cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/468d6fd5-e14b-4eb1-be9f-76f56c4a2d18
title: Input data and settings for running a Community Water Model (CWatM) of the Ebro River basin, Spain, 1990-2012

description: This dataset contains the input data and settings needed to run a Community Water Model (CWatM) of the Ebro River basin in Spain. The input data include: an elevation model of the catchment, flow direction map, river routing, lakes and reservoirs, soils, groundwater, land cover, crop coefficients population and GDP, and water demands for irrigation, livestock, industry, and domestic sectors.

CWatM is a distributed hydrological model simulating the water cycle at global and local levels maintained by IIASA BNR Water Security group. The model was used to assess water supply and demand, and environmental needs, including water management and human influence within the water cycle in the Ebro River basin.

description: The input data came from a variety of sources. Elevation and land cover data and flow direction maps came from Copernicus. The river routing data came from European Digital Elevation Model (v1.1). Lakes and reservoir data were obtained from the HydroLakes database. Soil hydraulic properties were from Dai et al., (2019). Groundwater data were from Global Hydrogeology MaPS (GLHYMPS). Crop co-efficients were from MIRCA2000. Data relating to water demand were from a range of published literature (e.g., KleinGoldewijk et al., 2017, Wriedt et al., 2009, Steinfeld et al., 2006, Gleick et al, 2009, Pastor et al., 2014). The specific details and sources of the input data are explained in more detail in the Readme.docx file included in this dataset.

All the datasets were projected and cropped for the area of study and resampled to a 1x1 km2 grid prior to running the model.

This CWatM model of the Ebro basin was developed by Dr David Haro Monteagudo from the University of Aberdeen in collaboration with Dr Andrea Momblanch Benavent from Cranfield University and the technical assistance of Dr Mikhail Smilovic and Dr Peter Burek from IIASA (Austria).
DOI: 10.5281/zenodo.16902731
title: Dataset of 160 students (100 Israelis and 60 Palestinians) of whom 100 played the PeaceMaker game in Jan2025

description: The study followed a pre-test post-test control group experimental design. The experimental group consisted of 100 participants, while the control group consisted of 60 participants. All students completed a pre-test on January 23rd, 2025. Experimental group students played the PeaceMaker game for 30 minutes while control group students did not. All students completed a post-test a week later, on January 30th, 2025. The data collection was conducted during a crucial time of the Israeli-Palestinian conflict, specifically a week of Israeli hostage-Palestinian prisoners releases, approximately 15 months after the ongoing Israel-Hamas war of Oct. 7th, 2023.

A total of 160 students (100 Israelis and 60 Palestinians) participated in the study. A cohort of Israeli participants (n=61) and a cohort of Palestinian participants (n=39) who registered for two different classes at two different universities in Israel were assigned in the experimental condition and played the PeaceMaker game during a single meeting of these classes, on January 23rd 2025, after completing a pre-test. Another cohort of Israeli participants (n=39) and another cohort of Palestinian participants (n=21) who registered for the same two classes at the same two universities in Israel were assigned to the control group condition and completed a pre-test on January 23rd, 2025. All students completed a post-test a week later, on January 30th, 2025.

Participants’ hope for peace was measured before and after the game, by capturing three interdependent but discrete components of hope: wish for peace, expectations that peace will materialize, and affective hopefulness (based on Leshem, 2017)
DOI: 10.57756/e15gvm
title: 3D model of a Giant Marine Turtle (NHMW-GEO-1977/1902/0001)

description: <p>3D scan of one of the only known complete fossilized skeletons of a giant marine turtle (<em>Archelon ischyros</em>), the largest marine turtle that ever lived and could reach a length of nearly 5 meters. These giants inhabited and cavorted around in the shallow tropical sea that covered North America some 70 million years ago. As this fossil is (as of 2025) mounted in Hall 10 of the NHMW, this is the only opportunity to see the underside of this fossil.</p>
DOI: 10.5285/6209742a-bfd6-4fbc-9b40-29d7d75d57b4
title: Simulations of Emerald Ash Borer (EAB) spread in Great Britain with optimised surveillance

description: This dataset contains a model, input data and outputs of the Emerald Ash Borer (EAB; Agrilus planipennis) lifecycle and spread across Great Britain. Nine different scenarios are considered related to how certain we are that EAB will arrive through known pathways related to wood imports (70%, 50%, 30%) and the probability that EAB would escape at port rather than at the onwards depots (25%, 50%, 75%).  

