cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.zqdhsf
title: Occurrence Download

description: A dataset containing 13442 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is United Kingdom National Whale Stranding Database 1913-2008"
 ]
}

 The dataset includes 13442 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020943-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xkfpya
title: Occurrence Download

description: A dataset containing 110 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tilia tomentosa Moench",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Living Specimen"
 ]
}

 The dataset includes 110 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020946-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j85a46
title: Occurrence Download

description: A dataset containing 651 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ijimaia loppei Roule, 1922",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 651 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020947-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2xn9zv
title: Occurrence Download

description: A dataset containing 1308 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Geranium viscosissimum Fisch. & C.A.Mey.",
 "Geometry POLYGON ((-110.0046 53.60524, -110.1944 53.6994, -110.3939 53.72009, -110.6345 53.85858, -110.937 53.85856, -111.2783 53.759, -111.4921 53.80273, -111.7162 53.79424, -111.7182 53.89368, -111.7881 53.92878, -112.028 53.93921, -112.203 54.05093, -112.258 54.06073, -112.5398 53.99898, -112.7881 54.06553, -112.8548 54.02931, -112.8548 53.95782, -113.049 53.87199, -113.3159 53.63662, -113.5614 53.50897, -113.6136 53.4916, -113.6392 53.44169, -113.655 53.38152, -113.9769 53.34162, -114.2559 53.37179, -114.293 53.39591, -114.2777 53.42577, -114.3358 53.43492, -114.3698 53.42719, -114.4398 53.35168, -114.5738 53.31588, -114.7942 53.32352, -114.8967 53.25145, -114.9941 53.11631, -115.888 52.6375, -118.5667 52.17635, -114.8778 50.27669, -114.7478 49.52898, -114.0634 48.99769, -110.005 48.99959, -110.0046 53.60524))"
 ]
}

 The dataset includes 1308 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020948-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vykc2n
title: Occurrence Download

description: A dataset containing 328 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Georgia and the South Sandwich Islands",
 "TaxonKey is Insecta"
 ]
}

 The dataset includes 328 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020949-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14285106
title: Generative artificial intelligence and machine learning methods to screen social media content

description: TikTok Pregnancy-Vape Data Collection README




Introduction


This repository contains scripts for collecting data from TikTok, including videos, metadata, and visual insights. The data collection process involves several steps, each outlined below along with instructions for setup and usage.



Requirements




Python 3.x

Required Python packages: pyktok, opencv-python, requests

Oracle Cloud Vision API credentials (for visual insights extraction)




Data Collection Steps




1. Metadata Extraction




Search for hashtags on tiktok and the use zeeschuimer extension from https://github.com/digitalmethodsinitiative/zeeschuimer




2. Deduplication




Combine metadata from multiple hashtag pairs into a single dataset.

Use the provided Python script for deduplication based on unique video IDs.

Run combineHashtagMetadata.py




3. Video Download




Utilize the pyktok library to download TikTok videos based on video IDs extracted during metadata collection.

Modify the script to specify the desired video download settings and output directory.

Run pyktokVideoCollection.py




4. Transcript Generation




Extract text overlays and descriptions from videos.

Transcribe files using OpenAI's Whisper.

Set up whisper according to https://github.com/openai/whisper

Run whisperTranscriptGenerator




5. Object and Text Detection




Extract image frames from videos at regular intervals.

Run framesGeneration.py

Analyze frames using Oracle Cloud Vision API to identify objects, text, faces, and other visual elements.

Record attributes such as detected faces, errors, image classification labels, and object detection model versions.

This script in oracleFramefeatureExtractor.py




Usage




Run each script sequentially, following the instructions provided within the scripts.

Customize script parameters as needed to suit specific data collection requirements.

Ensure proper API credentials, permissions and setup Oracle Cloud Vision API according to Oracle documentation.
DOI: 10.5281/zenodo.14285107
title: Generative artificial intelligence and machine learning methods to screen social media content

description: TikTok Pregnancy-Vape Data Collection README




Introduction


This repository contains scripts for collecting data from TikTok, including videos, metadata, and visual insights. The data collection process involves several steps, each outlined below along with instructions for setup and usage.



