cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/vdz5j9nfmk.1
title: Body movement as a digital biomarker in chronic pain rehabilitation - Virtual Reality Movement data

description: In a community clinic setting patients with chronic pain used a novel digital therapeutic intervention using virtual reality. This data set contains movement data which were collected using the sensors in the Oculus Quest 2 VR headset (Meta). The participants picked (grabbed and released) objects in the virtual reality environment.
DOI: 10.17632/mrhscrm53k
title: Dataset Scopus of Green Business Research in Indonesia

description: Dataset Scopus of Green Business Research in Indonesia
DOI: 10.16904/envidat.474
title: AFF agricultural land change scenarios in Europe 2015-2050

description: This dataset contains the spatial layers showing future land change pathways in Europe between 2015 and 2050, as simulated by the CLUMondo model and according to the Agricultural Futures Framework (AFF) scenarios.
Three scenarios are included:
- Land for Food and Land for Nature (LFLN)
- Land as Culture (LaC) 
- Land for Society (LfS)
description: Resource Title: AFF_agricultural land_change scenarios_Europe_2015_2050.zip
 Size: 3851250 bytes
 Format: application/x-zip-compressed
 URL: https://www.envidat.ch/dataset/15ae8f00-310e-4cee-95ed-d00f0aa25dbe/resource/a8d3393e-178f-43a7-9538-1437b0afd8b3/download/aff_agricultural-land_change-scenarios_europe-2015_2050.zip
 Description: This dataset contains the spatial layers showing future land change pathways in Europe between 2015 and 2050, as simulated by the CLUMondo model according to the Agricultural Futures Framework (AFF) scenarios.
description: Resource Title: ReadMe.pdf
 Size: 87640 bytes
 Format: application/pdf
 URL: https://www.envidat.ch/dataset/15ae8f00-310e-4cee-95ed-d00f0aa25dbe/resource/573e45b3-27b1-4139-b61b-06c3adc8871e/download/readme.pdf
 Description:
DOI: 10.17632/mrhscrm53k.1
title: Dataset Scopus of Green Business Research in Indonesia

description: Dataset Scopus of Green Business Research in Indonesia
DOI: 10.16904/envidat.443
title: Soil organic carbon drivers in the Swiss forest soil inventory

description: Data include SOC stocks at 556 old-growth Swiss forest sites from the Swiss forest soil inventory including environmental variables (elevation, mean annual precipitation, mean annual temperature, net primary production from MODIS, soil properties, forest types, measured SOC stocks (organic layers and mineral soil up to 100 cm depth) and stocks simulated by the Yasso20-model.
description: Resource Title: Data 556 Swiss Forest Soil sites
 Size: 138928 bytes
 Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
 URL: https://www.envidat.ch/dataset/a8e75c2f-bce8-4311-8867-4b48a6b4f2ff/resource/5c37d375-8b0d-4b50-b6a0-826ae253ccd6/download/data_envidat_swisssoil.xlsx
 Description:
DOI: 10.17632/gxnwxy53r9
title: Exploring Consumer Responses to SME Affiliate Marketing on TikTok: A Topic Modelling Approach Using LDA

description: This dataset contains a collection of consumer comments gathered from TikTok videos promoting spicy macaroni products affiliated with Micro, Small, and Medium Enterprises (MSMEs). The data were collected to analyze consumer communication patterns within the context of affiliate marketing on the TikTok platform. Comments include informal language, slang, abbreviations, and diverse expressions typical of social media discourse. The dataset was processed and subjected to Latent Dirichlet Allocation (LDA) topic modelling to identify key themes related to product taste sensations, consumption motivations, pricing factors, and perceived product value. This dataset supports research into digital marketing strategies, consumer behavior on social media, and the application of natural language processing techniques for informal text analysis.
DOI: 10.16904/envidat.450
title: Short-term Drainage Density Dynamics Dataset for the Erlenbach Catchment

