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GLOBGM_CMIP6: A Global Hyper-Resolution Groundwater Dataset for Assessing Historical and Future Groundwater Dynamics Under Climate and Socioeconomic Change - [quality_assurance]
No full textThis data package forms part of the GLOBGM_CMIP6 dataset which was simulated using GLOBGM, a global groundwater model. GLOBGM was used to
estimate global water table depth and groundwater heads at a spatial resolution of 30 arc-seconds (~1 km). The model was forced with outputs
from the PCR-GLOBWB model, obtained through the HYPFLOWSCI6 project. We provide long-term average, annual, and monthly estimates of water
table depth and groundwater heads at the global scale for a historical reference simulation following the ISIMIP3a protocol. This protocol
is designed for model evaluation and impact attribution. Additionally, we provide outputs following the ISIMIP3b protocol, which focuses on
impact attribution and climate change impact assessment. These outputs cover the historical baseline period (1960–2014) and future projections
(2015–2100) under three SSP-RCP scenarios: SSP1-2.6, SSP3-7.0, and SSP5-8.5. The data include simulations from five Global Climate Models (GCMs):
GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, and UKESM1-0-LL.
The date here pertains to quality assurance. For a comprehensive overview of the entire dataset and where to access
the data please see: https://vanjaarsveldbarry.github.io/globgm_cmip6
D2.6 European landscape scenicness dataset
No full textThe produced European landscape scenicness datasets are predictions by the machine learning model (Extreme Gradient Boosting classifier) trained on the ScenicOrNot data from GB. Two types of classification results are delivered: binary (0: unscenic to scenic, 1: highly scenic) and ternary (0: unscenic to medium, 1: scenic, 2: highly scenic).
The used features are the four landscape wilderness indicators from D2.5 (naturalness, ruggedness, remoteness, and human impact) and land cover categories, elevation, global horizontal irradiance, population density, proximity to waterbodies, and slope aspect angle
Finding Suitable Grounds research data for IJsselmeer cores
No full textThis dataset considers research data generated for IJsselmeer cores in the Finding Suitable Grounds project. The data is produced as part of twinned PhD research at the Utrecht University (Familetto) and University of Groningen (Smuk). The project studies the setting and speed of adoption of crop cultivation in the lowlands of the Netherlands, since the onset of the Neolithic (6000-4000 BC).
Metadata is provided for this parent folder, and the following subfolders:
\01_CorePhotos_OriginalLogging
\02_Chronology
\03_LOI_XRF
\04_ThinsectionScans
\05_ThinsectionMicrophotos
Contributors to respective subfolders are copied over as contributors to this parent folder.
Contributors are: Elena Familetto (PhD candidate; UU), Kim Cohen (co-PI; UU), Hans Huisman (PI; RUG, RCE)
Nico Willemse (RAAP archaeological consultancy), Seger Van den Brenk (Periplus surveying)
Ana Smuk (PhD candidate; RUG), Mans Schepers (RUG), Kim De Wit (UU), Wim Hoek (UU), Bertil van Os (RCE), B. Smit (RCE).
The Finding Suitable Grounds project, funded by the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO, Dutch Research Council, Grant Number 406.20.HW.005. Core collection took place prior to the start of the Finding Suitable Grounds project, and was funded by RCE. Original core descriptions and core photos fill folder 01_. These are the same materials as published on in Van den Brenk (2025). Materials generated from the Finding Suitable Grounds project are found in folders 02_ and above.
Folders 01-05 are shared as V1 of the dataset, at the submission of the first research paper (also PhD thesis chapter) in September 2025: Familetto et al..
With completion of foreseen further chapters and paper and PhD thesis submission, further folders and data set expansion to V2 is expected.
RUG=Rijksuniversiteit Groningen, UU= Utrecht University, RCE = Rijksdienst Cultureel Erfgoed, national cultural heritage agency, Amersfoort
Data supplement to "Coupling antigorite deformation and dehydration in high-pressure experiments"
No full textWe performed hydrostatic and co-axial deformation experiments at high-pressure and high-temperature conditions in a Griggs apparatus at the Earth Science Institute in Orléans (France). In this study we aim to constrain the effect of stress on serpentine dehydration reaction and to further refine the mechanism for dehydration.
We performed experiments at 1.5 GPa, and 620 °C to 670 °C, respectively. Experiments were performed at both hydrostatic and differentially stressed conditions.
The starting materials used in this study were a foliated serpentinite from Zermatt (CH) and a massiv serpentinite from Linnajavri (NOR).
In this repository we provide thinsection scans of the starting materials, log files (load, stress, strain) of the experimental runs and back-scattered electron (BSE) maps of all run products.
