cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25549/inscriptifact-ouc111120781
title: Votive tablet, UT 1599-23

description: [Text Description:] Votive tablet, temple offering. Same inscription as on cone [1599-4]. ❧ [Text or Publication Number Note:] UT 1599-23 ❧ [Excavation Description:] Warka ❧ [Medium:] Clay ❧ [Script Note:] Cuneiform, Non-Alphabetic ❧ [Physical Object Description:] Large clay tablet, dull beige-brown color. Fragile; chipped. 7 x 3.75cm.
DOI: 10.15468/dl.zrx83f
title: Occurrence Download

description: A dataset containing 19682 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pinus contorta Douglas ex Loudon"
 ]
}

 The dataset includes 19682 records from 210 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0202062-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111120914
title: Votive tablet, UT 1599-23

description: [Text Description:] Votive tablet, temple offering. Same inscription as on cone [1599-4]. ❧ [Text or Publication Number Note:] UT 1599-23 ❧ [Excavation Description:] Warka ❧ [Medium:] Clay ❧ [Script Note:] Cuneiform, Non-Alphabetic ❧ [Physical Object Description:] Large clay tablet, dull beige-brown color. Fragile; chipped. 7 x 3.75cm.
DOI: 10.34740/kaggle/dsv/8627217
title: BBC News
DOI: 10.15468/dl.zabbt3
title: Occurrence Download

description: A dataset containing 790 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "GadmGid is USA.10_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Elasmobranchii",
 "Year 2007-2022"
 ]
}

 The dataset includes 790 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0420784-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111356469
title: Scribal exercise: PNs + words, KTU 5.22

description: [Text Description:] Ugaritic Tablet KTU 5.22 ❧ [Text or Publication Number Note:] KTU 5.22; KTU2 5.22; KTU3 5.22; CTU 5.22; CAT 5.22; RS 26.135; DO 6772 ❧ [Excavation Description:] Found during excavations at Ras Shamra. ❧ [Medium:] Clay ❧ [Script Note:] Alphabetic Cuneiform
DOI: 10.25549/inscriptifact-ouc111329593
title: Latin Bible with Illuminations, MS.000158

description: [Text Description:] Latin Bible with Illuminations and Marginal Notes ❧ [Text or Publication Number Note:] MS.000158 ❧ [Medium:] Parchment ❧ [Script Note:] Gothic ❧ [Physical Object Description:] Folios approx. 15.7 x 24.5 cm. Two columns. ❧ [Physical Object Note:] Vellum with ink, red and black ❧ [Physical Object Note:] Illuminations, marginal notations, headings at top.
DOI: 10.15468/dl.k6cztv
title: Occurrence Download

description: A dataset containing 711006 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Chile",
 "DatasetKey is one of (iNaturalist Research-grade Observations, Programa de fotomonitoreo de objetos de conservación y amenazas en el Sistema Nacional de Áreas Protegidas (SNAP), Datos observacionales sobre biodiversidad Ministerio del Medio Ambiente 2015)",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 711006 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0062452-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pvv6nz
title: Occurrence Download

description: A dataset containing 119 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pelophylax shqipericus (Hotz, Uzzell, Günther, Tunner & Heppich, 1987)"
 ]
}

 The dataset includes 119 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0426797-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc112024768
title: Cuneiform Tablet 1913.14.1506, Spurlock 1913.14.1506

description: [Text Description:] Account concerning silver, barley, and refined bitumen ❧ [Text or Publication Number Note:] Spurlock 1913.14.1506; CDLI P421358 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Yellowish White (10YR 9/2) Light Brown (5YR 6.5/4) Dark Gray (N 3/ 6.6% R) ❧ [Physical Object Note:] 10.1 x 6.9 x 2.9 cm (213g)
DOI: 10.25549/inscriptifact-ouc111158509
title: A list of sacrifices, KTU 1.106

description: [Text Description:] List (sacrifices), ritual ❧ [Text or Publication Number Note:] KTU 1.106; KTU2 1.106; CTU 1.106; CAT 1.106; RS 24.250, 24.259; DO 6592 ❧ [Excavation Description:] Found during 1961 excavations at Ras Shamra. South Acropolis: RS 24.250 topographical point 3783 depth 3.45; RS 24.259 topographical point 3772 depth 3.20 ❧ [Medium:] Clay ❧ [Script Note:] Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet 122mm x 82mm; obverse is incomplete; reverse mostly complete ❧
DOI: 10.15468/dl.w6eagb
title: Occurrence Download

