cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/64719f0f4fcaafc8860a8828e825d438
title: Streamflow for Martinelli basin, 1982 - ongoing.

description: Some of these data were published as a data report: Caine, N., and L. Buchanan. 1987. Streamflow data from the Green Lakes Valley, 1981-1986. University of Colorado Long-Term Ecological Research Data Report 87/4. 34 pp. This is a summary of discharges from the Martinelli Basin and is based on stage records from the outlet channel 30 m below the road at the foot of the basin. NOTE: The LTER data portal display does not display important maintenance/log information or other EML metadata features. Please be sure to view the EML file (a text file that contains XML tags) which is included in the zip archive (click on "Download zip archive") pertaining to each dataset. The EML file name will have the following format: knb-lter-nwt.[3 digit dataset number].[version number].xml. Most web browsers can parse the EML so it's easier to read.
DOI: 10.6073/pasta/657d1d174636681d7a7430344b121175
title: Streamflow data for Saddle stream, 1999 - ongoing.

description: This is a summary of discharges from the stream draining Niwot Ridge Saddle to the south and is based on stage records gauged at a timber weir with a 120 degree V-notch plate, located 30 m upstream of Green Lakes road. It consists of daily flow volumes.
DOI: 10.6073/pasta/9415ac5a669c11c6501612a94f90e04a
title: Saddle catchment sensor network data, 2017- ongoing.

description: Spatial and temporal variability characterizes virtually all ecosystems, with resource supply changing over the course of growing season and across years due to climate variation. To better understand spatial heterogeneity in ecological response across landscape positions, we established a 16-node sensor array within a 45 hectare catchment landscape that measures temporal variability of important biogeochemical and hydrological controls on ecosystem processes. The array was established at the Niwot Saddle catchment in order to accompany long term water quality and discharge records taken at the top and bottom of this catchment. The region forms an important ecological linkage between the the terrestrial areas of the Niwot Ridge LTER and the aquatic component in the Green Lakes Valley.
DOI: 10.6073/pasta/3e1a61e877f1e63f013a3f890841f702
title: Temperature data for the Green Lake 4 buoy, 2018 - ongoing

description: High-resolution water quality data are fundamental to observing rapid ecological responses to meteorology, climate, and other disturbance events. Here we describe the deployment of a single buoy line with multiple sensors at fixed-depths from a subsurface float in the water-column of Green Lake 4 (GL4). Sensors on the buoy collect data in both summer and winter, thereby providing valuable insights into lake characteristics beyond our standard sampling period, including key transitional periods such as ice formation and ice break-up.
DOI: 10.6073/pasta/d40ce19c07e89bbf5870f282a21a93e9
title: Dissolved oxygen data for the Green Lake 4 buoy, 2018 - ongoing

description: High-resolution water quality data are fundamental to observing rapid ecological responses to meteorology, climate, and other disturbance events. Here we describe the deployment of a single buoy line with multiple sensors at fixed-depths from a subsurface float in the water-column of Green Lake 4 (GL4). Sensors on the buoy collect data in both summer and winter, thereby providing valuable insights into lake characteristics beyond our standard sampling period, including key transitional periods such as ice formation and ice break-up.
DOI: 10.6073/pasta/c99e2149c63fd58c463577f84adf4139
title: PAR data for the Green Lake 4 buoy, 2018 - ongoing

description: High-resolution water quality data are fundamental to observing rapid ecological responses to meteorology, climate, and other disturbance events. Here we describe the deployment of a single buoy line with multiple sensors at fixed-depths from a subsurface float in the water-column of Green Lake 4 (GL4). Sensors on the buoy collect data in both summer and winter, thereby providing valuable insights into lake characteristics beyond our standard sampling period, including key transitional periods such as ice formation and ice break-up.
DOI: 10.6073/pasta/ef0a80b1500c692338df74730a6c6d82
title: Chlorophyll-a data for the Green Lake 4 buoy, 2018 - ongoing

description: High-resolution water quality data are fundamental to observing rapid ecological responses to meteorology, climate, and other disturbance events. Here we describe the deployment of a single buoy line with multiple sensors at fixed-depths from a subsurface float in the water-column of Green Lake 4 (GL4). Sensors on the buoy collect data in both summer and winter, thereby providing valuable insights into lake characteristics beyond our standard sampling period, including key transitional periods such as ice formation and ice break-up.
DOI: 10.18434/m32122
title: Source code for labbench 0.20 release

