cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.60712/si-id405874.2
title: StrainInfo SI-ID 405874.2

description: StrainInfo dataset 405874 about a strain of Pseudomonas aeruginosa. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405875.2
title: StrainInfo SI-ID 405875.2

description: StrainInfo dataset 405875 about a strain of Rhodopirellula. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405876.2
title: StrainInfo SI-ID 405876.2

description: StrainInfo dataset 405876 about a strain of Corynebacterium striatum. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405877.3
title: StrainInfo SI-ID 405877.3

description: StrainInfo dataset 405877 about a strain of Fundidesulfovibrio magnetotacticus. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405878.2
title: StrainInfo SI-ID 405878.2

description: StrainInfo dataset 405878 about a strain of Campylobacter pinnipediorum subsp. caledonicus. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405879.2
title: StrainInfo SI-ID 405879.2

description: StrainInfo dataset 405879 about a strain of Joostella marina. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.5281/zenodo.14959942
title: Infra Red Recordings of Opposed-Flow Flame Propagation on Discrete PMMA Sheets Under Exploration Atmospheres in Microgravity

description: About

This dataset contains infra red recordings from a series of drop tower experiment conducted at ZARM. Thin PMMA samples were combusted under controlled atmospheric conditions and forced opposed flow. An overview of all experiment conditions and sample types is given in the index.csv file. Two kinds of samples were investigated: "full samples", i.e. continuous fuel strips, and "gap samples", i.e. fuel strips separated by air gaps of different widths. Consequently, if the `Gaps [Sequence]` or `Gap Material [Material]` fields are empty, the "full sample" was tested. For the "gap samples" the sequence of gaps is given as the individual widths of each gap in mm separated by slashes, e.g. '3/4/5' to refer to a sample with 3, 4 and 5 mm gaps.

The radial lens distortion of the individual frames was corrected as well as the temperature. The frames are stored as 3 dimensional arrays with the first two dimensions being the spatial and the third the time (or frame count) dimension. The value of each pixel corresponds to the measured temperature in °C at the pixel's location.

Usage

Experiment Overview

The experiment overview is given in the index.csv file. Here, the metadata for each experiment is given. The corresponding IR data can be found in the `Data Location [File]` column. 

Loading the frames

The frames are stored in hdf5 files as the 'data' dataset. The corresponding metadata is given as serialized JSON as the 'metadata' dataset. An example for loading the files in Python is given below:

import json
import h5py
import numpy as np
data_file = "exp0.hdf5"
with h5py.File(data_file, 'r') as f:
    metadata = json.loads(f["metadata"][()]) # dictionary with date, sample and experiment conditions
    data = np.array(f["data"]) # individual IR frames as a 3 dimensional array of shape (x, y, t)

Acknowledgments

The authors thank Jan Heißmeier and Michael Peters for technical support during the design phase and the experimental campaigns. This research has been funded by the German Federal Ministry for Economic Affairs and Climate Action through the German Space Agency at DLR in the framework of FLARE-G II & III (grants 50WM2160 & 50WM2456).
DOI: 10.60712/si-id405880.2
title: StrainInfo SI-ID 405880.2

description: StrainInfo dataset 405880 about a strain of Anoxybacillus. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.5281/zenodo.14959941
title: Infra Red Recordings of Opposed-Flow Flame Propagation on Discrete PMMA Sheets Under Exploration Atmospheres in Microgravity

description: About

This dataset contains infra red recordings from a series of drop tower experiment conducted at ZARM. Thin PMMA samples were combusted under controlled atmospheric conditions and forced opposed flow. An overview of all experiment conditions and sample types is given in the index.csv file. Two kinds of samples were investigated: "full samples", i.e. continuous fuel strips, and "gap samples", i.e. fuel strips separated by air gaps of different widths. Consequently, if the `Gaps [Sequence]` or `Gap Material [Material]` fields are empty, the "full sample" was tested. For the "gap samples" the sequence of gaps is given as the individual widths of each gap in mm separated by slashes, e.g. '3/4/5' to refer to a sample with 3, 4 and 5 mm gaps.