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pelophylax cypriensis Plötner, Baier, Akn, Mazepa, Schreiber, Beerli, Litvinchuk, Bilgin, Borkin & Uzzell, 2012"
 ]
}

 The dataset includes 53 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0426810-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111158490
title: Shirugazuz Learns the Risk of Snake-Charming, KTU 1.107, Incantation (snakes)

description: [Text Description:] Shapash and the gods collect the venom which the goddess of the sun will use to disperse the clouds that cover the earth ❧ [Text or Publication Number Note:] KTU 1.107; KTU2 1.107; CTU 1.107; CAT 1.107; RS 24.249, 24.251, 24.262, 24.265A, 24.267, 24.275; DO 6593 ❧ [Excavation Description:] Found during 1961 excavations at Ras Shamra. House of the Hurrian Priest, SA, Room 10: RS 24.251 topographical point 3751 depth 2.70; 24.262 topographical point 3784 depth 3.45; 24.265A topographical point 3751 depth 3.00 ❧ [Medium:] Clay ❧ [Script Note:] Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet; many fragments, text incomplete ❧
DOI: 10.15468/dl.7yb4sx
title: Occurrence Download

description: A dataset containing 146795 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gasterosteus aculeatus Linnaeus, 1758",
 "HasCoordinate is true"
 ]
}

 The dataset includes 146795 records from 431 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0202041-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1095911.10fu
title: SH1095911.10FU

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/sh1095913.10fu
title: SH1095913.10FU

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/sh1095914.10fu
title: SH1095914.10FU

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/sh1095915.10fu
title: SH1095915.10FU

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/sh1095918.10fu
title: SH1095918.10FU

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/sh1095919.10fu
title: SH1095919.10FU

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/sh1095920.10fu
title: SH1095920.10FU

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/sh1095923.10fu
title: SH1095923.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.18205661
title: Two-Stage Lightweight CNN with Weakly Supervised Defect Localization for Multimodal Photovoltaic Fault Detection

description: This repository contains three distinct photovoltaic (PV) datasets representing the full spectrum of solar fault detection: internal cell degradation (EL), thermal anomalies (IR), and surface-level obstructions (RGB). Each dataset includes both the Original (raw) images and the Refined (auto-annotated) versions generated by our Two-Stage Framework.

1. Electroluminescence (EL) PV Dataset





Modality: 8-bit Grayscale (Internal Inspection).




Purpose: Used to detect subsurface defects invisible to the naked eye, such as microcracks and electrical disconnects.




Content: The dataset comprises 2,624 images extracted from 44 distinct solar modules. It includes both monocrystalline (uniform background) and polycrystalline (complex grain boundary) cells.




Classes: Binary classification (Functional vs. Defective).




Challenge: The primary challenge is distinguishing actual microcracks from the jagged grain boundaries of polycrystalline cells, which often mimic defect patterns.



2. Thermal Infrared (IR) PV Dataset 





Modality: Thermal Infrared (Heat Anomaly Inspection).




Purpose: Used to identify heat-induced faults, such as hotspots and diode failures, captured via UAVs.




Content: A large-scale dataset of 20,000 thermal images.




Resolution: Extremely low native resolution ($40 \times 24$ pixels), presenting a significant challenge for feature extraction.




Classes: 12 Categories, including No-Anomaly, Hotspot, Hotspot-Multi, Diode, Diode-Multi, Shadowing, Cell, Cell-Multi, Cracking, Soiling, Vegetation, and Offline-Module.




