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

description: A dataset containing 2390507 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Données piscicoles et astacicoles des cours d'eau de France métropolitaine bancarisées dans ASPE (OFB) - Données acquises selon le protocole de pêche partielle par points - ASPE - OFB",
 {
 "or" : [
 "Geometry POLYGON((-15.64723 38.74421,20.64723 38.74421,20.64723 53.25579,-15.64723 53.25579,-15.64723 38.74421))",
 "Geometry POLYGON((2.96555 47.12606,2.98094 46.89513,2.92962 46.80019,3.00147 46.67446,3.14516 46.60774,3.21957 46.45635,3.29655 46.21515,3.23754 45.95086,3.14773 45.70196,3.31965 45.71223,3.45564 45.81487,3.53262 45.95856,3.50439 46.11765,3.43255 46.34088,3.40176 46.52306,3.29142 46.65906,3.15286 46.81302,3.28116 46.91822,3.19135 47.04395,2.96555 47.12606))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2390507 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004101-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6uzvuy
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Hoplostethus tenebricus"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004105-260226173443078/datasets/export for details.
DOI: 10.5281/zenodo.18813188
title: THE INTEGRATION OF ARTIFICIAL INTELLIGENCE IN EDUCATION: OPPORTUNITIES, EFFECTIVENESS, AND FUTURE PROSPECTS

description: The integration of artificial intelligence in education represents a transformative shift that is reshaping teaching, learning, and academic management. This study examines the opportunities, effectiveness, and future prospects of artificial intelligence within modern educational systems. Artificial intelligence enables personalized learning by analyzing student performance and adapting instructional content to individual needs, thereby improving engagement, motivation, and learning outcomes. It also enhances educational effectiveness through the automation of assessment, intelligent tutoring systems, and data-driven decision-making, allowing educators to focus on higher-level pedagogical activities. Furthermore, artificial intelligence promotes inclusive and accessible education by supporting learners with diverse needs and expanding remote learning opportunities. Despite these advantages, challenges related to data privacy, ethical considerations, and the evolving role of teachers remain significant. The study highlights that artificial intelligence should function as a supportive tool rather than a replacement for educators, emphasizing the importance of responsible implementation and digital competence. Future developments in artificial intelligence are expected to foster more adaptive, immersive, and lifelong learning environments, ultimately transforming the structure and philosophy of education.
DOI: 10.5281/zenodo.18813187
title: THE INTEGRATION OF ARTIFICIAL INTELLIGENCE IN EDUCATION: OPPORTUNITIES, EFFECTIVENESS, AND FUTURE PROSPECTS

description: The integration of artificial intelligence in education represents a transformative shift that is reshaping teaching, learning, and academic management. This study examines the opportunities, effectiveness, and future prospects of artificial intelligence within modern educational systems. Artificial intelligence enables personalized learning by analyzing student performance and adapting instructional content to individual needs, thereby improving engagement, motivation, and learning outcomes. It also enhances educational effectiveness through the automation of assessment, intelligent tutoring systems, and data-driven decision-making, allowing educators to focus on higher-level pedagogical activities. Furthermore, artificial intelligence promotes inclusive and accessible education by supporting learners with diverse needs and expanding remote learning opportunities. Despite these advantages, challenges related to data privacy, ethical considerations, and the evolving role of teachers remain significant. The study highlights that artificial intelligence should function as a supportive tool rather than a replacement for educators, emphasizing the importance of responsible implementation and digital competence. Future developments in artificial intelligence are expected to foster more adaptive, immersive, and lifelong learning environments, ultimately transforming the structure and philosophy of education.
DOI: 10.34740/kaggle/dsv/14991809
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5517/ccdc.csd.cc2m2tr9
title: CCDC 2415791: Experimental Crystal Structure Determination

description: Related Article: Juan Pan, Gang-Tao Bu, Si-Yi Wang, Jia-Tong Wu, Meng-Meng Li, Wei Guan, Qing-Shan Chen, Li-Li Zhang, Xiao-Chi Ma, Hai-Xue Kuang, Yan Liu||Phytochemistry|247||doi:10.1016/j.phytochem.2026.114845
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2m6l3k
title: CCDC 2419398: Experimental Crystal Structure Determination

description: Related Article: Rahul Kumar Singh, Dilip Sarkar, Upeshna Timsina, Saranita Roy Chowdhury, Arpita Das, Anoop Kumar, Muthukumari Muthaiyan, Palash Sanphui, Rajesh Kumar Das|2026|Comput. Biol. Med.|205||doi:10.1016/j.compbiomed.2026.111597
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2kgplb
title: CCDC 2367612: Experimental Crystal Structure Determination

