cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2glrd7
title: CCDC 2282139: Experimental Crystal Structure Determination

description: Related Article: Chao-Chao Teng, Yan Guo, Ke Cao, Han- Bo Yang, Qi-Jia Jiang, Dao-Yong Zhu, Shao-Hua Wang|2024|J.Organomet.Chem.|1008|123051|doi:10.1016/j.jorganchem.2024.123051
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.21227/jsg4-wp31
title: Cora

description: The Cora dataset consists of 2708 scientific publications classified into one of seven classes. The citation network consists of 5429 links. Each publication in the dataset is described by a 0/1-valued word vector indicating the absence/presence of the corresponding word from the dictionary. The dictionary consists of 1433 unique words.
DOI: 10.5281/zenodo.10607755
title: Replication Package: Threats to Validity in Green AI Research
DOI: 10.5281/zenodo.10607828
title: Replication Package: Threats to Validity in Green AI Research
DOI: 10.5281/zenodo.10610795
title: Replication Package: Threats to Validity in Green AI Research
DOI: 10.5281/zenodo.10806587
title: Replication Package: Threats to Validity in Green AI Research
DOI: 10.5281/zenodo.10607754
title: Replication Package: Threats to Validity in Green AI Research
DOI: 10.5281/zenodo.10806397
title: Replication Package: Threats to Validity in Green AI Research
DOI: 10.57687/fk2/ufm2qh/tgyurp
title: Data Teaser - Student Profiles.xls

description: :unav
DOI: 10.57687/fk2/ufm2qh/4tldzd
title: Data Dictionary - Student Profiles.xls

description: :unav
DOI: 10.5281/zenodo.10498986
title: Small Group and Survey Datasets: "Fostering Metacognition and Feedback Loops in a Summer Undergraduate Research Program: A Pilot Study"

description: These datasets accompany the paper "Fostering Metacognition and Feedback Loops in a Summer Undergraduate Research Program: A Pilot Study" by Chad Curtis PhD and Kaytlin Gomez.

The first dataset consists of free responses from n=12 students researchers during a Small Group Metacognitive Practice (SGMP) intervention conducted during the 2023 INBRE Summer Undergraduate Research Fellowship (iSURF) at Nevada State University. The files include:



transcription.docx: Transcriptions of both individual (n=12) and small group (n=4) responses from the SGMP session.

codingR1.xlsx: Codings used for the thematic analysis, as coded by the primary investigator.

codingR2.xlsx: Codings used for the thematic analysis, as coded by the co-author.

KrippendorffAlpha.xlsx: Inter-coder reliability calculations using Krippendorff's alpha.


The survey data was collected from n=11 participants at the end of the summer research program. The files include:



surveyData.csv: Anonymized responses to survey questions regarding the SGMP intervention.


This study was approved by the Nevada State University Review Board (Protocol #2305-0346). All procedures in the study were conducted in accordance with approved protocols. Written informed consent was obtained from the subjects for their anonymized information to be published with the article.
DOI: 10.5281/zenodo.10498987
title: Survey Data: "Fostering Metacognition and Feedback Loops in a Summer Undergraduate Research Program: A Pilot Study"

description: This dataset accompnies the paper "Fostering Metacognition and Feedback Loops in a Summer Undergraduate Research Program: A Pilot Study" by Chad Curtis PhD and Kaytlin Gomez. The survey data was collected from n=11 student researchers in the 2023 INBRE Summer Undergraduate Research Fellowship (iSURF) at Nevada State College. Subjects participated in a Small Group Metacognitive Practice session during week 2 of the program. The intervention was evaluated at the end of the 10-week program using the survey questions provided in the dataset.

This study was approved by the Nevada State University Review Board (Protocol #2305-0346). All procedures in the study were conducted in accordance with approved protocols. Written informed consent was obtained from the subjects for their anonymized information to be published with the article.
DOI: 10.5281/zenodo.10806580
title: Small Group and Survey Datasets: "Fostering Metacognition and Feedback Loops in a Summer Undergraduate Research Program: A Pilot Study"

description: These datasets accompany the paper "Fostering Metacognition and Feedback Loops in a Summer Undergraduate Research Program: A Pilot Study" by Chad Curtis PhD and Kaytlin Gomez.

