cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0163438.10fu
title: SH0163438.10FU

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/sh0163439.10fu
title: SH0163439.10FU

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: 10.5281/zenodo.18196303
title: Implementation Science, Program Fidelity, and Program Delivery in Scaling Early Literacy Interventions for Children Aged 3–13: A Systematic Review

description: This data set contains the qdpx coding file done through Qual Coder 3.7 , thematic coding master code list, Data set extracted against research questions and the bibliometric metadata of included studies
DOI: 10.5281/zenodo.18196304
title: Implementation Science, Program Fidelity, and Program Delivery in Scaling Early Literacy Interventions for Children Aged 3–13: A Systematic Review

description: This data set contains the qdpx coding file done through Qual Coder 3.7 , thematic coding master code list, Data set extracted against research questions and the bibliometric metadata of included studies
DOI: 10.15156/bio/sh0163440.10fu
title: SH0163440.10FU

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/sh0163441.10fu
title: SH0163441.10FU

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/sh0163442.10fu
title: SH0163442.10FU

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/sh0163443.10fu
title: SH0163443.10FU

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/sh0163444.10fu
title: SH0163444.10FU

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/sh0163445.10fu
title: SH0163445.10FU

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/sh0163446.10fu
title: SH0163446.10FU

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: 10.5281/zenodo.16310177
title: Usability Testing Dataset: SUS and CTA Evaluation on Legoas Smart Digital Auction Application

description: This dataset contains the results of usability testing conducted on the Legoas Smart Digital Auction mobile application. Two evaluation methods were applied: (1) the System Usability Scale (SUS) collected from 100 respondents using a 10-statement Likert scale questionnaire, and (2) the Concurrent Think Aloud (CTA) evaluation involving 2 users performing 30 scenario-based tasks while verbalizing their experience.The SUS dataset records user responses and final scores reflecting perceived usability, while the CTA dataset includes qualitative verbal responses categorized into five usability aspects: Learnability, Efficiency, Satisfaction, Memorability, and Errors.This open dataset is provided to support further research in usability testing, UX improvement, user-centered design, and digital auction platform development.
DOI: 10.5281/zenodo.16310178
title: Usability Testing Dataset: SUS and CTA Evaluation on Legoas Smart Digital Auction Application

description: This dataset contains the results of usability testing conducted on the Legoas Smart Digital Auction mobile application. Two evaluation methods were applied: (1) the System Usability Scale (SUS) collected from 100 respondents using a 10-statement Likert scale questionnaire, and (2) the Concurrent Think Aloud (CTA) evaluation involving 2 users performing 30 scenario-based tasks while verbalizing their experience.The SUS dataset records user responses and final scores reflecting perceived usability, while the CTA dataset includes qualitative verbal responses categorized into five usability aspects: Learnability, Efficiency, Satisfaction, Memorability, and Errors.This open dataset is provided to support further research in usability testing, UX improvement, user-centered design, and digital auction platform development.
DOI: 10.15468/dl.hdazjr
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus afromontanus",
 "HasCoordinate is true",
 "Geometry POLYGON ((-17.66889 -35.11691, 51.34702 -35.11691, 51.34702 37.62, -17.66889 37.62, -17.66889 -35.11691))"
 ]
}

 The dataset includes 11 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027166-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17617/4.fc
title: ChildLens: An Egocentric Video Dataset for Activity Analysis in Children

description: ChildLens is an egocentric video and audio dataset capturing naturalistic everyday experiences in children aged 3–5 years. It contains 109 hours of recordings from 62 children in their home environment, collected using a 140° wide-lens camera with a microphone embedded in a child-friendly vest. The dataset includes detailed annotations with five location classes (livingroom, playroom, bathroom, hallway, and other) and 14 activity classes, covering audio-only (child talking, singing/humming, listening to music/audiobook, other person talking, overheard speech), video-only (watching something, drawing, crafting things, dancing, playing with object), and multimodal activities (playing without object, reading book, making music, pretend play). 
The recordings, captured from chest height, offer a rich perspective on children’s daily interactions and behaviors. The dataset is designed to support research in developmental psychology, computer vision, and audio analysis.
DOI: 10.15468/dl.t3ctsf
title: Occurrence Download

description: A dataset containing 555 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Celtis boninensis"
 ]
}

 The dataset includes 555 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027167-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y8xyft
title: Occurrence Download

description: A dataset containing 654 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cynodon dactylon",
 "Country is India",
 "HasCoordinate is true"
 ]
}

