cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1215987
title: Standard Sample Description V2 Structural Metadata

description: Standard Sample Description V2 is a specification aimed at harmonising the collection of analytical measurement data for the presence of harmful or beneficial chemical substances in food, feed and water. The specification is a list of standardised data elements (items describing characteristics of samples or analytical results such as country of origin, product, analytical method, limit of detection, result, etc.), linked to controlled terminologies. This specification uses EFSA FoodEx2 to describe sampled foods. This file has been prepared to support the publication of data and interoperability. This file indicates which data elements from the specification will not be published to ensure full protection of confidential/sensitive information, for example personal data in accordance with Regulation (EC) No 45/2001 and to protect commercial interests, including intellectual property as specified in Article 4(2), first indent, of Regulation (EC) No 1049/2001. The Excel table contains information about the structural metadata elements of the data collection and their fact tables.<br> <br> The column <em>name</em> shows the name of the element (e.g. localOrg).<br> The column <em>description</em> describes how the content has to be interpreted.<br> The column <em>code</em> expresses the corresponding code of the structural metadata element.<br> The column <em>optional</em> says whether the structural metadata element is optional or not (then it is mandatory).<br> The column <em>dataType</em> contains the type which can be used to fill the structural metadata element and the possible maximal length of the field. The possible types are: text or number. <br> The column <em>catalogue</em> contains the name of the catalogue where the content of the structural metadata element has to be picked from (e.g. COUNTRY).<br> The column <em>data</em> <em>protection</em> contains whether the structural metadata element will be published or not (yes = will not be published, no = will be published).
description: EU; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.15412821
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - North Macedonia

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.  

The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. 

Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below:  



Commission Regulation (EU) 625/2017, on the application of food and feed law

Commission Delegated Regulation (EU) 2022/931

Commission Implementing Regulation (EU) 2022/932

Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006


These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, split by sampling year (data element ‘sampY’). 

More details are available in last year's finalised call for data ‘Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA’.

REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: 

OCC-CHEMMON2024 – Food and Veterinary Institute
description: MK; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.15412822
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - North Macedonia

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.  

The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. 

Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below:  



Commission Regulation (EU) 625/2017, on the application of food and feed law

Commission Delegated Regulation (EU) 2022/931

Commission Implementing Regulation (EU) 2022/932

Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006


These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, split by sampling year (data element ‘sampY’). 

More details are available in last year's finalised call for data ‘Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA’.

REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: 

OCC-CHEMMON2024 – Food and Veterinary Institute
description: MK; CSV; data.collection@efsa.europa.eu
DOI: 10.15468/dl.5yx8nb
title: Occurrence Download

description: A dataset containing 745 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Fritillaria cirrhosa D.Don"
 ]
}

 The dataset includes 745 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032587-250426092105405/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.29069330
title: good bins

description: Ecological impacts of climate change and ecological adaptation
DOI: 10.7939/r3-h65c-e275
title: Boardex Reports - Director Network ROW - 2021 November
DOI: 10.6084/m9.figshare.28702145
title: active viruses and active viral genes

description: active viruses and avtive viral genes
DOI: 10.6084/m9.figshare.28702166
title: good_bins.zip

description: metagenome assemblied genomes
DOI: 10.6084/m9.figshare.28702121.v1
title: RM-system.xlsx

description: methylases and restriction endonucleases prediction
DOI: 10.6084/m9.figshare.28702124
title: global_contig_microdiversity.tsv

description: microdiversity of viral community
DOI: 10.6084/m9.figshare.28702136
title: ARG annotation by ResFam

description: ARG annotation
DOI: 10.6084/m9.figshare.28702121
title: RM-system.xlsx

description: methylases and restriction endonucleases prediction
DOI: 10.6084/m9.figshare.28702124.v1
title: global_contig_microdiversity.tsv

description: microdiversity of viral community
DOI: 10.6084/m9.figshare.28702136.v1
title: ARG annotation by ResFam

description: ARG annotation
DOI: 10.15468/dl.mr2afe
title: Occurrence Download

description: A dataset containing 2695 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acipenser sturio Linnaeus, 1758"
 ]
}

