cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18368772
title: Processed monthly NDTI forecasting dataset for Wadi Dayqah Reservoir (Oman)

description: This record provides the processed data used in the manuscript “Interpretable Spatiotemporal Forecasting of the Normalized Difference Turbidity Index: A Hybrid Deep Learning Framework with Uncertainty Quantification” (Yavari et al.). The dataset contains monthly mean composites for Wadi Dayqah Reservoir (WDR), Oman, covering December 2018–March 2025 (76 months), prepared for pixel-wise one-month-ahead forecasting of the Normalized Difference Turbidity Index (NDTI; turbidity proxy).
DOI: 10.15468/dl.anh3zw
title: Occurrence Download

description: A dataset containing 9871 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Flora de las playas y dunas costeras de México"
 ]
}

 The dataset includes 9871 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011048-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qnn8ka
title: Occurrence Download

description: A dataset containing 571 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Goodenia pilosa",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 571 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011049-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18368584
title: SuperDARN data in netCDF format (2005-Mar)

description: 2005-Mar SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6633844
title: SuperDARN data in netCDF format (2005-Mar)

description: 2005-Mar SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.18357502
title: Mass spectrometry data profiling whole cell lipid extractions from Mycobacterium tuberculosis H37Rv and strains mutated in Rv3377c and Rv3378c

description: Mass spectrometry data files of whole cell lipid extracts from strains of Mycobacterium tuberculosis with engineered replacement of the gene(s) Rv3377c, Rv3378c, or both, as well as the non-mutated parental strain H36Rv.  Biological quadruplicate samples from each strain were profiled to assess terpene nucleoside biosynthesis.  These data were analyzed in the manuscript, “Mycobacteria that cause tuberculosis have retained ancestrally acquired genes for the biosynthesis of chemically diverse terpene nucleosides” (https://doi.org/10.1371/journal.pbio.3002813) and were included in analyzed form (DOI 10.5281/zenodo.8096634). Mass spectrometry data is provided as centroided mzXML files, along with an annotated sample list and instrument metadata.
DOI: 10.5281/zenodo.18357501
title: Mass spectrometry data profiling whole cell lipid extractions from Mycobacterium tuberculosis H37Rv and strains mutated in Rv3377c and Rv3378c

description: Mass spectrometry data files of whole cell lipid extracts from strains of Mycobacterium tuberculosis with engineered replacement of the gene(s) Rv3377c, Rv3378c, or both, as well as the non-mutated parental strain H36Rv.  Biological quadruplicate samples from each strain were profiled to assess terpene nucleoside biosynthesis.  These data were analyzed in the manuscript, “Mycobacteria that cause tuberculosis have retained ancestrally acquired genes for the biosynthesis of chemically diverse terpene nucleosides” (https://doi.org/10.1371/journal.pbio.3002813) and were included in analyzed form (DOI 10.5281/zenodo.8096634). Mass spectrometry data is provided as centroided mzXML files, along with an annotated sample list and instrument metadata.
DOI: 10.15468/dl.k5k775
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Tyto pollens"
 ]
}

 The dataset includes 34 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011050-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6xrdag
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Goodenia splendida",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 16 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011051-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18368846
title: MACROECONOMIC FACTORS AFFECTING BUSINESS VALUE: IN THE CONTEXT OF UZBEKISTAN AND THE GLOBAL MARKET.

description: This article examines the impact of key macroeconomic factors on business valuation in Uzbekistan amid structural reforms and increasing integration into the global economy. The study analyzes the transmission channels through which GDP dynamics, inflation, and exchange rate volatility affect asset valuation and discounting parameters, as well as the role of external shocks transmitted via trade, investment, and financial markets. A comparative analysis of Uzbekistan’s macroeconomic conditions with those of selected countries demonstrates that the instability of correlations between macroeconomic indicators and market capitalization necessitates the adaptation of conventional valuation models. The paper proposes a quantitative valuation framework that integrates domestic macroeconomic variables with global economic cycles, accounting for lagged effects, sectoral sensitivity, and scenario-based projections of inflation and interest rates. The practical relevance of the findings lies in the development of a methodological toolkit aimed at improving valuation accuracy and reducing investment risks under conditions of macroeconomic uncertainty.
DOI: 10.5281/zenodo.18368847
title: MACROECONOMIC FACTORS AFFECTING BUSINESS VALUE: IN THE CONTEXT OF UZBEKISTAN AND THE GLOBAL MARKET.

