cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.fkp7su
title: Occurrence Download

description: A dataset containing 39 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.occurrencestatus = 'PRESENT'
 AND (CAST(occurrence.taxonkey AS INTEGER) = 4559460 OR CAST(occurrence.acceptedtaxonkey AS INTEGER) = 4559460 OR CAST(occurrence.kingdomkey AS INTEGER) = 4559460 OR CAST(occurrence.phylumkey AS INTEGER) = 4559460 OR CAST(occurrence.classkey AS INTEGER) = 4559460 OR CAST(occurrence.orderkey AS INTEGER) = 4559460 OR CAST(occurrence.familykey AS INTEGER) = 4559460 OR CAST(occurrence.genuskey AS INTEGER) = 4559460 OR CAST(occurrence.specieskey AS INTEGER) = 4559460)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 39 records were derived from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011634-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/cdxs-dn21
title: "YOGPIPE: A Framework for Identifying Precise Yoga Angles for Diabetes Control and Management"

description: "The Yoga Diabetes dataset comprises images of various yoga postures that are specifically used for managing diabetes. These images represent different asanas designed to help regulate blood sugar levels, improve circulation, and reduce stress. The postures included in the dataset are:Kapal Bharti: A pranayama exercise aimed at improving metabolism and oxygenating the body.Vrksasana: A balancing pose that enhances mental focus and regulates blood sugar levels.Adho Mukha Svanasana: A forward bend that helps increase circulation and reduce stress.Ardha Matseyendrasana: A seated spinal twist promoting detoxification and improving digestion.Balasana: A restorative pose that relaxes the body and alleviates stress.Bhujangasana: A backbend that strengthens the spine and helps with digestion.Dhanurasana: A backbend posture that improves circulation and promotes overall wellness.Halasana: A pose that stretches the spine and relieves stress and tension.Makarasana: A relaxation pose that helps lower blood pressure and reduces mental strain.Pachittomottanasana: A forward bend that stretches the body and aids in digestion.Phalakasana: A plank pose that builds core strength and stabilizes the body.Salabhasana: A backbend that strengthens the core and improves posture.Salamba Sarvangasana: Shoulder stand that enhances blood flow and rejuvenates the body.Savasana: A relaxation pose that calms the mind and relieves stress.Upavishta Konsana: A seated posture that stretches the legs and promotes flexibility.Vajrasana: A seated posture that aids digestion and promotes concentration.Viprita Karani: A restorative inversion pose that boosts circulation and reduces stress.Vibhadrasana: A warrior pose that builds strength and increases mental focus.These postures were chosen for their beneficial effects on diabetes management and are utilized to train a model for yoga posture classification. The dataset is designed to evaluate the effectiveness of these postures in controlling blood sugar and improving overall health."
DOI: 10.21334/npolar.2025.44a880e0
title: Sea ice core data from BREATHE/SIDRiFT field school, north of Svalbard, May 2023
DOI: 10.5281/zenodo.17191401
title: AAL and AHA Platforms Dataset

description: This dataset on Ambient Assisted Living (AAL) and Active and Healthy Aging (AHA) platforms was used as input for machine learning algorithms in Žiga Kolar’s masters thesis, AI-Based Analysis of Platforms for Active and Healthy Aging in the EU. It consists of two files:



 The file data.xlsx contains a table where each row corresponds to a platform name. For each attribute, one column stores the raw (unprocessed) value, and the adjacent column stores its numeric representation. For instance, for the attribute Connectivity of heterogeneous IoT devices, the first column stores categorical values (e.g., Yes, No), while the adjacent column provides their numeric representation.

 The file platforms8.csv contains only the numeric values, obtained by transforming their corresponding categorical counterparts.
DOI: 10.5281/zenodo.17191402
title: AAL and AHA Platforms Dataset

description: This dataset on Ambient Assisted Living (AAL) and Active and Healthy Aging (AHA) platforms was used as input for machine learning algorithms in Žiga Kolar’s masters thesis, AI-Based Analysis of Platforms for Active and Healthy Aging in the EU. It consists of two files:



 The file data.xlsx contains a table where each row corresponds to a platform name. For each attribute, one column stores the raw (unprocessed) value, and the adjacent column stores its numeric representation. For instance, for the attribute Connectivity of heterogeneous IoT devices, the first column stores categorical values (e.g., Yes, No), while the adjacent column provides their numeric representation.