The first dataset consists of free responses from n=12 students researchers during a Small Group Metacognitive Practice (SGMP) intervention conducted during the 2023 INBRE Summer Undergraduate Research Fellowship (iSURF) at Nevada State University. The files include:



transcription.docx: Transcriptions of both individual (n=12) and small group (n=4) responses from the SGMP session.

codingR1.xlsx: Codings used for the thematic analysis, as coded by the primary investigator.

codingR2.xlsx: Codings used for the thematic analysis, as coded by the co-author.

KrippendorffAlpha.xlsx: Inter-coder reliability calculations using Krippendorff's alpha.


The survey data was collected from n=11 participants at the end of the summer research program. The files include:



surveyData.csv: Anonymized responses to survey questions regarding the SGMP intervention.


This study was approved by the Nevada State University Review Board (Protocol #2305-0346). All procedures in the study were conducted in accordance with approved protocols. Written informed consent was obtained from the subjects for their anonymized information to be published with the article.
DOI: 10.34863/k1mm-cf38
title: Dataset: Characterization, processing, and modeling of industrial recycled polyolefins
DOI: 10.5281/zenodo.10573427
title: Data and code from: Unoccupied aerial systems adoption in agricultural research

description:  

This repository contains data and code supporting the findings of the study on the adoption of Unoccupied Aerial Systems (UAS) in agricultural research as reported by Lachowiec et al (2024) in The Plant Phenome Journal.

We collected data through an online survey as well as through in person interviews.



Description of Repository Contents




Data


Data are in the /data directory:



Ag_Drones_Codebook_14Jun2023.pdf: Codebook providing detailed descriptions of survey questions and coding schemes. This contains detailed descriptions of the content of the two CSV files listed below.

Results_Ag_Drones_2021_Survey.csv: This is raw survey data collected from agricultural researchers regarding their use of UAS technology.

countries_code.csv: Country codes used in the survey data for respondent location.

interviews/: A directory containing interview transcripts and summary provided as both Microsoft Word and plain text (Markdown) formats, specifically:



Notes from nine one on one interviews named <interviewee last name>)UAS_Interview.[md|docx]

A summary document, Feldman_AG2PI_InterviewSummary_2022-08-10.docx.






Code


Code used to process data and generate the manuscript's analysis and figures.



data_code.R: R Script for preprocessing and cleaning the survey data.

dataAnalysis.R: R script for statistical analysis and visualization of survey results.




Citing this work


This repository contains data and code to support the manuscript:



Lachowiec, J., Feldman, M.J., Matias, F.I., LeBauer, D., Gregory, A. (2024). Unoccupied aerial systems adoption in agricultural research. Zenodo. The Plant Phenome Journal Volume(Issue), pages 00. doi:DOI


If you use the data or code from this repository, please also cite:



Lachowiec, J., Feldman, M.J., Matias, F.I., LeBauer, D., Gregory, A. (2024). Data and code from: Unoccupied aerial systems adoption in agricultural research. Zenodo. doi:10.5281/zenodo.10573428


And consider contributing cleaned data and code to this repository.



Acknowlegements and Support


Acknowledgments

We thank all survey respondents for their participation. We acknowledge the Montana State University HELPS lab for aiding in the development and implementation of the survey.

Funding

This research was supported by the intramural research program of the U.S. Department of Agriculture, National Institute of Food and Agriculture, Agricultural Genome to Phenome Initiative (2020-70412-32615 and 2021-70412-35233). The findings and conclusions in this preliminary presentation have not been formally disseminated by the U. S. Department of Agriculture and should not be construed to represent any agency determination or policy.
DOI: 10.5281/zenodo.10573428
title: Data and code from: Unoccupied aerial systems adoption in agricultural research

description:  

This repository contains data and code supporting the findings of the study on the adoption of Unoccupied Aerial Systems (UAS) in agricultural research as reported by Lachowiec et al (2024) in The Plant Phenome Journal.

We collected data through an online survey as well as through in person interviews.