Requirements




Python 3.x

Required Python packages: pyktok, opencv-python, requests

Oracle Cloud Vision API credentials (for visual insights extraction)




Data Collection Steps




1. Metadata Extraction




Search for hashtags on tiktok and the use zeeschuimer extension from https://github.com/digitalmethodsinitiative/zeeschuimer




2. Deduplication




Combine metadata from multiple hashtag pairs into a single dataset.

Use the provided Python script for deduplication based on unique video IDs.

Run combineHashtagMetadata.py




3. Video Download




Utilize the pyktok library to download TikTok videos based on video IDs extracted during metadata collection.

Modify the script to specify the desired video download settings and output directory.

Run pyktokVideoCollection.py




4. Transcript Generation




Extract text overlays and descriptions from videos.

Transcribe files using OpenAI's Whisper.

Set up whisper according to https://github.com/openai/whisper

Run whisperTranscriptGenerator




5. Object and Text Detection




Extract image frames from videos at regular intervals.

Run framesGeneration.py

Analyze frames using Oracle Cloud Vision API to identify objects, text, faces, and other visual elements.

Record attributes such as detected faces, errors, image classification labels, and object detection model versions.

This script in oracleFramefeatureExtractor.py




Usage




Run each script sequentially, following the instructions provided within the scripts.

Customize script parameters as needed to suit specific data collection requirements.

Ensure proper API credentials, permissions and setup Oracle Cloud Vision API according to Oracle documentation.
DOI: 10.15468/dl.6dzrc2
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tipuana tipu (Benth.) Kuntze",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Living Specimen"
 ]
}

 The dataset includes 10 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020950-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ccpvee
title: Occurrence Download

description: A dataset containing 280 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Macroparalepis affinis Ege, 1933",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 280 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020951-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t78vb6
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Toona sinensis (A.Juss.) M.Roem.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Living Specimen"
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020954-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25573/data.27934533
title: Soil microbial communities in dry and moist tropical forests exhibit distinct shifts in community composition but not diversity with succession

description: Metadata, R scripts and ASV abundance tables.Our study was conducted at two sites that represent dry (Los Santos) and moist (Agua Salud) tropical lowland forest types in Panama. The two sites have distinct tree species composition and richness, with relatively little species overlap. We collected 36 surface soil samples (0 to 15 cm depth) in three land use categories (cattle pasture, 20 year old secondary forest, and old secondary forest) at each site during the wet season. Cores were sampled at 10 m intervals along four replicate transects in each of the three land use categories at each site. Soil microbial communities were characterized using DNA meta barcoding using the primer sets 515F - 806R (Bacteria 16S V4 region, Caporaso et al. 2011), ITS1F - ITS2R (Fungi ITS1 rRNA region, White et al. 1990), and AMV4.5NF - AMDGR (AMF 18S rRNA region, van Geel et al. 2014) and sequenced on an Illumina MiSeq with 2x250 bp paired end sequencing. Data were processed using the R packages <i>DADA2</i>, <i>phyloseq</i>, <i>vegan</i>, <i>microbiome, </i>and associated packages. Sample metadata includes soil chemistry and alpha diversity calculations for each sample. Vegetation data was collected from the same plots as the soil samples. Raw fastq files and metadata can be found in the NCBI SRA archive in BioProject PRJNA1159263
DOI: 10.25573/data.27934533.v1
title: Soil microbial communities in dry and moist tropical forests exhibit distinct shifts in community composition but not diversity with succession

