cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10809725
title: Data of the publication "An insight into the capability of the actuator line method to resolve tip vortices"

description: This repository contains the data presented in "An insight into the capability of the actuator line method to resolve tip vortices", published by Melani et al. on the Wind Energy Science journal. More in detail, it contains all the data post-processed from BR-CFD, Frozen ALM, and Standard ALM simulations.
DOI: 10.5281/zenodo.10809726
title: Data of the publication "An insight into the capability of the actuator line method to resolve tip vortices"

description: This repository contains the data presented in "An insight into the capability of the actuator line method to resolve tip vortices", published by Melani et al. on the Wind Energy Science journal. More in detail, it contains all the data post-processed from BR-CFD, Frozen ALM, and Standard ALM simulations.
DOI: 10.6084/m9.figshare.25393525
title: Data for: Socially Assistive Walker for Daily Living Assistance in Older Adults

description: This repository contains supporting data for the article 'Socially Assistive Walker for Daily Living Assistance in Older Adults'. The excel file contains demographics, perception questions and open-ended questions.
DOI: 10.6084/m9.figshare.25393525.v1
title: Data for: Socially Assistive Walker for Daily Living Assistance in Older Adults

description: This repository contains supporting data for the article 'Socially Assistive Walker for Daily Living Assistance in Older Adults'. The excel file contains demographics, perception questions and open-ended questions.
DOI: 10.12770/a1066345-cf3b-4602-a3c5-5c5a5eaee278
title: Réanalyse du modèle de vagues MFWAM sur la Polynésie française (MFWAM_FR-POLYNESIA_005)
title: Réanalyse du modèle de vagues MFWAM sur la Polynésie française (MFWAM_FR-POLYNESIA_005)

description: Configuration régionale en Polynésie française d’une réanalyse de vagues sur 30 ans du modèle MFWAM (Météo France WAve Model) de Météo-France sur une grille régulière à 0.05° de résolution. 
Une configuration régionale du modèle MFWAM a été mise en place par Météo-France sur le domaine de la Polynésie française à une résolution spatiale de 0.05° pour des études climatologiques. La résolution temporelle est de 3 heures avec 30 années de simulation. Le vent en forçage est celui de la réanalyse ERA5. Une assimilation des données satellitaires est également effectuée.
description: Configuration régionale en Polynésie française d’une réanalyse de vagues sur 30 ans du modèle MFWAM (Météo France WAve Model) de Météo-France sur une grille régulière à 0.05° de résolution. 
Une configuration régionale du modèle MFWAM a été mise en place par Météo-France sur le domaine de la Polynésie française à une résolution spatiale de 0.05° pour des études climatologiques. La résolution temporelle est de 3 heures avec 30 années de simulation. Le vent en forçage est celui de la réanalyse ERA5. Une assimilation des données satellitaires est également effectuée.
DOI: 10.18739/a25t3g20t
title: Greenhouse gas flux measurements at the zero curtain, North Slope, Alaska, 2012-2023

description: Overview- This project proposes to create a long-term, year-round field observations to better understand the controls on greenhouse gas (GHG) emissions from the Arctic at time scales that will encompass significant climate change and variability. Research over decadal time frames is critical for understanding the effect of climate variability and change on carbon dioxide (CO2) and methane (CH4) fluxes and to provide the baseline needed to evaluate temporal changes. This is particularly relevant in arctic ecosystems where the large spatial heterogeneity prevents using nearby stations to build a time series in the GHG emissions, given that fluxes can vary substantially over the meter scale. This project will allow creating the longest running year-round Arctic eddy covariance network, and to standardize, upgrade, and apply the network to improve understanding of the long-term effects of climate variability and change on trace gas feedbacks from the Arctic. This project will make existing data more useful and relevant and will expand an already large user base. A special emphasis will be on the fall zero curtain period when an unfrozen soil layer hovers around 0°Celsius (C) supporting significant CO2 and CH4 releases to the atmosphere, and the entire cold season (Zona et al., 2016). Zero curtain processes plausibly explain how upland tundra can be a larger emitter of CH4 than low-lying, wet tundra, and how the cold seasons might emit more CH4 than the summer season (Zona et al., 2016, Commane et al., 2017). At present, however, cold season observations are too short to adequately test hypotheses concerning the controlling mechanisms or to develop understanding that allows us to predict, with confidence, future CO2 and CH4 fluxes form the Arctic. Five Arctic eddy covariance flux towers will be used to evaluate the long term changes in the CO2 and CH4 fluxes across three moisture environments in Barrow (recently renamed as Utqiaġvik) (CMDL (Climate Monitoring and Diagnostics Laboratory), BEO (Barrow Environmental Observatory), and BES (Biocomplexity Experiment South) towers) and a ~300km latitudinal gradient passing through Atqasuk (ATQ) and culminating in Ivotuk (IVO). These measurements are intended to be of sufficient duration and breadth to capture and interpret the effect of extreme and/or unexpected events on GHG fluxes in the Arctic. The support from this grant would allow expansion of the time series to a more than 20-year record of CO2 and 11-year record of CH4 fluxes, resulting in an unprecedented dataset, critical to refining our analytical and predictive ability of the controls of CH4 loss from the Arctic.
DOI: 10.26025/1912/69142
title:  Underway instrument data xa20230425_transit_discoverybay

