GNSS). Pebble-count data were collected at all 10 study reaches and included 4 measurements of grain size at each of 25 equally spaced stations along 4 separate transects across the active channel of each study reach. If 10 percent or more of the samples measured along the pebble-count transect were fine sand or silt (less than 2 millimeters), a streambed-sediment sample was collected for sieve-size analysis at the USGS Iowa Water Science Center Sediment Lab In Iowa City, Iowa.
DOI: 10.6085/aa/bbyx00_xxxibtnxmbr11_20160613.40.1
title: (:unkn)
DOI: 10.6085/aa/bbyx00_xxxibtnxmbr11_20160613.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Boiler Bay, Oregon, USA (BBYX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Boiler Bay, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2016-06-13. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/bbyx00_xxxibtnxmbr12_20160613.40.1
title: (:unkn)
DOI: 10.6085/aa/bbyx00_xxxibtnxmbr21_20160506.40.1
title: (:unkn)
DOI: 10.6085/aa/bbyx00_xxxibtnxmbr21_20160506.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Boiler Bay, Oregon, USA (BBYX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Boiler Bay, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2016-05-06. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/rkpx00_xxxibtnxmbr21_20160613.40.1
title: (:unkn)
DOI: 10.6085/aa/rkpx00_xxxibtnxmbr22_20160506.40.1
title: (:unkn)
DOI: 10.6085/aa/shlx00_xxxibtnxmbr11_20160613.40.1
title: (:unkn)
DOI: 10.6085/aa/shlx00_xxxibtnxmbr11_20160613.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Strawberry Hill, Oregon, USA (SHLX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Strawberry Hill, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2016-06-13. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/shlx00_xxxibtnxmbr12_20170429.40.1
title: (:unkn)
DOI: 10.6085/aa/bbyx00_xxxibtnxmbr12_20160613.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Boiler Bay, Oregon, USA (BBYX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Boiler Bay, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2016-06-13. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/bbyx00_xxxibtnxmbr22_20160506.40.1
title: (:unkn)
DOI: 10.6085/aa/bbyx00_xxxibtnxmbr22_20160506.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Boiler Bay, Oregon, USA (BBYX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Boiler Bay, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2016-05-06. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.