description: This article examines the impact of key macroeconomic factors on business valuation in Uzbekistan amid structural reforms and increasing integration into the global economy. The study analyzes the transmission channels through which GDP dynamics, inflation, and exchange rate volatility affect asset valuation and discounting parameters, as well as the role of external shocks transmitted via trade, investment, and financial markets. A comparative analysis of Uzbekistan’s macroeconomic conditions with those of selected countries demonstrates that the instability of correlations between macroeconomic indicators and market capitalization necessitates the adaptation of conventional valuation models. The paper proposes a quantitative valuation framework that integrates domestic macroeconomic variables with global economic cycles, accounting for lagged effects, sectoral sensitivity, and scenario-based projections of inflation and interest rates. The practical relevance of the findings lies in the development of a methodological toolkit aimed at improving valuation accuracy and reducing investment risks under conditions of macroeconomic uncertainty.
DOI: 10.15468/dl.fzgcvj
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leschenaultia formosa",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 16 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011053-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hz7g88
title: Occurrence Download

description: A dataset containing 88 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Chelonoidis alburyorum"
 ]
}

 The dataset includes 88 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011054-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yzjrb5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scaevola plumieri",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011055-260120142942310/datasets/export for details.
DOI: 10.5281/zenodo.18368878
title: MODERN METHODS OF TEACHING RUSSIAN AS A FOREIGN LANGUAGE: A REVIEW OF FOREIGN AND DOMESTIC RESEARCH

description: This article presents an overview of modern methods of teaching Russian as a foreign language, based on an analysis of domestic and international research. The article examines the main approaches to teaching, including communicative, activity-based, situational, and integrative approaches, as well as their theoretical foundations and practical application. It also analyzes the effectiveness of various methodological concepts, the challenges of their implementation in the educational process, and the role of digital technologies in developing language competence. The review identifies current trends, the potential and limitations of these methods, as well as prospects for their development in the context of improving the quality of teaching Russian as a foreign language.
DOI: 10.5281/zenodo.18368879
title: MODERN METHODS OF TEACHING RUSSIAN AS A FOREIGN LANGUAGE: A REVIEW OF FOREIGN AND DOMESTIC RESEARCH

description: This article presents an overview of modern methods of teaching Russian as a foreign language, based on an analysis of domestic and international research. The article examines the main approaches to teaching, including communicative, activity-based, situational, and integrative approaches, as well as their theoretical foundations and practical application. It also analyzes the effectiveness of various methodological concepts, the challenges of their implementation in the educational process, and the role of digital technologies in developing language competence. The review identifies current trends, the potential and limitations of these methods, as well as prospects for their development in the context of improving the quality of teaching Russian as a foreign language.
DOI: 10.15468/dl.qsx9a4
title: Occurrence Download

description: A dataset containing 16417 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aedes, Anopheles, Culex)",
 "Country is Italy",
 "HasCoordinate is true"
 ]
}

 The dataset includes 16417 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011056-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wbfcnx
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scaevola spicigera",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 11 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011057-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r73xr7
title: Occurrence Download

description: A dataset containing 184711 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ambrosia artemisiifolia"
 ]
}

 The dataset includes 184711 records from 1564 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011037-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p9hsuu
title: Occurrence Download

description: A dataset listing the 440 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-103.40008 20.40881,-103.35378 20.38478,-103.28825 20.38478,-103.26331 20.3968,-103.27186 20.4275,-103.29252 20.45621,-103.34523 20.45621,-103.38441 20.44553,-103.40008 20.42817,-103.40008 20.40881))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset's 440 records were derived from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003559-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wcvujt
title: Occurrence Download

description: A dataset containing 5 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.countrycode IN ('CN', 'HK')
 AND GBIF_STRINGARRAYCONTAINS(occurrence.classifications['d7dddbf4-2cf0-4f39-9b2a-bb099caae36c'], '3089150', TRUE)
 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.occurrencestatus = 'PRESENT'
 AND (occurrence.classificationdetails['d7dddbf4-2cf0-4f39-9b2a-bb099caae36c']['specieskey'] &lt;&gt; '' 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 5 records were derived from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003552-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6r5389
title: Occurrence Download

description: A dataset containing 4531 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Aloe vera"
 ]
}