description: Voyage data from Gramercy, Louisiana to Discovery Bay, Jamaica. The vessel left Gramercy, Louisiana April 28, 2023 and arrived in Discovery Bay, Jamaica on May 2, 2023. The data distribution may include data on either side of the transit while ship waits to dock.
Data collected is time stamped by the science Network Time Server and is considered raw. Data included in this distribution: (1) MET, which includes barometric pressure, humidity, rain (intensity and amount), true and relative wind speed, true and relative wind direction; (2) GPS which includes ship speed, heading, latitude, longitude; (3) ADCP data collected using UHDAS (https://zenodo.org/records/8371260).
DOI: 10.5281/zenodo.10810043
title: SpokeN-100: A Cross-Lingual Benchmarking Dataset for The Classification of Spoken Numbers in Different Languages

description: SpokeN-100 is a novel, entirely artificially generated benchmarking dataset tailored for speech recognition, representing a core challenge in the field of tiny deep learning. SpokeN-100 consists of spoken numbers from 0 to 99 spoken by 32 different speakers in four different languages, namely English, Mandarin, German and French, resulting in 12,800 audio samples.
DOI: 10.5281/zenodo.10810044
title: SpokeN-100: A Cross-Lingual Benchmarking Dataset for The Classification of Spoken Numbers in Different Languages

description: SpokeN-100 is a novel, entirely artificially generated benchmarking dataset tailored for speech recognition, representing a core challenge in the field of tiny deep learning. SpokeN-100 consists of spoken numbers from 0 to 99 spoken by 32 different speakers in four different languages, namely English, Mandarin, German and French, resulting in 12,800 audio samples.
DOI: 10.6084/m9.figshare.25392832
title: Between Prompts and Representation: A Case Study in Audiovisual Research-Creation with Generative Artificial Intelligence (Research Log).xlsx

description: This is a "prompt log", designed to monitor both human and non-human (AI) creative processes in real-time within the production of "El Majaya" a short fiction film produce using generative artificial intelligence (GenAI), drawing inspiration from a Caribbean imaginary of life after death. The "Prompt log" facilitated a retrospective critical analysis. The examination of the activity's registry and the prompt log reveals technical and representational challenges that emerged during the creation process, necessitating multiple iterations to achieve a visual representation aligned with the cultural identity and intentions of its creators, this results in more financial and time resources to produce one accurate shot.
DOI: 10.5281/zenodo.10810175
title: HEATDesalination - Case-study lowest-cost optimisation results

description: Optimisation results for the lowest lifetime cost system consisting of solar photovoltaic (PV), hybrid photovoltaic-thermal (PV-T) and solar-thermal collectors alongside battery and hot-water storage systems for meeting the electrical and thermal (hot-water) needs of three multi-effect distillation (MED) plants.

The updated results are from optimisations runs carried out in response to peer-review comments.
DOI: 10.5281/zenodo.7801892
title: HEATDesalination - Case-study lowest-cost optimisation results

description: Optimisation results for the lowest lifetime cost system consisting of solar photovoltaic (PV), hybrid photovoltaic-thermal (PV-T) and solar-thermal collectors alongside battery and hot-water storage systems for meeting the electrical and thermal (hot-water) needs of three multi-effect distillation (MED) plants.