description: The dataset contains time series of water levels, precipitation measured in the two sub-catchments of the Erlenbach catchment and its vicinity during summer and autumn 2021, as well as flowing drainage network lengths calculated for these areas using the CEASE method developed by the authors. Detailed description of the dataset is provided in the documentation.
description: Resource Title: short-term_drainage_density_dynamics_dataset.csv
 Size: 22884800 bytes
 Format: application/vnd.ms-excel
 URL: https://www.envidat.ch/dataset/509baa5e-b955-4bb9-a928-80fbccc0f610/resource/b0b19958-af5e-49bf-8ab1-b10191d7d950/download/short-term_drainage_density_dynamics_dataset.csv
 Description:
description: Resource Title: short-term_drainage_density_dynamics_dataset_documentation.docx
 Size: 1135026 bytes
 Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
 URL: https://www.envidat.ch/dataset/509baa5e-b955-4bb9-a928-80fbccc0f610/resource/a90d31fa-4d8e-4bf1-a650-3c0f8ce12ae4/download/short-term_drainage_density_dynamics_dataset_documentation.docx
 Description:
description: Resource Title: short-term_drainage_density_dynamics_dataset_documentation.pdf
 Size: 3718100 bytes
 Format: application/pdf
 URL: https://www.envidat.ch/dataset/509baa5e-b955-4bb9-a928-80fbccc0f610/resource/37aaedcc-8217-4229-9bf3-49fe7e06d925/download/short-term_drainage_density_dynamics_dataset_documentation.pdf
 Description:
DOI: 10.17632/gxnwxy53r9.1
title: Exploring Consumer Responses to SME Affiliate Marketing on TikTok: A Topic Modelling Approach Using LDA

description: This dataset contains a collection of consumer comments gathered from TikTok videos promoting spicy macaroni products affiliated with Micro, Small, and Medium Enterprises (MSMEs). The data were collected to analyze consumer communication patterns within the context of affiliate marketing on the TikTok platform. Comments include informal language, slang, abbreviations, and diverse expressions typical of social media discourse. The dataset was processed and subjected to Latent Dirichlet Allocation (LDA) topic modelling to identify key themes related to product taste sensations, consumption motivations, pricing factors, and perceived product value. This dataset supports research into digital marketing strategies, consumer behavior on social media, and the application of natural language processing techniques for informal text analysis.
DOI: 10.16904/envidat.124
title: High resolution monthly precipitation and temperature timeseries for the period 2006-2100

description: Predicting future climatic conditions at high spatial resolution is essential for many applications in science. Here we present data for monthly time series of precipitation and minimum and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation sums at ~5km spatial resolution globally for the years 1850-2100. We validated the performance of the downscaling algorithm by comparing model output with observed climates for the years 1950-2069. 
CHELSA_cmip5_ts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.
description: Resource Title: Data Access
 Size: 3298534883328 bytes
 Format: No Info
 URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav1%2F&prefix=chelsa_cmip5_ts%2F
 Description:
DOI: 10.16904/envidat.332
title: CHELSA-BIOCLIM+ A novel set of global climate-related predictors at kilometre-resolution

description: A multitude of physical and biological processes on which ecosystems and human societies depend are governed by climatic conditions. Understanding how these processes are altered by climate change is central to mitigation efforts. Based on mechanistically downscaled climate data, we developed a set of climate-related variables at yet unprecedented spatiotemporal detail as a basis for environmental and ecological analyses. We created gridded data for near-surface relative humidity (hurs), cloud area fraction (clt), near-surface wind speed (sfcWind), vapour pressure deficit (vpd), surface downwelling shortwave radiation (rsds), potential evapotranspiration (pet), climate moisture index (cmi), and site water balance (swb), at a monthly temporal and 30 arcsec spatial resolution globally starting 1980 until 2018. At the same spatial resolution, we further estimated climatological normals of frost change frequency (fcf), snow cover days (scd), potential net primary productivity (npp), growing degree days (gdd), and growing season characteristics for the periods 1981-2010, 2011-2040, 2041-2070, and 2071-2100, considering three shared socioeconomic pathways (SSP126, SSP370, SSP585) and five Earth system models. Time-series variables showed high accuracy when validated against observations from meteorological stations. Climatological normals were also highly correlated to observations although some variables showed notable biases, e.g., snow cover days (scd). Together, the data sets presented here allow improving our understanding of patterns and processes that are governed by climate, including the impact of recent and future climate changes on the world’s ecosystems and associated services to societies.
description: Resource Title: CHELSA-BIOCLIM+
 Size: 13194139533312 bytes
 Format: No Info
 URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav2%2F&prefix=%2F
 Description: Global extented set of bioclimatic variables at different temporal (e.g. monthly, annual, long term normals) resolution in Geotiff format.
description: Resource Title: CHELSA-BIOCLIM+ Technical Documentation 
 Size: 423097 bytes
 Format: application/pdf
 URL: https://www.envidat.ch/dataset/21d662b7-9c59-41da-aa82-7d8a879b8db7/resource/aa676d1f-5f7f-479b-af20-26066b0537d1/download/chelsa_file_specification_bioclim_plus.pdf
 Description: Technical documentation document including the variable names, units, scaling, offset, and background.
DOI: 10.16904/envidat.159
title: CHELSAcruts - High resolution temperature and precipitation timeseries for the 20th century and beyond