The radial lens distortion of the individual frames was corrected as well as the temperature. The frames are stored as 3 dimensional arrays with the first two dimensions being the spatial and the third the time (or frame count) dimension. The value of each pixel corresponds to the measured temperature in °C at the pixel's location.

Usage

Experiment Overview

The experiment overview is given in the index.csv file. Here, the metadata for each experiment is given. The corresponding IR data can be found in the `Data Location [File]` column. 

Loading the frames

The frames are stored in hdf5 files as the 'data' dataset. The corresponding metadata is given as serialized JSON as the 'metadata' dataset. An example for loading the files in Python is given below:

import json
import h5py
import numpy as np
data_file = "exp0.hdf5"
with h5py.File(data_file, 'r') as f:
    metadata = json.loads(f["metadata"][()]) # dictionary with date, sample and experiment conditions
    data = np.array(f["data"]) # individual IR frames as a 3 dimensional array of shape (x, y, t)

Acknowledgments

The authors thank Jan Heißmeier and Michael Peters for technical support during the design phase and the experimental campaigns. This research has been funded by the German Federal Ministry for Economic Affairs and Climate Action through the German Space Agency at DLR in the framework of FLARE-G II & III (grants 50WM2160 & 50WM2456).
DOI: 10.60712/si-id405881.2
title: StrainInfo SI-ID 405881.2

description: StrainInfo dataset 405881 about a strain of Bacillus. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405882.3
title: StrainInfo SI-ID 405882.3

description: StrainInfo dataset 405882 about a strain of Spirosoma endophyticum. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405883.3
title: StrainInfo SI-ID 405883.3

description: StrainInfo dataset 405883 about a strain of Pseudomonas chengduensis. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.5281/zenodo.14203629
title: Hawkes et al 2025 UKB-WGS-Olink Summary Statistics

description: Summary statistics for Hawkes et. al 202X "Whole genome sequencing analysis identifies rare, large-effect non-coding variants and regulatory regions associated with circulating protein levels". Single variant summary statistics (minor allele count >=5) for EUR, AFR and SAS ancestries, and aggregates for EUR-only .
DOI: 10.60712/si-id405884.2
title: StrainInfo SI-ID 405884.2

description: StrainInfo dataset 405884 about a strain of Alteromonas macleodii. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405885.2
title: StrainInfo SI-ID 405885.2

description: StrainInfo dataset 405885 about a strain of Escherichia coli. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405886.2
title: StrainInfo SI-ID 405886.2

description: StrainInfo dataset 405886 about a strain of Vibrio phage 1.135.O._10N.222.54.B6. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405887.3
title: StrainInfo SI-ID 405887.3

description: StrainInfo dataset 405887 about a strain of Parabacteroides faecis. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405888.2
title: StrainInfo SI-ID 405888.2

description: StrainInfo dataset 405888 about a strain of Paenibacillus. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.60712/si-id405889.3
title: StrainInfo SI-ID 405889.3

description: StrainInfo dataset 405889 about a strain of Haloplasma contractile. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
DOI: 10.15468/dl.zzs8yx
title: Occurrence Download

description: A dataset containing 172052 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Phragmites australis (Cav.) Trin. ex Steud.",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 172052 records from 464 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005029-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13284788
title: Ethereum Price Data Binance API (2017–Now)
DOI: 10.26023/j2cb-e2rx-j700
title: MethaneAIR: Airborne Imaging Spectrometer Level 2 Ungridded Data. Version 1.0