 The dataset includes 4531 records from 343 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003564-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uqywen
title: Occurrence Download

description: A dataset listing the 0 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Global Register of Introduced and Invasive Species - France"
 ]
}

 The dataset's 0 records were derived from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003562-260129131611470/datasets/export for details.
DOI: 10.5281/zenodo.18443610
title: Score Result Questionare Partisipant
DOI: 10.5281/zenodo.18443611
title: Score Result Questionare Partisipant
DOI: 10.6084/m9.figshare.29469164.v2
title: Data sets

description: PCBIS
DOI: 10.5281/zenodo.18443339
title: PLENet
DOI: 10.5281/zenodo.18443340
title: PLENet
DOI: 10.5281/zenodo.18436093
title: ASSETS_D2.3_UNED_Castilla-LeonTranscriptions

description: This dataset contains fully anonymised interview transcripts collected for Deliverable 2.3 of the ASSETS project within Work Package 2.3, contributing to the qualitative phase of the project and informing Deliverable 2.5. The qualitative phase aims to capture nuanced insights and lived experiences related to the political, regulatory, and labour landscape of the social economy across European regions.

The transcripts derive from semi-structured qualitative interviews conducted in Castilla y León (Spain) with a diverse group of social economy stakeholders, including representatives of social and solidarity economy organisations and networks, public administration staff, political actors, university-based and non-academic researchers, employees of intermediary organisations, and members of social movements.

The interviews explore regional social economy ecosystems, existing legal and policy frameworks, institutional arrangements, labour conditions, and perceived barriers and enabling factors affecting the development, sustainability, and scaling of social economy initiatives.

All transcripts have been fully anonymised in accordance with ethical requirements and data protection regulations. This dataset supports the qualitative analysis reported in Deliverable 2.3 and contributes to a comparative understanding of social economy governance, policy design, and labour conditions across territorial contexts. It is shared to enhance transparency, reusability, and future research on institutional ecosystems and enabling environments for the social economy.
DOI: 10.5281/zenodo.18436092
title: ASSETS_D2.3_UNED_Castilla-LeonTranscriptions

description: This dataset contains fully anonymised interview transcripts collected for Deliverable 2.3 of the ASSETS project within Work Package 2.3, contributing to the qualitative phase of the project and informing Deliverable 2.5. The qualitative phase aims to capture nuanced insights and lived experiences related to the political, regulatory, and labour landscape of the social economy across European regions.

The transcripts derive from semi-structured qualitative interviews conducted in Castilla y León (Spain) with a diverse group of social economy stakeholders, including representatives of social and solidarity economy organisations and networks, public administration staff, political actors, university-based and non-academic researchers, employees of intermediary organisations, and members of social movements.

The interviews explore regional social economy ecosystems, existing legal and policy frameworks, institutional arrangements, labour conditions, and perceived barriers and enabling factors affecting the development, sustainability, and scaling of social economy initiatives.

All transcripts have been fully anonymised in accordance with ethical requirements and data protection regulations. This dataset supports the qualitative analysis reported in Deliverable 2.3 and contributes to a comparative understanding of social economy governance, policy design, and labour conditions across territorial contexts. It is shared to enhance transparency, reusability, and future research on institutional ecosystems and enabling environments for the social economy.
DOI: 10.15468/dl.tgc9wq
title: Occurrence Download

description: A dataset containing 34437 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-103.7381 17.91491, -100.063 17.91491, -100.063 20.39456, -103.7381 20.39456, -103.7381 17.91491))",
 "TaxonKey is Mammalia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 34437 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003567-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.