description: CHELSAcruts is a delta change monthly climate dataset for the years 1901-2016 for mean monthly maximum temperatures, mean monthly minimum temperatures, and monthly precipitation sum. Here we use the delta change method by B-spline interpolation of anomalies (deltas) of the CRU TS 4.01 dataset. Anomalies were interpolated between all CRU TS grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2 (Karger et al. 2017, Scientific Data). This method has the assumption that climate only varies on the scale of the coarser (CRU TS) dataset, and the spatial pattern (from CHELSA) is consistent over time. This is certainly a rather crude assumption, and for time periods for which more accurate data is available CHELSAcruts should be avoided if possible (e.g. use CHELSA V1.2 for 1979-2015). Different to CHELSA V1.2, CHELSAcruts does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages.
CHELSAcruts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.
description: Resource Title: Data Access
 Size: 3298534883328 bytes
 Format: No Info
 URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav1%2F&prefix=chelsa_cruts%2F
 Description: CHELSAcruts is a delta change monthly climate dataset for the years 1901-2016 for mean monthly maximum temperatures, mean monthly minimum temperatures, and monthly precipitation sum.
description: Resource Title: CHELSA Technical Documentation 
 Size: NaN
 Format: application/pdf
 URL: http://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf
 Description: As the CHELSA project is continuously expanded, certain new parameters, time scales etc. are not included anymore in the original publication (Karger et al. 2017). We are therefore provide this document as a guideline of the current climatic parameters available and will expand it as new parameters or time periods will become available. Please refer to the version history for changes made in the document.
DOI: 10.16904/envidat.434
title: Supporting information for case study on the application of spore sampling for the monitoring of macrofungi

description: Resources associated with the manuscript *A case study on the application of spore sampling for the monitoring of macrofungi* ([Schlegel et al. 2024](https://doi.org/10.1111/1755-0998.13941)).
Airborne environmental DNA (eDNA) monitoring of fungi was evaluated on a species-rich grassland site. Extensive fruiting body surveys yielded 29 waxcap and clavarioid species, 19 of which were also detectable in air eDNA. The analysis indicates that spores of locally occurring fruiting bodies were detected, in addition to a large diversity of common fungal species, while rare and threatened species were under-represented in the air.
*Version 1* of the dataset was submitted during the review phase. *Version 2* contains minor changes and clarifications, and is up to date with the [published supplement](https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F1755-0998.13941&file=men13941-sup-0001-AppendixS1.pdf) of the study.
The contents of the ZIP archive:
* analysis scripts in [R-Markdown](https://rmarkdown.rstudio.com) format, including the rendered PDF output with figures and tables (*analysis* directory)
* eDNA sample metadata (*amplicon_meta*) and results of the amplicon clustering (*amplicon_data*) and the source code of the pipeline (*amplicon_pipeline*)
* positions of all fruiting body groups found in the surveys (3838 GPS points) (*surveys*)
* positions of the spore traps, taxonomy of studied grassland fungi and red-list species, and many more resources
Please refer to `README.pdf` inside the archive for a complete description of the file structure and information on how to reproduce the analyses.
description: Resource Title: Data files and analysis scripts (Version 1)
 Size: 29336906 bytes
 Format: application/zip
 URL: https://www.envidat.ch/dataset/5ecb89e0-7abf-42ce-b210-24dcdee781d9/resource/9ac066a9-e65a-4bf9-937e-a43f6aae41e3/download/suppinfo.zip
 Description: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of fungi". Please refer to README.pdf inside the archive for more information.
description: Resource Title: Data files and analysis scripts (Version 2)
 Size: 32072370 bytes
 Format: application/zip
 URL: https://www.envidat.ch/dataset/5ecb89e0-7abf-42ce-b210-24dcdee781d9/resource/d056b217-18c0-4733-b204-602289cf7eee/download/supplementary_data.zip
 Description: This ZIP archive contains the data and source code necessary to reproduce the analyses for the manuscript "A case study on the application of spore sampling for the monitoring of macrofungi". Please refer to README.pdf inside the archive for more information.
DOI: 10.16904/envidat.538
title: CALISHTO campaign dataset for the publication Biological and Dust Aerosols as Sources of Ice-nucleating Particles in the Eastern Mediterranean