description: IMPORTANT NOTE: As of 30 September 2024, the PI has asked that this dataset be hidden/removed from the archive. Users should contact Steve Wofsy (Harvard) for the latest version of the data. The data in the EOL archive is *not* the latest version and the PI will manage all versions of this dataset. MethaneAIR (“MAIR”) is a dual imaging spectrometer observing reflected sunlight at 1.65 µm (CH4 and CO2) and 1.27 µm. It measures absorption spectra with high spectral resolution, fine spatial resolution, wide swath, and high signal-to-noise ratio, enabling high-contrast, fine-grained images of CH4 column mean dry mole fraction. MAIR duplicates the spectroscopy of the upcoming MethaneSAT satellite (“MSAT”, launch Q1 2023). Development of the MAIR sensor and associated retrieval algorithms was supported by MethaneSAT LLC (a subsidiary of the Environmental Defense Fund). In 2019, NSF supported science demonstration flights of MAIR with an EAGER grant, carried out in August 2021 on the NCAR Gulfstream V. Two engineering test flights in Nov. 2019 (TF01, TF02) were successful, but the flight series was terminated due to avionics failures on the GV. The series was rescheduled for March 2020, but the US shut down that month due to COVID-19. Flights rescheduled for June 2021 were pushed to late July/August of 2021 to accommodate another mission that had been displaced by unavailability of the C-130. After a short test flight (TF03), research flights RF04-RF09 targeted oil and gas infrastructure in Texas, New Mexico, and North Dakota. There were also 21 flight segments on RF04 and RF05 to compare emission rates of methane derived from MethaneAIR data to controlled releases carried out near Odesa, TX, by the Stanford group of Adam Brandt. Engineering test flight TF10 was carried out at the end of the flight series. The spectrometer was inverted to view the upward-looking port of the G-V, recording the spatial pattern of airglow in the 1.27 µm band. This is a large dataset. Please only order the flights needed. See the readme for more information.
DOI: 10.5281/zenodo.17282131
title: Digital Twin of a Pipe Conveying Fluid: Flow Rate Anomaly Detection and Quantification via Multi-fidelity Kalman Filters and Event Based Cameras Signals

description: Numerical results of a digital twin (DT) framework for a pipe conveying fluid recorded using two event-based cameras (EVB). The DT framework consists of an unscented Kalman filter (UKF) for parameter identification and a linear Kalman filter (LKF) coupled with dynamic mode decomposition (DMD) for real-time monitoring and anomaly detection. 

The test case concerns a 75-second recording with a time interval of 0.025 s for a change in flow velocity in the pipe carrying the fluid occurring at t = 18.4 s. The flowrate is the unknown parameter and is initialized as 5.84 m/s and is then reduced to 5.21 m/s. Details of the implementation are available in the associated article.

A README.txt file is available below for the description of each file.
DOI: 10.5281/zenodo.17282132
title: Digital Twin of a Pipe Conveying Fluid: Flow Rate Anomaly Detection and Quantification via Multi-fidelity Kalman Filters and Event Based Cameras Signals

description: Numerical results of a digital twin (DT) framework for a pipe conveying fluid recorded using two event-based cameras (EVB). The DT framework consists of an unscented Kalman filter (UKF) for parameter identification and a linear Kalman filter (LKF) coupled with dynamic mode decomposition (DMD) for real-time monitoring and anomaly detection. 

The test case concerns a 75-second recording with a time interval of 0.025 s for a change in flow velocity in the pipe carrying the fluid occurring at t = 18.4 s. The flowrate is the unknown parameter and is initialized as 5.84 m/s and is then reduced to 5.21 m/s. Details of the implementation are available in the associated article.

A README.txt file is available below for the description of each file.
DOI: 10.26023/7f5z-5qba-bb0w
title: University of Wyoming King Air (UWKA) Low-Rate Flight Level Data for TRANS2AM 2021 Phase. Version 1.0

description: Low Rate (1 Hz) flight level data from the University of Wyoming King Air aircraft during Phase 1 (July and August 2021) of the TRANS2AM campaign. The base of operations was the Laramie Airport (KLAR) in Laramie, Wyoming with most flights over northeastern Colorado. Includes navigation and state parameters as well as aerosol size data from the PCASP.
DOI: 10.26023/xtxm-wf8h-3x0v
title: University of Wyoming King Air (UWKA) Mid-Rate Flight Level Data for TRANS2AM 2021 Phase. Version 1.0