The updated results are from optimisations runs carried out in response to peer-review comments.
DOI: 10.5281/zenodo.7801893
title: HEATDesalination - Case-study lowest-cost optimisation results

description: Optimisation results for the lowest lifetime cost system consisting of solar photovoltaic (PV), hybrid photovoltaic-thermal (PV-T) and solar-thermal collectors alongside battery and hot-water storage systems for meeting the electrical and thermal (hot-water) needs of three multi-effect distillation (MED) plants.
DOI: 10.26025/1912/69143
title: Underway instrument data xa20230506_transit_gramercy

description: Voyage data from Discovery Bay, Jamacia to Gramercy, Louisiana. The vessel left Discovery Bay, Jamaica May 8, 2023 and arrived in Gramercy, Louisiana on May 13, 2023. The data distribution may include data on either side of the transit while ship waits to dock.
Data collected is time stamped by the science Network Time Server and is considered raw. Data included in this distribution: (1) MET, which includes barometric pressure, humidity, rain (intensity and amount), true and relative wind speed, true and relative wind direction; (2) GPS which includes ship speed, heading, latitude, longitude; (3) ADCP data collected using UHDAS (https://zenodo.org/records/8371260).
DOI: 10.25345/c5dr2pm1d
title: MassIVE MSV000094294 - B._Raktan_Ahmed_P131_VS15_2024
title: This dataset consists of 363 raw MS files and associated peak lists and result files, acquired on a TripleTOF 6600 mass spectrometer operated in Data Independent Acquisition mode (SWATH). It also includes the sequence database used for analysis and the MSPLIT spectral library which was generated from paired samples acquired in Data Dependent Acquisition (DDA) mode. All sample generation, streptavidin affinity purification, mass spectrometric acquisition, and data analysis was performed by B. Raktan Ahmed. The files are associated with a manuscript submitted for publication by Dyakov et al. that provides a spatial map of nuclear body-associated proteins with a focus on the paraspeckle and nuclear speckle. Anne-Claude Gingras is the corresponding author of the manuscript and should be contacted for questions about this dataset (gingras@lunenfeld.ca). This submission is associated with 4 Supplementary Files (in addition to this README file): Table 1 describes the composition of this dataset Table 2 lists the protein evidence for the entire dataset Table 3 lists the SAINT output (results) Internal reference from the Gingras lab ProHits implementation: Project: P131 Export version VS15 SAINT Task ID: 6779
DOI: 10.5281/zenodo.10790858
title: Forest disturbances in Europe mapped at high spatial detail and in near-real-time: Logging in protected Estonian forests

description: Data description

These datasets were generated for the Geostory "Forest disturbances in Europe mapped at high spatial detail and in near-real-time: Logging in protected Estonian forests" in the context of the Open Earth Monitor Cyberinfrastructure project.

We used open source high-resolution Sentinel-1 satellite data to develop a wall-to-wall map of forest disturbances in the four-year period between the start of 2020 and end of 2023 in Estonia. First results are presented. The methodology is based on RADD-alerts developed for the pan-tropics (Reiche et al. 2021). Three years (2017-2019) of imagery was used as a historical period, and detections were generated for ~4 years (2020-2023). Winter images from November through March were not included as frozen conditions can introduce false detections. This will be addressed in the next version. Disclaimer: Disturbance maps have not been validated.

Two additional layers are provided for visualization: a forest baseline layer (forestcover), masking out non-forest disturbance detections, was derived from Copernicus 10m 2018 forest cover density and GLAD 30m 2019 tree removal datasets, and a protected areas layer (natura), which displays the extent of Natura 2000 coverage in Estonia.

'.SLD' files are provided for visualization (note: the disturbance .SLC file must be adjusted to contain appropriate time reference fields).

Naming Convention

To ensure consistency and ease of use across and within the projects, we follow the standard Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describes important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. For instance:



disturbance_radd_c_10m_s_20200101_20200131_eu_epsg.3035_v20240222.tif


with the following fields:



Generic variable name: disturbance

Variable procedure combination i.e. method standard: radd

Position in the probability distribution / variable type: c

Spatial support: 10m

Depth reference or depth interval e.g. below ("b"), above ("a") ground or at surface ("s"): s

Time reference begin time (YYYYMMDD): 20200101

Time reference end time: 20200131

Bounding box (2 letters max): eu 

EPSG code: epsg.3035

Version code i.e. creation date: v20240222


Source Data

Disturbance maps:

Contains modified Copernicus Sentinel data [2017-2023] and Generated using European Union's EEA-10 Copernicus DEM; https://doi.org/10.5270/ESA-c5d3d65

Forest baseline:

Generated using European Union's Copernicus Land Monitoring Service information; https://doi.org/10.2909/486f77da-d605-423e-93a9-680760ab6791 and GLAD tree removal; https://doi.org/10.1016/j.rse.2023.113797

Natura 2000: 

Generated using European Environmental Agency's Natura 2000 layers; https://sdi.eea.europa.eu/data/dae737fd-7ee1-4b0a-9eb7-1954eec00c65
DOI: 10.5281/zenodo.10790859
title: Forest disturbances in Europe mapped at high spatial detail and in near-real-time: Logging in protected Estonian forests

description: Data description

These datasets were generated for the Geostory "Forest disturbances in Europe mapped at high spatial detail and in near-real-time: Logging in protected Estonian forests" in the context of the Open Earth Monitor Cyberinfrastructure project.

We used open source high-resolution Sentinel-1 satellite data to develop a wall-to-wall map of forest disturbances in the four-year period between the start of 2020 and end of 2023 in Estonia. First results are presented. The methodology is based on RADD-alerts developed for the pan-tropics (Reiche et al. 2021). Three years (2017-2019) of imagery was used as a historical period, and detections were generated for ~4 years (2020-2023). Winter images from November through March were not included as frozen conditions can introduce false detections. This will be addressed in the next version. Disclaimer: Disturbance maps have not been validated.

Two additional layers are provided for visualization: a forest baseline layer (forestcover), masking out non-forest disturbance detections, was derived from Copernicus 10m 2018 forest cover density and GLAD 30m 2019 tree removal datasets, and a protected areas layer (natura), which displays the extent of Natura 2000 coverage in Estonia.

'.SLD' files are provided for visualization (note: the disturbance .SLC file must be adjusted to contain appropriate time reference fields).

Naming Convention

To ensure consistency and ease of use across and within the projects, we follow the standard Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describes important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. For instance:



disturbance_radd_c_10m_s_20200101_20200131_eu_epsg.3035_v20240222.tif


with the following fields:



Generic variable name: disturbance

Variable procedure combination i.e. method standard: radd

Position in the probability distribution / variable type: c

Spatial support: 10m

Depth reference or depth interval e.g. below ("b"), above ("a") ground or at surface ("s"): s

Time reference begin time (YYYYMMDD): 20200101

Time reference end time: 20200131

Bounding box (2 letters max): eu 

EPSG code: epsg.3035

Version code i.e. creation date: v20240222


Source Data

Disturbance maps:

Contains modified Copernicus Sentinel data [2017-2023] and Generated using European Union's EEA-10 Copernicus DEM; https://doi.org/10.5270/ESA-c5d3d65

Forest baseline:

Generated using European Union's Copernicus Land Monitoring Service information; https://doi.org/10.2909/486f77da-d605-423e-93a9-680760ab6791 and GLAD tree removal; https://doi.org/10.1016/j.rse.2023.113797

Natura 2000: 

Generated using European Environmental Agency's Natura 2000 layers; https://sdi.eea.europa.eu/data/dae737fd-7ee1-4b0a-9eb7-1954eec00c65
DOI: 10.25612/837.47g8g87zgq94
title: Harris County Voter Registration Data - Individual Level (With Duplicates)

description: Individual level Harris County voter registration data with duplicates as of 02/10/2024.
DOI: 10.6084/m9.figshare.25393567
title: FBphT.csv

description: Data repository for publication:<b>"Unpunctual in diversity: The effect of stand species richness on spring phenology of deciduous tree stands varies among species and years"</b>by T.Heinecke, P.DeFrenne, K.Verheyen, I.Nijs, E.Matthysen and M.Campioli
DOI: 10.6084/m9.figshare.25393567.v1
title: FBphT.csv

description: Data repository for publication:<b>"Unpunctual in diversity: The effect of stand species richness on spring phenology of deciduous tree stands varies among species and years"</b>by T.Heinecke, P.DeFrenne, K.Verheyen, I.Nijs, E.Matthysen and M.Campioli
DOI: 10.25612/837.ra9k9kna02m4
title: Harris County Voter Registration Data - Individual Level (Without Duplicates)

description: Individual level Harris County voter registration data without duplicates as of 02/10/2024.
DOI: 10.5066/p9s9fmou
title: Model Data Set and Executables Supporting the Journal Publication for "What Makes a First-Magnitude Spring?--Global Uncertainty Analysis of a Speleogenesis Model to Gain Insight into Karst Spring Genesis"

