cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18334502
title: NP-LankaPaddy

description: The NP-LankaPaddy dataset is an openly accessible, in-field paddy leaf disease image dataset collected under real cultivation conditions in Northern Province of Sri Lanka. It comprises 2,002 RGB images representing four major paddy leaf diseases: brown spot, rice blast, sheath blight, and leaf streak. The images were captured under natural field conditions across four districts in the Northern Province of Sri Lanka: Jaffna, Mannar, Kilinochchi, and Mullaitivu during the two main rice-growing seasons, namely the Maha season (September–March; 1,667 images) and the Yala season (April–August; 335 images).

The dataset includes samples from commonly cultivated rice varieties such as Aattakkari, BG406, BG360, and BG300. Image acquisition was performed using mobile phone cameras (iPhone 14 and Samsung Galaxy A54) rather than professional imaging equipment, in order to reflect realistic and practical deployment scenarios. The NP-LankaPaddy dataset exhibits high diversity, encompassing images captured from varied viewing angles, under different lighting conditions, and with diverse backgrounds and environmental variations, without any artificial filtering or post-capture alterations. This diversity ensures that the dataset closely reflects real-world field conditions. Following acquisition, all images were resized to a uniform resolution of 768 × 1024 pixels. The dataset is organised into training (1,400 images) and testing (602 images) subsets.
DOI: 10.5281/zenodo.18334503
title: NP-LankaPaddy

description: The NP-LankaPaddy dataset is an openly accessible, in-field paddy leaf disease image dataset collected under real cultivation conditions in Northern Province of Sri Lanka. It comprises 2,002 RGB images representing four major paddy leaf diseases: brown spot, rice blast, sheath blight, and leaf streak. The images were captured under natural field conditions across four districts in the Northern Province of Sri Lanka: Jaffna, Mannar, Kilinochchi, and Mullaitivu during the two main rice-growing seasons, namely the Maha season (September–March; 1,667 images) and the Yala season (April–August; 335 images).

The dataset includes samples from commonly cultivated rice varieties such as Aattakkari, BG406, BG360, and BG300. Image acquisition was performed using mobile phone cameras (iPhone 14 and Samsung Galaxy A54) rather than professional imaging equipment, in order to reflect realistic and practical deployment scenarios. The NP-LankaPaddy dataset exhibits high diversity, encompassing images captured from varied viewing angles, under different lighting conditions, and with diverse backgrounds and environmental variations, without any artificial filtering or post-capture alterations. This diversity ensures that the dataset closely reflects real-world field conditions. Following acquisition, all images were resized to a uniform resolution of 768 × 1024 pixels. The dataset is organised into training (1,400 images) and testing (602 images) subsets.
DOI: 10.5281/zenodo.18617948
title: Data and code used for the SSRB river synchrony manuscript

description: Please check the README.txt in the zip folder.
DOI: 10.5281/zenodo.18617947
title: Data and code used for the SSRB river synchrony manuscript

description: Please check the README.txt in the zip folder.
DOI: 10.71955/duedata-2026-mlf2kz1i
title: Iterations for active sampling in inelastic neutron scattering

description: &lt;p&gt;We combine Linear Spin Wave Theory with active-learning sampling, resulting in a Kalman Filter enhanced Adversarial Bayesian Optimization (KFABO) algorithm. This algorithm approximates the magnon spectrum using a minimal number of sampling points and iterations. Despite the limited iterations, the algorithm effectively addresses noisy neutron scattering data, providing reliable magnetic interactions that replicate the experimental spectra for 2D CrSBr. It can also reveal hidden or weak interactions, such as those induced by spin-orbit coupling.&lt;/p&gt;
&lt;p&gt;The attached files illustrate the sampling process during different iteration scenarios. "Theoretical_SPINW_woDMI.gif" shows the iterations for the case including only Heisenberg exchange (J) interactions. "Theoretical_SPINW_wDMI.gif" displays iterations for the case including both Dzyaloshinskii-Moriya interactions (DMI) and Heisenberg exchange interactions. Finally, "Experimental_SPINW_wDMI.gif" represents the iterations during the fitting of the experimental spin wave data.&lt;/p&gt;
&lt;b&gt;Methods&lt;/b&gt;
&lt;p&gt;We combine Linear Spin Wave Theory (LSWT), Active Learning Sampling, and Adaptive Noise Reduction to form the Kalman Filter enhanced Adversarial Bayesian Optimization Algorithm (KFABO). This algorithm integrates two coupled Bayesian Optimization (BO) algorithms with a Kalman filter. The first BO algorithm, termed fBO, employs trust region Bayesian optimization (Turbo) on our linear response model to search for optimal parameters, aiming to minimize the difference between theoretically predicted and real LSW function values of the measured sample points. The second algorithm, termed sBO, is a standard BO that selects sampling points with maximum information gain relative to the current state, specifically, those points that can better characterize the real LSW function given the current samples and the fitted LSW function.&lt;/p&gt;
description: Funding:
Federal Ministry of Education and Research of Germany in the framework of the Palestinian-German Science Bridge (BMBF grant number 01DH16027).
Priority Programmes SPP 2244 "2D Materials Physics of van der Waals heterobilayer"  (project LO 1659/7-1)
SPP 2137 “Skyrmionics” (Projects LO 1659/8-1) of the Deutsche Forschungsgemeinschaft (DFG)
Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 405553726 - TRR 270.
Federal Ministry of Education and Research, and the state governments participating on the basis of the resolutions of the GWK for national high performance computing at universities (www.nhr-verein.de/unsere-partner).
DOI: 10.15468/jgm7ci
title: Wider Countryside Butterfly Scheme (WCBS)