description: Related Article: Darakhshan Parveen, Avadhesh Pratap Singh, Alok Kumar Verma, Abhishek Kumar, Divya Pratap Singh, Suryabhan Singh, Ashish Kumar Singh, Shrishila N. Unki, Gurushantappa Kadakol||J.Organomet.Chem.|||doi:10.1016/j.jorganchem.2026.124097
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.nk84tj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Hoplostethus rubellopterus"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004106-260226173443078/datasets/export for details.
DOI: 10.5281/zenodo.18763222
title: Dataset for the "Psychometric Evaluation of A Creative Thinking Performance Test for Science Education"

description: This dataset contains respondents’ scores and supporting metadata for an essay-based creative thinking assessment in science education on the topic “Biomass-Based Renewable Energy.” The Excel file includes participant codes (e.g., MHS1, MHS2), demographic information (gender) and institution code (A/B), item-level scores for 8 essay questions, and the mean score per respondent.

The eight items were developed to measure four creative thinking dimensions: Sensitivity (Items 1–2), Flexibility (Items 3–4), Novelty/Originality (Items 5–6), and Elaboration (Items 7–8). Responses were scored using an analytic rubric with a 0–4 scale for each dimension. The accompanying metadata file provides the full item indicators, question prompts, and the scoring rubric.

Participants were undergraduate students in a Primary School Teacher Education program enrolled in the course Basic Concepts of Natural Science at two public universities in Aceh and North Sumatra, Indonesia. Data were collected during April–May 2025. All records are anonymized and do not contain personal identifiers.

Files included:





Excel dataset (item scores and respondent-level mean scores)




Extended data document (instrument description, item indicators, and scoring rubric)
DOI: 10.5281/zenodo.18763221
title: Dataset for the "Psychometric Evaluation of A Creative Thinking Performance Test for Science Education"

description: This dataset contains respondents’ scores and supporting metadata for an essay-based creative thinking assessment in science education on the topic “Biomass-Based Renewable Energy.” The Excel file includes participant codes (e.g., MHS1, MHS2), demographic information (gender) and institution code (A/B), item-level scores for 8 essay questions, and the mean score per respondent.

The eight items were developed to measure four creative thinking dimensions: Sensitivity (Items 1–2), Flexibility (Items 3–4), Novelty/Originality (Items 5–6), and Elaboration (Items 7–8). Responses were scored using an analytic rubric with a 0–4 scale for each dimension. The accompanying metadata file provides the full item indicators, question prompts, and the scoring rubric.

Participants were undergraduate students in a Primary School Teacher Education program enrolled in the course Basic Concepts of Natural Science at two public universities in Aceh and North Sumatra, Indonesia. Data were collected during April–May 2025. All records are anonymized and do not contain personal identifiers.

Files included:





Excel dataset (item scores and respondent-level mean scores)




Extended data document (instrument description, item indicators, and scoring rubric)
DOI: 10.5281/zenodo.18813186
title: DEVELOPMENT OF ARTIFICIAL INTELLIGENCE SMART HOME SECURITY SYSTEM

description: This article discusses the development of a smart home security system based on artificial intelligence based on modern information technologies and the concept of the "Internet of Things" (IoT). The author analyzes the shortcomings of traditional security systems and shows the advantages of mechanisms for face recognition, detection of unusual movements and real-time decision-making using artificial intelligence algorithms. The stages of the system's operation are also described in detail, from data collection to automatic response measures.
DOI: 10.5281/zenodo.18813185
title: DEVELOPMENT OF ARTIFICIAL INTELLIGENCE SMART HOME SECURITY SYSTEM

description: This article discusses the development of a smart home security system based on artificial intelligence based on modern information technologies and the concept of the "Internet of Things" (IoT). The author analyzes the shortcomings of traditional security systems and shows the advantages of mechanisms for face recognition, detection of unusual movements and real-time decision-making using artificial intelligence algorithms. The stages of the system's operation are also described in detail, from data collection to automatic response measures.
DOI: 10.15468/dl.44ceth
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Hoplostethus confinis"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004107-260226173443078/datasets/export for details.
DOI: 10.5064/f6bktttt/7wsdhj
title: Posner-Quaglia_DataNarrative.pdf
DOI: 10.5064/f6bktttt/n53z0d
title: Posner-Quaglia_Dataset_Integrationism_202503.pdf
DOI: 10.5064/f6bktttt/pqmrfk
title: README_Posner-Quaglia.txt
DOI: 10.15468/dl.3gmbp8
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sieruela hirta",
 "Country is Madagascar",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079215-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25446/oxford.29637653
title: Saqqara, dipinto, 19th-20th Dynasty (see100115)