description: This data set provides the supporting data for the publication "What Makes a First Magnitude Sping?--Global Uncertainty Analysis of a Speleogenesis Model to Gain Insight into Karst Spring Genesis". This publication documents a speleogenesis model that was used to generate karst networks. Morris Method Global Sensitivity Analysis (MM-GSA) is used to efficiently sample input parameters to define a potential karst network. The MM-GSA provides information about sensitivity of hydrologic and transport response metrics (e.g., peak flows, peak timing, mass flux) to evaluated input parameters (e.g. network density, proto-conduit length distribution). There were 390 models in the analysis, therefore one replicate is provided as an example. The data set includes one complete replicate including the input data for the initial protoconduit network that is evolved into a network through the speleogenesis model, the flow model for hydrologic metric evaluation, and the transport model for transport metric evaluation. A table of the parameters that varied in each replicate is provided to so the entire ensemble may be reconstructed. A copy of the model executables is provided. The results for all hydrologic and transport metrics is provided for each replicate.
DOI: 10.6084/m9.figshare.25393243
title: Szafranskia beskidensis, phylogenetic dataset

description: Alignment.
DOI: 10.17909/npbb-0x08
title: F200W

description: NIRCam image F200W
DOI: 10.5281/zenodo.10641395
title: Occurrence data on PCNs provided to EFSA

description: The file contains the raw occurrence dataset on PCNs in food and feed as extracted from EFSA DWH on 25th October 2022 and presented in the EFSA scientific opinion on the risks for animal and human health related to the presence of polychlorinated naphthalenes (PCNs) in feed and food. This dataset is compliant with EFSA SSD2 data model and contains two additional columns documenting issues identified in the cleaning process (column: issue) and the outcome of the action taken (column: outcome) to address the issue (e.g., delete record or update values in specific fields). The link to the catalogues of controlled terminologies for the updated textual description of fields values can be found under "Related works, supplemented by”.
description: EU; eng; xlsx; FEEDCO@efsa.europa.eu
DOI: 10.5281/zenodo.10641396
title: Occurrence data on PCNs provided to EFSA

description: The file contains the raw occurrence dataset on PCNs in food and feed as extracted from EFSA DWH on 25th October 2022 and presented in the EFSA scientific opinion on the risks for animal and human health related to the presence of polychlorinated naphthalenes (PCNs) in feed and food. This dataset is compliant with EFSA SSD2 data model and contains two additional columns documenting issues identified in the cleaning process (column: issue) and the outcome of the action taken (column: outcome) to address the issue (e.g., delete record or update values in specific fields). The link to the catalogues of controlled terminologies for the updated textual description of fields values can be found under "Related works, supplemented by”.
description: EU; eng; xlsx; FEEDCO@efsa.europa.eu
DOI: 10.6084/m9.figshare.25393564
title: Models

description: Data repository for publication:<b>Unpunctual in diversity: The effect of stand species richness on spring phenology of deciduous tree stands varies among species and years</b>by T.Heinecke, P.DeFrenne, K.Verheyen, I.Nijs, E.Matthysen and M.Campioli
DOI: 10.6084/m9.figshare.25393564.v1
title: Models

description: Data repository for publication:<b>Unpunctual in diversity: The effect of stand species richness on spring phenology of deciduous tree stands varies among species and years</b>by T.Heinecke, P.DeFrenne, K.Verheyen, I.Nijs, E.Matthysen and M.Campioli
DOI: 10.6084/m9.figshare.25393621
title: TPS file of landmark and semilandmarks from teleost fish scales.

description: We aimed to apply two methods of geometric morphometry on a dataset of scales from 5 different teleost species: <i>Danio rerio</i>, <i>Dicentrarchus labrax</i>, <i>Mullus surmuletus</i>, <i>Sardina pilchardus</i>, and <i>Sparus aurata</i>. 232 scales were analyzed. Danrer = Danio rerio; Diclab = Dicentrarchus labrax, Mulsur = Mullus surmuletusSarpil = Sardina pilchardiusm Spaaur = Sparus aurata.
DOI: 10.6084/m9.figshare.24182559.v3
title: Code, data and distribution layers :: peer review Version

description: The data and code used in Species Distribution Modelling, the coefficient of correlation of climatic predictors, the cross-validation data splits, the spatial autocorrelation estimates per species, as well as the distribution layers (at a 0.05º resolution) per species and climate scenario.