description: This is the source code package for the labbench python module, version 0.20, which is its first public release. The purpose of labbench is to streamline and organize complicated laboratory automation tasks that involve large-scale benchtop automation, concurrency, and/or data management. It is built around a system of wrappers that facilitate robust, concise exception handling, type checking, API conventions, and synchronized device connection through python context blocks. The wrappers also provide convenient new functionality, such as support for automated status displays in jupyter notebooks, simplified threaded concurrency, and automated, type-safe logging to relational databases.Together, these features help to minimize the amount of "copy-and-paste" code that can make your lab automation scripts error-prone and difficult to maintain.The python code that results can be clear, concise, reusable and maintainable, and provide consistent formatting for stored data. The result helps researchers to meet NIST's open data obligations, even for complicated, large, and heterogeneous datasets.Several past and ongoing projects in the NIST Communication Technology Laboratory (CTL) published data that were acquired by automation in labbench. We release it here both for transparency and to invite public use and feedback. Ongoing updates to this source code will be maintained on the NIST github page at https://github.com/usnistgov/labbench.The code was developed in python, documented with the python sphinx package and markdown, and shared through the USNISTGOV organization on GitHub.INSTALLATIONlabbench can run on any computer that supports python 3.6. The hardware requirements are discussed here: https://docs.anaconda.com/anaconda/install/#requirements1. Install your favorite distribution of a python version 3.6 or greater2. In a command prompt, pip install git+https://gitlab.nist.gov/gitlab/ssm/labbench3. (Optional) install an NI VISA [1] runtime, for example this one for windows.USAGEThe source distribution contains detailed information including* README.md - documentation to get started using labbench* LICENSE.md - license and redistribution information* doc/labbench-api.pdf - complete listing of the module and documentation
DOI: 10.6073/pasta/4a08e4abec654a9f725b07593bce8b8c
title: Soil moisture, temperature, and electrical conductivity data from the black sand extended growing season length experiment, hourly, 2018 - ongoing

description: As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how changes in growing season length may affect biotic and abiotic components, NWT LTER researchers established 5 experimental sites each containing a pair 10 x 40m rectangular plots. These blocks include north and south facing aspects, subalpine and alpine tundra meadows in a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot of each block by adding chemically inert black sand, while keeping the second plot as an unmanipulated control (black sand was added to these plots after snow had naturally melted). This dataset includes measurements of soil temperature, moisture, and electrical conductivity.
DOI: 10.18112/openneuro.ds003216.v1.0.4
title: Whole brain layer-fMRI connectome: An open dataset
DOI: 10.15468/v7zjrn
title: Fantastic lizards and where to find them: cis-Andean microteiids (Squamata: Alopoglossidae & Gymnophthalmidae) from the Colombian Orinoquia and Amazonia

description: This dataset contains the digitized treatments in Plazi based on the original journal article Diago-Toro, María F., García-Cobos, Daniela, Brigante-Luna, Giovanni D., Vásquez-Restrepo, Juan D. (2021): Fantastic lizards and where to find them: cis-Andean microteiids (Squamata: Alopoglossidae & Gymnophthalmidae) from the Colombian Orinoquia and Amazonia. Zootaxa 5067 (3): 377-400, DOI: https://doi.org/10.11646/zootaxa.5067.3.3
DOI: 10.6084/m9.figshare.13394102
title: De-identified location-based services dataset

description: De-identified Twitter data from Singapore (2012-2016)
DOI: 10.6084/m9.figshare.13394102.v1
title: De-identified location-based services dataset

description: De-identified Twitter data from Singapore (2012-2016)
DOI: 10.5519/qd.2wxloyk8
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (3082 records)
DOI: 10.6084/m9.figshare.16989073
title: unigene.fasta

description: Transcript sequence of <i>Triplophysa Yarkandensis </i>transcriptome after sequencing and stitching.
DOI: 10.6084/m9.figshare.16989073.v1
title: unigene.fasta

description: Transcript sequence of <i>Triplophysa Yarkandensis </i>transcriptome after sequencing and stitching.
DOI: 10.5281/zenodo.5670387
title: Are terrestrial biosphere models fit for simulating the global land carbon sink?

