cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25504/fairsharing.1831c6
title: FAIRsharing record for: PhageDive
title: null

description: This FAIRsharing record describes:  PhageDive is a specific database for bacteriophages and archaeal viruses. Built on the BacDive model, it gathers and links all the experimental data and metadata of the viruses present in different culture collections. Its implementation aims to facilitate access to all viruses information for the scientific community. The database covers taxonomy, host strain, phage morphology, life cycle, origin and genomic data.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.2416d0
title: FAIRsharing record for: Clinical Research Data Sharing Repository
title: crDSR

description: This FAIRsharing record describes:  The clinical research Data Sharing Repository is capable of holding any type of digital object -data sets, documents, media file etc- in a secure research environment (TRE). The repository collects the metadata necessary for the Findability of the objects, promoting data sharing in clinical research.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.d80c2e
title: FAIRsharing record for: Trinity College Dublin Policy on Good Research Practice
title: null

description: This FAIRsharing record describes:  This policy advocates that “research shall be conducted ethically and with integrity, and shall be founded upon the principles of honesty, reliability, objectivity, impartiality, independence, fairness, respect, accountability, open communication, compliance with duties of care, and responsibility for future generations of researchers. It is imperative that the principles of sound research design/ methodology be applied in the seeking of new knowledge, so as to ensure trust in the accuracy of the data collected and facilitate correct interpretation of the data” (Ensuring Research Integrity in Ireland, p.8). The guidelines outlined in this policy apply to all staff and students conducting research, including all staff categories, all students - undergraduate and postgraduate - and all others in the research community, including visitors and adjunct staff, and staff involved in research in College’s affiliated teaching hospitals and other institutions. 
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.77d162
title: FAIRsharing record for: RDA Common Descriptive Attributes of Research Data Repositories
title: DRAWG

description: This FAIRsharing record describes:  The RDA Common Descriptive Attributes of Research Data Repositories outlines a list of common, concise, high-level descriptors that represent information that can be useful in describing a research data repository along with examples of how each attribute can be expressed as metadata in different schemata, limitations and potential complications that each might pose in harmonization, a brief rationale for why each attribute is important and a gap analysis of how easy or difficult it may currently be to locate this information from a data repository. The attributes are conceptual with examples provided for illustration purposes without endorsement of any particular approach, standard or implementation.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.b3df6f
title: FAIRsharing record for: Lunaris
title: null

description: This FAIRsharing record describes:  Lunaris is Canada’s national discovery service for multidisciplinary data from research institutions across the country. Datasets from over 90 academic, government, and research repositories are made discoverable in a bilingual interface that provides keyword and map-based searching.


description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.da9bec
title: FAIRsharing record for: ITINERIS HUB
title: null

description: This FAIRsharing record describes:  ITINERIS is dedicated to building the Italian Hub of Research Infrastructures in the environmental scientific domain.
The ITINERIS HUB is the unique access point to the comprehensive collection of knowledge, data, analytics tool and services provided by the Italian Research Infrastructures (RIs) in the environmental scientific domain for the observation and study of processes in the atmosphere, marine domain, terrestrial biosphere, and geosphere.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.298642
title: FAIRsharing record for: Cambridge University Press - Data-Centric Engineering - Research Transparency
title: CUP - DCE

description: This FAIRsharing record describes:  Data-Centric Engineering (DCE) is a peer-reviewed open-access journal dedicated to the transformative impact of data science for research and practice across all areas of engineering. Articles explore the benefits of data science methods and models for improving the reliability, resilience, safety, efficiency and usability of engineered systems. This journal supports best practices in research openness and transparency. The policies for this journal outline their expectations for authors to help ensure that the research results published by DCE are as transparent as possible.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.43894f
title: FAIRsharing record for: StrainInfo
title: null

description: This FAIRsharing record describes:  In microbiology, the communication and comparison of research findings and data is often complicated by the existence of a number of different designation and identifiers for the same strain. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.aa4f35
title: FAIRsharing record for: MassIVE.quant
title: null

description: This FAIRsharing record describes:  MassIVE.quant is an extension of the Mass Spectrometry Interactive Virtual Environment (MassIVE) to provide the opportunity for large-scale deposition of heterogeneous experimental datasets, and facilitate a community-wide conversation about the necessary extent of experiment documentation and the benefits of its use. MassIVE.quant supports various reproducibility scopes, such as the infrastructure to fully automate the workflow, to store, and to browse the intermediate results. In addition, MassIVE.quant provides a collection of consistently documented and analyzed benchmark datasets.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.78e99f
title: FAIRsharing record for: Italian Archive of Historical Earthquake Data
title: ASMI