description: This repository contains all observational data sets during CALISHTO campaign used for the paper:
Gao, K., Vogel, F., Foskinis, R., Vratolis, S., Gini, M. I., Granakis, K., Billault-Roux, A.-C., Georgakaki, P., Zografou, O., Fetfatzis, P., Berne, A., Papagiannis, A., Eleftheridadis, K., Möhler, O., and Nenes, A.: Biological and dust aerosol as sources of ice nucleating particles in the Eastern Mediterranean: source apportionment, atmospheric processing and parameterization, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-511, 2024.
description: Resource Title: Dataset.zip
 Size: 4156413 bytes
 Format: application/x-zip-compressed
 URL: https://www.envidat.ch/dataset/39f75c08-a270-464c-8ba7-85ec0e772005/resource/b33e0972-068c-4337-a205-d8edd302de9b/download/dataset.zip
 Description: This dataset includes all processed and raw data in the paper titled "Biological and dust aerosol as sources of ice nucleating particles in the Eastern Mediterranean: source apportionment, atmospheric processing and parameterization"
DOI: 10.17632/fdr7znz5dh
title: Data and code associated with: Spectral preferences of mosquitos are altered by odors

description: This dataset is a supplement to the article "Spectral preferences of mosquitos are altered by odors". The article focuses on wind tunnel behavioral bioassay investigations of mosquito spectral preferences, along with supporting photographic and spectrographic measurements. The methods describing the generation of this data are described in the associated article with additional methodological details given in the subfolder "read me.txt" files. The dataset also includes Arduino and python code that was used to generate odor and visual stimuli. See "read me.txt" files for additional details.

Article Abstract:
"Vision underlies many important behaviors in insects generally and in mosquitos specifically. Mosquito vision plays a role in predator avoidance, mate finding, oviposition, locating vertebrate hosts, and vectoring disease. Recent work has shown that when sensitized to CO2, the visual responses of Aedes aegypti are wavelength-dependent, but little is known about how other olfactory stimuli can modulate visual responses. The visual cues associated with flowers, vertebrate hosts, or oviposition sites differs substantially and it is possible that odors might prime the mosquito visual system to respond to these different resources. To investigate the interplay of olfactory and visual cues, we adapted previously used wind tunnel bioassays to use quasi-monochromatic targets (390-740 nm) created with a novel LED synth. We coupled these visual targets with CO2 and the odors representative of vertebrate hosts, floral nectar or oviposition sites and assessed responses via 3D tracking of female mosquitos. When CO2 alone is present, we observe a lower preference for wavelengths in the green portion of the visible spectrum with a gradual increase as wavelengths moved towards the violet and red ends of the spectrum. However, when odors associated both with flowers and oviposition sites were present, we observed significant increases in mosquito preference for green (475-575 nm) stimuli. In contrast when vertebrate host odor was present, we saw increased preference for stimuli across the entire visible spectrum. These odor shifts in the mosquito spectral preferences suggest these preferences are not fixed and shift depending on behavioral context."
DOI: 10.16904/envidat.239
title: Challenging the sustainability of urban beekeeping: evidence from Swiss cities