Description of Repository Contents




Data


Data are in the /data directory:



Ag_Drones_Codebook_14Jun2023.pdf: Codebook providing detailed descriptions of survey questions and coding schemes. This contains detailed descriptions of the content of the two CSV files listed below.

Results_Ag_Drones_2021_Survey.csv: This is raw survey data collected from agricultural researchers regarding their use of UAS technology.

countries_code.csv: Country codes used in the survey data for respondent location.

interviews/: A directory containing interview transcripts and summary provided as both Microsoft Word and plain text (Markdown) formats, specifically:



Notes from nine one on one interviews named <interviewee last name>)UAS_Interview.[md|docx]

A summary document, Feldman_AG2PI_InterviewSummary_2022-08-10.docx.






Code


Code used to process data and generate the manuscript's analysis and figures.



data_code.R: R Script for preprocessing and cleaning the survey data.

dataAnalysis.R: R script for statistical analysis and visualization of survey results.




Citing this work


This repository contains data and code to support the manuscript:



Lachowiec, J., Feldman, M.J., Matias, F.I., LeBauer, D., Gregory, A. (2024). Unoccupied aerial systems adoption in agricultural research. Zenodo. The Plant Phenome Journal Volume(Issue), pages 00. doi:DOI


If you use the data or code from this repository, please also cite:



Lachowiec, J., Feldman, M.J., Matias, F.I., LeBauer, D., Gregory, A. (2024). Data and code from: Unoccupied aerial systems adoption in agricultural research. Zenodo. doi:10.5281/zenodo.10573428


And consider contributing cleaned data and code to this repository.



Acknowlegements and Support


Acknowledgments

We thank all survey respondents for their participation. We acknowledge the Montana State University HELPS lab for aiding in the development and implementation of the survey.

Funding

This research was supported by the intramural research program of the U.S. Department of Agriculture, National Institute of Food and Agriculture, Agricultural Genome to Phenome Initiative (2020-70412-32615 and 2021-70412-35233). The findings and conclusions in this preliminary presentation have not been formally disseminated by the U. S. Department of Agriculture and should not be construed to represent any agency determination or policy.
DOI: 10.25345/c5sx64m8t
title: MassIVE MSV000094291 - Revealing the Heterogeneity in Lung Compartment Inflammatory Cell Protein Interactions in Acute Respiratory Distress Syndrome
title: We compared the bronchoalveolar lavage cell proteins from healthy controls (n=3) to acute respiratory distress syndrome (ARDS, n=6). Subgroup analysis was performed to determine the differences between ARDS survivors (n=3) and non-survivors (n=3). The cells were processed to maximize protein recovery, followed by trypsin digestion and labeling with TMT-10Plex reagent. Spectral data acquisition was conducted using 2D LC-MS/MS Orbitrap Fusion instrumentation.
DOI: 10.6073/pasta/34e2dbf5746458221e35746f2a76b110
title: SEV-LTER Mean x Variance Experiment Desert Grassland Soil Moisture and Temperature

description: We designed novel field experimental infrastructure to resolve the relative importance of changes in the climate mean and variance in regulating the structure and function of dryland populations, communities, and ecosystem processes. The Mean x Variance Experiment (MVE) adds three novel elements to prior designs (Gherardi & Sala 2013) that have manipulated interannual variance in climate in the field by (i) determining interactive effects of mean and variance with a factorial design that crosses a drier mean with increased (more) variance, (ii) studying multiple dryland ecosystem types to compare their susceptibility to transition under interactive climate drivers, and (iii) adding stochasticity to our treatments to permit the antecedent effects that occur under natural climate variability. This new infrastructure enables direct experimental tests of the hypothesis that interactions between the mean and variance of precipitation will have larger ecological impacts than either the mean or variance in precipitation alone. 
 A subset of plots have soil moisture and temperature sensors to evaluate treatment effectiveness by addressing, How do MVE manipulations alter the mean and variance in soil moisture and temperature? And, how does micro-environmental variation among plots influence how much MVE treatments alter soil moisture profiles over three soil depths? 
 This data package includes soil moisture and temperature sensor data from the Mean x Variance Climate experiment in the Desert grassland ecosystem at the Sevilleta National Wildlife Refuge, Socorro, NM.
DOI: 10.13020/j4ak-ps65
title: Data for Boundary Frustration in Double-Gyroid Thin Films