description: This repository contains the data and code required for reproducing the results presented in the paper "Are terrestrial biosphere models fit for simulating the global land carbon sink?" by Seiler et al., 2021. The study evaluates an ensemble of terrestrial biosphere models (TRENDY; v9; S3 simulations) against a wide range of reference data using the Automated Model Benchmarking R package (AMBER; version 1.1.1). The only requirement for reproducing our results is access to a Linux machine with conda, an open-source package management system and environment management system, installed. Follow the steps described in the <em>readme</em> file to install AMBER and run the analysis. The repository also contains all output produced by our analysis.
DOI: 10.5281/zenodo.5670386
title: Are terrestrial biosphere models fit for simulating the global land carbon sink?

description: This repository contains the data and code required for reproducing the results presented in the paper "Are terrestrial biosphere models fit for simulating the global land carbon sink?" by Seiler et al., 2021. The study evaluates an ensemble of terrestrial biosphere models (TRENDY; v9; S3 simulations) against a wide range of reference data using the Automated Model Benchmarking R package (AMBER; version 1.1.1). The only requirement for reproducing our results is access to a Linux machine with conda, an open-source package management system and environment management system, installed. Follow the steps described in the <em>readme</em> file to install AMBER and run the analysis. The repository also contains all output produced by our analysis.
DOI: 10.18112/openneuro.ds003810.v1.0.1
title: Motor Imagery vs Rest - Low-Cost EEG System
DOI: 10.23636/6g9b-9d72
title: Ordnance Survey Old / First series England and Wales 1:63360 (georeferenced sheet images)

description: Map sheet images for the Ordnance Survey Old Series / First Series England and Wales 1:63360, georeferenced and cropped at the neatlike (can be viewed together as a seamless composite). Geotiff format. The original (ungeoreferenced) sheet images can be found at: https://commons.wikimedia.org/wiki/Category:Ordnance_Survey_Old/First_series_England_and_Wales_1:63360_(full_sheets). The sheets were georeferenced by relating the sheet corners to their coordinates (no internal control points applied), using sheet boundary data created by the Charles Close Society (see https://www.charlesclosesociety.org/KMLFILE). Where sheets were issued as quarter sheets (NW, NE, SW, SE), a digital composite of the full sheet has been created. The filenames include the sheet number. See an index map at: https://commons.wikimedia.org/wiki/Category:Ordnance_Survey_Old/First_series_England_and_Wales_1:63360_(full_sheets)#/media/File:Ordnance_Survey_One-inch_Old_Series_England_&_Wales_Index.png The imagery is medium resolution.
DOI: 10.5519/qd.bu854ge1
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (152 records)
DOI: 10.11583/dtu.16988434
title: Turbulence measurements from NTK1500

description: The dataset includes time series of wind data from a 60 m mast located next to a 1.5 MW Nordtank wind turbine in Tjæreborg Enge, Esbjerg, DK. The time series represent more than 150 hours from the period Nov 1997 - Feb 1998.<br>Detailed site documentation is available here.<br><br>Public data Run statistics stored as NetCDF format 1) ntk1500_all.nc2) Ntk1500_concurrent.nc Raw time series (ascii), with a duration of 600 sec, sampled with 40 Hz.: 3) Ntk1500.zip<br>
DOI: 10.11583/dtu.16988434.v1
title: Turbulence measurements from NTK1500

description: The dataset includes time series of wind data from a 60 m mast located next to a 1.5 MW Nordtank wind turbine in Tjæreborg Enge, Esbjerg, DK. The time series represent more than 150 hours from the period Nov 1997 - Feb 1998.<br>Detailed site documentation is available here.<br><br>Public data Run statistics stored as NetCDF format 1) ntk1500_all.nc2) Ntk1500_concurrent.nc Raw time series (ascii), with a duration of 600 sec, sampled with 40 Hz.: 3) Ntk1500.zip<br>
DOI: 10.5281/zenodo.5659573
title: Computer-aided Veress needle guidance using endoscopic optical coherence tomography and convolutional neural networks