description: Data on: (1) (Dataset 1) spatial distribution of urban beekeeping (number of hives and number of beekeeping locations) in 14 Swiss cities (Geneva, Lausanne, Biel, Neuchatel, Basel, Zurich, Chur, Luzern, St. Gallen, Winterthur, Bern, Lugano, Bellinzona, Thun) for the period 2012-2018; (2) (Dataset 2) aggregated data to model the sustainability of urban beekeeping.
description: Resource Title: Dataset 1
 Size: 144526 bytes
 Format: application/vnd.ms-excel
 URL: https://www.envidat.ch/dataset/07e84672-abe5-43c2-ae7d-f15d28674db7/resource/67cc3748-cca6-491a-a259-90835d32bde9/download/dataset_1.csv
 Description: Dataset 1: Processed data for urban beekeeping 2012 & 2018
description: Resource Title: Dataset 2
 Size: 20820 bytes
 Format: application/vnd.ms-excel
 URL: https://www.envidat.ch/dataset/07e84672-abe5-43c2-ae7d-f15d28674db7/resource/0dfd2c10-a6f8-4ef0-85f6-0fa1d99dad8e/download/dataset_2.csv
 Description: Dataset 2: Processed data for modelling balance urban greenspace
description: Resource Title: Not used: 
 Size: 1543627 bytes
 Format: application/vnd.ms-excel
 URL: https://www.envidat.ch/dataset/07e84672-abe5-43c2-ae7d-f15d28674db7/resource/19c0b00b-578a-4917-b552-bd86a36b98a6/download/aggreated.data.fig1.csv
 Description: Not used for the analyses and not link to the paper.
description: Resource Title: Dataset 3
 Size: 94990 bytes
 Format: text/csv
 URL: https://www.envidat.ch/dataset/07e84672-abe5-43c2-ae7d-f15d28674db7/resource/29911cdc-420c-4fe5-aa2f-ac5be06a4acf/download/dataset_3.csv
 Description: Dataset on the the number of beehives and apiaries on the years 2012, 2013, 2014, 2015, 2016, 2017, 2018 in several Swiss cities.
DOI: 10.17632/fdr7znz5dh.2
title: Data and code associated with: Spectral preferences of mosquitos are altered by odors

description: This dataset is a supplement to the article "Spectral preferences of mosquitos are altered by odors". The article focuses on wind tunnel behavioral bioassay investigations of mosquito spectral preferences, along with supporting photographic and spectrographic measurements. The methods describing the generation of this data are described in the associated article with additional methodological details given in the subfolder "read me.txt" files. The dataset also includes Arduino and python code that was used to generate odor and visual stimuli. See "read me.txt" files for additional details.

Article Abstract:
"Vision underlies many important behaviors in insects generally and in mosquitos specifically. Mosquito vision plays a role in predator avoidance, mate finding, oviposition, locating vertebrate hosts, and vectoring disease. Recent work has shown that when sensitized to CO2, the visual responses of Aedes aegypti are wavelength-dependent, but little is known about how other olfactory stimuli can modulate visual responses. The visual cues associated with flowers, vertebrate hosts, or oviposition sites differs substantially and it is possible that odors might prime the mosquito visual system to respond to these different resources. To investigate the interplay of olfactory and visual cues, we adapted previously used wind tunnel bioassays to use quasi-monochromatic targets (390-740 nm) created with a novel LED synth. We coupled these visual targets with CO2 and the odors representative of vertebrate hosts, floral nectar or oviposition sites and assessed responses via 3D tracking of female mosquitos. When CO2 alone is present, we observe a lower preference for wavelengths in the green portion of the visible spectrum with a gradual increase as wavelengths moved towards the violet and red ends of the spectrum. However, when odors associated both with flowers and oviposition sites were present, we observed significant increases in mosquito preference for green (475-575 nm) stimuli. In contrast when vertebrate host odor was present, we saw increased preference for stimuli across the entire visible spectrum. These odor shifts in the mosquito spectral preferences suggest these preferences are not fixed and shift depending on behavioral context."
DOI: 10.17632/stmb3j2kvr
title: Raw Data_AI Risk Perception and Career Readiness in College Students

description: The dataset, "Raw Data_AI Risk Perception and Career Readiness in College Students," was collected from undergraduate students across various universities using a cross-sectional survey between March and May 2025. After data cleaning, 934 valid responses were retained for analysis. The study aimed to examine how AI risk perception and growth mindset influence career readiness, with career adaptability as a mediating mechanism and perceived social support as a moderator. The dataset contains self-reported data on students’ AI risk perception, growth mindset, career adaptability, career readiness, and perceived social support. Structural equation modeling was employed to test the hypotheses. This dataset provides valuable insights into how students psychologically prepare for AI-induced career disruption and the role of cognitive resources and vulnerabilities in shaping career outcomes. The findings can inform the design of adaptive career education and support systems for students in the AI era.