The model outputs can be used to predict the best places to locate surveillance technologies (i.e., girdled trees or traps) and included in this dataset are optimised trap locations for 27 scenarios (three trapping types for each of the nine different scenarios). 
description: The model requires the entry point to be initialized. We developed maps to identify the most likely first incursion point at locations across Great Britain on a 1km x 1km grid. These maps were informed by data from the forestry commission on likely entry points, and data on firewood use. When creating these maps, we considered nine scenarios related to how certain we are that EAB will arrive through known pathways related to wood imports (70%, 50%, 30%) and the probability that EAB would escape at port rather than at the onwards depots (25%, 50%, 75%).  For each scenario we sampled 10000 realizations for likely entry points.  These form the inputs to our model.

The model is set up to run for annual time steps for 8 years. For each simulated year the larval density and tree health is recorded in infested cells and reported in output files. The model is currently set up to do this for up to 10000 realizations of entry point. The data in the output file can then be used to optimize surveillance. We did this using simulated annealing for three trapping types (Girdled, sticky straps and under bark sampling) in the nine different scenarios. 

The model code was developed in Visual Studio, but plain text files have been provided so that the code can be compiled and run outside of Visual Studio. The model code was checked for errors and the outputs were validated, as far as possible, against spread characteristics from the US.
DOI: 10.5285/e7fdf789-e663-4422-92c2-ea8019b3cc26
title: Biologging data of captive red deer, Prague, Czechia, June-November 2023

description: This dataset contains biologging data of captive red deer Cervus elaphus, to study sleep behaviour. This includes acceleration (m/s2), magnetometer (gauss), and temperature (degrees Celsius) measurements, collected using collar-mounted accelerometer and magnetometer recorders at 20Hz.

This data was collected from 18 adult individuals; 13 male, 5 female, in 2023 over three deployments. Deployment 1 (males) 13/06/23 – 1/8/23; deployment 2 (males) 04/09/23 – 08/11/23; deployment 3 (females) 13/11/23 – 21/11/23. Deer were housed at the VUZV facility, Uhrineves, Prague, Czech Republic.

This dataset was funded by NERC, as part of project “NE/X010368/1: Sleep in the landscape of fear” and was measured to aid in the creation of a classification model to detect sleep in red deer from collar accelerometers, as well as to test arousal thresholds in sleeping deer.

description: Biologgers were calibrated immediately prior to deployment. Deer were manipulated in a standard farm handling crush and were not immobilised for deployment. Biologgers were recovered in the same manner.

Data was downloaded directly from the Daily Diary logger units and stored in raw format. Data has been transformed into .txt format for reusability across different software. No other processing has taken place, other than screening for device failures, which have been removed from the dataset.
DOI: 10.15468/dl.9nqchj
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-73.36881 -3.85912,-73.36509 -3.86656,-73.35998 -3.86928,-73.3522 -3.86549,-73.33484 -3.85961,-73.33133 -3.85648,-73.31805 -3.85534,-73.31795 -3.84529,-73.32165 -3.84149,-73.32298 -3.83808,-73.32071 -3.83675,-73.32108 -3.83324,-73.32526 -3.82869,-73.32953 -3.82897,-73.32459 -3.83447,-73.32678 -3.83618,-73.32545 -3.8432,-73.32251 -3.84984,-73.32526 -3.85031,-73.32858 -3.84955,-73.3331 -3.84991,-73.34196 -3.84748,-73.36034 -3.84473,-73.36667 -3.85582,-73.36881 -3.85912))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 26 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002016-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5285/f712c52f-1ce9-4603-bc33-685221a14f50
title: Policy and community interviews on trypanosomiasis in Hurungwe District, Zimbabwe (2012-2013)

description: This resource contains anonymised interviews with community members in Chundu Ward, Hurungwe District, Zimbabwe, conducted to further our understanding of how the local community interacts with tsetse. Semi-structured interviews were conducted with key informants in 2012 to 2013 to investigate livelihood strategies including hunting, livestock keeping and cultivation, and how they influenced the risk of contracting trypanosomiasis. Human African trypanosomiasis (HAT) occurs sporadically within the Zambezi Valley in Zimbabwe and is transmitted by the tsetse fly (Glossina morsitans morsitans and Glossina pallidipes). African animal trypanosomiasis (AAT) is more prevalent and places significant constraints on livestock keeping. Approaches taken by local people to control or manage the disease were also investigated during the interviews.

This research was part of a wider research project, the Dynamic Drivers of Disease in Africa Consortium (DDDAC) and these interviews contributed to this consortium. 

