cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/4dzjt9mrfy.2
title: Are Treatment Wetlands suitable surrogate habitats for birds? A study on avian diversity in Northern Italy

description: Treatment Wetlands (TWs) are artificial wetlands designed for wastewater treatment. TW technology combines economic utility with ecological and conservation benefits. This study investigates whether TWs can serve as surrogate habitats for birds by comparing them with semi-natural wetlands and the surrounding landscape. 

Specifically, we assessed bird diversity across three habitat types (TWs, semi-natural wetlands, and dry landscape as control) using Hill numbers and analyzed differences in waterbird guilds. Additionally, generalized linear models (GLMs) were applied to explore relationships between environmental variables and bird diversity. Bird diversity data were collected through point counts within 300x300 m plots, while environmental variables were derived via photointerpretation. 

Results showed no significant differences in overall bird diversity between TWs, semi-natural wetlands, and control sites. However, guild-specific analysis revealed that waterbird diversity in TWs exceeded that of the controls and was comparable to semi-natural wetlands. Furthermore, the extent of free water, reedbed coverage, and urbanization degree of the surrounding matrix were positively associated with bird diversity. These findings suggest that TWs can function as suitable surrogate habitats, providing ecological value akin to semi-natural wetlands for most of the tested waterbird guilds. 

In each folder, you can find the various dataframes related to a sampling season. These include both those containing bird abundance data and environmental data. Additionally, the R script is also provided.
DOI: 10.17632/4dzjt9mrfy.3
title: Are Treatment Wetlands suitable surrogate habitats for birds? A study on avian diversity in Northern Italy

description: Treatment Wetlands (TWs) are artificial wetlands designed for wastewater treatment. TW technology combines economic utility with ecological and conservation benefits. This study investigates whether TWs can serve as surrogate habitats for birds by comparing them with semi-natural wetlands and the surrounding landscape. 

Specifically, we assessed bird diversity across three habitat types (TWs, semi-natural wetlands, and dry landscape as control) using Hill numbers and analyzed differences in waterbird guilds. Additionally, generalized linear models (GLMs) were applied to explore relationships between environmental variables and bird diversity. Bird diversity data were collected through point counts within 300x300 m plots, while environmental variables were derived via photointerpretation. 

Results showed no significant differences in overall bird diversity between TWs, semi-natural wetlands, and control sites. However, guild-specific analysis revealed that waterbird diversity in TWs exceeded that of the controls and was comparable to semi-natural wetlands. Furthermore, the extent of free water, reedbed coverage, and urbanization degree of the surrounding matrix were positively associated with bird diversity. These findings suggest that TWs can function as suitable surrogate habitats, providing ecological value akin to semi-natural wetlands for most of the tested waterbird guilds. 

In each folder, you can find the various dataframes related to a sampling season. These include both those containing bird abundance data and environmental data. Additionally, the R script is also provided.
DOI: 10.5281/zenodo.14932010
title: Magma Pool - Sediment Interaction Experiments

description: Content description will arrive with the content ;-)
DOI: 10.5281/zenodo.14932009
title: Magma Pool - Sediment Interaction Experiments

description: Content description will arrive with the content ;-)
DOI: 10.17632/fkwnt8tndv.1
title: Bio-Photonics Light Scattering Dataset for AI-Based Tissue Imaging

description: 🔬 Research Hypothesis
This research hypothesizes that light propagation in biological tissues follows predictable scattering patterns governed by Monte Carlo-based photon transport models. By simulating photon interactions within a biological medium, a synthetic dataset can be generated to support AI-driven medical imaging applications, such as optical coherence tomography (OCT) and diffuse optical tomography. The dataset explores how different optical properties—scattering coefficient, anisotropy, and absorption—affect photon propagation and whether AI models can learn to differentiate between scattering profiles.

📊 Key Findings
The dataset consists of 2000 grayscale images, each representing the intensity distribution of photons in a simulated biological medium. Photon propagation follows expected physical principles, with intensity patterns matching theoretical models of light transport in tissues.

Key observations include the effect of anisotropic scattering, where high anisotropy values lead to forward-directed light propagation, while increased scattering coefficients result in greater lateral diffusion. Shorter wavelengths (450 nm) show stronger scattering and shallower penetration, whereas longer wavelengths (780 nm) experience lower scattering and deeper penetration, consistent with real tissue optics.