 The dataset includes 654 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027172-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5nc5sr5w
title: MassIVE MSV000098589 - Bioactive compounds discovery from French Guiana plant extracts through antitubercular screening and Molecular Networking
title: In this study, we investigated seven medicinal plant species from French Guiana as potential sources of novel antitubercular compounds. Using ultrasound-assisted extraction, liquid-liquid partitioning, and UHPLC-HRMS/MS, we created a library of 72 samples screened against Mycobacterium tuberculosis H37Ra. The most active fractions were the non-polar extracts from Indigofera suffruticosa, Tetradenia riparia, and Zingiber zerumbet. Through bioactivity-guided molecular networking, we integrated metabolomic and bioassays data to prioritize and annotate active metabolites, primarily flavonoids. Computational tools (GNPS, SIRIUS, TIMA-R) further enhanced structural prediction and dereplication. This approach offers an efficient strategy to identify known and novel bioactive compounds without requiring exhaustive isolation.
DOI: 10.15468/dl.hu9kgp
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Chinese Taipei",
 "TaxonKey is Castanopsis sclerophylla"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027174-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16034045
title: Benthic Ecological Survey Data for Tanzania Mainland and Zanzibar

description: This dataset contains the results of the Benthic Ecological Survey (BES), a methodology refined by the Wildlife Conservation Society (WCS) during the USAID Heshimu Bahari project to map benthic substrates across the coastal waters of Tanzania, including Zanzibar. The survey was conducted as part of the Heshimu Bahari project, an initiative supported by USAID, to support the strengthening of climate resilience and productivity of reef fisheries, particularly through the creation of a network of Fishery Replenishment Zones (FRZs) along the Tanzanian coastline. Producing reliable maps of benthic substrates is identified as the crucial first step for this work.

The BES methodology was developed by WCS to bridge a critical gap in data collection tools for benthic substrates, specifically targeting scales between approximately 10 km² and 100 km². This boat-based survey utilizes a photo-quadrat method, deploying a GoPro camera attached to a metal tripod to capture images of the benthos at predetermined, georeferenced sites without the need for divers. Images are subsequently analyzed using CoralNet, an online platform where experts label 25 random points per image into 21 substrate categories.

The survey covered the entire Tanzanian coastline, including the islands of Zanzibar and Latham Island, for waters shallower than 50 meters. A regular grid of 1 km spacing was used for station selection, with 500m intervals for Latham Island. In total, the project surveyed 11,690 sites, collecting over 35,000 photoquadrats and covering an equivalent area of approximately 11,526 km² of coastline.

The data is organized in several folders,



analysis folder, containing the results in CSV and NetCDF format. The CSV format is in both summaries, with coordinates and data averaged over the 3 replicas per site, and full, with data for each replica. The NetCDF files are created using the data in summaries, mapped on the 500 m regular grid of the survey space for each label in the CoralNet label set.

coralnet_medatadat folder, contains the annotation data for each sub-region and the corresponding metadata. For each sampled station we collected station ID, date, time, depth and GPS coordinates. These are linked to the labelled data from CoralNet to create the CSV files in the analysis folder. 

A folder with the Python scripts we developed to process the data

HB_WCS_BES_report.pdf, a technical report detailing the methodology and describing results from some preliminary analysis
DOI: 10.5281/zenodo.16310216
title: Benthic Ecological Survey Data for Tanzania Mainland and Zanzibar

description: This dataset contains the results of the Benthic Ecological Survey (BES), a methodology refined by the Wildlife Conservation Society (WCS) during the USAID Heshimu Bahari project to map benthic substrates across the coastal waters of Tanzania, including Zanzibar. The survey was conducted as part of the Heshimu Bahari project, an initiative supported by USAID, to support the strengthening of climate resilience and productivity of reef fisheries, particularly through the creation of a network of Fishery Replenishment Zones (FRZs) along the Tanzanian coastline. Producing reliable maps of benthic substrates is identified as the crucial first step for this work.

The BES methodology was developed by WCS to bridge a critical gap in data collection tools for benthic substrates, specifically targeting scales between approximately 10 km² and 100 km². This boat-based survey utilizes a photo-quadrat method, deploying a GoPro camera attached to a metal tripod to capture images of the benthos at predetermined, georeferenced sites without the need for divers. Images are subsequently analyzed using CoralNet, an online platform where experts label 25 random points per image into 21 substrate categories.

The survey covered the entire Tanzanian coastline, including the islands of Zanzibar and Latham Island, for waters shallower than 50 meters. A regular grid of 1 km spacing was used for station selection, with 500m intervals for Latham Island. In total, the project surveyed 11,690 sites, collecting over 35,000 photoquadrats and covering an equivalent area of approximately 11,526 km² of coastline.

The data is organized in several folders,



analysis folder, containing the results in CSV and NetCDF format. The CSV format is in both summaries, with coordinates and data averaged over the 3 replicas per site, and full, with data for each replica. The NetCDF files are created using the data in summaries, mapped on the 500 m regular grid of the survey space for each label in the CoralNet label set.

coralnet_medatadat folder, contains the annotation data for each sub-region and the corresponding metadata. For each sampled station we collected station ID, date, time, depth and GPS coordinates. These are linked to the labelled data from CoralNet to create the CSV files in the analysis folder. 

A folder with the Python scripts we developed to process the data

HB_WCS_BES_report.pdf, a technical report detailing the methodology and describing results from some preliminary analysis
DOI: 10.15468/dl.tk2fzf
title: Occurrence Download

description: A dataset containing 10476 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cenchrus spinifex"
 ]
}

 The dataset includes 10476 records from 376 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027170-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wwx38m
title: Occurrence Download

description: A dataset containing 1418 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cenchrus myosuroides"
 ]
}

 The dataset includes 1418 records from 139 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027175-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.