cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.5sb6sh
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-99.54012 27.31619,-99.53593 27.31534,-99.53365 27.31906,-99.5306 27.32211,-99.52565 27.32228,-99.51575 27.32498,-99.50852 27.33243,-99.50147 27.33801,-99.50167 27.34173,-99.50509 27.34528,-99.50566 27.34984,-99.503 27.36084,-99.49938 27.36811,-99.50281 27.36895,-99.50662 27.36101,-99.5089 27.35492,-99.50966 27.34765,-99.50776 27.34274,-99.50662 27.33987,-99.50795 27.33581,-99.51804 27.32854,-99.5228 27.326,-99.52718 27.32566,-99.53289 27.32498,-99.53593 27.32177,-99.54012 27.31619))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Testudines"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093371-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.95ekfw
title: Occurrence Download

description: A dataset containing 527 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Rubus apetalus var. apetalus)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 527 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093372-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mxdrxw
title: Occurrence Download

description: A dataset containing 119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((21.55246 40.97719,21.61342 41.0112,21.61887 41.0144,21.62409 41.01782,21.62908 41.02142,21.63381 41.02522,21.63828 41.0292,21.64248 41.03334,21.64638 41.03764,21.64999 41.04209,21.6533 41.04666,21.65629 41.05136,21.65895 41.05617,21.66128 41.06108,21.66328 41.06607,21.66494 41.07112,21.66624 41.07624,21.6672 41.0814,21.66781 41.08659,21.66806 41.09179,21.66796 41.097,21.66751 41.1022,21.6667 41.10737,21.6646 41.11837,21.66339 41.12371,21.6618 41.129,21.65983 41.13421,21.65751 41.13934,21.65482 41.14436,21.65178 41.14927,21.64839 41.15405,21.64467 41.15869,21.64063 41.16317,21.63628 41.16748,21.63162 41.17161,21.62668 41.17554,21.62147 41.17928,21.61601 41.18279,21.61029 41.18609,21.60436 41.18914,21.59822 41.19196,21.59188 41.19452,21.58537 41.19683,21.57871 41.19887,21.57191 41.20064,21.565 41.20214,21.55799 41.20336,21.5509 41.20429,21.54376 41.20494,21.538 41.20534,21.53165 41.20568,21.5253 41.20578,21.51894 41.20566,21.49982 41.20497,21.49293 41.20458,21.48608 41.20393,21.47928 41.20302,21.47255 41.20185,21.46591 41.20041,21.45938 41.19873,21.45297 41.19679,21.4467 41.19461,21.44058 41.19219,21.43464 41.18954,21.42889 41.18666,21.42334 41.18356,21.41801 41.18026,21.41291 41.17675,21.40806 41.17305,21.40346 41.16917,21.39914 41.16511,21.3951 41.16089,21.39135 41.15653,21.35688 41.11402,21.35342 41.10949,21.35028 41.10484,21.34745 41.10008,21.34496 41.09521,21.3428 41.09024,21.34098 41.08521,21.33951 41.0801,21.33839 41.07495,21.33762 41.06976,21.33721 41.06455,21.33715 41.05933,21.33745 41.05411,21.3381 41.04891,21.33911 41.04374,21.3396 41.0416,21.34098 41.0364,21.34272 41.03126,21.34481 41.0262,21.34725 41.02122,21.35003 41.01635,21.35314 41.01159,21.35658 41.00696,21.36033 41.00247,21.36439 40.99814,21.36875 40.99397,21.37338 40.98998,21.37829 40.98617,21.38345 40.98256,21.38885 40.97917,21.39448 40.97599,21.40033 40.97303,21.40637 40.97031,21.41258 40.96783,21.41897 40.9656,21.42549 40.96362,21.43215 40.96191,21.43891 40.96045,21.44577 40.95927,21.4527 40.95836,21.45968 40.95772,21.4667 40.95736,21.47373 40.95727,21.48076 40.95747,21.48776 40.95793,21.49472 40.95868,21.50163 40.9597,21.50845 40.96098,21.51517 40.96254,21.52178 40.96436,21.52826 40.96643,21.53458 40.96876,21.54073 40.97134,21.54669 40.97415,21.55246 40.97719)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC0 1.0, CC-BY 4.0)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 119 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093374-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c50863h4f
title: MassIVE MSV000095141 - Label Free BioID interaction datasets, Soderling Lab
title: Quantitative LC/MS/MS was performed on 2 uL (1 ug) of each sample, using a nanoAcquity UPLC system (Waters Corp) coupled to a Thermo Orbitrap Fusion Lumos high resolution accurate mass tandem mass spectrometer (Thermo) equipped with a FAIMSPro device via a nanoelectrospray ionization source. Briefly, the sample was first trapped on a Symmetry C18 20 mm x 180 um trapping column (5 ul/min at 99.9/0.1 v/v water/acetonitrile), after which the analytical separation was performed using a 1.8 um Acquity HSS T3 C18 75 um x 250 mm column (Waters Corp.) with a 90-min linear gradient of 5 to 30% acetonitrile with 0.1% formic acid at a flow rate of 400 nanoliters/minute (nL/min) with a column temperature of 55C. Data collection on the Fusion Lumos mass spectrometer was performed for three difference compensation voltages (-40v, -60v, -80v). Within each CV, a data-dependent acquisition (DDA) mode of acquisition with a r 120,000 (m/z 200) full MS scan from m/z 375 - 1500 with a target AGC value of 4e5 ions was performed. MS/MS scans were acquired in the Orbitrap at r 50,000 ( m/z 200) from m/z 100 with a target AGC value of 1e5 and max fill time of 35 ms. The total cycle time for each CV was 1s, with total cycle times of 3 sec between like full MS scans. A 20s dynamic exclusion was employed to increase depth of coverage. The total analysis cycle time for each sample injection was approximately 2 hours
DOI: 10.15468/dl.m8tehz
title: Occurrence Download

