cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25346/s6/fhklvz/kmoqlj
title: spectra_02e_270.mat
DOI: 10.25346/s6/fhklvz/kqujap
title: ms02_spectrum_02a.mp4
DOI: 10.25346/s6/fhklvz/n1o9hj
title: spectra_02i_180.mat
DOI: 10.25346/s6/fhklvz/nbiwqb
title: spectra_video_05e.mat
DOI: 10.25346/s6/fhklvz/nnwkyo
title: spectra_02a_180.mat
DOI: 10.25346/s6/fhklvz/nomotf
title: spectra_05a_180.mat
DOI: 10.25346/s6/fhklvz/ofy6fy
title: ms04_spectrum_02e.mp4
DOI: 10.25346/s6/fhklvz/p6tmt1
title: en_profile_L5_05e.mat
DOI: 10.25346/s6/fhklvz/pclzqg
title: spectra_02f_270.mat
DOI: 10.25346/s6/fhklvz/qs9ejq
title: ms03_spectrum_02i.mp4
DOI: 10.25346/s6/fhklvz/qt4m4c
title: spectra_02g_180.mat
DOI: 10.25346/s6/fhklvz/rw6kjl
title: dll_tau.png
DOI: 10.25346/s6/fhklvz/smlldn
title: spectra_1_90.png
DOI: 10.25346/s6/fhklvz/tg09y0
title: spectra_2_270.png
DOI: 10.25346/s6/fhklvz/tvtwj5
title: ms06_spectrum_05e.mp4
DOI: 10.25346/s6/fhklvz/tzeb8c
title: spectra_05e_270.mat
DOI: 10.25346/s6/fhklvz/ulmnha
title: dll_tau_r600.png
DOI: 10.25346/s6/fhklvz/wgu3q7
title: ms01_spectrum_02f.mp4
DOI: 10.25346/s6/fhklvz/wl2tok
title: spectra_05e.mat
DOI: 10.25346/s6/fhklvz/wldwww
title: E.png
DOI: 10.25346/s6/fhklvz/wtsubh
title: spectra_2_90.png
DOI: 10.25346/s6/fhklvz/zxmpsm
title: spectra_02e.mat
DOI: 10.25346/s6/fhklvz/ud0ez3
title: spectra_02f_90.mat
DOI: 10.25346/s6/fhklvz/vmhdwn
title: spectra_video_02i.mat
DOI: 10.25346/s6/fhklvz/8wwl8j
title: spectra_05a_270.mat
DOI: 10.25346/s6/fhklvz/iq32kj
title: spectra_02i_270.mat
DOI: 10.34740/kaggle/dsv/11222917
title: ⏳ endoflife.date database (duckdb)
DOI: 10.25346/s6/fhklvz/dn1y7s
title: spectra_02a_270.mat
DOI: 10.15468/dl.3pqefj
title: Occurrence Download

description: A dataset containing 360 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ustilaginoidea virens (Cooke) Takah."
 ]
}

 The dataset includes 360 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007679-250325103851331/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.28694411
title: Datasets for CMIP6 downscaling of the historical and future climate

description: Datasets for CMIP6 downscaling of the historical and future climate
DOI: 10.15468/dl.f76ge4
title: Occurrence Download

description: A dataset containing 46423 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Bosque Mesófilo de Montaña de México"
 ]
}

 The dataset includes 46423 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007680-250325103851331/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.28632464
title: <b>DocFEE: A Document-Level Chinese Financial Event Extraction Dataset</b>

