cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/5vg-h79-k7p
title: Papillicardium papillosum (Poli, 1791)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/vtk-gbp-waa
title: Pomatias elegans (O. F. Müller, 1774)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/py8-gyp-ew4
title: Helcion concolor (Krauss, 1848)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.60712/si-id404732.1
title: StrainInfo SI-ID 404732.1

description: StrainInfo dataset 404732 about a strain of Tepidimicrobium. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404733.1
title: StrainInfo SI-ID 404733.1

description: StrainInfo dataset 404733 about a strain of Bounagaea algeriensis. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404560.1
title: StrainInfo SI-ID 404560.1

description: StrainInfo dataset 404560 about a strain of Marinimicrobium haloxylanilyticum. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404561.1
title: StrainInfo SI-ID 404561.1

description: StrainInfo dataset 404561 about a strain of Saliphagus infecundisoli. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.15468/dl.metzgc
title: Occurrence Download

description: A dataset containing 497339 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "TaxonKey is Ericaceae",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 497339 records from 499 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026458-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60712/si-id404562.1
title: StrainInfo SI-ID 404562.1

description: StrainInfo dataset 404562 about a strain of Nocardioides. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404659.1
title: StrainInfo SI-ID 404659.1

description: StrainInfo dataset 404659 about a strain of Lysobacter. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404660.1
title: StrainInfo SI-ID 404660.1

description: StrainInfo dataset 404660 about a strain of Labilithrix luteola. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404661.1
title: StrainInfo SI-ID 404661.1

description: StrainInfo dataset 404661 about a strain of Acetoanaerobium pronyense. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404662.1
title: StrainInfo SI-ID 404662.1

description: StrainInfo dataset 404662 about a strain of Halomicrobium. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404734.1
title: StrainInfo SI-ID 404734.1

description: StrainInfo dataset 404734 about a strain of Ilumatobacter fluminis. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404735.1
title: StrainInfo SI-ID 404735.1

description: StrainInfo dataset 404735 about a strain of Mycobacterium. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404736.1
title: StrainInfo SI-ID 404736.1

description: StrainInfo dataset 404736 about a strain of Defluviitoga tunisiensis. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404737.1
title: StrainInfo SI-ID 404737.1

description: StrainInfo dataset 404737 about a strain of Paracoccus. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id404563.1
title: StrainInfo SI-ID 404563.1

description: StrainInfo dataset 404563 about a strain of Halomonas sediminis. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.5281/zenodo.17506332
title: My test
DOI: 10.5281/zenodo.17506283
title: Oncological Risk of Agricultural Zones (ORAZ) — Russia, 2022

description: This dataset accompanies the research article "The Oncological Footprint of Industrial Dairy Systems in Russia: Evidence of a Regional Anomaly Driven by Agricultural Intensification".

It introduces the Oncological Risk of Agricultural Zones (ORAZ) index — a novel composite metric designed to quantify the latent oncological risk associated not with dairy consumption, but with the intensity of industrial dairy production in a region. The index integrates four environmental and agricultural dimensions:

Livestock density (dairy cattle per 1,000 ha of arable land)Agrochemical load (mineral fertilizers + 0.5 × pesticides, kg/ha)Water vulnerability (proximity of livestock operations to surface water bodies)Ecological fragility (low forest cover as a proxy for reduced environmental buffering)The dataset covers 78 federal subjects of the Russian Federation for the year 2022 and includes:

Calculated ORAZ values (normalized, mean = 1.0)Oncological anomalies (Δ): residuals from a multivariate model predicting cancer incidence based on socioeconomic, demographic, and diagnostic factorsInput variables: GDP per capita, livestock statistics, agrochemical use, forest cover, and moreA statistically significant correlation (r = 0.71, p < 0.001) was found between high ORAZ scores and unexplained excess cancer incidence—particularly in the Central Black Earth zone—while traditional pastoral regions (e.g., Altai, Tuva) show low ORAZ and negative anomalies despite high dairy availability.

This work reframes agricultural intensification as an environmental determinant of cancer risk and provides a scalable tool for eco-oncological surveillance in rapidly industrializing regions.

