cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.12697647
title: Kilometre-scale regional climate model simulations of two atmospheric river case studies in West Antarctica

description: Regional climate model simulations produced using the MetUM, HCLIM and Polar-WRF models at 1 km horizontal grid spacing. The data span two case studies in which an atmospheric river made landfall over the Amundsen Sea Embayment and Thwaites / Pine Island ice shelves. The first is a winter case (23-30 June 2020) and the second a summer case (3-9 February 2020). 

Data are gridded, in native model coordinates, and saved as netcdf.

Data produced by:

HCLIM: José Abraham Torres

MetUM: Ella Gilbert

Polar-WRF: Denys Pishniak

Data were produced to support the analysis presented in Gilbert et al. (2024) [preprint] . The research was funded by the PolarRES project, which is funded under the EU's Horizon 2020 programme call H2020-LC-CLA-2018-2019-2020 under grant agreement 101003590. MetUM simulations were performed on the ARCHER2 UK National Supercomputer.
DOI: 10.5281/zenodo.7539477
title: CCG Starter Data Kit: Mozambique

description: A starter data kit for Mozambique
DOI: 10.5519/0029634
title: Psyl'list

description: Psyl'list is an online database dedicated to jumping plant lice. The aim of this ongoing project was originally to make up for the absence of a world catalogue for Psylloidea, in organizing taxonomic data and providing easy access to the published taxonomic data that is already available but scattered in the literature. Additional informations about geographical distribution, host-plants, parasitoids, predators, etc... are partly available for some species. This information is continuously supplemented and updated.
DOI: 10.57707/fmi-b2share.840b8a856abf43e18b3fbb329eed5305
title: Automatic GPP data

description: CO2 exchange of three separate linden shoots was measured with an automatic chamber system operating continuously at the site from June to September in 2020-2021. The chambers were mostly open enabling natural radiation and precipitation conditions. They closed automatically two times per hour for 2 minutes at a time resulting in 48 exchange rates per chamber in one day in naturally varying environmental conditions.
The CO2 exchange was calculated from the rate of change in the CO2 concentration during the closure. A simple light response curve was fitted into these exchange rates. Daily photosynthesis was then calculated by summing the instantaneous rates. Data has been used in Thölix et al., 2024.
DOI: 10.57707/fmi-b2share.e638f63a3e6f45eb890e964726154964
title: Daily NEE data from Kumpula Helsinki

description: The net ecosystem exchange (NEE) was estimated from the eddy covariance measurements located in SMEAR III station. Measurements coming from the vegetation sector based on wind direction were used in order to limit emissions from the road located east of the tower. The daily values of NEE were calculated from the vegetation sector, with complete data coverage for a full day available for only 15 % of the days. Consequently, when individual data gaps were shorter than four hours, they were filled using linear interpolation. Dataset has been used in Thölix et al., 2024.
DOI: 10.57707/fmi-b2share.f7ba414bfd3642168ac38a95835b06bc
title: Soil respiration, soil carbon, soil temperature, and soil moisture measured in urban green spaces in Helsinki during 2020-2022

description: Dataset associated with Karvinen et al. (2024) article entitled "Soil respiration across a variety of tree-covered urban green spaces in Helsinki, Finland". Soil respiration CO2 flux, soil temperature, and soil moisture were measured during the growing season (May-September) in 2020-2022 at four measurement sites encompassing a variety of urban green space types commonly found in the city: a small urban forest (Forest), a managed park (Park), road verge between a roadway and a sidewalk (Streetside), and a fruit orchard (Orchard). Soil samples were collected from all measurement sites during the campaign years to determine soil density as well as soil organic carbon (SOC) and nitrogen (SON) content and stock. Article DOI: https://doi.org/10.5194/soil-10-381-2024.
DOI: 10.6073/pasta/b082f2cab94810a14456482db686f128
title: Bisley Tower I Meteorological data (Bisley Tower)