description: During laparoscopic surgery, the Veress needle is commonly used in pneumoperitoneum establishment. Precise placement of the Veress needle is still a challenge for the surgeon. In this study, a computer-aided endoscopic optical coherence tomography (OCT) system was developed to effectively and safely guide Veress needle insertion. This endoscopic system was tested by imaging subcutaneous fat, muscle, abdominal space, and the small intestine from swine samples to simulate the surgical process, including the situation with small intestine injury. Each tissue layer was visualized in OCT images with unique features and subsequently used to develop a system for automatic localization of the Veress needle tip by identifying tissue layers (or spaces) and estimating the needle-to-tissue distance. We used convolutional neural networks (CNNs) in automatic tissue classification and distance estimation. The average testing accuracy in tissue classification was 98.53±0.39%, and the average testing relative error in distance estimation reached 4.42±0.56% (36.09±4.92 μm). The dataset is split into two parts:<br> (1) <strong>Classification</strong>. The zip file <em>veress_classification_raw_images.zip</em> contains 40K images from 8 swine samples where there are 1K images per layer (skin, fat, muscle, abdominal space, and small intestine)<br> (2) <strong>Regression</strong>. The zip file <em>veress_regression_raw_images.zip</em><strong> </strong>contains 8K images of the abdominal space from the same 8 swine samples, and the ground truth distance labels for each sample are found in the Excel files <em>S[1-8]_distance_measurement_20210803.xlsx.</em>
DOI: 10.5281/zenodo.5659572
title: Computer-aided Veress needle guidance using endoscopic optical coherence tomography and convolutional neural networks

description: During laparoscopic surgery, the Veress needle is commonly used in pneumoperitoneum establishment. Precise placement of the Veress needle is still a challenge for the surgeon. In this study, a computer-aided endoscopic optical coherence tomography (OCT) system was developed to effectively and safely guide Veress needle insertion. This endoscopic system was tested by imaging subcutaneous fat, muscle, abdominal space, and the small intestine from swine samples to simulate the surgical process, including the situation with small intestine injury. Each tissue layer was visualized in OCT images with unique features and subsequently used to develop a system for automatic localization of the Veress needle tip by identifying tissue layers (or spaces) and estimating the needle-to-tissue distance. We used convolutional neural networks (CNNs) in automatic tissue classification and distance estimation. The average testing accuracy in tissue classification was 98.53±0.39%, and the average testing relative error in distance estimation reached 4.42±0.56% (36.09±4.92 μm). The dataset is split into two parts:<br> (1) <strong>Classification</strong>. The zip file <em>veress_classification_raw_images.zip</em> contains 40K images from 8 swine samples where there are 1K images per layer (skin, fat, muscle, abdominal space, and small intestine)<br> (2) <strong>Regression</strong>. The zip file <em>veress_regression_raw_images.zip</em><strong> </strong>contains 8K images of the abdominal space from the same 8 swine samples, and the ground truth distance labels for each sample are found in the Excel files <em>S[1-8]_distance_measurement_20210803.xlsx.</em>
DOI: 10.6084/m9.figshare.16989526
title: stocks_to_watch.csv.zip

description: see readme
DOI: 10.6084/m9.figshare.16989526.v1
title: stocks_to_watch.csv.zip

description: see readme
DOI: 10.6084/m9.figshare.16989532
title: covid-19_cases.csv.zip

description: see readme
DOI: 10.6084/m9.figshare.16989532.v1
title: covid-19_cases.csv.zip

description: see readme
DOI: 10.5258/soton/d2023
title: The generation of femtosecond optical vortex beams with megawatt powers directly from a fiber based Mamyshev oscillator

description: Abstract: Numerous approaches have been developed to generate optical vortex beams carrying orbital angular momentum (OAM) over the past decades, but the direct intracavity generation of such beams with practical output powers in the femtosecond regime still remains a challenge. Here we propose and experimentally demonstrate the efficient generation of high-peak-power femtosecond optical vortex pulses from a Mamyshev oscillator (MO) based on few-mode polarization-maintaining (PM) ytterbium-doped fibers (YDFs). By employing an appropriate intracavity transverse spatial mode selection technique, ultrafast pulses carrying OAM with selectable topological charge of l = ±1 are successfully generated with an average output power of ~5.72 W at ~24.35 MHz repetition rate, corresponding to a single pulse energy of ~235 nJ. The chirped pulses can be compressed to ~76 fs outside the cavity, leading to a pulse peak power of ~2.2 MW. To the best of our knowledge, this is by far the highest pulse energy and peak power for optical vortex pulses ever generated directly from a fiber oscillator. This unprecedented level of performance should be of great interest for a variety of applications including materials processing and imaging.
DOI: 10.6084/m9.figshare.16989535.v1
title: covid-19_meassures.zip