description: We have used self-consistent field theory to predict the morphology and preferred orientation of the double-gyroid phase in thin films of AB diblock polymers. A manuscript has been submitted containing this data, and is expected to appear shortly. The data were generated using the C++ version of the open-source software PSCF (https://pscf.cems.umn.edu/). All input and output files from PSCF used to generate the data in the paper are included in this dataset, as well as the code used to process the data and generate the figures.
description: All input and output files from PSCF used to generate the data in the paper are included in this dataset, as well as the code used to process the data and generate the figures. Users should be able to replicate all results of our calculations using the PSCF software and the inputs/scripts in this dataset.
DOI: 10.5281/zenodo.10652300
title: Pulseimpute Sample 2
DOI: 10.5281/zenodo.10668771
title: Pulseimpute Sample 2
DOI: 10.5281/zenodo.10652299
title: Pulseimpute Sample 2
DOI: 10.5281/zenodo.10806615
title: Pulseimpute Sample 2
DOI: 10.5066/p9levh2k
title: Water chemistry data from the Big Creek and Monumental Creek tributaries of the Lower Middle Fork Salmon River, Idaho, 2021

description: This USGS data release evaluates the impact of historical mining sites on water quality using samples collected in late July 2021 from Big Creek tributaries Coin Creek, Smith Creek, and Monumental Creek in Valley County, Idaho. These data were collected to support a fisheries mining impact assessment in the Middle Fork Salmon River. Specific conductance, pH, and stream temperature were measured in the field. Analyses include major cations and anions, alkalinity, trace metals, total mercury, and methylmercury.
DOI: 10.5066/p13yb3af
title: Summary of Detection Data for Breeding Common Loons in North-central Minnesota (2023)

description: The Deepwater Horizon oil spill caused extensive injury to natural resources in the Gulf of Mexico, and Gavia immer (common loon) were negatively affected from the spill. The Open Ocean Trustee Implementation Group funded the project Restoration of Common Loons in Minnesota to restore common loons lost to the spill. In 2020–21, study lakes in an eight-county region in north-central Minnesota were identified to focus project activities. In 2023 surveys were conducted on these lakes to monitor common loon territory occupancy, nest success, and chick survival. This dataset includes a summary of total number of artificial nesting platforms (ANP), total number of ANP and natural nests, ANP and natural nest success, total number of chicks hatched, and number of chicks that survived to August surveys for 141 territories across 56 lakes within the eight-county study area. The 2021-2022 dataset can be located at https://doi.org/10.5066/P9LA536E. We intend to present formal analyses of these and subsequently-collected data after the completion of this multi-year study.
DOI: 10.5281/zenodo.10806596
title: Software Engineers Engagement and Job Satisfaction: A Survey with Practitioners Working Remotely in a Public Organization - Supplementary material
DOI: 10.5281/zenodo.10806597
title: Software Engineers Engagement and Job Satisfaction: A Survey with Practitioners Working Remotely in a Public Organization - Supplementary material
DOI: 10.6073/pasta/24e53510ff57bb8abc122c980836fc19
title: ASM01 Soil water content measured by neutron probe at Konza Prairie

description: Data set contains measurements of soil moisture (%volume) at various depths (25-200 cm) in deep (lowland) soils collected on LTER grazed and ungrazed watersheds burned at 1-, 4-, and 20-year intervals. Soil moisture measured by the neutron probe method.
DOI: 10.5066/p93kygeg
title: Upper Klamath Lake and Clear Lake sampling for suckers from 2015 through 2022

description: Data in this data set include effort expended to collect suckers for cohort tracking and metrics and observations for each sucker captured from 2015 through 2022. There are two levels of data. All Nets data contains 5102 records and the data file is 609 KB. Captures data contains 3764 records and the data file is 504 KB. The data files can be linked by setID which is a unique identifier for a unique net set. Data files are CSV files that are comma delimited.
DOI: 10.22002/v208k-qmb68
title: Dataset: Loss of mitochondrial DNA is associated with reduced DNA content variability in Saccharomyces cerevisiae

