cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0214086.10fu
title: SH0214086.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0214087.10fu
title: SH0214087.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13023/kgs.data.2022.01
title: Kentucky Geological Survey Landslide Inventory [2022-01]

description: The KGS landslide inventory provides the locations of known landslides and areas susceptible to debris flows. Various types of landslides are represented including slides, flows, rockfalls, and creep. The data are available as ArcGIS geodatabase feature classes. Landslide locations and associated attributes are compiled from Kentucky Geological Survey research, published maps, state and local government agencies, the public, and media reports. A confidence ranking system assigns a value to each feature. A description of the feature classes is here: https://kgs.uky.edu/kgsmap/helpfiles/landslide_help.shtm

The inventory viewed in a GIS with geology, soils, slope or other terrain-based data can serve as a basis for landslide hazard and risk assessment. It is not intended for site specific investigations. The point features represent larger landslide deposits that have not been mapped in detail and may fall within different parts of the slide area. The absence of landslides in an area does not infer that a landslide does not exist or that the ground is stable. A professional geologist or geotechnical engineer should be consulted for planned construction at identified landslide locations or identified landslide areas. A professional geologist or geotechnical engineer should also be consulted for slope stabilization and other mitigation efforts related to existing slides.
description: © 2022 University of Kentucky
DOI: 10.21335/nmdc-1094330803
title: NoBa - A shifting chessboard - climate projections

description: The Nordic and Barents Seas Atlantis model (NoBa) simulations run with SSP1-2.6, SSP2-4.5 and SSP5-8.5 downscaled simulations fromthe Nemo-NAA10km ocean model. In total 27 simulations, including combinations of increasing/decreascing phytoplankton and zooplankton components. The size of the increase/decrease was determined by outputs from the NORWECOM.e2e model. The simulations were used to study impact on climate change on the components in the region, with focus on the processes driving the observed changes (Nilsen et al., 2024).
DOI: 10.24432/c5959t
title: Mushroom
DOI: 10.14284/323
title: IHO Sea Areas, version 3

description: This dataset represents the boundaries of the major oceans and seas of the world. The source for the boundaries is the publication 'Limits of Oceans Seas, Special Publication No. 23' published by the IHO in 1953.
DOI: 10.5281/zenodo.10829926
title: Questionnaire survey among members of the Czech Pirate Party regarding the use of the online voting system Helios

description: LimeSurvey application, where only Pirate Party members had access to the survey via a unique URL sent in an e-mail invitation that allowed members to fill out the questionnaire once. The poll ran from 22 February to 14 March 2024. 213 members out of a total of 1,179 party members completed the 19-question poll in full, a response rate of 18.6%. 16 research questions were Yes or No answers, 3 questions were socio-demographic questions focusing on gender, age and educational attainment. 47 women, 146 men and 20 respondents did not classify themselves as male or female. The age group 18-30 years included 27 respondents, 31-40 years included 93 respondents, 41-50 years included 56 respondents, 51-60 years included 24 respondents, 61-70 years included 11 respondents, 71 years and above included 2 respondents. In terms of highest completed education of the respondents, 60 have high school degree, 27 have bachelor's degree, 97 have master's degree, 13 have doctoral degree and 16 have other degree.
DOI: 10.5281/zenodo.8347012
title: TotalSegmentator segmentations and radiomics features for NCI Imaging Data Commons CT images

description: This dataset contributes volumetric segmentations of the anatomic regions in a subset of CT images available from NCI Imaging Data Commons [1] (https://imaging.datacommons.cancer.gov/) automatically generated using the TotalSegmentation model v1.5.6 [2]. The initial release includes segmentations for the majority of the CT scans included in the National Lung Screening Trial (NLST) collection [3], [4] already available in IDC. Direct link to open this analysis result dataset in IDC (available after release of IDC v18): https://portal.imaging.datacommons.cancer.gov/explore/filters/?analysis_results_id=TotalSegmentator-CT-Segmentations. 

Specifically, for each of the CT series analyzed, we include segmentations as generated by TotalSegmentator, converted into DICOM Segmentation object format using dcmqi v1.3.0 [5], and first order and shape features for each of the segmented regions, as produced by pyradiomics v3.0.1 [6]. Radiomics features were converted to DICOM Structured Reporting documents following template TID1500 using dcmqi. TotalSegmentator analysis on the NLST cohort was executed using Terra platform [7]. Implementation of the workflow that was used for performing the analysis is available at https://github.com/ImagingDataCommons/CloudSegmentator [8].