description: Several meteorological parameters are being measured at Bisley since 1993. Correlations between elevation and stream-runoff and rainfall, elevation and air and soil temperature, and between trhoughfall and vegetation types have been found. These relationships are used inhydrologic and nutrient budgets as well as in environmental models . Electronic sensors are placed at the field location to support other activities. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
DOI: 10.6073/pasta/ed65a4722119ae4b104236d0f954b5df
title: Lake exposure to wildfire smoke in North America, 2019-2021

description: Wildfire activity is increasing globally. The resulting smoke plumes can travel hundreds to thousands of kilometers, reflecting or scattering sunlight and depositing ash within ecosystems. Several key physical, chemical, and biological processes in lakes are controlled by factors affected by smoke. The spatial and temporal scales of lake exposure to smoke are extensive and underrecognized. We introduce the concept of the lake smoke-day, or the number of days any given lake is exposed to smoke in any given fire season, and quantify the total lake smoke-day exposure in North America from 2019-2021. Because smoke can be transported at continental to intercontinental scales, even regions that may not typically experience direct burning of landscapes by wildfire are at risk of smoke exposure. We found that 99.3% of North America was covered by smoke, affecting a total of 1,333,687 lakes &gt;=10 ha. An incredible 98.9% of lakes experienced at least 10 smoke-days a year, with 89.6% of lakes receiving over 30 lake smoke-days, and lakes in some regions experiencing up to 4 months of cumulative smoke-days. Herein we review the mechanisms through which smoke and ash can affect lakes by altering the amount and spectral composition of incoming solar radiation and depositing carbon, nutrients, or toxic compounds that could alter chemical conditions and impact biota. We develop a conceptual framework that synthesizes known and theoretical impacts of smoke on lakes to guide future research. Finally, we identify emerging research priorities that can help us better understand how lakes will be affected by smoke as wildfire activity increases due to climate change and other anthropogenic activities.
DOI: 10.17632/7fvgj4jsp7.3
title: BUS-UCLM: Breast ultrasound lesion segmentation dataset

description: The proposed dataset is comprised of breast ultrasound images from 38 patients. It consists of 683 images, of which 174 are benign, 90 are malignant, and 419 are normal. Scans were obtained with a Siemens ACUSON S2000TM Ultrasound System between 2022 and 2023. The ground truth is presented in separate files as RGB segmentation masks where green denotes benign lesions, red denotes malignant lesions, and black denotes the background or normal breast tissue. This dataset constitutes a valuable resource for research in breast cancer diagnosis, lesion detection, medical imaging, and health care applications. It facilitates researchers and practitioners to develop and examine machine learning models for the identification of benign and malignant lesions across full real cases. The segmentation annotations made by expert radiologists enable precise model training and evaluation, making this dataset a benefit in the field of computer vision and public health.
DOI: 10.18434/t4859z
title: X-ray Transition Energies, NIST Standard Reference Database 128
DOI: 10.18462/iir.pcm.2018.0033
title: Study on the effect of nanoparticle dispersion on the melting of PCM in hemicylindrical cell.

description: The melting process of nano-enhanced phase change material (NePCM) contained in a horizontal hemicylindrical vessel isothermally heated on straight wall is numerically investigated. A simulation adopts enthalpy-porosity technique and finite volume method to solve the simultaneous governing equations. The behaviour features of melting such as the progress and the shape of melting interface, melt fraction and charging time are studied according to the influence of the concentration of the nanoparticles loading, and the temperature of the hot wall. The results reveal that increasing the nanoparticles loading leads to enhance the effective thermal conductivity, increase the heat transfer exchange within the phase change material, and decrease the melting time. Also, it is found that the effect of the hot wall temperature on the melting process is significant.
DOI: 10.5067/telnd-nc005
title: GRACE MONTHLY LAND WATER MASS GRIDS NETCDF RELEASE 5.0
DOI: 10.5281/zenodo.10814381
title: JoostVerduijn/RamanAnalysisPipeline: Raman Analysis Pipeline V1

description: No description provided.
DOI: 10.5281/zenodo.14563359
title: MERRA-2/SIRS model data

description: MERRA-2/SIRS model specific humidity inputs and disease variable outputs from SIRS model run with HCoV-HKU1 parameters.