The research was funded by NERC project no NE/J000701/1 with support from the Ecosystem Services for Poverty Alleviation Programme (ESPA).
description: After initial community meetings to identify tsetse affected areas, candidates for key informant interviews were selected on the basis of their knowledge of the subject. The interviewees included indigenous people, mainly Korekore, and migrants from other parts of the country who are settled in the study area. Initial contacts were made with these candidates in 2012. During these meetings informed consent was sought for interviews and the date for actual interviewing was agreed. Semi-structured interviews were conducted in person between 2012 and 2013 and recorded with prior consent. The interviews were conducted by experienced researchers from the University of Zimbabwe, assisted by a research assistant. The audio recordings were processed into text transcripts in Microsoft Word and stored securely at the University of Zimbabwe. To meet the requirements of the Environmental Information Data Centre the Microsoft Word document was anonymised and converted into Rich Text Format (rtf).
DOI: 10.15468/dl.pxf8xn
title: Occurrence Download

description: A dataset containing 792 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "TaxonKey is Phylloscopus laetus",
 "Year 2024-2025"
 ]
}

 The dataset includes 792 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002018-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4121/f2fb5beb-2e36-45ef-9054-c7bd8712720c
title: Supplementary Material for Paper: Characterizing nature-based living labs from their seeds in the past

description: The dataset consists of the following information:(1) The paper "Characterizing nature-based living labs from their seeds in the past" distinguishes nine characteristics in nature-based living labs, the first five of which are always present, while the last four are sometimes evident. The table in this dataset presents seven nature-based living labs (from Dataset B in the paper) and describes how each of these living labs exhibits these characteristics. <br>(2) The second part of the database comprises figures derived from VOSviewer output. The data set consists of three major figures.Figure 1 consists of the bibliometric Coupling of living lab literature according to countriesFigure 2 consists of the co-occurrence of keywords in the living lab literatureFigure 3 consists of five sub-figures illustrating the relationship between living labs keywords
DOI: 10.4121/f2fb5beb-2e36-45ef-9054-c7bd8712720c.v1
title: Supplementary Material for Paper: Characterizing nature-based living labs from their seeds in the past

description: The dataset consists of the following information:(1) The paper "Characterizing nature-based living labs from their seeds in the past" distinguishes nine characteristics in nature-based living labs, the first five of which are always present, while the last four are sometimes evident. The table in this dataset presents seven nature-based living labs (from Dataset B in the paper) and describes how each of these living labs exhibits these characteristics. <br>(2) The second part of the database comprises figures derived from VOSviewer output. The data set consists of three major figures.Figure 1 consists of the bibliometric Coupling of living lab literature according to countriesFigure 2 consists of the co-occurrence of keywords in the living lab literatureFigure 3 consists of five sub-figures illustrating the relationship between living labs keywords
DOI: 10.15468/dl.3q4p63
title: Occurrence Download

description: A dataset containing 195511 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-16.09443 46.60044,22.39013 42.05092,22.39013 62.97162,-7.92348 62.97162,-16.09443 46.60044))",
 "HasGeospatialIssue is false",
 "TaxonKey is Scomber scombrus"
 ]
}

 The dataset includes 195511 records from 164 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001994-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7mje2u
title: Occurrence Download

description: A dataset containing 15164 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Paratrechina longicornis"
 ]
}

 The dataset includes 15164 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002019-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/v3bjktmkd4
title: Raw Data and Survey Videos for the Three-Dimensional Habitat Selection Analysis of François' Langurs

description: This repository contains a subset of point cloud files from our study to facilitate the verification of variable extraction, along with detailed records of François' langurs obtained via supplementary UAV surveys. The uploaded code demonstrates the methodology used to extract three-dimensional habitat structural variables from these raw point clouds. Furthermore, this link provides the complete raw dataset used for statistical analysis, derived from all presence and control quadrats.
DOI: 10.17632/v3bjktmkd4.1
title: Raw Data and Survey Videos for the Three-Dimensional Habitat Selection Analysis of François' Langurs

description: This repository contains a subset of point cloud files from our study to facilitate the verification of variable extraction, along with detailed records of François' langurs obtained via supplementary UAV surveys. The uploaded code demonstrates the methodology used to extract three-dimensional habitat structural variables from these raw point clouds. Furthermore, this link provides the complete raw dataset used for statistical analysis, derived from all presence and control quadrats.
DOI: 10.5281/zenodo.17435614
title: Experimental dataset: Experimental Study on the Mooring System Dynamics of Container Ships: Coupling Effects of Wave Conditions, Berth Locations, and Mooring Line Types

description: This dataset contains the experimental data supporting the research article " Experimental Study on the Mooring System Dynamics of Container Ships: Coupling Effects of Wave Conditions, Berth Locations, and Mooring Line Types" (published in Ocean Engineering). The physical model tests were conducted in the large-scale wave basin at Hohai University, focusing on the mooring dynamics of a 50,000 DWT container ship model under various wave and mooring configurations.

The dataset includes synchronized time-series measurements of:





Six-degree-of-freedom (6-DOF) ship motions: Sampled at 50 Hz. The translational motions (surge, sway, heave) are in meters (m), and the rotational motions (roll, pitch, yaw) are in degrees (°).