description: The Wider Countryside Butterfly Survey is part of the UK Butterfly Monitoring Scheme (UKBMS). The WCBS is a standarised monitoring scheme for monitoring widespread butterflies in the UK. It is based on sampling along transects within 1km squares selected at random across the UK (stratified by BTO or BC regional networks). Additional UKBMS data from traditional fixed transect sites, often called 'Pollard Walks' is available within a separate dataset – see https://registry.nbnatlas.org/public/show/dr1206.

The surveys are undertaken by volunteers and other recorders, who contribute their data free of charge. Where you use the information you must acknowledge the UKBMS using the following attribution statement: Contains UK Butterfly Monitoring Scheme (UKBMS) data © copyright and database right Butterfly Conservation, the Centre for Ecology & Hydrology, British Trust for Ornithology, and the Joint Nature Conservation Committee.
DOI: 10.15468/aqe7ua
title: Caddisfly (Trichoptera) records from Britain (excluding Northern Ireland and Channel Islands) up to July 2024 from the National Trichoptera (Caddisfly) Recording Scheme

description: The Trichoptera dataset was assembled by the UK Trichoptera (Caddisfly) Recording Scheme. The scheme is linked to those for Mayflies and Stoneflies under the umbrella of the Riverfly Recording Schemes which is one of the Biological Records Centre family of schemes. 

The data comes from a wide range of sources ranked in terms of contribution: volunteer recorders; statutory monitoring bodies, especially the Environment Agency; national and local entomological and natural history publications and ‘grey’ literature; museum collections; local record centres; consultants. 

The principal aim of the Caddisfly Recording Scheme is to collate all available caddis records to produce comprehensive distribution maps and conservation reviews. Several of the data sets it contains are independently submitted to the NBN and an effort was made to exclude those from this download.

The data set contains duplicate records where the same record has arrived from different sources, e.g. as an entry in a collector’s notebook then as a collated list and possibly then as a published record. 

The data base is only set up to take data at up to 8 figure grid reference resolution but more detailed data is available for a few records and can be requested from the scheme organiser.
Additional information about individual records is sometimes available and can be requested from the scheme organiser.
DOI: 10.15468/i46are
title: All taxa records for Leicestershire and Rutland

description: Data collected from local naturalists through NatureSpot's recording website since its establishment in 2009. Records include some data collected prior to 2009 but submitted post 2009. The dataset includes over 120,000 records of over 5,000 species and covering most taxon groups, all from Leicestershire and Rutland.
Additional_information
DOI: 10.6084/m9.figshare.31323169
title: Datasets on the impacts of straw and biochar amendments on soil properties and N<sub>2</sub>O emissions in a subtropical forest soil

description: We conducted an 80-day controlled microcosm experiment to investigate how straw and biochar amendments influence soil physicochemical properties and N<sub>2</sub>O emissions in a subtropical forest soil.
DOI: 10.6084/m9.figshare.31323169.v1
title: Datasets on the impacts of straw and biochar amendments on soil properties and N<sub>2</sub>O emissions in a subtropical forest soil

description: We conducted an 80-day controlled microcosm experiment to investigate how straw and biochar amendments influence soil physicochemical properties and N<sub>2</sub>O emissions in a subtropical forest soil.
DOI: 10.6084/m9.figshare.31323178
title: <b>Soil salinity mapping of oasis farmland using hybrid deep learning and texture normalization</b>