 The file platforms8.csv contains only the numeric values, obtained by transforming their corresponding categorical counterparts.
DOI: 10.21334/npolar.2024.a1ab4151
title: Snow pits from BREATHE/SIDRiFT field school, north of Svalbard, May 2023
DOI: 10.15468/dl.cp9kqa
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Datura pruinosa",
 "Year 1970-2020"
 ]
}

 The dataset includes 12 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011672-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bc67na
title: Occurrence Download

description: A dataset containing 28903 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Australia",
 "HasCoordinate is true",
 "Year is 1929"
 ]
}

 The dataset includes 28903 records from 115 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011665-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14860272
title: Reconciling urban food metabolic pattern with its environment – a "mission impossible"?
DOI: 10.5281/zenodo.15042065
title: Reconciling urban food metabolic pattern with its environment – a "mission impossible"?
DOI: 10.7910/dvn/rxdci1
title: Replication Data for Optimizing Economic Complexity

description: This repository can can be used to reproduce the results from "Optimizing Economic Complexity" by Viktor Stojkoski and Cesar Hidalgo.

It consists of the following files:

eci-optimization-reproducibility-package-ipynb - A python notebook, which when run gives the tables and figures from the main manuscript and the supplementary material. 

ecioptimization-py - A document consisting of a set of functions needed to run ECI Optimization

trade_data - A folder containing yearly bilateral trade data by exporter, importer and HS4 category (HS92 Rev.1992) from 1998 to 2022 (in USD)

msa_data - A folder containing yearly overall payroll for each U.S. MSA and activity from 2003 to 2022 (in USD)

data - an additional folder containing Economic Complexity Index estimates for countries using trade data from 1999 to 2022.
DOI: 10.5281/zenodo.17191808
title: Agronomic data of V. articulata core collection accessions

description: Agronomic data of V. articulata core collection accessions Table S8a: asociated to publication https://www.mdpi.com/2073-4395/14/2/326
DOI: 10.5281/zenodo.17191809
title: Agronomic data of V. articulata core collection accessions

description: Agronomic data of V. articulata core collection accessions Table S8a: asociated to publication https://www.mdpi.com/2073-4395/14/2/326
DOI: 10.15468/dl.neme3a
title: Occurrence Download

description: A dataset containing 171027 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ribes rubrum",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 171027 records from 1086 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011607-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17031/6745ef5fe2b35
title: 2006 Shell UK Exploration and Production Ltd Pipeline/Umbilical route infill survey UKCS blocks 21/25. Teal P2 to Teal P1 and Teal P2 to Teal W1/W2 Buta

description: This report presents the results of an environmental baseline survey conducted on the 13thOctober 2006 aboard the Gardline Shipping survey vessel MV Sea Explorer. The survey was conducted by Gardline Environmental Ltd on behalf of Shell U.K in UKCS 21/25. Sampling was undertaken along a proposed pipeline route from the Teal P1 well to the proposed Teal P2 relief well and a proposed umbilical route between Teal P2 and the Teal W1/W2 water injection well.
DOI: 10.5281/zenodo.17130961
title: Data & Image Archive for "Compensatory Respiration Supports Survival During Extended Heat Stress in Microcystis aeruginosa" Microcystis extended temperature stress study (2025, v1.0)

description: Description

This repository contains the complete raw data and figure-source files underlying the manuscript:

Title:  Compensatory Respiration Supports Survival During Extended Heat Stress in Microcystis aeruginosaAuthors: Oded Liran et al.Study focus: Extended heat stress responses in Microcystis aeruginosa strains PCC7806 (reference) and C-1004 (Lake Kinneret isolate), with emphasis on photosynthesis-respiration interactions during extended heat stress.

What’s included





Raw measurements: Chlorophyll fluorescence (JTS), dark pulse kinetics (JTS), temperature/time-course experiments, growth curves, MIMS recordings, RT-PCR machine outputs, Spectrofluorometer output, code snippets and scripts used to extract genomic comparison data between the two strains.