Absorption plays a critical role, reducing photon intensity as light penetrates deeper into the simulated medium. The structured variation in light intensity ensures that AI models can be trained to predict tissue properties from scattering patterns.

📖 How to Interpret and Use This Dataset
Each image represents a Monte Carlo photon transport simulation, where photons undergo multiple scattering and absorption events. The brightness of each pixel corresponds to photon concentration, with brighter areas indicating regions of higher intensity.

Researchers can analyze images by filtering them based on optical properties, such as wavelength or scattering coefficient. AI models can use the dataset for training in tissue classification and reconstruction of subsurface structures. The dataset is also valuable for validating Monte Carlo-based light transport models by comparing the generated images to experimental optical imaging data.

📌 Applications and Use Cases
This dataset is applicable to biomedical optics, AI-driven medical imaging, and laser-tissue interaction studies. It provides training data for AI models used in OCT and laser scanning microscopy. In physics and engineering, it supports the study of light transport in scattering media.

For AI research, the dataset enables training deep learning models to classify tissue structures based on scattering properties. It is also useful for developing AI algorithms that reconstruct subsurface tissue features from optical measurements.
DOI: 10.15468/dl.jpbcy9
title: Occurrence Download

description: A dataset containing 3048 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coffea canephora Pierre ex A.Froehner"
 ]
}

 The dataset includes 3048 records from 151 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000229-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/vzwc8tcrfh.1
title: The SWI/SNF PBAF complex facilitates REST occupancy at repressed chromatin

description: Uncropped western blot data relative to manuscript "The SWI/SNF PBAF complex facilitates REST occupancy at repressed chromatin"
DOI: 10.15468/dl.r5mp3s
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Atractylis arbuscula Svent. & Michaelis)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2020"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000231-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vxjgbd
title: Occurrence Download

description: A dataset containing 76392 species occurrences available in GBIF matching the query:
{
 "and" : [
 "IucnRedListCategory is EX",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 76392 records from 916 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000207-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zktkuj
title: Occurrence Download

description: A dataset containing 2930 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Diplodus cervinus (Lowe, 1838)"
 ]
}

 The dataset includes 2930 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000233-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7c8qq5
title: Occurrence Download

description: A dataset containing 1902 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year is greater than or equal to 1981",
 "Year is less than or equal to 2010",
 "HasCoordinate is true",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "VerbatimScientificName is Cystopteris fragilis",
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 1902 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000234-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ant9d6
title: Occurrence Download

description: A dataset containing 3042392 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "HasCoordinate is true",
 "Year is 2012",
 "Month is April"
 ]
}

 The dataset includes 3042392 records from 425 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000209-250226150154925/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/yxt-356-mn5
title: Viola canina × riviniana x canina subsp. ruppii × riviniana

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0028170.10fu
title: SH0028170.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/yvs-r6j-f67
title: Polygala vulgaris L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0028171.10fu
title: SH0028171.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/9l8-648-2gx
title: Polygala amarella Crantz

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/gde-l60-te2
title: Viola canina × riviniana x canina subsp. ruppii × riviniana

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0028172.10fu
title: SH0028172.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/8c4-9w3-avy
title: Myriophyllum L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/fb0-hel-cm9
title: Viola canina × riviniana x canina subsp. ruppii × riviniana

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0028173.10fu
title: SH0028173.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0028174.10fu
title: SH0028174.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/ens-vzk-5x4
title: Polygala amarella Crantz

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/z45-ggm-k4g
title: Epilobium parviflorum Schreb.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0028175.10fu
title: SH0028175.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/lq5-h31-7h9
title: Polygala amarella Crantz

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/ms6-xx9-985
title: Ruppia L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0028176.10fu
title: SH0028176.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/c0a-8md-n1g
title: Cornus suecica L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0028177.10fu
title: SH0028177.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/efg-968-9t3
title: Viola canina × rupestris x canina subsp. ruppii × rupestris

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/x3l-95p-mw3
title: Viola canina × riviniana x canina subsp. ruppii × riviniana

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15156/bio/sh0028178.10fu
title: SH0028178.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.3535/1ac-8tt-swm
title: Viola canina × riviniana x canina subsp. ruppii × riviniana

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/53f-5bs-4j6
title: Viola canina × riviniana x canina subsp. ruppii × riviniana

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.