Due to the large size of the files, they are stored in the cloud buckets maintained by IDC, and the attached files are the manifests that can be used to download the actual files.

The GCP and AWS manifests provided with this dataset record can be used to download the corresponding files from the IDC Google Cloud Storage (GCS) or Amazon S3 (AWS) buckets free of charge following the instructions available in IDC documentation here: https://learn.canceridc.dev/data/downloading-data. Specifically, you will need to install the s5cmd command line tool on your computer (see instructions at https://github.com/peak/s5cmd#installation), and follow the manifest-specific download instructions accompanying the file list below.

If you use the files referenced in the attached manifests, we ask you to cite this dataset and the preprint describing how it was generated [9].

Specific files included in the record are:





totalsegmentator_ct_segmentations_aws.s5cmd.zip: compressed AWS-based manifest (to download the files described in the manifest, execute this command: s5cmd --no-sign-request --endpoint-url https://s3.amazonaws.com run totalsegmentator_ct_segmentations_aws.s5cmd)




totalsegmentator_ct_segmentations_gcs.s5cmd.zip: GCS-based manifest (to download the files described in the manifest, execute this command:  s5cmd --no-sign-request --endpoint-url https://storage.googleapis.com run totalsegmentator_ct_segmentations_gcs.s5cmd)




Gen3-based manifest (see details in https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids).
DOI: 10.5441/002/edbt.2018.83
title: Spatio-Temporal-Keyword Pattern Queries over Semantic Trajectories with Hermes@Neo4j
DOI: 10.1285/i20356609v13i1p154
title: Misleading Memes. The Effects of Deceptive Visuals of the British National Party

description: This study investigates how visual manipulation is employed on the Facebook page of a far-right party; and whether manipulation evokes different forms of engagement from Facebook users. The study takes as a case the Facebook page of the British National Party (BNP), which has recently been censored from the social media platform. It therefore provides a rare insight in the visual practices of the party's online political communication. A manual coding of 342 images into factual, funny, fallacious or fabricated content finds that completely fabricated information in images is rare. However, most images do contain information that is presented in a fallacious or misleading manner. The results show how deliberate manipulated images evoke more engagement in the form of comments and more negative emotional responses than images that present information in a factual or funny manner.
DOI: 10.17863/cam.46071
title: Research data supporting "HALO: Post-Link Heap-Layout Optimisation"

description: Source code for running the HALO pipeline. This includes a client for the pin binary instrumentation framework, a patch to the BOLT binary optimiser, a custom memory allocator, and scripts for analysis of the profiled data. See the file README.md within the repository for a detailed description and usage instructions.
DOI: 10.5067/terra/modis/l3m/chl/2018
title: MODIS-TERRA Level 3 Mapped Chlorophyll Data Version R2018.0
DOI: 10.5281/zenodo.13937177
title: Data for "Precursory Locking Precedes Slip Events on Laboratory Fault"

description: To run data plotting codes, unpack the zip folders and run the .m files in the same folder as the unzipped data folders.

 

"PlotEventCatalog.m" - Generates a plot of each individual event catalog in the data.  Can be used to perform independant analysis of the event catalog

"PlotLockingEventHistograms.m" - Plots normal and bivariate histograms comparing the predictive power of random points vs locking events on the prediction of future slip events

"PlottingCodePrecursoryLocking.m" - Plots data for figure 3 of the paper
DOI: 10.15151/esrf-es-514138045
title: In situ mapping of crack progression in nanocrystalline FeCr: nanoscale stress-strain evolution in nanocrystalline microstructure

description: Although nanocrystalline materials do exhibit outstanding mechanical properties, the underlying correlation between their nanoscopic microstructure with a large volume fraction of grain boundaries and nanoscopic the plasticity-fracture process interactions still remain unclear. Here, in situ nanodiffraction will be used to characterize nanocrystalline supersaturated FeCr alloys machined using FIB as cantilevers during stepwise loading. We aim to follow nanoscopic crack propagation and elasto-plastic deformation using SAXS and to simultaneously assess X-ray elastic strain and texture evolution at the crack tip using WAXS. The experiment will be performed using a dedicated in situ micromechanical stage developed for ID13 and complemented by numerical analysis. The results will uncover the nanoscopic plasticity-fracture process interactions at the crack tip of nanocrystalline FeCr, aiming to better understanding of semi-brittle fracture.
DOI: 10.15151/esrf-es-644167190
title: Scanning and In-situ MLL Development for X-ray Nanodiffraction on Thin Film, Space and Additively Manufactured Applications
DOI: 10.15485/2453885
title: Groundwater and Surface Water Flow (GSFLOW) model files to explore bedrock circulation depth and porosity in Copper Creek, Colorado