description: Soil salinization in arid oases reduces farmland productivity and requires high-precision remote sensing monitoring. However, texture-induced scattering hinders accurate soil salinity mapping. This dataset supports a hybrid deep learning framework that combines a texture normalization strategy (TNS) with multi-temporal, multi-source remote sensing imagery and environmental covariates to map soil salinity in oasis farmland.<b>Contents.</b> The repository provides (i) field observations of soil salinity (and related soil properties where available), (ii) multi-temporal remote sensing predictors derived from satellite imagery, (iii) environmental covariates (e.g., terrain, climate, land surface conditions), and (iv) code/metadata needed to reproduce data preprocessing and model training/evaluation.<b>Data organization.</b> Files are organized into folders including <code>data/</code> (tabular samples and/or raster predictors), <code>metadata/</code> (variable definitions, units, coordinate reference system, missing-value rules), <code>code/</code> (scripts for preprocessing and modeling), and <code>docs/</code> (README and usage notes). A README file documents variable meanings, units, spatial reference (EPSG/projection), spatial resolution, temporal coverage, and the recommended workflow for reproduction.<b>Usage.</b> The dataset can be used to (1) reproduce the experiments reported in the associated study, (2) benchmark alternative machine learning/deep learning models under consistent inputs, and (3) support follow-up research on soil salinity mapping in arid agro-ecosystems.<b>Licence and notes.</b> The data are released under <b>CC BY 4.0</b>. If point locations are included, any sensitive information has been anonymized or spatially generalized to protect privacy and field-site security.
DOI: 10.6084/m9.figshare.31323178.v1
title: <b>Soil salinity mapping of oasis farmland using hybrid deep learning and texture normalization</b>

description: Soil salinization in arid oases reduces farmland productivity and requires high-precision remote sensing monitoring. However, texture-induced scattering hinders accurate soil salinity mapping. This dataset supports a hybrid deep learning framework that combines a texture normalization strategy (TNS) with multi-temporal, multi-source remote sensing imagery and environmental covariates to map soil salinity in oasis farmland.<b>Contents.</b> The repository provides (i) field observations of soil salinity (and related soil properties where available), (ii) multi-temporal remote sensing predictors derived from satellite imagery, (iii) environmental covariates (e.g., terrain, climate, land surface conditions), and (iv) code/metadata needed to reproduce data preprocessing and model training/evaluation.<b>Data organization.</b> Files are organized into folders including <code>data/</code> (tabular samples and/or raster predictors), <code>metadata/</code> (variable definitions, units, coordinate reference system, missing-value rules), <code>code/</code> (scripts for preprocessing and modeling), and <code>docs/</code> (README and usage notes). A README file documents variable meanings, units, spatial reference (EPSG/projection), spatial resolution, temporal coverage, and the recommended workflow for reproduction.<b>Usage.</b> The dataset can be used to (1) reproduce the experiments reported in the associated study, (2) benchmark alternative machine learning/deep learning models under consistent inputs, and (3) support follow-up research on soil salinity mapping in arid agro-ecosystems.<b>Licence and notes.</b> The data are released under <b>CC BY 4.0</b>. If point locations are included, any sensitive information has been anonymized or spatially generalized to protect privacy and field-site security.
DOI: 10.25835/vwaa7o0s
title: Code Supplement: Robust stability of event-triggered nonlinear moving horizon estimation

description: This dataset contains the MATLAB code for the simulations in " Robust stability of event-triggered nonlinear moving horizon estimation"
DOI: 10.71955/duedata-2026-mlf091yh
title: Data associated with the publication "Temperature-dependent magnetocrystalline anisotropy of Fe2AlB2 single crystals"

description: &lt;p&gt;This dataset was created to determine the temperature-dependence of the magnetocrystalline anisotropy constants of Fe&lt;sub&gt;2&lt;/sub&gt;AlB. The dataset includes data from magnetometry and ferromagnetic resonance measurements on Fe&lt;sub&gt;2&lt;/sub&gt;AlB&lt;sub&gt;2&lt;/sub&gt; single crystals. The dataset was produced experimentally and post-processed with Origin and Mathematica.&lt;/p&gt;
&lt;b&gt;Methods&lt;/b&gt;
&lt;p&gt;The magnetometry measurements were conducted using a custom-built insert for the VSM option of a Quantum Design PPMS-14T system. Temperature was monitored with a Cernox CX-1050-BC resistive temperature sensor. The ferromagnetic resonance measurements were conducted using a custom-built insert for a Quantum Design PPMS DynaCool system consisting of a coplanar waveguide (CPW) connected to two semi-rigid coaxial cables. The FMR microwave absorption was detected via a Keysight N5227B PNA vector network analyzer (VNA). Temperature was monitored with a Cernox CX-1050-SD.&lt;/p&gt;
description: Funding: German Research Foundation (DFG) within the Collaborative Research
Center/Transregio (CRC/TRR) 270 HoMMage (Project-No. 405553726, subprojects B02, A04, B01).
DOI: 10.15468/dl.jhmttz
title: Occurrence Download

description: A dataset containing 362 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DecimalLatitude is -34.7681210190346,-34.6241657521494",
 "DecimalLongitude is 19.4891247990648,19.6594670358124",
 "TaxonKey is one of (Mammalia, Amphibia, Squamata, Testudines, Crocodylia)"
 ]
}