Files included:

oraz_regions_full.csv — main datasetsources_description.txt — data provenance and methodologycalculate_oraz.py — demonstrative Python scriptoraz_russia.geojson — GIS layer with simplified regional boundaries

All source data are derived from open Russian federal statistics (Rosstat, Federal Oncological Registry, Ministry of Agriculture). The dataset is published to support transparency, reproducibility, and further research at the intersection of food systems, environmental health, and oncology.
DOI: 10.5281/zenodo.17506284
title: Oncological Risk of Agricultural Zones (ORAZ) — Russia, 2022

description: This dataset accompanies the research article "The Oncological Footprint of Industrial Dairy Systems in Russia: Evidence of a Regional Anomaly Driven by Agricultural Intensification".

It introduces the Oncological Risk of Agricultural Zones (ORAZ) index — a novel composite metric designed to quantify the latent oncological risk associated not with dairy consumption, but with the intensity of industrial dairy production in a region. The index integrates four environmental and agricultural dimensions:

Livestock density (dairy cattle per 1,000 ha of arable land)Agrochemical load (mineral fertilizers + 0.5 × pesticides, kg/ha)Water vulnerability (proximity of livestock operations to surface water bodies)Ecological fragility (low forest cover as a proxy for reduced environmental buffering)The dataset covers 78 federal subjects of the Russian Federation for the year 2022 and includes:

Calculated ORAZ values (normalized, mean = 1.0)Oncological anomalies (Δ): residuals from a multivariate model predicting cancer incidence based on socioeconomic, demographic, and diagnostic factorsInput variables: GDP per capita, livestock statistics, agrochemical use, forest cover, and moreA statistically significant correlation (r = 0.71, p < 0.001) was found between high ORAZ scores and unexplained excess cancer incidence—particularly in the Central Black Earth zone—while traditional pastoral regions (e.g., Altai, Tuva) show low ORAZ and negative anomalies despite high dairy availability.

This work reframes agricultural intensification as an environmental determinant of cancer risk and provides a scalable tool for eco-oncological surveillance in rapidly industrializing regions.

Files included:

oraz_regions_full.csv — main datasetsources_description.txt — data provenance and methodologycalculate_oraz.py — demonstrative Python scriptoraz_russia.geojson — GIS layer with simplified regional boundaries

All source data are derived from open Russian federal statistics (Rosstat, Federal Oncological Registry, Ministry of Agriculture). The dataset is published to support transparency, reproducibility, and further research at the intersection of food systems, environmental health, and oncology.
DOI: 10.5281/zenodo.17222820
title: Dataset for submitted paper: "Experimental Characterization of Miniature DC Motors for Robotics in High Magnetic Field Environments"
DOI: 10.5281/zenodo.17222821
title: Dataset for submitted paper: "Experimental Characterization of Miniature DC Motors for Robotics in High Magnetic Field Environments"
DOI: 10.34740/kaggle/dsv/13586360
title: Predictive Churn Intelligence – Flask & ML
DOI: 10.5281/zenodo.17505365
title: WGS-based de novo genome assemblies and comparative functional annotations on genomic architecture and molecular variation in Oecophylla smaragdina (Formicidae: Hymenoptera)

