cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18163411
title: Music Interaction Dataset

description: This dataset captures real-world music listening behaviors and contextual metadata from January 2021 to January 2025, sampled at 30-minute intervals. It reflects the streaming activity of 50 anonymized users across a variety of devices and locations. Designed to support the development of intelligent music recommendation systems, this dataset offers rich contextual information suitable for personalization, behavioral analysis, sentiment modeling, and federated learning applications.

Each record represents a user-song interaction and is timestamped with detailed user metadata, song descriptors, audio features, emotional indicators, and session-level dynamics. The dataset is especially useful for tasks such as preference prediction, session-based recommendation, genre classification, and user intent modeling.

Feature Overview

User Profile: user_id, age, gender, location, subscription_type, device_type

Behavioral Patterns: listening_time_mins, sessions_per_day, time_of_day, day_of_week, recent_skip_rate, first_time_listening

User Preferences: preferred_genre, preferred_artist, repeat_count, added_to_playlist, finished_song

Content Metadata: song_id, title, artist, album, genre, release_year, language, duration_sec, explicit, popularity

Audio Features: tempo, key, mode, time_signature, energy, danceability, acousticness, instrumentalness, liveness, valence, loudness, speechiness

Sentiment and Emotion: lyrics_sentiment, emotion_tag

Interaction Logs: play_count, skip_count, time_spent_on_song

Session-Level Context: context_type, song_position_in_session, session_duration_mins

Target Label: liked (1 if user liked the song, 0 if skipped)
DOI: 10.13145/bacdive18838.20251217.10
title: Sorangium cellulosum

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0086326.10fu
title: SH0086326.10FU

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.18163410
title: Music Interaction Dataset

description: This dataset captures real-world music listening behaviors and contextual metadata from January 2021 to January 2025, sampled at 30-minute intervals. It reflects the streaming activity of 50 anonymized users across a variety of devices and locations. Designed to support the development of intelligent music recommendation systems, this dataset offers rich contextual information suitable for personalization, behavioral analysis, sentiment modeling, and federated learning applications.

Each record represents a user-song interaction and is timestamped with detailed user metadata, song descriptors, audio features, emotional indicators, and session-level dynamics. The dataset is especially useful for tasks such as preference prediction, session-based recommendation, genre classification, and user intent modeling.

Feature Overview

User Profile: user_id, age, gender, location, subscription_type, device_type

Behavioral Patterns: listening_time_mins, sessions_per_day, time_of_day, day_of_week, recent_skip_rate, first_time_listening

User Preferences: preferred_genre, preferred_artist, repeat_count, added_to_playlist, finished_song

Content Metadata: song_id, title, artist, album, genre, release_year, language, duration_sec, explicit, popularity

Audio Features: tempo, key, mode, time_signature, energy, danceability, acousticness, instrumentalness, liveness, valence, loudness, speechiness

Sentiment and Emotion: lyrics_sentiment, emotion_tag

Interaction Logs: play_count, skip_count, time_spent_on_song

Session-Level Context: context_type, song_position_in_session, session_duration_mins

Target Label: liked (1 if user liked the song, 0 if skipped)
DOI: 10.15468/dl.9cf6zz
title: Occurrence Download

description: A dataset containing 44419 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 {
 "or" : [
 "Geometry POLYGON((-62.52784 11.39778,-57.5432 11.39778,-57.5432 18.58363,-62.52784 18.58363,-62.52784 11.39778))",
 "Geometry POLYGON((-54.72541 1.9558,-50.98203 1.9558,-50.98203 6.38816,-54.72541 6.38816,-54.72541 1.9558))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Testudines, Reptilia, Reptilia, Reptilia, Reptilia, Amphibia, Orchidaceae)"
 ]
}

 The dataset includes 44419 records from 117 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021019-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jq58ps
title: Occurrence Download

description: A dataset containing 136 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Protoparmeliopsis laatokkaensis (Räsänen) Moberg & R.Sant."
 ]
}