description: <b>DocFEE: A Document-Level Chinese Financial Event Extraction Dataset</b><br><br>DocFEE is a large-scale, document-level dataset designed for financial event extraction in Chinese. It contains ​<b>19,044 annotated documents</b> spanning nine critical financial event types, including <i>Bankruptcy Liquidation</i>, <i>Major Safety Incident</i>, <i>Equity Pledge</i>, and <i>Senior Executive Death</i>, among others. Each document is annotated with ​<b>38 distinct argument types</b> to capture intricate event details, such as dates, amounts, stakeholders, and contextual impacts.The dataset addresses the challenges of document-level event extraction, where events and their arguments may span multiple sentences or exhibit cross-sentence dependencies. On average, documents contain ​<b>1.86 events</b> with a broad event range (<b>960.06</b> <b>characters</b>) and a median document length of<b> 2,277.25</b> <b>characters</b>, reflecting real-world complexity. Key features include fine-grained annotations for diverse financial scenarios, such as tracking shareholder reductions (<i>Reduction Start Date</i>, <i>Shareholder</i>, <i>Reduction Amount</i>) or quantifying losses in <i>Major Asset Loss</i> events (<i>Loss Amount</i>, <i>Other Losses</i>).DocFEE supports research in financial NLP, regulatory compliance, and risk analysis by providing robust, structured data for modeling cross-sentence event relations and argument extraction in long-form texts. Its comprehensive annotations and domain specificity make it a valuable resource for advancing document-level understanding in Chinese financial contexts.<br><br>Please refer to README.pdf for detailed description.
DOI: 10.25375/uct.28690247
title: Data on communication and team dynamics extracted from 38 patient discussions

description: <b>Background:</b> Antimicrobial resistance (AMR) is of critical concern requiring multimodal mitigation strategies, including effective communication in antimicrobial stewardship (AMS) and infection prevention and control (IPC). Despite multidisciplinary healthcare worker (HCW) collaboration being essential to IPC and AMS, professional hierarchies, silos, and health system barriers impact infection care outcomes.<b>Aims:</b> This thesis investigates optimisation of infection related clinical practices using team dynamics and communication. Four connected studies addressed the following research questions related to IPC and AMS care: 1) What existing evidence supports hospital HCW team communication to improve practices? 2) Can reflexive workshops with sociograms enhance multidisciplinary team dynamics and communication in a South African tertiary hospital Intensive Care Unit (ICU)? 3) Can a visual ICU nursing handover tool support structured and consistent practice for every patient review? 4) How can the learning on adopting sociograms to describe team dynamics and communication for IPC and AMS be generalisable to other settings?<b>Study Design: </b>The mixed methods design included 1) scoping review of literature on effective HCWs’ team communication in hospitals to enhance IPC and AMS bedside team communication 2) ethnographic study using sociograms to analysing ICU team interactions 3) participatory action research study with ICU nurses to design and adopt a nursing handover tool for structured IPC and AMS 4) collaborative knowledge transfer of sociogram approach through a pilot study with surgical teams in India.<b>Results: </b>Limited evidence suggests effective multidisciplinary communication enhances teamwork and patient outcomes. Communication practices vary across disciplines, highlighting the need for self-assessment and tailored interventions. Structured communication strategies reduced opportunities for missed clinical information and enhanced clarity and target of clinical tasks. Sociograms and team reflexivity revealed dominant communication roles in ICU teams highlighting areas for improvement. A visual handover tool improved consistent AMS and IPC information transfer. Sociograms in the operating theatre provided insights into team dynamics and communication patterns in India.<b>Conclusion:</b> Enhancing communication and teamwork among HCWs is vital for infection management. Targeted, structured communication on IPC and AMS can improve patient care. Using sociograms and reflexive feedback fosters team participation and problem- solving, engaging busy clinicians in co-design of interventions.
DOI: 10.18150/ecbr3d
title: DendroSpec - Spectroscopic Methods for Rapid Phenotyping of Trees Reflecting their Ecological Resilience

description: The overall objective of the DENDRO-SPEC project is to generate new knowledge allowing better understanding the effect of genetic variation in tree populations combined with stand conditions, silvicultural practices and local microclimate on mechanisms of xylogenesis and, consequently, characteristics of generated wood. For that reason, an innovative measurement protocol and original hardware set-up optimal for routine assessment of the wide range of wood properties will be developed. The prototype scanning system will integrate state-of-the-art near infrared spectroscopic technologies with cutting-edge data mining solutions. It will allow mapping a wide range of wood characteristics, considering the natural variability at the scale of a single tree, forest plot, or even overall population. Research will be conducted on a unique sample set of Scots pine wood available due to the proceeding fifty-year in-field project experiment. It is expected that DENDRO-SPEC methodology will demonstrate its highest suitability toward fast, non-destructive and complete characterization of wood. Therefore, it will be adopted as a new standard in several ongoing national research initiatives covering numerous trial seed plantations in Poland and Slovenia, not to mention other locations worldwide. Consequently, the spectroscopic system will allow detailed characterization of several thousand planted trees distributed around the country within seed collection stations, mother forests or experimental fields. DENDRO-SPEC is a financed by the National Science Center and ARRS (Slovenian Research Agency – No N4-0274).
DOI: 10.15468/dl.dt4ae5
title: Occurrence Download

description: A dataset containing 7584 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Proyecto interno ejecutado por la CONABIO: Sistema de información sobre Bosque Mesófilo de Montaña de México para apoyo en programas de restauración (Fase 1)"
 ]
}