Software to convert specific humidity to R0, run the model, and process the output are available through Zenodo or Github.
DOI: 10.5281/zenodo.14658911
title: Datasets and code for "Precipitation and temperature driven future changes to flooding in Alaska"

description: This repository provides selected codes (jupyter notebooks) and generated data (hydrographs and flood maps) for the Geophysical Research Letter study "Precipitation and temperature driven future changes to flooding in Alaska" by Michalek et al. (2025).
DOI: 10.5441/002/edbt.2014.77
title: Heterogeneous Stream Processing and Crowdsourcing for Urban Traffic Management
DOI: 10.6073/pasta/ac2730ec2c56ffe08302a8c3cc50cd90
title: Bisley Tower (TOWER I) Meteorological Station

description: Several meteorological parameters are being measured at Bisley since 1993. Correlations between elevation and stream-runoff and rainfall, elevation and air and soil temperature, and between trhoughfall and vegetation types have been found. These relationships are used inhydrologic and nutrient budgets as well as in environmental models .Electronic sensors are placed at the field location to support other activities.
DOI: 10.6084/m9.figshare.26379442.v1
title: Data for Wright et al., 2024, submitted to JGR Space Physics

description: IDL save file for data from numerical simulations used to make figures in the paper.
DOI: 10.15468/dl.p42muz
title: Occurrence Download

description: A dataset containing 20641 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Capsicum annuum L."
 ]
}

 The dataset includes 20641 records from 422 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001600-250212154643175/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14030743
title: Processed species-level data for "Global Biodiversity Loss from Outsourced Deforestation"

description: This repository holds processed species-level data for the following paper:



Wiebe, R.A.* and Wilcove, D.S. 2025. Global Biodiversity Loss from Outsourced Deforestation.


*rwiebe@princeton.edu, Guyot Hall, Princeton University, Princeton, NJ

In this analysis, we quantified the range loss to forest-dwelling vertebrates that is attributable to demand for agricultural and forestry products by developed countries in 2001-2015.

We used several datasets in this analysis. Data on forest cover and forest loss were sourced from Hansen et al. and publicly available to download online: https://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.7.html. Data on range maps for species were sourced from the IUCN and downloaded from the IUCN’s API (https://www.iucnredlist.org/resources/spatial-data-download) and its partner BirdLife International’s API (http://datazone.birdlife.org/species/requestdis). These datasets are made available for academic research on request, and an API key is necessary for their downloads. We sourced data on land use attribution from Nguyen Tien Hoang and Keiichiro Kanemoto, from their 2021 publication “Mapping the deforestation footprint of nations reveals growing threat to tropical forests.” These data are not publicly available, but the authors kindly provided the data on request.

Code necessary to replicate the analysis can be found in a public repository at: https://github.com/AlexWiebe/Outsourced-Biodiversity-Loss.
DOI: 10.11570/22.0082
title: The PHANGS-JWST Treasury Survey: Star Formation, Feedback, and Dust Physics at High Angular resolution in Nearby GalaxieS
DOI: 10.14284/537
title: LifeWatch observatory data: monthly CTD temperature and salinity measurements in the Belgian Part of the North Sea

description: In the framework of the Lifewatch marine observatory a number of fixed stations on the Belgian Part of the North Sea (BPNS) are visited on a monthly or seasonal basis using the RV Simon Stevin. A grid of nine stations covers the coastal zone and are sampled monthly. Eight additional stations, located further at sea, are sampled on a seasonal basis. This dataset contains CTD-profile data from LifeWatch sampling campaigns in the Belgian part of the North Sea.
DOI: 10.17632/dv3j9wc59v.1
title: Keyphrases CS&Math Russian

description: Dataset contains CS/Math articles abstracts (in Russian) obtained from two sources: mathnet.ru and cyberleninka.ru. For each article publication year, journal name, authors, title, keyphrases and abstract  are provided.
DOI: 10.17632/fff64w3rzn.3
title: Dataset of NaTech events triggered by lightning within the Process Industry