The data are organised in two folders, with subfolders for individual experimental runs. Detailed information about the data files as well as information on how the data is processed is given in the explanatory file READme.txt. Contact person: Lisa Eberhard - [email protected]
Data package from meandering river experiments with Eurotank facility
No full textThis datapackage supplements the papers mentioned below on experiments with self-formed braided rivers and meandering rivers, for which vegetation, silica powder or crushed nutshell were used to form floodplains. All experiments were conducted in the Eurotank facility: a flume of 11 by 6 m, so most experiments have river plains of about 10 m long and 3 m wide. This package accommodates files contain gridded digital surface elevation data (DSMs) made by photogrammetry and, for some experiments, overhead images.
The data is provided in 3 subfolders. Detailed information about the files in these subfolders as well as information on how the data is processed is given in the explanatory file Data_description_meandering_experiments_yoda.txt. Contact person is Maarten Kleinhans - [email protected] - https://www.uu.nl/medewerkers/MGKleinhan
5G Network Simulation Dataset - Utrecht
No full textThis dataset contains simulation results for a 5G network in Utrecht, used in the paper *Network-Scale Impact of Vegetation Loss on Coverage and Exposure for 5G Networks*. It includes input configurations and output files detailing base station activity, exposure levels, and user traffic
Faulted samples from the Groningen gas field, the Netherlands
No full textGas production from the Groningen gas field in the northeast of the Netherlands caused compaction and induced seismicity on pre-existing faults within the Rotliegend reservoir. Knowledge on the fault zone composition diagenetic features, and internal structure is required to provide constraints for friction experiments, microphysical models on fault frictional behaviour, and models that simulate fault reactivation, nucleation and seismic slip in the Groningen field. The dataset Faulted samples from the Groningen gas field, the Netherlands contains (micro)structural data, obtained from selected wells in the Groningen gas field. Wells were selected based on proximity to major fault structures previously interpreted in the Groningen field (NAM, 2020; https://public.yoda.uu.nl/geo/UU01/1QH0MW.html) and based on the presence of deformation features visible in available core photographs (NAM, 2022; https://public.yoda.uu.nl/geo/UU01/6JHXY9.html). Microstructural data comprise full thin section digital scans (plane polarized and cross polarized light) and scanning electron microscopy (SEM) images including secondary electron (SE), backscatter (BSE), cathodoluminescence (CL) and electron dispersive X-ray (EDX) maps. The data accompanies the paper entitled: Interaction between diagenesis and faulting in deep buried reservoirs: inferences from the Groningen gas field (Arts et al., submitted)
Post-Polymerisation Modification of Polyolefins through C-H bond Activation by Frustrated Radical Pairs
No full textThis paper describes the work on C-H bond activation of polyolefins using frustrated radical pairs and the subsequent oxidation to obtain a carbonyl functionalized polyolefin backbone.
We have tested 2 different polyolefin samples during this work, PE and PP and demonstrate to functionalise both of these materials using LiHMDS and TEMPO BF4 as the FRP and mCPBA as the oxidant in the second step.
We observe that the carbonyls are installed in-chain and on the preterminal position.
Lastly we do not observe any backbone cleavage or crosslinking and demonstrate that the thermal properties of the polymers are not affected by the functionalisation
Python-JAX-based fast Stokesian dynamics
No full textData package accompanying the publication with the above title in SciPost. This package provides all the relevant information, scripts, and source codes for bench-marking the presented software (jfsd). The accompanying publication provides the full details. In brief, this package contains the data required to reproduce the graphs in the paper, as well as the numerical solver source code and analysis scripts required to process the raw simulation output. In the main directory there is a Readme.txt file that describes the content and use of the elements contained therein, e.g., how to run various script to obtain the raw data. These are Python codes, and binary files containing data in a 'numpy array' format
The data package for: "An N-Heterocyclic Germylene with a Versatile Metal-Binding Pocket: Insights into Heterodinuclear Bonding and Reactivity".
No full textThe files contain the spectroscopical and computational data within this publication
##Methodological information:
NMR-Spectroscopical data was collected on an Agilent MRF 400 equipped with a OneNMR probe and Optima Tune system, 400 MHz Jeol EZCL G system with an HFX probe or a Varian VNMR-S-400 equipped with an AutoX probe. IR-Spectroscopical data was collected on a PerkinElmer SpectrumTwo Infrared Spectrophotometer equipped with an ATR-probe. Computational data was collected using the Gaussian 16 rev. C.02 software. All files are unprocessed and can be read into notepad or specific computational software (e.g. ChemCraft)
## Data specific information:
NMR files are .mnova files that can be opened using the MestreNova software. Files relating to the computations are .inp/.log/.out that can be opened using Notepad or any other text editing software and the calculated structures can be visualised using computational software such as ChemCraft, Avogadro or Gaussview
## Licenses or restrictions placed on the data:
All data is provided under a CC-BY-NC licens