description: This FAIRsharing record describes:  The Italian Archive of Historical Earthquake Data (ASMI) makes data available on more than 6,000 earthquakes of interest for the Italian peninsula since 461 BC, data that is extracted from more than 450 seismological studies. ASMI grant access to the various existing studies and alternative datasets for each earthquake. The archived information can be accessed by earthquake or by study, and provides multiple types of data (intensity data, description of the effects, hypocentral parameters) presented in different formats such as texts, tables and interactive maps. ASMI is the data collection, homogenization, comparison and validation tool for compiling the Italian Macroseismic Database (DBMI) and the Parametric Catalogue of Italian Earthquakes (CPTI).
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.d67b36
title: FAIRsharing record for: IVOA Vocabulary: Datalink core
title: null

description: This FAIRsharing record describes:  Terms in this vocabulary relate (abstract) datasets to files or other electronic artefacts, giving the relation between the two. They are originally intended for use in the semantics column in the output from the DataLink-1.0 {links} capability. As specified in DataLink-1.0, terms from this vocabulary are used in the semantics column of {links} output output using only the identifier prefixed with a hash (i.e., "#word").
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.c29400
title: FAIRsharing record for: MIChI Standard for Reporting Liquid-State NMR Experiments of Small Molecules
title: MARGARITAS

description: This FAIRsharing record describes:  MARGARITAS stands for "Michi stAndard foR reportinG liquid-stAte nmR experImenTs of smAll moleculeS". This MIChI standard is a proposal from NFDI4Chem to outline essential metadata required for documenting liquid-state NMR experiments of small molecules. We aim to make it suitable for NMR repositories and the supplementary materials of publications. The standard consists of two parts: tabular recommendations that include the actual checklist of properties and textual guidelines explaining the meaning and use of the checklist. We actively maintain and optimise our MIChI, which results in new versions.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.5d98bd
title: FAIRsharing record for: Data, Optimization, Model and Evaluation Registry
title: DOME Registry

description: This FAIRsharing record describes:  The DOME registry provides a curated set of annotations for ML papers following the DOME recommendations. Data collection, annotation and integration in The DOME Registry is the result of an effort of expert curators. 
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.6084/m9.figshare.28473902
title: Dataset

description: This study analyzes the narrative strategies of North Korea’s Rodong Sinmun newspaper, focusing on 2,576 headlines published between 2023 and 2024. Using computational text analysis methods, I reveal a Dual-Framing Strategy that emphasizes either personalization or collectivism, depending on the context. I argue that while political coverage predominantly glorifies Kim Jong Un, emphasizing his role as the regime’s leader, economic narratives adopt a collectivist framing, underscoring shared responsibility and self-reliance (Juche doctrine). Notably, Kim Jong Un is entirely absent from economic coverage, challenging assumptions that all propaganda in the DPRK is inherently personalist. This differentiation shields the leader from potential criticism over economic challenges while reinforcing ideological cohesion. Additionally, political coverage highlights ideological and diplomatic alliances, avoiding substantial references to international economic relations. The evidence presented underscores the calculated use of propaganda in North Korea to maintain legitimacy and ideological coherence, crafting narratives that do not uniformly rely on personalism.
DOI: 10.25934/pr00008283.0
title: Available datapackage for study 'Phase IIIb Study to Evaluate the Safety and Tolerability of Herceptin SC With Perjeta and Docetaxel in Patients With HER2-positive Advanced Breast Cancer'

description: This is an open-label, single-arm, multicenter, Phase IIIb study to evaluate the safety and tolerability of Herceptin SC in combination with Perjeta IV plus docetaxel in female patients with HER2-positive metastatic or locally recurrent breast cancer. Enrolled patients are to receive study medication until disease progression, unacceptable toxicity, withdrawal of consent, death, or predefined study end, whichever occurs first. The anticipated time on study treatment is approximately 24 months. The target sample size is 400.
DOI: 10.25934/pr00008285.0
title: Available datapackage for study 'A Randomized, Multicenter, Open-Label, Phase III Trial Comparing Trastuzumab Plus Pertuzumab Plus a Taxane Following Anthracyclines Versus Trastuzumab Emtansine Plus Pertuzumab Following Anthracyclines as Adjuvant Therapy in Patients With Operable HER2-Positive Primary Breast Cancer'

description: This two-arm, randomized, open-label, multicenter study will evaluate the efficacy and safety of trastuzumab emtansine in combination with pertuzumab versus trastuzumab in combination with pertuzumab and a taxane as adjuvant therapy in participants with human epidermal growth (HER) factor 2 (HER2)-positive primary invasive breast cancer. Following surgery and anthracycline-based chemotherapy, participants will receive either trastuzumab emtansine at a dose of 3.6 milligrams per kilogram (mg/kg) and pertuzumab at a dose of 420 milligrams (mg) intravenously (IV) every 3 weeks (q3w) or trastuzumab at a dose of 6 mg/kg and pertuzumab at a dose of 420 mg IV q3w in combination with a taxane.
DOI: 10.15468/dl.bzu94b
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Lichen herbarium TRH, NTNU University Museum",
 "Country is Croatia"
 ]
}