Mooring line forces: Sampled at 37 Hz, with values in Newtons (N).
DOI: 10.17632/hmdpvh8vvs
title: DNA-Inspired Time Series Encoding: A Glimpse Into The Next 4-Hour Timeframe

description: In this work, we introduce a bio‑inspired encoding framework for forecasting the direction of financial time series. Motivated by the limitations of linear models and the opacity of many deep learning approaches, we draw an analogy to genetics: observable micro‑patterns are encoded into symbolic "Financial DNA" sequences. These sequences are then analyzed using a probabilistic state‑transition mechanism to estimate the likelihood of subsequent market directions. We evaluate the approach on Bitcoin hourly OHLCV data with a rolling backtest. Among the horizons considered, modeling transitions from current Financial DNA patterns to the 4‑hour‑ahead price direction yields the strongest results, achieving a win ratio of 0.729. The findings suggest that compact, interpretable symbolic representations can capture salient, recurring structures in noisy, non‑stationary markets and support effective directional forecasts.
DOI: 10.5281/zenodo.17435613
title: Experimental dataset: Experimental Study on the Mooring System Dynamics of Container Ships: Coupling Effects of Wave Conditions, Berth Locations, and Mooring Line Types

description: This dataset contains the experimental data supporting the research article " Experimental Study on the Mooring System Dynamics of Container Ships: Coupling Effects of Wave Conditions, Berth Locations, and Mooring Line Types" (published in Ocean Engineering). The physical model tests were conducted in the large-scale wave basin at Hohai University, focusing on the mooring dynamics of a 50,000 DWT container ship model under various wave and mooring configurations.

The dataset includes synchronized time-series measurements of:





Six-degree-of-freedom (6-DOF) ship motions: Sampled at 50 Hz. The translational motions (surge, sway, heave) are in meters (m), and the rotational motions (roll, pitch, yaw) are in degrees (°).




Mooring line forces: Sampled at 37 Hz, with values in Newtons (N).
DOI: 10.17632/hmdpvh8vvs.1
title: DNA-Inspired Time Series Encoding: A Glimpse Into The Next 4-Hour Timeframe

description: In this work, we introduce a bio‑inspired encoding framework for forecasting the direction of financial time series. Motivated by the limitations of linear models and the opacity of many deep learning approaches, we draw an analogy to genetics: observable micro‑patterns are encoded into symbolic "Financial DNA" sequences. These sequences are then analyzed using a probabilistic state‑transition mechanism to estimate the likelihood of subsequent market directions. We evaluate the approach on Bitcoin hourly OHLCV data with a rolling backtest. Among the horizons considered, modeling transitions from current Financial DNA patterns to the 4‑hour‑ahead price direction yields the strongest results, achieving a win ratio of 0.729. The findings suggest that compact, interpretable symbolic representations can capture salient, recurring structures in noisy, non‑stationary markets and support effective directional forecasts.
DOI: 10.17632/h5fwm9nc2c.4
title: The Environmental Administrative Penalties and Firm Digital Transformation: A Reexamination of Porter Hypothesis

description: This is the STATA data set and STATA code for empirical part of The Environmental Administrative Penalties and Firm Digital Transformation: A Reexamination of Porter Hypothesis
DOI: 10.15468/dl.5j7uqy
title: Occurrence Download

description: A dataset containing 3398 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Salamandra lanzai"
 ]
}

 The dataset includes 3398 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002022-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sqjzvm
title: Occurrence Download

description: A dataset containing 25478 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Meetnetten.be - Bat winter roosts counts (totals per site) Flanders, Belgium"
 ]
}

 The dataset includes 25478 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002020-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k8enr2
title: Occurrence Download

description: A dataset containing 6082 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Salamandra infraimmaculata"
 ]
}

 The dataset includes 6082 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002023-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5286/isis.e.rb2520260-1
title: Solution Structure and Aggregation of Branched Soil-Release Polymers

description: Soil release polymers are important components of modern laundry formulations. Their role is to adsorb on fabric surfaces and present a surface which inhibits persistent binding of soils. We have successfully characterised their adsorption on model PET surfaces but to complete the picture and fully understand the relationship between SRP structure and surface behaviour, it is also necessary to consider (i) aggregation behaviour in solution and (ii) interaction with surfactants that are necessarily also present in detergent formulations. We seek beamtime for SANS experiments to explore this behaviour of SRP aggregation in a way that goes far beyond what is possible with preliminary DLS experiments. SANS offers a unique opportunity not only to resolve the structure of the aggregations unambiguously, but also to explore a greater range of concentration, and (with contrast variation) to identify and isolate the contribution to aggregation behaviour induced by surfactants. These experiments are essential to validate the computational models that are the overall goal of the wider project.