 The dataset includes 7584 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007681-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15100426
title: AgroLens

description: This dataset has been curated for a student research project at the Technische Hochschule Ingolstadt together with Mi4Poeople and its Soil project (https://de.mi4people.org/soil-quality-evaluation-system).

All information about the dataset can be found in the related paper:https://arxiv.org/abs/2503.22276

Code is at:https://github.com/cvims/AgroLens
DOI: 10.5281/zenodo.15100427
title: AgroLens

description: This dataset has been curated for a student research project at the Technische Hochschule Ingolstadt together with Mi4Poeople and its Soil project (https://de.mi4people.org/soil-quality-evaluation-system).

All information about the dataset can be found in the related paper:https://arxiv.org/abs/2503.22276

Code is at:https://github.com/cvims/AgroLens
DOI: 10.6084/m9.figshare.28694432
title: phantom experiment data - original -JAPANESE.xlsx

description: The fundamental dataset of an experiment transcribed from a handwriting in the lab. This dataset supports a submitted manuscript of journal paper under review. All experiment details and captions are recorded in Japanese.
DOI: 10.6084/m9.figshare.28694432.v1
title: phantom experiment data - original -JAPANESE.xlsx

description: The fundamental dataset of an experiment transcribed from a handwriting in the lab. This dataset supports a submitted manuscript of journal paper under review. All experiment details and captions are recorded in Japanese.
DOI: 10.5281/zenodo.13371197
title: 14C-daterade järnframställningsplatser  i Sverige/Radiocarbon dated Bloomery sites in Sweden

description: A  compilation of  analysed radiocarbon samples  from iron production in bloomery furnaces in Sweden. The samples are collected from different types of features  associated  with direct iron production in bloomeries, such as furnaces, slag heaps  charcoal production features  etc. The dataset contains more than 1200 analysed samples, a large majority of all analysed samples from prehistoric iron production in Sweden.

The compilation was done in 2023 as part of  the research project Den tidiga järnframställningens Kronologi.
DOI: 10.5281/zenodo.13371198
title: 14C-daterade järnframställningsplatser  i Sverige/Radiocarbon dated Bloomery sites in Sweden

description: A  compilation of  analysed radiocarbon samples  from iron production in bloomery furnaces in Sweden. The samples are collected from different types of features  associated  with direct iron production in bloomeries, such as furnaces, slag heaps  charcoal production features  etc. The dataset contains more than 1200 analysed samples, a large majority of all analysed samples from prehistoric iron production in Sweden.

The compilation was done in 2023 as part of  the research project Den tidiga järnframställningens Kronologi.
DOI: 10.15468/dl.nbeaee
title: Occurrence Download

description: A dataset containing 194 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is 2023 Contributions of Plant Specimen Data inside China",
 "TaxonKey is Manglietia insignis (Wall.) Blume"
 ]
}

 The dataset includes 194 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007683-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2ng6cw
title: Occurrence Download

description: A dataset containing 1617849 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-111.03862 43.87959,-107.21904 43.87959,-107.21904 45.90301,-111.03862 45.90301,-111.03862 43.87959))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1617849 records from 613 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007673-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u5jsst
title: Occurrence Download

description: A dataset containing 8793 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "TaxonKey is Acrostichum aureum L."
 ]
}

 The dataset includes 8793 records from 378 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007684-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15111080
title: Electron density dataset from the multi-Needle Langmuir Probe (m-NLP) on the International Space Station (ISS) during superstorm between May 10 and 12, 2024.

description: Electron density dataset from the multi-Needle Langmuir Probe (m-NLP) on the International Space Station (ISS) during superstorm between May 10 and 12, 2024.