 The dataset includes 136 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007049-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pf8hqq
title: Occurrence Download

description: A dataset containing 287 records in GBIF matching the query:
SELECT "year", GBIF_EEARGCode( 1000, decimalLatitude, decimalLongitude, COALESCE(coordinateUncertaintyInMeters, 1000) ) AS eeaCellCode, classKey, class, genusKey, genus, COUNT(*) AS occurrences, MIN(COALESCE(coordinateUncertaintyInMeters, 1000)) AS minCoordinateUncertaintyInMeters, MIN(GBIF_TemporalUncertainty(eventDate, null)) AS minTemporalUncertainty FROM occurrence WHERE occurrenceStatus = 'PRESENT' AND genusKey IN (2284443, 2202786, 2162003, 2161911, 2161467, 7652364, 2176168, 2149911, 3092125, 2771094, 8782549, 2457378, 2453882, 2457825, 2454645, 2465626, 2466496, 2459675, 2444141, 2444221, 2447418, 2441658, 2442664, 3266899, 2473221, 2445496, 5221394, 2443339, 4553469) AND countrycode = 'BE' AND "year" &gt;= 1900 AND hasCoordinate = TRUE AND genusKey IS NOT 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 (LOWER(identificationVerificationStatus) NOT IN ( 'unverified', 'unvalidated', 'not validated', 'under validation', 'not able to validate', 'control could not be conclusive due to insufficient knowledge', 'uncertain', 'unconfirmed', 'unconfirmed - not reviewed', 'validation requested' ) OR identificationVerificationStatus IS NULL) AND COALESCE(coordinateUncertaintyInMeters, 1000) &lt;= 10000 GROUP BY "year", eeaCellCode, classKey, class, genusKey, genus ORDER BY "year" DESC, eeaCellCode ASC, genusKey ASC;

 The dataset's 287 records were derived from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007042-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4cdb5d
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Protapanteles porthetriae (Muesebeck, 1928)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 33 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007050-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5523/bris.2zfsfzzmm3fed2c397n38lznqj
title: Partitioning of Ionic Surfactants in Aerosol Droplets Containing Glutaric Acid, Sodium Chloride, or Sea Salts

description: This data set provides the data underlying the figures in our publication "Partitioning of Ionic Surfactants in Aerosol Droplets Containing Glutaric Acid, Sodium Chloride, or Sea Salts", Atmospheric Chemistry and Physics, 2025.
DOI: 10.34808/tpwa-cx63
title: Numerical and experimental generated data during project https://doi.org/10.1109/TMTT.2023.3318702

description: The dataset was generated using a procedure for the globalized design of microwave devices, which employs simplex-based regression models built at the level of operating parameters and performance figures of the circuit of interest. The computational efficiency of our technique stems from the topological simplicity of the surrogate and its updating rules, as well as the nearly linear dependence between the circuit dimensions and its operational parameters. Furthermore, the updating rules of the regression model guarantee convergence of the optimization process. The global search capability of our technique is validated through repetitive optimization of three microstrip circuits. A perfect success rate is demonstrated along with a low (average) computational cost of just about 80 EM analyses of the circuit at hand.
DOI: 10.12751/g-node.ls2xxj
title: The dorsal and ventral hippocampus contribute differentially to spatial working memory and spatial coding in the prefrontal cortex

description: The hippocampus (HPC) supports spatial working memory (SWM) through its interactions with the prefrontal cortex (PFC). However, it is not clear whether and how the dorsal (dHPC) and ventral (vHPC) poles of the HPC make distinct contributions to SWM and whether they differentially influence the PFC. To address this question, we optogenetically silenced the dHPC or the vHPC while simultaneously recording from the PFC of mice performing a SWM task. We found that whereas both HPC subregions were necessary during the encoding phase of the task, only the dHPC was necessary during the choice phase. Silencing of either subregion altered the spatial firing patterns of PFC neurons. However, only silencing of the vHPC affected their coding of spatial goals. These results thus reveal distinct contributions of the dorsal and ventral HPC poles to SWM and the coding of behaviorally-relevant spatial information by PFC neurons.
description: IsSupplementTo: S.S. Babl, T. Sigurdsson (2025): The dorsal and ventral hippocampus contribute differentially to spatial working memory and spatial coding in the prefrontal cortex, PLOS Biology.
DOI: 10.15468/dl.b748t3
title: Occurrence Download

description: A dataset containing 32585 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ulva lactuca L."
 ]
}

 The dataset includes 32585 records from 366 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007052-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sq7bpg
title: Occurrence Download

description: A dataset containing 172 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Geometry POLYGON((-97.93972 22.12421,-97.7461 24.90532,-97.26204 25.86739,-97.48793 27.13802,-96.8748 28.30917,-99.19825 29.83216,-102.65115 29.72012,-103.03839 26.01248,-101.61851 22.00458,-97.93972 22.12421))",
 "HasGeospatialIssue is false",
 "TaxonKey is Panthera onca (Linnaeus, 1758)"
 ]
}