description: A dataset containing 1478065 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON((33.11 -0.28, 42.61 -0.28, 42.61 5.11, 33.11 5.11, 33.11 -0.28))"
 ]
}

 The dataset includes 1478065 records from 631 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093362-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26099020
title: Supporting Information Deitrick etal 2024

description: Data supporting study of erosion within mangrove forest
DOI: 10.15468/dl.9mh4ga
title: Occurrence Download

description: A dataset containing 130 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aremonia agrimonoides subsp. agrimonoides)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 130 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093375-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ad3w35
title: Occurrence Download

description: A dataset containing 1251 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((21.93261 3.60069,25.39766 3.60069,25.39766 7.06574,21.93261 7.06574,21.93261 3.60069))",
 "TaxonKey is Lepidoptera"
 ]
}

 The dataset includes 1251 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093377-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25810/8pez-h060.53
title: Asian Newspaper Coverage of Climate Change or Global Warming, 2004-2024 - May 2024

description: The Media and Climate Change Observatory Data monitors 126 sources (across newspapers, radio and TV) in 58 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.5281/zenodo.12534638
title: Chapter 3
DOI: 10.5281/zenodo.11552795
title: Chapter 3
DOI: 10.5281/zenodo.11552796
title: Chapter 3
DOI: 10.5281/zenodo.12534674
title: structures_metadata.db

description: structures_metadata.db for the ENPKG graph
DOI: 10.5281/zenodo.12534675
title: structures_metadata.db

description: structures_metadata.db for the ENPKG graph
DOI: 10.25345/c5vh5cv9f
title: MassIVE MSV000095142 - Season-dependent variation in glucosinolate and S-methyl-L-cysteine sulfoxide and hydrolysis in Brassica oleracea
title: Brassica vegetables are rich in phytochemicals, such as glucosinolates (GLSs) and S methyl L cysteine sulfoxide (SMCSO), which are sulfur-containing secondary metabolites. To optimize the quality of B. oleracea vegetables towards increased potential to release specific hydrolysis products from GLSs and SMCSO levels, these compounds were monitored over the harvest seasons of different B. oleracea cultivars in three consecutive years under field conditions. Proteome analysis was performed to correlate the formation of specific metabolites with underlying proteins involved in their formation.
DOI: 10.15468/dl.qde7fg
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xenogorgia Bayer & Muzik, 1976"
 ]
}

 The dataset includes 12 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093380-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.25707630
title: Criterios de búsqueda Granfluencers

description: Criterios de búsqueda en las bases de datos WoS y Scopus para seleccionar literatura relacionada con los creadores de contenido llamados granfluencers
DOI: 10.6084/m9.figshare.25707630.v1
title: Criterios de búsqueda Granfluencers

description: Criterios de búsqueda en las bases de datos WoS y Scopus para seleccionar literatura relacionada con los creadores de contenido llamados granfluencers
DOI: 10.15468/dl.avaj6n
title: Occurrence Download

description: A dataset containing 841 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Accipiter poliogaster (Temminck, 1824)"
 ]
}

 The dataset includes 841 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093382-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8yw4hz
title: Occurrence Download

description: A dataset containing 172 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Alfaroa mexicana D.E.Stone"
 ]
}

 The dataset includes 172 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093381-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.znjhq2
title: Occurrence Download

description: A dataset containing 119141 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Alytidae"
 ]
}

 The dataset includes 119141 records from 1443 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093378-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18668033
title: Data of Gamified Project-Based Learning in History Education: A Strategy to Enhance Students' Digital Literacy in the Digital Era
title: figure 1
title: figure 2

description: Background

Amid the ongoing development of digital literacy in Indonesia, the 2022 Indonesian Digital Literacy Index released by the Ministry of Communication and Information Technology indicates that the national level of digital literacy remains moderate. This condition highlights the need for innovative and pedagogically grounded strategies to enhance students’ digital literacy, particularly in history education, which often relies on conventional instructional approaches. Integrating gamification within project-based learning offers potential to foster active engagement and meaningful digital skill development.