The dataset has electron density(Ne), geographic latitude (GLAT), geographic longitude (GLON), and altitude (ALT).

For more detailed position information, we add GLAT_TLE, GLON_TLE, and ALT_TLE based on two-line element set (TLE).

We also include magnetic local time (MLT), magnetic latitude for quasi-dipole (MLAT_QD) and magnetic latitude for Apex (MLAT_APEX) for the magnetic coordinate system.

The data period is from 2024-05-10 00:00:01 to 2024-05-12 23:59:59.
DOI: 10.5281/zenodo.15111081
title: Electron density dataset from the multi-Needle Langmuir Probe (m-NLP) on the International Space Station (ISS) during superstorm between May 10 and 12, 2024.

description: Electron density dataset from the multi-Needle Langmuir Probe (m-NLP) on the International Space Station (ISS) during superstorm between May 10 and 12, 2024.

The dataset has electron density(Ne), geographic latitude (GLAT), geographic longitude (GLON), and altitude (ALT).

For more detailed position information, we add GLAT_TLE, GLON_TLE, and ALT_TLE based on two-line element set (TLE).

We also include magnetic local time (MLT), magnetic latitude for quasi-dipole (MLAT_QD) and magnetic latitude for Apex (MLAT_APEX) for the magnetic coordinate system.

The data period is from 2024-05-10 00:00:01 to 2024-05-12 23:59:59.
DOI: 10.15468/dl.hy7yvv
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cuculus canorus Linnaeus, 1758",
 "Continent is Europe",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Living Specimen",
 "Year is greater than or equal to 1981",
 "Year is less than or equal to 2005"
 ]
}

 The dataset includes 7 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007685-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.7878550
title: Publication data for article "Scientific and technological knowledge grows linearly over time"

description: This dataset includes metadata for academic publications used in the article Scientific and technological knowledge grows linearly over time. The dataset contains citation relationships, publication dates, and academic fields for 213,715,816 publications from 1800 to 2020. These publications cover 292 secondary subjects in 19 major disciplines, including Economics, Biology, Computer Science, Physics, and more. The data are requested from Acemap (https://www.acemap.info, Shanghai Jiao Tong University) and sourced from the last snapshot of Microsoft Academic Graph (MAG) as of December 31, 2021.

The dataset includes two gzip-compressed files, which contain all data in CSV format after decompression. Sample data is presented below:



paper_date_refs.csv (paper_date_refs.tar.gz)



paper_id

date

reference_ids (separated by comma)



field_paper (field_paper.tar.gz)



field_paper/Computer science.csv



paper_id



field_paper/Biology.csv



paper_id



...
DOI: 10.5281/zenodo.7878551
title: Publication data for article "Scientific and technological knowledge grows linearly over time"

description: This dataset includes metadata for academic publications used in the article Scientific and technological knowledge grows linearly over time. The dataset contains citation relationships, publication dates, and academic fields for 213,715,816 publications from 1800 to 2020. These publications cover 292 secondary subjects in 19 major disciplines, including Economics, Biology, Computer Science, Physics, and more. The data are requested from Acemap (https://www.acemap.info, Shanghai Jiao Tong University) and sourced from the last snapshot of Microsoft Academic Graph (MAG) as of December 31, 2021.

The dataset includes two gzip-compressed files, which contain all data in CSV format after decompression. Sample data is presented below:



paper_date_refs.csv (paper_date_refs.tar.gz)



paper_id

date

reference_ids (separated by comma)



field_paper (field_paper.tar.gz)



field_paper/Computer science.csv



paper_id



field_paper/Biology.csv



paper_id



...
DOI: 10.15468/dl.v9cgbm
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hypselotriton Wolterstorff, 1934"
 ]
}

 The dataset includes 14 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007687-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7nz2ru
title: Occurrence Download

description: A dataset containing 1208 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Sinomenium acutum (Thunb.) Rehder & E.H.Wilson"
 ]
}

 The dataset includes 1208 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007688-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1186751.10fu
title: SH1186751.10FU

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/sh1186754.10fu
title: SH1186754.10FU

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/sh1186755.10fu
title: SH1186755.10FU

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.