description: Cell cycle distribution data for strains from the Saccharomyces cerevisiae haploid deletion collection.
DOI: 10.17597/isas.darts/hyb2-00900
title: Hayabusa2 MASCOT Magnetometer Bundle

description: This PDS4 bundle collects all the operational data products produced by the Hayabusa2 MASCOT Fluxgate Magnetometer, MasMag.
DOI: 10.25346/s6/wgrirc/erh1ts
title: circ.function.R
DOI: 10.25346/s6/wgrirc/qnummj
title: globalARcatalog_MERRA2_2019_v3.0.nc
DOI: 10.25346/s6/wgrirc/qtetaw
title: asm_cyg.12hr.merra2.ar.grid.20190120.l2.wind-mss-cdr.sand310.nc
DOI: 10.25346/s6/wgrirc/t9v7oa
title: rot.matrix.R
DOI: 10.25346/s6/wgrirc
title: ROTATE: A Coordinate System for Analyzing Atmospheric Rivers [Algorithm Code]

description: To be completed..
DOI: 10.25346/s6/wgrirc/2xhfn4
title: netcdf.write.carts.R
DOI: 10.25346/s6/wgrirc/lhlzvi
title: ROTATE.R
DOI: 10.5281/zenodo.10806610
title: Just another copy and paste? Comparing the security vulnerabilities of ChatGPT generated code and StackOverflow answers

description: Supplemental material for the paper "Just another copy and paste? Comparing the security vulnerabilities of ChatGPT generated code and StackOverflow answers" published in DLSP 2024.
DOI: 10.5281/zenodo.10806611
title: Just another copy and paste? Comparing the security vulnerabilities of ChatGPT generated code and StackOverflow answers

description: Supplemental material for the paper "Just another copy and paste? Comparing the security vulnerabilities of ChatGPT generated code and StackOverflow answers" published in DLSP 2024.
DOI: 10.5517/ccdc.csd.cc2h1zq8
title: CCDC 2295820: Experimental Crystal Structure Determination

description: Related Article: Yuanyuan Che|2023|CSD Communication|||
description: Related Article: Ying Cao, Yuanyuan Che, Lang Liu, Yakun Tang, Yuming Yu|2024|New J.Chem.|48|4726|doi:10.1039/D3NJ05828J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2h7dtz
title: CCDC 2301031: Experimental Crystal Structure Determination

description: Related Article: Liyan Zhang, Zhichao Xu, Zhaoxin Meng, Xianwen Wei, Weibin Yu, Guozan Yuan|2024|Inorg.Chem.Commun.|162|112249|doi:10.1016/j.inoche.2024.112249
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hjyll
title: CCDC 2310200: Experimental Crystal Structure Determination

description: Related Article: Qiu Sun, Andreas Eitzinger, Robin Esken, Patrick W. Antoni, Robert J. Mayer, Armin R. Ofial, Max M. Hansmann|2024|Angew.Chem.,Int.Ed.|63|e202318283|doi:10.1002/anie.202318283
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.25387504
title: Data obtained for publication Appl Surf Sci 638 (2023) 158089

description: Data obtained for publication Appl Surf Sci 638 (2023) 158089
DOI: 10.6084/m9.figshare.25387504.v1
title: Data obtained for publication Appl Surf Sci 638 (2023) 158089

description: Data obtained for publication Appl Surf Sci 638 (2023) 158089
DOI: 10.5517/ccdc.csd.cc2hjymm
title: CCDC 2310201: Experimental Crystal Structure Determination

description: Related Article: Qiu Sun, Andreas Eitzinger, Robin Esken, Patrick W. Antoni, Robert J. Mayer, Armin R. Ofial, Max M. Hansmann|2024|Angew.Chem.,Int.Ed.|63|e202318283|doi:10.1002/anie.202318283
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hjynn
title: CCDC 2310202: Experimental Crystal Structure Determination

description: Related Article: Qiu Sun, Andreas Eitzinger, Robin Esken, Patrick W. Antoni, Robert J. Mayer, Armin R. Ofial, Max M. Hansmann|2024|Angew.Chem.,Int.Ed.|63|e202318283|doi:10.1002/anie.202318283
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.