description: Mid Rate (10 Hz) flight level data from the University of Wyoming King Air aircraft during Phase 1 (July and August 2021) of the TRANS2AM campaign. The base of operations was the Laramie Airport (KLAR) in Laramie, Wyoming with most flights over northeastern Colorado. Includes navigation and state parameters as well as aerosol size data from the PCASP.
DOI: 10.34740/kaggle/dsv/13284822
title: BITCOIN Historical Datasets 2018-2025 Binance API
DOI: 10.26023/tkv3-wj7t-pp0j
title: University of Wyoming King Air (UWKA) High-Rate Flight Level Data for TRANS2AM 2021 Phase. Version 1.0

description: High Rate (25 Hz) flight level data from the University of Wyoming King Air aircraft during Phase 1 (July and August 2021) of the TRANS2AM campaign. The base of operations was the Laramie Airport (KLAR) in Laramie, Wyoming with most flights over northeastern Colorado. Includes navigation and state parameters as well as aerosol size data from the PCASP.
DOI: 10.26023/emat-jpbx-s20t
title: PRECIP: NCAR S-Pol radar time series data. Version 1.0

description: S-Pol radar time series data collected during the Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP) from 25 May 2015 to 11 August 2022. The dataset contains the raw in-phase (I) and quadrature (Q) information archived as time series. Each file contains 10 minutes of data and is ~4 G large.
DOI: 10.26023/206w-788s-fv0n
title: LEE: WhatsApp Chat Archives. Version 1.0

description: This dataset is an archive of WhatsApp chat conversations and related media (photos, video) that took place primarily during IOPs, IOP planning, and instrument maintenance coordination among teams. They serve as informal, private field notes shared among the project participants.
DOI: 10.26023/gykc-9aq4-6x0h
title: PRECIP: NCAR S-Pol site camera images. Version 1.0

description: JPEG images from four cameras mounted at the S-Pol radar site during the Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP). The S-Pol cameras were located at the west coast of Taiwan and collected data from May 25 to August 11, 2022. The cameras pointed to the north, east, south, and west. Images were taken every minute.
DOI: 10.26023/fhzj-pf5c-w602
title: SWEX: ISS Surface Meteorology Products. Version 1.0

description: Surface meteorology products collected by the EOL/Integrated Sounding System team during the Sundowner Wind Experiment field campaign in Santa Barbara, CA. Data were collected at three sites: ISS1=Santa Barbara County Fire Department, ISS2=Rancho Alegre, and ISS3=Sedgwick Reserve. Final meteorology products are in netCDF format. PurpleAir aerosol data are in ascii format archived here as tar.gz files by site. Refer to the data report for details.
DOI: 10.6084/m9.figshare.30291250
title: Supplementary Material 1 - Prompt

description: Social media is reshaping the future of tourism, and travel brands are shifting budgets toward travel influencers, many of whom happen to use surprise posts. However, how travel influencers deploy surprise in practice is varied and academically not understood. A novel methodology is utilised, incorporating human analysis for inter-coding travel influencers’ social media posts, and corroborated by artificial intelligence (ChatGPT). Our analysis validates that travel influencers’ surprise posts significantly differ from non-surprise posts. Furthermore, a typology of surprise strategies in travel influencers’ social media posts is developed that articulates how surprise is constructed and used in travel influencer marketing.
DOI: 10.6084/m9.figshare.30291250.v1
title: Supplementary Material 1 - Prompt

description: Social media is reshaping the future of tourism, and travel brands are shifting budgets toward travel influencers, many of whom happen to use surprise posts. However, how travel influencers deploy surprise in practice is varied and academically not understood. A novel methodology is utilised, incorporating human analysis for inter-coding travel influencers’ social media posts, and corroborated by artificial intelligence (ChatGPT). Our analysis validates that travel influencers’ surprise posts significantly differ from non-surprise posts. Furthermore, a typology of surprise strategies in travel influencers’ social media posts is developed that articulates how surprise is constructed and used in travel influencer marketing.
DOI: 10.26023/g4zw-wdwv-1r0a
title: SWEX: ISS Webcam Imagery. Version 1.0