description: Oecophylla smaragdina, the Asian weaver ant, is a socially complex arboreal species with three distinct morphological castes queen, drone, and worker. Despite its pronounced caste differentiation, the genomic basis underlying these phenotypic distinctions remains less understood. In this study, we present caste-specific draft genome assemblies and functional annotations to investigate the genomic architecture and diversity among castes. Whole-genome sequencing was performed using the Illumina NovaSeq 6000 platform. GenomeScope analysis estimated genome sizes ranging from 210-227 Mb, with low repeat content (0.6–1.4%). Assemblies generated via SPAdes revealed that the worker genome was the most contiguous (N50: 16 kb; scaffolds: 120,615). BUSCO assessments (Hymenoptera_odb10) indicated the highest completeness in the worker genome (84.2%), followed by the queen (74.8%) and drone (72.3%). QUAST comparisons against the reference genome (GCA_048542515.1) supported these findings, with the worker genome showing the largest genome fraction (95.47%). Structural annotation using AGAT identified 32,485 genes in the queen, 17,904 in the drone, and 17,723 in the worker. Functional annotation through InterProScan and eggNOG-mapper revealed enrichment in transcription and signal transduction categories across all castes. Gene ontology analysis highlighted caste-specific pathways like reproductive functions in queens, metabolic processes in workers, and neural functions in drones. Phylogenetic reconstruction confirmed close clustering of all three castes within O. smaragdina and the broader Formicidae lineage. All sequencing data have been deposited in the NCBI Sequence Read Archive under BioProject ID PRJNA1078118. These draft genome assemblies provide a foundational resource for future investigations into caste differentiation, eusociality, and evolutionary genomics in ants.
DOI: 10.5281/zenodo.17505364
title: WGS-based de novo genome assemblies and comparative functional annotations on genomic architecture and molecular variation in Oecophylla smaragdina (Formicidae: Hymenoptera)

description: Oecophylla smaragdina, the Asian weaver ant, is a socially complex arboreal species with three distinct morphological castes queen, drone, and worker. Despite its pronounced caste differentiation, the genomic basis underlying these phenotypic distinctions remains less understood. In this study, we present caste-specific draft genome assemblies and functional annotations to investigate the genomic architecture and diversity among castes. Whole-genome sequencing was performed using the Illumina NovaSeq 6000 platform. GenomeScope analysis estimated genome sizes ranging from 210-227 Mb, with low repeat content (0.6–1.4%). Assemblies generated via SPAdes revealed that the worker genome was the most contiguous (N50: 16 kb; scaffolds: 120,615). BUSCO assessments (Hymenoptera_odb10) indicated the highest completeness in the worker genome (84.2%), followed by the queen (74.8%) and drone (72.3%). QUAST comparisons against the reference genome (GCA_048542515.1) supported these findings, with the worker genome showing the largest genome fraction (95.47%). Structural annotation using AGAT identified 32,485 genes in the queen, 17,904 in the drone, and 17,723 in the worker. Functional annotation through InterProScan and eggNOG-mapper revealed enrichment in transcription and signal transduction categories across all castes. Gene ontology analysis highlighted caste-specific pathways like reproductive functions in queens, metabolic processes in workers, and neural functions in drones. Phylogenetic reconstruction confirmed close clustering of all three castes within O. smaragdina and the broader Formicidae lineage. All sequencing data have been deposited in the NCBI Sequence Read Archive under BioProject ID PRJNA1078118. These draft genome assemblies provide a foundational resource for future investigations into caste differentiation, eusociality, and evolutionary genomics in ants.
DOI: 10.6084/m9.figshare.28768094
title: Morocco 2050: A Vision of Economic Dynamism, Social Progress, and Geopolitical Influence.

description: By 2050, Morocco could be among the world’s most dynamic emerging nations, Africa’s first climate-resilient economy, a regional leader in digital innovation, and a geopolitical bridge across three continents. This vision is not a distant dream; it is a trajectory already being shaped today. As global paradigms shift from climate upheaval to the AI revolution, from energy transitions to the fragmentation of traditional alliances, Morocco finds itself uniquely positioned to capitalise on its geographic, cultural, and strategic endowments.The stakes are high. What Morocco chooses to invest in over the next two decades will define its place in a reconfigured world order. This paper presents a forward-looking framework for policymakers, investors, civil society, and international partners seeking to contribute to and benefit from Morocco’s long-term transformation.Far more than a speculative blueprint, Morocco 2050 offers an integrated roadmap for sustainable growth, institutional resilience, and inclusive social progress. It invites its readers to envision Morocco not only as a gateway to Africa but as a model for balancing tradition and modernity, sovereignty and openness, continuity and innovation.Anchored in evidence and foresight, this report sets out a comprehensive strategy across sectors from renewable energy and digital economy to education, healthcare, logistics, and cultural industries. It explores the enablers of national renewal: good governance, adaptive policies, global partnerships, and the mobilisation of Morocco’s greatest asset, its people, both at home and across its diaspora.Morocco 2050 is a call to action. It is designed to guide decision-makers and attract visionary investors who understand that building the future is no longer optional; it is imperative. The time to shape Morocco’s success story is now.
DOI: 10.6084/m9.figshare.28768094.v1
title: Morocco 2050: A Vision of Economic Dynamism, Social Progress, and Geopolitical Influence.