description: Metadata, R scripts and ASV abundance tables.Our study was conducted at two sites that represent dry (Los Santos) and moist (Agua Salud) tropical lowland forest types in Panama. The two sites have distinct tree species composition and richness, with relatively little species overlap. We collected 36 surface soil samples (0 to 15 cm depth) in three land use categories (cattle pasture, 20 year old secondary forest, and old secondary forest) at each site during the wet season. Cores were sampled at 10 m intervals along four replicate transects in each of the three land use categories at each site. Soil microbial communities were characterized using DNA meta barcoding using the primer sets 515F - 806R (Bacteria 16S V4 region, Caporaso et al. 2011), ITS1F - ITS2R (Fungi ITS1 rRNA region, White et al. 1990), and AMV4.5NF - AMDGR (AMF 18S rRNA region, van Geel et al. 2014) and sequenced on an Illumina MiSeq with 2x250 bp paired end sequencing. Data were processed using the R packages <i>DADA2</i>, <i>phyloseq</i>, <i>vegan</i>, <i>microbiome, </i>and associated packages. Sample metadata includes soil chemistry and alpha diversity calculations for each sample. Vegetation data was collected from the same plots as the soil samples. Raw fastq files and metadata can be found in the NCBI SRA archive in BioProject PRJNA1159263
DOI: 10.15468/dl.43u2an
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Torreya californica Torr.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Living Specimen"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020955-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cxh49t
title: Occurrence Download

description: A dataset containing 1267 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Naucrates ductor (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1267 records from 130 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020956-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qa6r7f
title: Occurrence Download

description: A dataset listing the 33 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is United Kingdom National Whale Stranding Database 1913-2008"
 ]
}

 The dataset's 33 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020944-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2uaa8s
title: Occurrence Download

description: A dataset containing 12534 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "TaxonKey is Alces alces (Linnaeus, 1758)"
 ]
 },
 "HasCoordinate is TRUE",
 "Year is greater than or equal to 2010",
 "Year is less than or equal to 2023",
 "DecimalLatitude is greater than or equal to 36.29073536915104",
 "DecimalLatitude is less than or equal to 65.32354893559595",
 "DecimalLongitude is greater than or equal to -119.94752109081536",
 "DecimalLongitude is less than or equal to -13.173794847392001",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 12534 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020957-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5a8582
title: Occurrence Download

description: A dataset containing 14417473 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON((-84.93962 -4.33921,-71.47373 -19.06905,-67.73051 -17.02729,-67.68189 -3.99892,-75.0225 0.66796,-84.93962 -4.33921))"
 ]
}

 The dataset includes 14417473 records from 1981 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020938-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive14467.20250331.9.3
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0082116.10fu
title: SH0082116.10FU

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: 10.13145/bacdive14467.20251217.10
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0082117.10fu
title: SH0082117.10FU

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: 10.15468/dl.q276dy
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((89.02501599999999 23.940898, 88.948184 23.935322, 88.87326400000001 23.918729, 88.802117 23.891535, 88.736508 23.854414, 88.67806299999999 23.808288, 88.62822199999999 23.754301, 88.58821 23.693793, 88.559003 23.628259, 88.54130600000001 23.559321, 88.535538 23.488679, 88.541821 23.418074, 88.559983 23.349244, 88.58955899999999 23.283878, 88.629807 23.22358, 88.67973000000001 23.169827, 88.738094 23.123934, 88.803465 23.087024, 88.874244 23.059996, 88.9487 23.043511, 89.02501599999999 23.037971, 89.101332 23.043511, 89.175788 23.059996, 89.246567 23.087024, 89.311938 23.123934, 89.370302 23.169827, 89.420225 23.22358, 89.46047299999999 23.283878, 89.490049 23.349244, 89.508211 23.418074, 89.514494 23.488679, 89.508726 23.559321, 89.491029 23.628259, 89.461822 23.693793, 89.42180999999999 23.754301, 89.37196900000001 23.808288, 89.313524 23.854414, 89.24791500000001 23.891535, 89.176768 23.918729, 89.101848 23.935322, 89.02501599999999 23.940898))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076767-251120083545085/datasets/export for details.
DOI: 10.13145/bacdive14468.20250331.9.3
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14468.20251217.10
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14469.20250331.9.3
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14469.20251217.10
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0082118.10fu
title: SH0082118.10FU

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: 10.13145/bacdive14470.20241212.9.2
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0082119.10fu
title: SH0082119.10FU

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: 10.13145/bacdive14470.20251217.10
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14471.20241212.9.2
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.