 The dataset includes 172 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007054-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/11020791
title: Visual Scene Instructions for Generative LLMs
DOI: 10.6084/m9.figshare.27161856
title: GRK5 as a Novel Therapeutic Target for Immune Evasion in Testicular Cancer: Insights from Multi-Omics Analysis and Immunotherapeutic Validation

description: Raw data
DOI: 10.6084/m9.figshare.27161856.v2
title: GRK5 as a Novel Therapeutic Target for Immune Evasion in Testicular Cancer: Insights from Multi-Omics Analysis and Immunotherapeutic Validation

description: Raw data
DOI: 10.6084/m9.figshare.27161856.v1
title: Immune Subtype Identification and GRK5 as a Therapeutic Target in Testicular Cancer: A Predictive Model for Tailored Immunotherapy

description: Raw data
DOI: 10.5285/a1be11d5-5a44-4adb-9b0a-2efd833dfd2a
title: Unconfined compressive strength (UCS) data of tests conducted on salt samples from the Northwich Halite Member

description: The dataset contains unconfined compressive strength data of salt samples collected from the Northwich Halite Member at the Winsford Mine in Cheshire, UK. Each sample was unconfined and deformed under standard uniaxial stress conditions, where the primary principal stress corresponds to the axial stress and the intermediate and minimum principal stresses are equal to 0. Each sample was axially compressed using either a constant strain rate of 1e-5 per second or a constant loading rate of 200 N/s. The tests were completed using a servo-controlled stiff load frame in the Rock Mechanics and Physics Laboratory at the British Geological Survey, Keyworth UK. The data are separated into individual Microsoft Excel files, with each file representing a single test. Each file contains time, force, stress, displacement, and strain data.
DOI: 10.21227/1n2q-6770
title: Curvilinear Structure Segmentation Dataset

description: This dataset comprises images of curvilinear structures captured across eight distinct natural scene categories: branch, crack, floor, scratch, soil, wire, leaf, and tyre. It serves as a comprehensive benchmark for curvilinear structure segmentation, offering diverse visual patterns with variations in texture, lighting, and structural complexity. The dataset is designed to challenge and advance segmentation models by providing real-world curvilinear structures with irregular shapes, varying widths, and complex backgrounds. By covering a wide range of natural scenes, it supports the development and evaluation of both deep learning-based and traditional segmentation methods. This resource facilitates research on improving the accuracy and robustness of curvilinear structure segmentation algorithms.
DOI: 10.15468/dl.8ydhz2
title: Occurrence Download

description: A dataset containing 1594 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Sylvia melanocephala (Gmelin, 1789)",
 "Year 2020-2020"
 ]
}

 The dataset includes 1594 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007056-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k6wxua
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Protapanteles thompsoni (Lyle, 1927)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007057-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34808/7jw3-4264
title: Bioelectrochemical detection of COVID protein (RBD) on boron doped diamond – supporting measurements

description: This dataset includes a series of supporting electrochemical measurements in the topic of bioelectrochemical detection of COVID proteins (RBD - Receptor Bindign Domain) on boron doped diamond electrodes (BDD). The specific receptor (ACE-2 - angiotensin convertase enzyme) is attached via EDC/NHS linkers according to the previously optimized parameters (10.34808/hheg-zg78). Supporting measurements include: stability of the Ag/AgCl reference electrode, influence of the buffer and supporting electrolyte concentrations, influence of electrode annealing. Finally, efficacy of COVID detection is evaluated using EIS in supporting electrolyte only (without redox markers).
DOI: 10.34808/hheg-zg78
title: Bioelectrochemical detection of COVID protein (RBD) on boron doped diamond - optimization of functionalziation parameters

description: The following dataset is a comprehensive overview of preparation of biofunctionalizaed BDD (boron-doped diamond) electrodes and their application in electrochemical sensing of COVID protein RBD. The specific receptor against RBD (Receptor Binding Domain) protein ACE-2 (Angiotensin Convertase Enzyme) is attached to the surface of BDD via a series of modification steps (diazonium electrografting, EDC/NHS linkers, and ACE-2 proteins). Functionalization parameters (linker concentrations, incubation times) are optimized towards optimal sensing performance. Influence of BSA adsorption after functionalizations on RBD detection is investigated. Stability and selectivity of the functionalziation is verified. Alternative route of functionalziation via his-tag was tested with negative results.
DOI: 10.34808/3dk4-ah25
title: The original data (emulated HHDCs) presented in the study entitled "Generative Diffusion Models for Compressed Sensing of Satellite LiDAR Data: Evaluating Image Quality Metrics in Forest Landscape Reconstruction"