Gels: Original image stacks (TIFF), uncropped blots, and high-resolution micrographs.



Project background 

We compare thermotolerance strategies in two closely related M. aeruginosa strains under extended temperature stress. 

Citation

Please cite the dataset as:Liran, O., et al. (2025). Source data and images for manuscript titled: "Compensatory Respiration Supports Survival During Extended Heat Stress in Microcystis aeruginosa (PCC7806 vs C-1004)". 

License & reuse





License: CC BY 4.0 (recommended for open reuse).




Embargo: 31.12.2029, or sooner, upon publication of the related manuscript




Reuse notes: Report any re-processing steps; retain original filenames in derived work.



Related identifiers



ORCIDs: Oded Liran 0000-0002-3429-4065


Contact

Correspondence: oded.liran@ocean.org.ilIssues/queries about files or metadata: please open a Zenodo “Notes” entry referencing the file path.

Keywords: Microcystis, heat shock, photosynthesis, respiration, MIMS, PAM, JTS, Lake Kinneret, cyanobacteria, source data.
DOI: 10.5281/zenodo.17130962
title: Data & Image Archive for "Compensatory Respiration Supports Survival During Extended Heat Stress in Microcystis aeruginosa" Microcystis extended temperature stress study (2025, v1.0)

description: Description

This repository contains the complete raw data and figure-source files underlying the manuscript:

Title:  Compensatory Respiration Supports Survival During Extended Heat Stress in Microcystis aeruginosaAuthors: Oded Liran et al.Study focus: Extended heat stress responses in Microcystis aeruginosa strains PCC7806 (reference) and C-1004 (Lake Kinneret isolate), with emphasis on photosynthesis-respiration interactions during extended heat stress.

What’s included





Raw measurements: Chlorophyll fluorescence (JTS), dark pulse kinetics (JTS), temperature/time-course experiments, growth curves, MIMS recordings, RT-PCR machine outputs, Spectrofluorometer output, code snippets and scripts used to extract genomic comparison data between the two strains.




Gels: Original image stacks (TIFF), uncropped blots, and high-resolution micrographs.



Project background 

We compare thermotolerance strategies in two closely related M. aeruginosa strains under extended temperature stress. 

Citation

Please cite the dataset as:Liran, O., et al. (2025). Source data and images for manuscript titled: "Compensatory Respiration Supports Survival During Extended Heat Stress in Microcystis aeruginosa (PCC7806 vs C-1004)". 

License & reuse





License: CC BY 4.0 (recommended for open reuse).




Embargo: 31.12.2029, or sooner, upon publication of the related manuscript




Reuse notes: Report any re-processing steps; retain original filenames in derived work.



Related identifiers



ORCIDs: Oded Liran 0000-0002-3429-4065


Contact

Correspondence: oded.liran@ocean.org.ilIssues/queries about files or metadata: please open a Zenodo “Notes” entry referencing the file path.

Keywords: Microcystis, heat shock, photosynthesis, respiration, MIMS, PAM, JTS, Lake Kinneret, cyanobacteria, source data.
DOI: 10.15468/dl.62c828
title: Occurrence Download

description: A dataset containing 788 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Datura metel",
 "Year 1970-2020"
 ]
}

 The dataset includes 788 records from 142 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011668-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mkbkpe
title: Occurrence Download

description: A dataset containing 1099 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Amphibia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((82.5 22.5,90 22.5,90 30,82.5 30,82.5 22.5))"
 ]
}

 The dataset includes 1099 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040896-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8v398n
title: Occurrence Download

description: A dataset containing 232 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is LAO",
 "OccurrenceStatus is Present",
 "TaxonKey is Orchidaceae"
 ]
}

 The dataset includes 232 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040894-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0173446.10fu
title: SH0173446.10FU

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/sh0173447.10fu
title: SH0173447.10FU

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/sh0173448.10fu
title: SH0173448.10FU

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/sh0173449.10fu
title: SH0173449.10FU

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/sh0173450.10fu
title: SH0173450.10FU

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/sh0173451.10fu
title: SH0173451.10FU

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.