description: This study delves into the impactful realm of lightning strikes, a meteorological phenomenon that poses substantial risks to the process industry by potentially triggering technological disruptions. Despite constituting merely 13% of NaTech (Natural-Technological) events, lightning events hold significant consequences within the process industry. To better comprehend this, a meticulous analysis of past lightning-triggered events was conducted, utilizing open-source industrial-accident databases to create a new dataset. The research builds upon prior studies concerning NaTech events triggered by lightning and updates the information, encompassing events until the close of 2022. A systematic classification system was introduced, in adherence to NaTech risk field recent studies, enhancing the accuracy of information. Moreover, adjustments were made in compliance with international regulations governing lightning strikes. From deep analysis of past events collected in this new dataset, the variables relationship can be elucidated allowing the estimation of conditional probabilities governing critical dependencies associated with the industrial infrastructure, such as the source and the state of damage, the final scenario, and the sensible equipment or macro-sector bolster industrial vulnerability awareness against this common natural factor. Novel insights in this line could be deepened in a contribution submitted to the Heliyon Journal part of Elsevier’s Cell Press entitled.
DOI: 10.17909/jhv7-w834
title: Data from Comprehensive Parameter Determination of Exoplanet through Asteroseismic Host Star Constraints

description: These data were used for the asteroseismic analysis and planetary transit analysis presented in this paper.
DOI: 10.26025/1912/27650
title: Martha’s Vineyard Coastal Observatory

description: Martha's Vineyard Coastal Observatory (MVCO) is a leading research and engineering facility operated by Woods Hole Oceanographic Institution. MVCO has been collecting ocean and atmospheric data at 3 sites on and near Martha's Vineyard since 2001. A meteorological mast (met mast) on South Beach in Edgartown, MA has collected atmospheric data since May 31 2001. An Air Sea Interaction Tower (ASIT) has been collecting atmospheric and subsurface oceanic data since August 5, 2004. A seafloor node (12m node) has been collecting oceanic data from the seafloor since June 14, 2001. This dataset encompasses the core data (wind speed and direction, air pressure, temperature and relative humidity, water temperature and salinity, and wave data) that has been collected during this period. To learn more about the facility and see additional data collected during short term deployments, visit the MVCO Website (https://mvco.whoi.edu/).
DOI: 10.5281/zenodo.10802054
title: Dataset of the Paper: Security Weaknesses of Copilot-Generated Code in GitHub Projects: An Empirical Study

description: This dataset collected from GitHub was used to conduct an empirical study on security issues in GitHub Copilot-generated code. We provide below a brief description of each folder and file:

1. source-data foldercontains all the code files from the Code and Repository labels that we collected from github and used in our study. Code snippets are included in these code files.

2. scan-result foldercontains the commands used to perform security scans and all the results from security scans performed using static analysis tools.

3. filtered-result foldercontains the results we kept after filtering the scan results in Step 5.

4. fix-result foldercontains code snippets before and after fixes in RQ3 and the results of fixes for security issues.

5. project-url.xlsxprovides the projects from the Repository label and source files from the Code label that contain Copilot-generated code from GitHub.--SOURCE gives the URL of the project from GitHub.--FILE gives the path to the source code file in the project (only for the source files from the Code label).--NOTE gives the statement describing the project as generated by Copilot.--FUNCTION gives a functional description of the project.--DOMAIN gives the application domain that the project containing the Copilot-generated code belongs to.

6. corresponding_cwe.xlsxprovides warning messages from static analysis tools corresponding to CWEs.

7. files_with_security_issues.xlsxprovides information about code snippets with security issues.

8. cwe-result.xlsxprovides the types and quantities of CWEs identified in the scan results.
DOI: 10.5281/zenodo.14182726
title: BeEST single pixel data for conservative wavepacket analysis
title: Direct Experimental Constraints on the Spatial Extent of a Neutrino Wavepacket

description: One day of data from a single STJ pixel from the BeEST experiment.  The data file is the calibaration laser and EC signal energy spectra.  The code file produces limits on uncertainty of the energy measurement and corresponding limits on decay product wavepackets.
DOI: 10.5281/zenodo.14548531
title: Bluetooth Low Energy Separate Channel Fingerprinting dataset with Frequency-Scanned Antennas and Monopole

description: This dataset contains Bluetooth Low Energy Separate Channel (SC BLE) Fingerprinting (FP) data recorded in an indoor facility. The dataset includes Received Signal Strength Information (RSSI) data collected from two independent location systems: one created with four BLE beacons connected to four traditional monopole antennas, and the other four beacons connected to two dual-port Frequency-Scanned Leaky Wave Antennas (FS LWA). Both systems are installed covering the same 7m x 5m area located in a basement zone. 