 The dataset includes 2695 records from 119 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032588-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7939/r3-14p4-8t17
title: Trace element compositions of mineral inclusions in Koidu diamonds

description: Trace element compositions of mineral inclusions in Koidu diamonds
DOI: 10.6084/m9.figshare.28171535
title: International Public Multilateral Climate Finance Dataset from 2000 to 2023

description: International multilateral public climate finance plays a key role in the global climate financing landscape, yet the availability of a comprehensive, publicly accessible, and transparent database remains inadequate. This study establishes a global multilateral public climate finance database covering the period from 2000 to 2023. The primary objective is to identify and track climate-related projects and their funding flows supported by major multilateral development finance institutions (MDFIs) and multilateral climate funds (MCFs). Using machine learning methods, we extracted and classified climate mitigation and adaptation-related projects from project-level data, creating a climate finance database containing detailed information on funding sources, institutions, project types, recipient countries, financing amounts, and financing types. This database provides valuable insights into the distribution and trends of international climate finance, offering data support for climate finance policies and decision-making.
DOI: 10.5281/zenodo.15284358
title: Landslide Reference Data (Sentinel-1 & Sentinel-2)

description: This dataset contains a curated landslide inventory compiled to support supervised machine learning applications, particularly deep learning models such as U-Net. It includes labeled reference data for large landslides that occurred worldwide from July 2015 onwards, enabling the availability of both Sentinel-1 and Sentinel-2 satellite data for each event.

The majority of landslides were identified through reports on The Landslide Blog and subsequently verified via visual interpretation of pre- and post-event Sentinel imagery. An exception is the dataset subset from southern Kyrgyzstan, based on previous studies and manual corrections.

The inventory features landslides of varying sizes and types across diverse environmental and climatic conditions, with rainfall-triggered events being the most common. It encompasses both single-event landslides and clusters of multiple landslides within a single event.

Note: The full dataset files will be submitted and made available in a forthcoming new version of this record.
description: This is a placeholder record to reserve a DOI for citation purposes. The full dataset and associated files will be submitted in an upcoming new version.
DOI: 10.5281/zenodo.15421843
title: Landslide Reference Data (Sentinel-1 & Sentinel-2)

description: This dataset contains a curated landslide inventory compiled to support supervised machine learning applications, particularly deep learning models such as U-Net. It includes labeled reference data for large landslides that occurred worldwide from July 2015 onwards, enabling the availability of both Sentinel-1 and Sentinel-2 satellite data for each event.

The majority of landslides were identified through reports on The Landslide Blog and subsequently verified via visual interpretation of pre- and post-event Sentinel imagery. An exception is the dataset subset from southern Kyrgyzstan, based on previous studies and manual corrections.

The inventory features landslides of varying sizes and types across diverse environmental and climatic conditions, with rainfall-triggered events being the most common. It encompasses both single-event landslides and clusters of multiple landslides within a single event.
DOI: 10.15468/dl.72gyht
title: Occurrence Download

description: A dataset containing 847 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acipenser transmontanus Richardson, 1836"
 ]
}

 The dataset includes 847 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032590-250426092105405/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/11819441
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.11171629
title: An anisotropic, brittle damage model for finite strains with a generic damage tensor regularization: material subroutines

description: This dataset contains the material subroutines of models A, B, and C of the publication:

T. van der Velden, S. Reese, H. Holthusen, and T. Brepols. An anisotropic, brittle damage model for finite strains with a generic damage tensor regularization.

The standalone environments comprise local uniaxial tension and uniaxial strain tests.