 The dataset includes 362 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010828-260208012135463/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.31283989.v1
title: <b>Examining the infographic design instructional process</b>

description: <b>Examining the infographic design instructional process</b>
DOI: 10.15468/dl.ccfhxd
title: Occurrence Download

description: A dataset containing 429 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eurema hecabe, Curetis acuta, Brachydiplax chalybea)",
 "Country is Korea, Republic of",
 "HasCoordinate is true"
 ]
}

 The dataset includes 429 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010836-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nusd7s
title: Occurrence Download

description: A dataset containing 4907 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DecimalLatitude is -27.1040415473263,-26.9868257257771",
 "DecimalLongitude is 26.5198515965957,26.7931931591592"
 ]
}

 The dataset includes 4907 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010834-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mxuqsa
title: Occurrence Download

description: A dataset containing 104 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)"
 ]
 }
 },
 "Year is greater than or equal to 1900",
 "TaxonKey is Cyperus angustatus"
 ]
}

 The dataset includes 104 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010830-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3phc4f
title: Occurrence Download

description: A dataset containing 2278 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bomarea edulis",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 2278 records from 189 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010829-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bj54u2
title: Occurrence Download

description: A dataset containing 1294 species occurrences available in GBIF matching the query:
{
 "and" : [
 "VerbatimScientificName is Tachycineta euchrysea",
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Year 2011-2021",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen, Material citation, Material sample)"
 ]
 }
 }
 ]
}

 The dataset includes 1294 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0086707-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc112017691
title: Cuneiform Tablet 1913.14.0254, Spurlock 1913.14.0254

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.0254; CDLI P420636 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Yellowish Gray (10YR 8.5/1) Brownish Pink (5YR 8/3) Dark Gray to Black (N 2.5/ 4.6% R) -discoloration ❧ [Physical Object Note:] 5 x 4.7 x 2.4 cm (71g) ❧ [Physical Object Note:] Seal impressions
DOI: 10.15468/dl.py2k97
title: Occurrence Download

description: A dataset containing 15553 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Quercus agrifolia Née"
 ]
}

 The dataset includes 15553 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0259215-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5sg6df
title: Occurrence Download

description: A dataset containing 11396 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is PELD-ELPA Species composition and abundance patterns of fish assemblages at shallow waters of Patos Lagoon estuary"
 ]
}

 The dataset includes 11396 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0398736-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc112043966
title: Cuneiform Tablet 1913.14.0146, Spurlock 1913.14.0146

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.0146; CDLI P420527 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Pale Orange Yellow (10YR 8/3) ❧ [Physical Object Note:] 8.2x4.9 x 2.5 cm (110g)
DOI: 10.15468/dl.w5kq88
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pabstiella transparens (Schltr.) Luer"
 ]
}

 The dataset includes 17 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0086710-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc112043967
title: Cuneiform Tablet 1913.14.0146, Spurlock 1913.14.0146

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.0146; CDLI P420527 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Pale Orange Yellow (10YR 8/3) ❧ [Physical Object Note:] 8.2x4.9 x 2.5 cm (110g)
DOI: 10.25549/inscriptifact-ouc112043926
title: Cuneiform Tablet 1913.14.0169, Spurlock 1913.14.0169

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.0169; CDLI P420550 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Yellowish White (10YR 9/2) Brownish Pink (5YR 8/3) ❧ [Physical Object Note:] 7.5 x 4.5 x 2.3 cm (82g) ❧ [Physical Object Note:] Seal impressions
DOI: 10.25549/inscriptifact-ouc112043969
title: Cuneiform Tablet 1913.14.0146, Spurlock 1913.14.0146

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.0146; CDLI P420527 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Pale Orange Yellow (10YR 8/3) ❧ [Physical Object Note:] 8.2x4.9 x 2.5 cm (110g)
DOI: 10.25549/inscriptifact-ouc112046544
title: Cuneiform Tablet 1913.14.0222, Spurlock 1913.14.0222

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.0222; CDLI P420604 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Yellowish Gray (2.5Y 8/2) ❧ [Physical Object Note:] 3.4 x 3.2 x 1.9 cm (25g) ❧ [Physical Object Note:] Seal impressions
DOI: 10.25549/inscriptifact-ouc112046494
title: Cuneiform Tablet 1913.14.0222, Spurlock 1913.14.0222

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.0222; CDLI P420604 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Yellowish Gray (2.5Y 8/2) ❧ [Physical Object Note:] 3.4 x 3.2 x 1.9 cm (25g) ❧ [Physical Object Note:] Seal impressions