description: This data package contains integrated hydrological model input and output files for Copper Creek, Colorado (24 km2), a tributary of the East River located in the headwaters of the Upper Colorado River Basin. The model code is the U.S. Geological Survey (USGS) Groundwater and Surface Water Flow (GSFLOW) model. The model contains a 100-m grid resolution and a daily timestep. The land surface model is dynamically linked to a three-dimensional groundwater flow model that allows for streamflow gaining and losing conditions. The groundwater model contains 12 model layers and extends 400 m below land surface. The original Copper Creek model was modified to contain geologic layers representing saprolite, shallow bedrock, and deep bedrock. Endmember depth versus hydraulic conductivity relationships and porosity values for fractured crystalline rock are simulated. For the shallow case, median flow depths occur in the shallow saprolite at depths &lt;8 m, while the deep case promotes a median groundwater flow depth of 100 m. With this modeling framework we compare streamflow response to a plausible worst-case drought lasting up to five years. Streamflow metrics of analysis include average streamflow, fraction of stream network that is dry, no-flow duration, average groundwater flow to streams and time to recovery following the drought. Results and implications are presented in a paper submitted to Geophysical Research Letters titled, "The role of bedrock circulation depth and porosity in mountain streamflow response to prolonged drought" by Rosemary WH. Carroll, Andrew H. Manning and Kenneth H Williams. A Readme.txt file provides instructions on how to download all model files and execute each model scenario. In addition to the GSFLOW output/prms/copper_drought.csv file containing daily basin water stores and fluxes (refer to GSFLOW manual) and the output/prms/copper_drought_statvar.dat file with output defined in the gsflow3.control file (refer to GSFLOW Manual), output files also include spatially distributed daily values of total evapotranspiration, canopy evaporation, precipitation, snowfall, infiltration, snow water equivalent, potential evapotranspiration, recharge, sublimation, soil moisture, contributing interflow, water table elevations, changes in groundwater storage, groundwater evapotranspiration, interbasin groundwater flow (limited to the alluvium below the stream outlet), and surface-groundwater exchanges within the river system.
DOI: 10.21227/24mb-vt61
title: OpenNebula Virtual Machine Profiling for Intrusion Detection System

description: Intrusion Detection System can be build for private cloud using OpenNebula. OpenNebula is a cloud computing platform for managing heterogenous distributed data center infrastructure. The database is generated using a private cloud setup using KVM and OpenNebula. OpenNebula provides API to monitor Virtual Machines (VMs) running on the infrastructure. Total 6 VMs were deployed on the infrastructure. The monitoring data was collected over 63 Hours. Attacks were simulated on few of the VMs for variable time duration. These data is tagged as Normal and Attack data based on the known attack scenario. The dataset can be used to profile VM behaviour based on OpenNebula monitoring features. A machine learning model can be trained for the same.
DOI: 10.26179/9tke-0s16
title: 1137 years of high-resolution Continuous Flow Analysis impurity data from the Mount Brown South Ice Core
DOI: 10.3334/cdiac/otg.woce_a05_1998
title: Partial pressure (or fugacity) of carbon dioxide, dissolved inorganic carbon (DIC), pH on seawater scale, total alkalinity (TA), water temperature, salinity and other variables collected from discrete sample and profile observations during NOAA Ship Ronald H. Brown cruise 31RBOACES24N_2, OACES-98 (EXPOCODE 33RO19980123), along the WOCE Section A05 in the North Atlantic Ocean from 1998-01-23 to 1998-02-23 (NCEI Accession 0113920)