description: see readme
DOI: 10.6084/m9.figshare.16989535
title: covid-19_meassures.zip

description: see readme
DOI: 10.15151/esrf-es-617065513
title: Molecular machines in energy transduction, cellular signaling and defense processes

description: Within this BAG we are focussing mainly on three topics: 1.) proteins that use the energy of light, ATP, GTP or NADH to perform essential biological functions, either embedded in the membrane or in the cytosol 2.) proteins of different essential signaling or metabolic processes in plants like the ethylene pathway or the nitrogen metabolism 3.) proteins involved in the immune system of prokaryotic bacteria and plants or associated with diseases like cancer or developmental disorders
DOI: 10.6084/m9.figshare.16989538
title: stock_prices.csv.zip

description: see readme
DOI: 10.6084/m9.figshare.16989529
title: mobility_combined.csv

description: see readme
DOI: 10.15468/xrpaua
title: Two new species of Petalophthalmus and Ipirophthalmus (Crustacea: Mysida: Petalophthalmidae), from New Zealand

description: This dataset contains the digitized treatments in Plazi based on the original journal article Forman, Jeffrey S., Schnabel, Kareen E. (2021): Two new species of Petalophthalmus and Ipirophthalmus (Crustacea: Mysida: Petalophthalmidae), from New Zealand. Zootaxa 5061 (3): 451-475, DOI: https://doi.org/10.11646/zootaxa.5061.3.3
DOI: 10.5258/soton/d2026
title: Dataset for Electrodeposition of GeSbTe Based Resistive Switching Memory in Crossbar Arrays

description: This dataset is for the paper titled “Electrodeposition of GeSbTe Based Resistive Switching Memory in Crossbar Arrays” with authors Jaafar, Ayoub; Meng, Lingcong; Noori, Yasir; Zhang, Wenjian; Han, Yisong; Beanland, Richard; Smith, David; Reid, Gillian; de Groot, C.H. (Kees); Huang, Ruomeng; Bartlett, Philip to the Journal of Physical Chemistry C. (Manuscript ID: jp-2021-08549r)
DOI: 10.6084/m9.figshare.16989445
title: AntiDepResponse2021

description: GWAS summary statistics from the Psychiatric Genomics Consortium (PGC)
DOI: 10.34892/wtba-jc15
title: Global relative rate of natural capital depletion of soil and sediments

description: Global relative rate of natural capital depletion of soil and sediments, measured through soil erosion, change in soil salinity, and change in soil carbon stocks. The relative depletion rates enable the identification of hotspots of natural capital depletion (defined as the top 20% of values), where human activities will be associated with higher risks of ecosystem service loss or degradation. This will, in turn, present higher risks for financial institutions investing in these areas.

Global Soil Erosion from EC JRC (https://esdac.jrc.ec.europa.eu/content/global-soil-erosion), Global Soil salinity change from Ivushkin et al (2019) (https://data.isric.org) and Soil Organic Carbon Stocks from Soils Revealed (https://soilsrevealed.org/)

For soil erosion, the EC JRC rate of soil erosion dataset for 2012 was rescaled from 0-1 and log(x+1) transformed. For soil salinity, 1986 values were subtracted from 2016 (except where data were missing – in that case 2009 or 1992 data had to be used to replace 2016 and 1986 values respectively). Negative values (indicating a decrease in salinity) were set to 0, as only an increase in salinity was interpreted as depletion of soil. The salinity layer was then rescaled from 0-1. For soil carbon, depletion was determined by subtracting 2000 (baseline) data from the 2018 (most recent) layer. Positive values (indicating a gain in carbon) were set to 0, as only a decrease in carbon stock was interpreted as depletion of soil, and the resulting values were multiplied by -1, then rescaled from 0-1. The resulting erosion, salinity, and carbon layers were summed and rescaled from 0-1 to produce the soil depletion layer.
DOI: 10.5258/soton/d2017
title: Supporting data set for "Immunotherapy in Synucleinopathies - Raw values from processed images and biochemical studies

description: This dataset supports University of Southampton Doctoral Thesis titled "Immunotherapy in Synucleinopathies". It contains Excel spreadsheets of the image analysis conducted in Chapter 3-6 of the thesis titled "Immunotherapy in Synucleinopathies". This dataset also contains the raw values of the antibody titre analysis conducted in Chapter 6. The raw values comprise several large files and are available on request from https://library.soton.ac.uk/datarequest