The codes are written in FORTRAN. All derivates are computed by AceGen and are, thereafter, exported to FORTRAN. The R8LIB (r8lib.f90) was downloaded from <https://people.math.sc.edu/Burkardt/f_src/r8lib/r8lib.html>.
DOI: 10.5281/zenodo.11171630
title: An anisotropic, brittle damage model for finite strains with a generic damage tensor regularization: material subroutines

description: This dataset contains the material subroutines of models A, B, and C of the publication:

T. van der Velden, S. Reese, H. Holthusen, and T. Brepols. An anisotropic, brittle damage model for finite strains with a generic damage tensor regularization.

The standalone environments comprise local uniaxial tension and uniaxial strain tests.

The codes are written in FORTRAN. All derivates are computed by AceGen and are, thereafter, exported to FORTRAN. The R8LIB (r8lib.f90) was downloaded from <https://people.math.sc.edu/Burkardt/f_src/r8lib/r8lib.html>.
DOI: 10.15468/dl.qhnx49
title: Occurrence Download

description: A dataset containing 4154 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 GBIF_EEARGCODE(10000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000)) eeacellcode,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.continent = 'EUROPE'
 AND occurrence.countrycode IN ('ES', 'FR', 'EE', 'CH', 'NO', 'UA', 'GB', 'SE', 'FI')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.taxonkey = 2433433 OR occurrence.acceptedtaxonkey = 2433433 OR occurrence.kingdomkey = 2433433 OR occurrence.phylumkey = 2433433 OR occurrence.classkey = 2433433 OR occurrence.orderkey = 2433433 OR occurrence.familykey = 2433433 OR occurrence.genuskey = 2433433 OR occurrence.specieskey = 2433433)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL AND occurrence.hascoordinate = TRUE)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year",
 GBIF_EEARGCODE(10000, decimallatitude, decimallongitude, COALESCE(coordinateuncertaintyinmeters, 1000))

 The dataset's 4154 records were derived from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032584-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9g5v32
title: Occurrence Download

description: A dataset containing 1668169 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "OccurrenceStatus is Present",
 "TaxonKey is Rubiaceae"
 ]
}

 The dataset includes 1668169 records from 4047 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032577-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15430521
title: Section Extraction and Rigor Analysis for Neurotrauma Journals

description: This dataset and accompanying code support a project analyzing scientific rigor and transparency in two neuroscience journals: Journal of Neurotrauma and Experimental Neurology. Using a custom Python pipeline, Methods and Rigor & Transparency sections were extracted from full-text articles in PubMed Central's Open Access subset. The extracted data is analyzed with SciScore to assess compliance with scientific best practices. The project highlights differences in reporting standards based on journal policy changes and includes structured JSON data and Jupyter notebooks for reproducibility.
DOI: 10.5281/zenodo.15430522
title: Section Extraction and Rigor Analysis for Neurotrauma Journals

description: This dataset and accompanying code support a project analyzing scientific rigor and transparency in two neuroscience journals: Journal of Neurotrauma and Experimental Neurology. Using a custom Python pipeline, Methods and Rigor & Transparency sections were extracted from full-text articles in PubMed Central's Open Access subset. The extracted data is analyzed with SciScore to assess compliance with scientific best practices. The project highlights differences in reporting standards based on journal policy changes and includes structured JSON data and Jupyter notebooks for reproducibility.
DOI: 10.5281/zenodo.15499038
title: IODP Expedition 399 Interstitial water composite report

description: This composite report includes data from numerous interstitial water (IW) analyses (e.g., ICP-LIQUIDS and IONCHROM) in a variable set of columns. Each row combines the data from several tests (groups of measurements made on the same sample at the same time) for a particular IW sample. If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate analysis (ALKALINITY, ICP-LIQUIDS, IONCHROM, SALINITY, SPEC, TITRATOR, and potentially others). Major and minor elements were determined by inductively coupled plasma-atomic emission spectrocsopy (ICP-LIQUIDS). Cations and anions were measured by ion chromatography (IONCHROM). Complex ions were measured by colorimetric measurements using a UV-VIS spectrometer (SPEC). Alkalinity and chloride was measured by titration (ALKALINITY and TITRATOR). Dissolved carbon (DC), dissolved inorganic carbon (DIC), and dissolved organic carbon (DOC) were measured by combustion in a total organic carbon (TOC) analyzer. Salinity was measured by refractometer (SALINITY). pH was measured by ion-selective electrode as part of the alkalinity procedure and is reported in the ALKALINITY analysis.
DOI: 10.5281/zenodo.15499039
title: IODP Expedition 399 Interstitial water composite report