description: Webcam photos collected by the EOL/Integrated Sounding System team during the Sundowner Wind Experiment field campaign in Santa Barbara, CA. Data were collected at three sites: (1) Santa Barbara County Fire Department, (2) Rancho Alegre, and (3) Sedgwick Reserve. All photos are compressed into weekly or monthly tar.gz files gathered by site and camera type to keep the file size manageable. Refer to the data report for details.
DOI: 10.5281/zenodo.17282573
title: MULTIMEDIA INTEGRATION IN PRESCHOOL ENGLISH: A PEDAGOGICALLY SOUND APPROACH
DOI: 10.5281/zenodo.17282574
title: MULTIMEDIA INTEGRATION IN PRESCHOOL ENGLISH: A PEDAGOGICALLY SOUND APPROACH
DOI: 10.26023/rb11-0hz1-qv0f
title: SWEX: ISS Ceilometer CL31 Data Products. Version 1.0

description: Vaisala C31 ceilometer data products collected by the EOL/Integrated Sounding System group during the Sundowner Wind EXperiment (SWEX) field campaign in Santa Barbara, CA. The instrument was mounted on the ISS3 trailer located at the Sedgwick site. Data are in daily raw DAT and netCDf format. DAT files are ordered as a single compressed tar.gz file. Included are text files that contain MLH (Mixed Layer Height) information. These files are ordered as a single compressed tar.fz file. Preview plots are available.
DOI: 10.5281/zenodo.17282587
title: TUG`MA  YURAK  NUQSONI.
DOI: 10.5281/zenodo.17282588
title: TUG`MA  YURAK  NUQSONI.
DOI: 10.6084/m9.figshare.30291274
title: Supplementary Material 2 - Analysis

description: Social media is reshaping the future of tourism, and travel brands are shifting budgets toward travel influencers, many of whom happen to use surprise posts. However, how travel influencers deploy surprise in practice is varied and academically not understood. A novel methodology is utilised, incorporating human analysis for inter-coding travel influencers’ social media posts, and corroborated by artificial intelligence (ChatGPT). Our analysis validates that travel influencers’ surprise posts significantly differ from non-surprise posts. Furthermore, a typology of surprise strategies in travel influencers’ social media posts is developed that articulates how surprise is constructed and used in travel influencer marketing.
DOI: 10.6084/m9.figshare.30291274.v1
title: Supplementary Material 2 - Analysis

description: Social media is reshaping the future of tourism, and travel brands are shifting budgets toward travel influencers, many of whom happen to use surprise posts. However, how travel influencers deploy surprise in practice is varied and academically not understood. A novel methodology is utilised, incorporating human analysis for inter-coding travel influencers’ social media posts, and corroborated by artificial intelligence (ChatGPT). Our analysis validates that travel influencers’ surprise posts significantly differ from non-surprise posts. Furthermore, a typology of surprise strategies in travel influencers’ social media posts is developed that articulates how surprise is constructed and used in travel influencer marketing.
DOI: 10.5281/zenodo.17282592
title: COMMUNICATIVE NORMS IN ENGLISH PHONETICS: FROM STANDARD TO NON-STANDARD VARIETIES
DOI: 10.5281/zenodo.17282593
title: COMMUNICATIVE NORMS IN ENGLISH PHONETICS: FROM STANDARD TO NON-STANDARD VARIETIES
DOI: 10.26023/vy3v-71ar-150a
title: SWEX: ISS Ceilometer CL51 Data Products. Version 1.0

description: Vaisala C51 ceilometer data products collected by the EOL/Integrated Sounding System group during the Sundowner Wind EXperiment (SWEX) field campaign in Santa Barbara, CA. The instrument was mounted on the ISS2 trailer located at the Rancho Alegre site. Data are available in raw ASCII DAT format and in netCDF format. DAT files are ordered as a single compressed tar.gz file. netCDf files were created by the Vaisala BLView software. Preview plots are available.
DOI: 10.25346/s6eecgix/j6qws8
title: colorTarget.jpg