Challenge: Extreme class imbalance (50% of data is "No-Anomaly") and spatial sparsity.



3. Aerial RGB PV Dataset 





Modality: Optical RGB (Surface Inspection).




Purpose: Used to classify surface-level obstructions and physical degradation visible from low-altitude drone flights.




Content: 875 high-resolution images acquired under varying outdoor lighting conditions.




Classes: 6 Categories: Clean, Dusty, Bird Drop, Electrical Damage, Physical Damage, and Snow-Covered.




Challenge: Distinguishing between transient environmental obstructions (e.g., bird drops, snow) and permanent physical damage (e.g., shattered glass) amidst complex ground clutter.





Dataset Structure in Zip Files







Original Datasets: Contain the raw images exactly as collected/standardized.




Refined Datasets: Contain the output of Phase 1 (Auto-Annotation). These images have been processed by the WSOL module to generate cropped or spatially focused regions of interest (ROI), removing background noise (e.g., roof tiles in RGB or grain boundaries in EL) to facilitate high-precision fine-tuning in Phase 2.
DOI: 10.5281/zenodo.18205662
title: Two-Stage Lightweight CNN with Weakly Supervised Defect Localization for Multimodal Photovoltaic Fault Detection

description: This repository contains three distinct photovoltaic (PV) datasets representing the full spectrum of solar fault detection: internal cell degradation (EL), thermal anomalies (IR), and surface-level obstructions (RGB). Each dataset includes both the Original (raw) images and the Refined (auto-annotated) versions generated by our Two-Stage Framework.

1. Electroluminescence (EL) PV Dataset





Modality: 8-bit Grayscale (Internal Inspection).




Purpose: Used to detect subsurface defects invisible to the naked eye, such as microcracks and electrical disconnects.




Content: The dataset comprises 2,624 images extracted from 44 distinct solar modules. It includes both monocrystalline (uniform background) and polycrystalline (complex grain boundary) cells.




Classes: Binary classification (Functional vs. Defective).




Challenge: The primary challenge is distinguishing actual microcracks from the jagged grain boundaries of polycrystalline cells, which often mimic defect patterns.



2. Thermal Infrared (IR) PV Dataset 





Modality: Thermal Infrared (Heat Anomaly Inspection).




Purpose: Used to identify heat-induced faults, such as hotspots and diode failures, captured via UAVs.




Content: A large-scale dataset of 20,000 thermal images.




Resolution: Extremely low native resolution ($40 \times 24$ pixels), presenting a significant challenge for feature extraction.




Classes: 12 Categories, including No-Anomaly, Hotspot, Hotspot-Multi, Diode, Diode-Multi, Shadowing, Cell, Cell-Multi, Cracking, Soiling, Vegetation, and Offline-Module.




Challenge: Extreme class imbalance (50% of data is "No-Anomaly") and spatial sparsity.



3. Aerial RGB PV Dataset 





Modality: Optical RGB (Surface Inspection).




Purpose: Used to classify surface-level obstructions and physical degradation visible from low-altitude drone flights.




Content: 875 high-resolution images acquired under varying outdoor lighting conditions.




Classes: 6 Categories: Clean, Dusty, Bird Drop, Electrical Damage, Physical Damage, and Snow-Covered.




Challenge: Distinguishing between transient environmental obstructions (e.g., bird drops, snow) and permanent physical damage (e.g., shattered glass) amidst complex ground clutter.





Dataset Structure in Zip Files







Original Datasets: Contain the raw images exactly as collected/standardized.




Refined Datasets: Contain the output of Phase 1 (Auto-Annotation). These images have been processed by the WSOL module to generate cropped or spatially focused regions of interest (ROI), removing background noise (e.g., roof tiles in RGB or grain boundaries in EL) to facilitate high-precision fine-tuning in Phase 2.
DOI: 10.15156/bio/sh1095926.10fu
title: SH1095926.10FU

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/sh1095927.10fu
title: SH1095927.10FU

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.