description: The dataset contains four subsets of original data (emulated HHDCs) presented in the study entitled "Generative Diffusion Models for Compressed Sensing of Satellite LiDAR Data: Evaluating Image Quality Metrics in Forest Landscape Reconstruction" submitted to the journal "Remote Sensing".
The raw LiDAR data, being the source for the emulated HHDCs, centered on the Smithsonian Environmental Research Center (SERC) in the state of Maryland (Latitude 38.88° N, Longitude 76.56° W) are available at NEON (National Ecological Observatory Network) website: Discrete return LiDAR point cloud (DP1.30003.001), RELEASE-2024. https://doi.org/10.48443/hj77-kf64.
A dataset of emulated HHDCs was created using high-resolution point clouds from the SERC region. The input low-resolution HHDC footprints were modeled with a uniform diameter of 10 meters, spaced 3 meters apart along the swath and 6 meters across the swath, with a vertical resolution of 0.5 meters (these values were chosen to match the LiDAR instrument currently under development as part of NASA’s CASALS project). These HHDCs were standardized to a fixed size of 16 × 32 × 128 (footprints across the swath × footprints along the swath × height), corresponding to a forest tile covering 96 × 96 meters with a height of 64 meters. For super-resolution to 3 meters, the high-resolution output HHDC footprints were designed to increase the resolution while maintaining the same coverage area. Specifically, the footprints were assigned a radius of 3 meters, with a 3-meter separation both along and across the swath, and a vertical resolution of 0.5 meters. This configuration resulted in a tensor size of 32 × 32 × 128 while preserving the original 96 × 96 meters area. Using the approach described above, four subsets were created using different sizes of reconstructed areas defined by the lengths of square sides equal to 576 m, 288 m, 144 m, and 96 m.
The dataset was created within the joint IMPRESS-U project entitled ”EAGER IMPRESS-U: Exploratory Research on Generative Compression for Compressive Lidar” co-funded by U.S. National Science Foundation NSF under Grant No. 2404740, Science & Technology Center in Ukraine (STCU) Agreement No. 7116, and National Science Centre, Poland (NCN), Grant no. 2023/05/Y/ST6/00197.
DOI: 10.15468/dl.tz35bp
title: Occurrence Download

description: A dataset containing 172 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Geometry POLYGON((-97.93972 22.12421,-97.7461 24.90532,-97.26204 25.86739,-97.48793 27.13802,-96.8748 28.30917,-99.19825 29.83216,-102.65115 29.72012,-103.03839 26.01248,-101.61851 22.00458,-97.93972 22.12421))",
 "HasGeospatialIssue is false",
 "TaxonKey is Panthera onca (Linnaeus, 1758)"
 ]
}

 The dataset includes 172 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007062-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j966u5
title: Occurrence Download

description: A dataset containing 1391 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Lepus granatensis Rosenhauer, 1856",
 "Year 2020-2025"
 ]
}

 The dataset includes 1391 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007063-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.angrdu
title: Occurrence Download

description: A dataset containing 172 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Geometry POLYGON((-97.93972 22.12421,-97.7461 24.90532,-97.26204 25.86739,-97.48793 27.13802,-96.8748 28.30917,-99.19825 29.83216,-102.65115 29.72012,-103.03839 26.01248,-101.61851 22.00458,-97.93972 22.12421))",
 "HasGeospatialIssue is false",
 "TaxonKey is Panthera onca (Linnaeus, 1758)"
 ]
}

 The dataset includes 172 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007064-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mk8fuz
title: Occurrence Download

description: A dataset containing 33392 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hemigrapsus takanoi Asakura & Watanabe, 2005"
 ]
}

 The dataset includes 33392 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007061-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34808/ba97-n715
title: Application of Artificial Intelligence by Poland’s Public Administration. METADATA

description: This metadata provides information related to the publication "Application of Artificial Intelligence by Poland’s Public Administration" (https://doi.org/10.4337/9781802207347.00017), published in the book "Research Handbook on Public Management and Artificial Intelligence" (119-137)
The file contains the following information: 
- Interviewee information: Excel table including information about the profiles of the different interviewees involved in the research: Identification, Date of the interview, Length of the interview
- Interview guide: Guide used in the interviews, including information about the company/start-up, information about their participation in national contests, information of who was benefiting from their innovations, motivations to engage in the contest, project submitted to the competition, role of state agencies in the innovation process and a general evaluation of the overall process.