description: By 2050, Morocco could be among the world’s most dynamic emerging nations, Africa’s first climate-resilient economy, a regional leader in digital innovation, and a geopolitical bridge across three continents. This vision is not a distant dream; it is a trajectory already being shaped today. As global paradigms shift from climate upheaval to the AI revolution, from energy transitions to the fragmentation of traditional alliances, Morocco finds itself uniquely positioned to capitalise on its geographic, cultural, and strategic endowments.The stakes are high. What Morocco chooses to invest in over the next two decades will define its place in a reconfigured world order. This paper presents a forward-looking framework for policymakers, investors, civil society, and international partners seeking to contribute to and benefit from Morocco’s long-term transformation.Far more than a speculative blueprint, Morocco 2050 offers an integrated roadmap for sustainable growth, institutional resilience, and inclusive social progress. It invites its readers to envision Morocco not only as a gateway to Africa but as a model for balancing tradition and modernity, sovereignty and openness, continuity and innovation.Anchored in evidence and foresight, this report sets out a comprehensive strategy across sectors from renewable energy and digital economy to education, healthcare, logistics, and cultural industries. It explores the enablers of national renewal: good governance, adaptive policies, global partnerships, and the mobilisation of Morocco’s greatest asset, its people, both at home and across its diaspora.Morocco 2050 is a call to action. It is designed to guide decision-makers and attract visionary investors who understand that building the future is no longer optional; it is imperative. The time to shape Morocco’s success story is now.
DOI: 10.34740/kaggle/dsv/13586386
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.6skzeq
title: Occurrence Download

description: A dataset containing 10303 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Collection Ornithologie - SNSD"
 ]
}

 The dataset includes 10303 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011529-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cxu6vj
title: Occurrence Download

description: A dataset containing 10303 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Collection Ornithologie - SNSD"
 ]
}

 The dataset includes 10303 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011530-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17506394
title: MassBank <=> PubChem Deposition/Annotation Repository

description: This is a repository to exchange MassBank record and substance information to create deposition and annotation files in PubChem.

Supporting code in: https://gitlab.com/uniluxembourg/lcsb/eci/pubchem/-/tree/master/massbank_eu

Credits:



LCSB-ECI: Anjana Elapavalore, Todor Kondic, Emma Schymanski

PubChem: Jeff Zhang, Paul Thiessen, Ben Shoemaker, Evan Bolton

MassBank Consortium: Rene Meier, Steffen Neumann, Tobias Schulze


Note: 20230419 files removes deprecated records from the 2022.12 release and still has InChIKeys added manually for ACES records (listed as NA) for annotation; all are present in the deposition. The unique substance file did not change, but close to 200 deprecated records were removed from the annotation set. 20230908, 20231129, 20240610, 20241126, 20250502: ACES InChIKeys added manually. 20251024: now automated.
DOI: 10.5281/zenodo.5139996
title: MassBank <=> PubChem Deposition/Annotation Repository

description: This is a repository to exchange MassBank record and substance information to create deposition and annotation files in PubChem.

Supporting code in: https://gitlab.com/uniluxembourg/lcsb/eci/pubchem/-/tree/master/massbank_eu

Credits:



LCSB-ECI: Anjana Elapavalore, Todor Kondic, Emma Schymanski

PubChem: Jeff Zhang, Paul Thiessen, Ben Shoemaker, Evan Bolton

MassBank Consortium: Rene Meier, Steffen Neumann, Tobias Schulze


Note: 20230419 files removes deprecated records from the 2022.12 release and still has InChIKeys added manually for ACES records (listed as NA) for annotation; all are present in the deposition. The unique substance file did not change, but close to 200 deprecated records were removed from the annotation set. 20230908, 20231129, 20240610, 20241126, 20250502: ACES InChIKeys added manually. 20251024: now automated.