Methods

This study employed a Research and Development (R&D) design to develop and validate a gamified project-based learning model in history education. Data were collected through questionnaires, classroom observations, focused group discussions (FGD), and expert validation surveys. Qualitative data were analyzed using interactive analysis techniques, including data reduction, data display, and conclusion drawing, while quantitative data were analyzed using percentage-based descriptive statistics. The sample consisted of 147 undergraduate students from history education programs at Universitas Pendidikan Indonesia, Yogyakarta State University, and Malang State University during the 2023/2024 academic year.

Results

The findings demonstrate that integrating game elements into project-based history learning guided by the TPACK (Technological Pedagogical and Content Knowledge) framework effectively enhances students’ digital literacy. Improvements were observed across four key dimensions: digital skills, digital ethics, digital security, and digital culture. Validation results indicated that the instructional design, project media quality, and student-developed game programs met satisfactory to high standards.

Conclusions

Gamified project-based learning represents a viable and effective instructional strategy for strengthening digital literacy in history education. The model supports the development of both technical competencies and responsible digital behavior, contributing to more holistic digital citizenship in higher education.
DOI: 10.15468/dl.jt5jpz
title: Occurrence Download

description: A dataset containing 152 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nananthus N.E.Br."
 ]
}

 The dataset includes 152 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007579-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eg9egf
title: Occurrence Download

description: A dataset containing 94 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Evodia meliaefolia (Hance ex Walp.) Benth."
 ]
}

 The dataset includes 94 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007581-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7v978d
title: Occurrence Download

description: A dataset containing 1248714 records in GBIF matching the query:
SELECT PRINTF('%04d-%02d', "year", "month") AS yearMonth, GBIF_EEARGCode(10000, decimalLatitude, decimalLongitude, COALESCE(coordinateUncertaintyInMeters, 10000)) AS eeaCellCode, basisOfRecord, datasetKey, countryCode, speciesKey, species, family, class, COUNT(*) AS occurrences FROM occurrence WHERE occurrenceStatus = 'PRESENT' AND continent = 'EUROPE' AND speciesKey IN (2978552, 2489005, 3190653, 2498252, 3084923, 2340977, 2706080, 2502792, 3170247, 2440934, 3129663, 2882443, 2437394, 2437399, 3189935, 5828232, 4284921, 2704521, 2482499, 2702865, 5329212, 2225776, 8909595, 8979506, 8971201, 5712056, 2350580, 2350570, 2984306, 6063677, 7287606, 3034825, 3628745, 3642949, 2984537, 7978544, 2891770, 8848208, 2865565, 9799308, 2394486, 8114276, 5855350, 2427091, 5421039, 5420991, 2650436, 2869311, 5289808, 2394604, 2440946, 4264680, 5361785, 5361762, 2433536, 5358460, 2434552, 5219858, 2498305, 2226990, 3086784, 2390064, 4033648, 2870583, 7965247, 2765942, 2227300, 9442269, 5218786, 2362868, 2977647, 2486131, 5824863, 5274863, 5219681, 5219683, 5035187, 5035230, 5035017, 2437450, 2480764, 2443002, 3054399, 6164088, 6247411, 1315391, 5217334) AND hasCoordinate = TRUE AND (coordinateUncertaintyInMeters &lt;= 10000 OR coordinateUncertaintyInMeters IS NULL) AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE') AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE') AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID') AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH') AND "month" IS NOT NULL GROUP BY yearMonth, eeaCellCode, basisOfRecord, datasetKey, countryCode, speciesKey, species, family, class ORDER BY yearMonth DESC, eeaCellCode ASC, countryCode ASC

 The dataset's 1248714 records were derived from 4442 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007559-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1376131.10fu
title: SH1376131.10FU

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/sh1376132.10fu
title: SH1376132.10FU

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/sh1376134.10fu
title: SH1376134.10FU

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/sh1376136.10fu
title: SH1376136.10FU

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/sh1376137.10fu
title: SH1376137.10FU

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/sh1376139.10fu
title: SH1376139.10FU

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.