The dataset includes a reference radiomap file for each point equidistant 50cm to generate Fingerprinting techniques. The calibrated radiomap files are included in the Calibration_21112023 folder. In the name of each file, the {x, y} position where the data were recorded is included, with a total of 130 reference points. The data labelled as P1 and P2 are the RSSI recorded from beacons connected to FS LWA1, while P3 and P4 data corresponds to RSSI obtained from beacons of FS LWA2. Finally, P5, P6, P7 and P8 data sets belong to beacons connected to individual monopole antennas. Each calibration file contains 100 samples of RSSI received from the corresponding beacons at each one of the 130 reference points forming the calibration grid. 

The dataset also includes test samples for different days. These days are labelled as day 1, 8, 15, 22, 29, 51, 86 and 94 after the calibration day 0. This way, the variation of the different SC FP BLE antenna systems’ performance over time, can be studied. This classification of the data as a function of time, is categorized in the folders with the names Test_day_XX_date. As done with the reference calibration information for day 0, a file with the RSSI collected in each reference point (within a total of 130 grid points) can be found in each folder. The name of the file indicates the reference point where the data were collected. 

Different to the reference calibration data of day 0 (where 100 RSSI samples were considered for each one of the 130 calibrated {x, y} positions), the test data obtained in different subsequent days is composed by ten samples of RSSI for each one of the 130 test point. 

Moreover, to test the performance of the systems when some modifications occur where the calibration was performed, some data tests are collected adding several offices' furniture on the days 15, 22, 29, 51 and 94 after the calibration procedure performed at day 0. These data are stored in folders with the name Test_day_XX_with_furnitures_date. Similar to the previous test data, the name of the file includes 130 reference {x,y} points, with 10 RSSI samples each, and for the corresponding eight beacons (P1..P8), which are labelled for both monopole (P5, P6, P7 and P8) and FS LWA antenna systems (P1 and P2 for FS LWA1 and P3 and P4 for FS LWA2).
DOI: 10.5281/zenodo.3653909
title: Predictive maintenance dataset.

description: <em>Public (anonymized) predictive maintenance datasets from Huawei Munich Research Center.</em> Datasets from a variety of IoT sensors for predictive maintenance in elevator industry. The data is useful for predictive maintenance of elevators doors in order to reduce unplanned stops and maximizing equipment life cycle. The dataset contains operation data, in the form of timeseries sampled at 4Hz in high-peak and evening elevator usage in a building (between 16:30 and 23:30). For an elevator car door the system we consider: Electromechanical sensors (Door Ball Bearing Sensor), Ambiance (Humidity) and Physics (Vibration).
DOI: 10.5281/zenodo.3936389
title: SMART Building Additional Data

description: <strong>SMART Building Additional Data</strong> Authors: J. Barthelemy, B. Arshad, N. Verstaevel, D. Guastella, P. Perez<br> Contact: SMART Infrastructure Facility - smart-iot@uow.edu.au<br> Version: 09 July 2020 <strong>Description</strong> The time series data has been generated by Droplet and Pycom sensors installed in the SMART Infrastructure Facility of the University of Wollongong. This dataset consist of a subset of the original complete SMART Infrastructure Facility Building Data (see 10.5281/zenodo.3935060) and additional data collected by the Pycom sensors See the floor plans for the disposition of the additional sensors. <strong>Notes</strong> - Droplet sensors specifications: https://nube-io.com/wp-content/uploads/Droplet-Specifications-V5.0-1.pdf<br> - More information about the SMART Infrastructure Facility is available here: https://www.uow.edu.au/smart/