description: This composite report includes data from numerous interstitial water (IW) analyses (e.g., ICP-LIQUIDS and IONCHROM) in a variable set of columns. Each row combines the data from several tests (groups of measurements made on the same sample at the same time) for a particular IW sample. If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate analysis (ALKALINITY, ICP-LIQUIDS, IONCHROM, SALINITY, SPEC, TITRATOR, and potentially others). Major and minor elements were determined by inductively coupled plasma-atomic emission spectrocsopy (ICP-LIQUIDS). Cations and anions were measured by ion chromatography (IONCHROM). Complex ions were measured by colorimetric measurements using a UV-VIS spectrometer (SPEC). Alkalinity and chloride was measured by titration (ALKALINITY and TITRATOR). Dissolved carbon (DC), dissolved inorganic carbon (DIC), and dissolved organic carbon (DOC) were measured by combustion in a total organic carbon (TOC) analyzer. Salinity was measured by refractometer (SALINITY). pH was measured by ion-selective electrode as part of the alkalinity procedure and is reported in the ALKALINITY analysis.
DOI: 10.15468/dl.a42ysq
title: Occurrence Download

description: A dataset containing 240581825 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "License is one of (CC-BY 4.0, CC0 1.0)",
 "TaxonKey is Plantae",
 "Year 1980-2025"
 ]
}

 The dataset includes 240581825 records from 9048 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004263-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17044/scilifelab.30009196
title: Ultrasound-guided, magnetothermal wax capsule for localized gastrointestinal drug delivery

description: Oral drug delivery to specific lesions in the gastrointestinal (GI) tract remains a major challenge. The current systems depend on internal physiological triggers such as pH, enzymatic activity, and luminal pressure, which exhibit wide intra- and inter-patient variability. To address this, an ingestible capsule was developed to enable on-demand, site-specific drug release in response to an external alternating magnetic field (AMF), with ultrasound imaging used for real-time localization. The capsule is composed of a low-melting-point wax matrix embedded with superparamagnetic iron oxide nanoparticles (SPIONs), which generate heat upon AMF exposure, resulting in rapid wax melting and burst drug release. SPIONs exhibited no toxicity in zebrafish embryonic development, demonstrating excellent biocompatibility. Capsules were fabricated in a hemispherical shape using a 3D-printed mold, yielding highly reproducible batches with a mass variation within ±10%. A Design of Experiments (DoE) approach identified an optimized formulation comprising a 6:4 docosane:eicosane wax blend, 10 wt% SPION loading, and a 1.5 mm capsule shell thickness, achieving efficient magnetic heating while maintaining mechanical strength (&gt; 2 N), sufficient for withstanding GI transit.The optimized capsule formulation exhibited no cytotoxicity <i>in vitro</i> and remained intact throughout sequential incubation in simulated gastric, intestinal, and colonic fluids. No drug leakage or significant metal leaching (≤ 0.6%) was obtained. The capsule was successfully visualized in a porcine abdominal model using a handheld ultrasound device commonly used at the bedside in the clinic. AMF exposure triggered complete drug release within 33 seconds <i>in vitro</i>. <i>In vivo</i> studies in mice further demonstrated capsule localization via ultrasound, and AMF-triggered capsule melting in the colon via endoscopy. In conclusion, this magnetothermal capsule platform integrates non-invasive imaging and externally triggered drug release to enable localized GI drug delivery, representing a promising strategy for precision treatment of GI diseases.