 The dataset includes 102 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003405-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/9f3y-ya34
title: Air Temperature in East London

description: This dataset accompanies the IEEE IoT Journal paper titled "A Dual System IoT Strategy for Hyperlocal Spatial-Temporal Microclimate Monitoring in Urban Environments Using LoRa." It is intended for validating bespoke sensors against commercial sensors. The data were collected using two different types of sensors deployed at eight locations in East London, starting on August 1, 2023, and covering a period of one year. This paper focuses on the comparison of the two systems at the co-located sites, where in Fish Islands, sensors were installed in varied landscapes, including open residential areas, closed-off sections with limited sky exposure, riversides, and central squares. In Hackney Wick, sensors were placed in squares with different shading levels, at crossroads, and near bus stops to evaluate the impact of solar radiation and human activity on temperature readings. The proximity of these deployments enables the examination of microclimatic variations between adjacent urban areas.
DOI: 10.15468/dl.gcwtq4
title: Occurrence Download

description: A dataset containing 9334 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pinus sylvestris L.",
 "Year 1965-2025"
 ]
}

 The dataset includes 9334 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003411-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14919086
title: AMPERE Summary Plot Movies (2023-Jan)

description: 2023-Jan AMPERE summary plot movies. See included zenodo_summary_plot_movie_description document for details.
DOI: 10.5281/zenodo.14919087
title: AMPERE Summary Plot Movies (2023-Jan)

description: 2023-Jan AMPERE summary plot movies. See included zenodo_summary_plot_movie_description document for details.
DOI: 10.25318/3610041901-fra
title: Tableaux entrées-sorties provinciaux, entrées et sorties, niveau sommaire, prix de base

description: Ce tableau contient 23037 séries, avec des données pour les années 2007 - 2011 (il n'y a pas nécessairement de données pour toutes les années pour l'ensemble des combinaisons), et sa dernière date de diffusion remonte au 2015-11-10. Ce tableau contient des données telles que décrites par les dimensions suivantes (Les combinaisons ne sont pas toutes disponibles) : Géographie (15 éléments : Canada; Terre-Neuve-et-Labrador; Île-du-Prince-Édouard; Nouvelle-Écosse; ...) Entrées-sorties (2 éléments : Entrées; Sorties) Industries (36 éléments : Ensemble des industries; Cultures agricoles et élevage; Foresterie et exploitation forestière; Pêche, chasse et piégeage; ...).
DOI: 10.15468/dl.eby6ar
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Vertebrate Zoology Division - Ornithology, Yale Peabody Museum",
 "Country is Croatia"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003406-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14919172
title: FORMATION AND DEVELOPMENT OF CORPUS LINGUISTICS
DOI: 10.5281/zenodo.14919173
title: FORMATION AND DEVELOPMENT OF CORPUS LINGUISTICS
DOI: 10.15468/dl.rs9uh8
title: Occurrence Download

description: A dataset containing 2936 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pontia edusa",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1970",
 "Country is one of (Italy, Switzerland, Germany, Austria, Slovenia, France)"
 ]
}

 The dataset includes 2936 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0073043-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7rf32u
title: Occurrence Download

description: A dataset containing 96 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.hascoordinate = TRUE
 AND occurrence.hasgeospatialissues = FALSE
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (CAST(occurrence.taxonkey AS INTEGER) = 2874512 OR CAST(occurrence.acceptedtaxonkey AS INTEGER) = 2874512 OR CAST(occurrence.kingdomkey AS INTEGER) = 2874512 OR CAST(occurrence.phylumkey AS INTEGER) = 2874512 OR CAST(occurrence.classkey AS INTEGER) = 2874512 OR CAST(occurrence.orderkey AS INTEGER) = 2874512 OR CAST(occurrence.familykey AS INTEGER) = 2874512 OR CAST(occurrence.genuskey AS INTEGER) = 2874512 OR CAST(occurrence.specieskey AS INTEGER) = 2874512)
 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)
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"

 The dataset's 96 records were derived from 83 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0073022-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.