description: Djoser Pyramid Complex North Chapel, loose block, 19th Dynasty. Image copyright - Griffith Institute Archive
DOI: 10.25446/oxford.29637653.v1
title: Saqqara, dipinto, 19th-20th Dynasty (see100115)

description: Djoser Pyramid Complex North Chapel, loose block, 19th Dynasty. Image copyright - Griffith Institute Archive
DOI: 10.15468/dl.26ht6t
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Monomorium destructor",
 "Country is Palau",
 "HasCoordinate is true"
 ]
}

 The dataset includes 34 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079216-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/6nt-9t4-dt9
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ymw-wp0-ec8
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/6et-a13-0vq
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/s93-3qd-dv3
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/fqs-lev-7qn
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/0m1-28d-y16
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/n5r-dcs-lkg
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/lgd-end-44x
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/yv3-6vs-t0g
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7gb-5sf-lpz
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/d0y-80r-sn5
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/c4t-20s-8ef
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/gex-dwk-wpa
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/fen-fhz-4aj
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/hn2-atf-66b
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/48r-6qr-tzt
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/vj2-p7p-3he
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/28a-qgb-rvq
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/m2c-g8n-rdp
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/gxl-8r2-p43
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/k7d-twq-8aa
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7k2-9g6-rva
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/l8k-qmr-2a5
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/vkd-5r7-yyn
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/b17-vt2-gkm
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/tz0-njq-lnt
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/apn-75s-dsb
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ye4-0ed-a2e
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/rlm-m8z-sn1
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ssh-skc-22q
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/1s6-5rb-098
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/s37-yt9-mmn
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.15468/dl.t6zgb5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Scapania jensenii)",
 "Country is one of (Norway)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1986",
 "Year is less than or equal to 2025",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Machine Observation"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025896-260208012135463/datasets/export for details.
DOI: 10.15156/bio/sh1791838.10fu
title: SH1791838.10FU

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: 10.25345/c53x8403w
title: MassIVE MSV000100452 - Conditional Ank Mouse Plasma Untargeted Metabolomic Data
title: We collected and subjected plasma samples from 12 week old male and female mice (male Ank+/+: n=10, male AnkKI/KI: n=8, female Ank+/+: n=8, female AnkKI/KI: n=5) for untargeted metabolomics analysis. Metabolites were isolated using a methanol liquid phase extraction (methanol/plasma 4:1 ratio) and a simultaneous protein precipitation protocol. The dried extracts were then reconstituted in 0.1% formic acid in water to normalize the sample concentration at 10 mg/mL. The samples were then centrifuged at 12,500 rpm for 10 min, and the supernatant was transferred to an LCMS vial (Waters Corp., MA) for untargeted metabolomics analysis. The samples were analyzed via tandem mass spectrometry on a Xevo G2 XS UPLC MS/MS (ultra high performance liquid chromatography tandem mass spectrometry) instrument (Waters Corporation) operated in both positive and negative electrospray ionization modes. Chromatographic separations were performed using an Acquity UPLC HSS T3 column (150 x 2.1 mm, 1.8 um particle size) (Waters Corp., MA) maintained at 40C. Water and acetonitrile, both containing 0.1% formic acid were used as solvents A and B respectively; and water and acetonitrile, both with 10 mM triethylammonium acetate were used as solvents C and D respectively. The injection volume was 10 uL. The mobile phase gradient at 0.3 mL/min was maintained as follows, 0 to 0.5 min: 5% B/D; 8.5 to 9 min: 98% B/D; and 9.25 to 12.5 min: 5% B/D. The mass range for MS and MS2 acquisitions were 110 to 2000 Da and 50 to 2000 Da, respectively. Leucine enkephalin at 400 pg/uL was used for real-time mass correction. A collision energy ramp of 4 to 40 V was applied for MS2 acquisition. The UPLC MS/MS raw data files were analyzed via Progenesis QI software (v 2.4, Waters Corporation) to perform retention time alignment, peak picking, cross sample normalization, and adduct deconvolution.