description: This dataset includes chemical, discrete sample, physical and profile data collected during NOAA Ship Ronald H. Brown cruise 31RBOACES24N_2, OACES-98 (EXPOCODE 33RO19980123), along the WOCE Section A05 in the North Atlantic Ocean from 1998-01-23 to 1998-02-23. These data include partial pressure (or fugacity) of carbon dioxide (pCO2), dissolved inorganic carbon (DIC), pH on seawater scale, total alkalinity (TA), water temperature, salinity, silicate, nitrate, nitrite, phosphate, chlorofluorocarbons (CFC-11, CFC-12, CFC-113), carbon tetrachloride (CCL4), delta carbon-13, delta carbon-14, dissolved oxygen and total organic carbon (TOC). The instruments used to collect these data include Alkalinity titration, CTD, Coulometer for DIC measurement, flask with closed headspace for discrete carbon dioxide (CO2) measurement, bottle and spectrophotometer. These data were collected by David S. Bitterman and Rik Wanninkhof of NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), Kitack Lee of Pohang University of Science and Technology School of Environmental Science and Engineering, and Frank J. Millero of Rosenstiel School of Marine and Atmospheric Science (RSMAS) as part of the WOCE_AR01(A05), CARINA/33RO19980123 dataset. The CARINA (CARbon dioxide IN the Atlantic Ocean) data synthesis project is an international collaborative effort of the EU IP CARBOOCEAN, and U.S. partners. It has produced a merged internally consistent dataset of open ocean subsurface measurements for biogeochemical investigations, in particular, studies involving the carbon system. The original focus area was the North Atlantic Ocean, but over time the geographic extent expanded and CARINA now includes data from the entire Atlantic, the Arctic Ocean, and the Southern Ocean.
DOI: 10.35111/mfam-hf33
title: Second DIHARD Challenge Evaluation - SEEDLingS

description: <h3>Introduction</h3><br>
<p>Second DIHARD Challenge Evaluation - SEEDLinGS was developed by Duke University and LDC and contains approximately two hours of English child language recordings along with corresponding annotations used in support of the <a href="https://dihardchallenge.github.io/dihard2">Second DIHARD Challenge</a>.</p><br>
<p>The DIHARD Challenges are a set of shared tasks on diarization focusing on "hard" diarization; that is, speech diarization for challenging corpora where there was an expectation that existing state-of-the-art systems would fare poorly. As with the <a href="https://dihardchallenge.github.io/dihard1/">first challenge</a>, the second development and evaluation sets were drawn from a diverse sampling of sources including monologues, map task dialogues, broadcast interviews, sociolinguistic interviews, meeting speech, speech in restaurants, clinical recordings, extended child language acquisition recordings, and YouTube videos.</p><br>
<h3>Data</h3><br>
<p>Source data is from the <a href="https://homebank.talkbank.org/access/Password/Bergelson.html">SEEDLingS</a> (The Study of Environmental Effects on Developing Linguistic Skills) corpus, designed to investigate how infants' early linguistic and environmental input plays a role in their learning. Recordings were generated in the home environment of infants in the Rochester, New York area. A subset of that data was annotated by LDC for use in the First and Second DIHARD Challenges.</p><br>
<p>This release, when combined with Second DIHARD Challenge Evaluation - Eleven Sources (<a href="../../../LDC2022S06">LDC2022S06</a>), contains the evaluation set audio data and annotation, except for CHiME-5 audio files which must be obtained from the University of Sheffield.</p><br>
<p>All audio is provided in the form of 16 kHz, 16-bit, mono-channel FLAC files. The diarization for each recording is stored as a NIST Rich Transcription Time Marked (RTTM) file. RTTM files are space-separated text files containing one turn per line. Segmentation files are stored as HTK label files. Each of these files contains one speech segment per line. Scoring regions for each recording are specific by un-partitioned evaluation map (UEM) files. All annotation file types are encoded as UTF-8. More information about file formats, data sources and domains is contained in the included documentation.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2019, 2022 Duke University, © 2019, 2022 Trustees of the University of Pennsylvania
DOI: 10.3886/icpsr27901.v1
title: Assessing Happiness and Competitiveness of World Major Metropolises, 2006
title: Version 1

description: This study aimed to empirically examine happiness and community/city conditions assessed by residents living in ten major cities of the world: Beijing, Berlin, London, Milan, New York City, Paris, Seoul, Stockholm, Tokyo, and Toronto. Respondents were asked questions about themselves and their city of residence. Questions focused on a range of topics including the economy, culture and education, welfare, safety, environment, living conditions, city administration, community life, health, and happiness. Demographic questions included city of residence, gender, age, education level, income level, occupation, marital status, and religion.
description: ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes..
description: Datasets: 
 
 DS1: Dataset
description: computer-assisted telephone interview (CATI) 
In order to conform to SPSS variable naming conventions, original variable names containing periods have been renamed; periods in these variable names have been substituted with underscores "_".
description: Persons aged 18 and over living in Seoul, London, Paris, Berlin, Milan, New York City, Toronto, Tokyo, Beijing, and Stockholm. Smallest Geographic Unit: city
description: Representative random sampling. Gender/age distribution of the completed samples should be largely in line with overall population of the surveyed city.