cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/kjb4c7865j
title: Lichen diversity, indicator species, and community turnover along a fog oasis–Andean gradient in Peru: a baseline for climate change biomonitoring

description: Lichens are sensitive bioindicators of environmental change, yet their diversity patterns remain poorly documented in the hyperarid ecosystems of southern Peru. This study characterizes, for the first time, lichen diversity, community composition, and indicator species along a coastal-Andean altitudinal gradient (683–3,756 m a.s.l.) encompassing fog oases (lomas) and high-Andean shrublands in Moquegua, a region facing increasing pressure from large-scale copper mining and projected climate change impacts. We established 175 sampling units across 35 stations in seven sectors, identifying 53 lichen species belonging to 33 genera, 13 families, 10 orders, and 3 classes (Lecanoromycetes, Candelariomycetes, and Arthoniomycetes). Alpha diversity indices (Shannon, Simpson, Pielou) were compared between ecosystems using Wilcoxon and t-tests, community composition was analyzed through NMDS and PERMANOVA, environmental predictors were evaluated using GLM and LM, and indicator species were identified with the IndVal.g index.
Simpson diversity was significantly higher in Andean shrublands than in coastal fog oases (0.83 ± 0.06 vs. 0.75 ± 0.09; p = 0.029), while Pielou's evenness showed highly significant differences (0.90 ± 0.06 vs. 0.77 ± 0.08; p &lt; 0.001). Remarkably, community composition showed complete species turnover between ecosystems (β-diversity = 1), with 28 species exclusive to coastal fog oases and 25 species exclusive to Andean shrublands—a pattern rarely documented in lichenological studies. PERMANOVA confirmed highly significant compositional differences at both ecosystem (R² = 0.280, p = 0.001) and sector (R² = 0.765, p = 0.001) levels. Altitude and climatic zone emerged as the primary environmental predictors, explaining 60.9% of Shannon diversity variance. Thirty-four indicator species were identified with significant ecological fidelity (p ≤ 0.05), including Umbilicaria polyphylla (IndVal = 0.980) for Andean shrublands and Flavopunctelia flaventior (IndVal = 0.707) for coastal fog oases.
DOI: 10.17632/kjb4c7865j.1
title: Lichen diversity, indicator species, and community turnover along a fog oasis–Andean gradient in Peru: a baseline for climate change biomonitoring

description: Lichens are sensitive bioindicators of environmental change, yet their diversity patterns remain poorly documented in the hyperarid ecosystems of southern Peru. This study characterizes, for the first time, lichen diversity, community composition, and indicator species along a coastal-Andean altitudinal gradient (683–3,756 m a.s.l.) encompassing fog oases (lomas) and high-Andean shrublands in Moquegua, a region facing increasing pressure from large-scale copper mining and projected climate change impacts. We established 175 sampling units across 35 stations in seven sectors, identifying 53 lichen species belonging to 33 genera, 13 families, 10 orders, and 3 classes (Lecanoromycetes, Candelariomycetes, and Arthoniomycetes). Alpha diversity indices (Shannon, Simpson, Pielou) were compared between ecosystems using Wilcoxon and t-tests, community composition was analyzed through NMDS and PERMANOVA, environmental predictors were evaluated using GLM and LM, and indicator species were identified with the IndVal.g index.
Simpson diversity was significantly higher in Andean shrublands than in coastal fog oases (0.83 ± 0.06 vs. 0.75 ± 0.09; p = 0.029), while Pielou's evenness showed highly significant differences (0.90 ± 0.06 vs. 0.77 ± 0.08; p &lt; 0.001). Remarkably, community composition showed complete species turnover between ecosystems (β-diversity = 1), with 28 species exclusive to coastal fog oases and 25 species exclusive to Andean shrublands—a pattern rarely documented in lichenological studies. PERMANOVA confirmed highly significant compositional differences at both ecosystem (R² = 0.280, p = 0.001) and sector (R² = 0.765, p = 0.001) levels. Altitude and climatic zone emerged as the primary environmental predictors, explaining 60.9% of Shannon diversity variance. Thirty-four indicator species were identified with significant ecological fidelity (p ≤ 0.05), including Umbilicaria polyphylla (IndVal = 0.980) for Andean shrublands and Flavopunctelia flaventior (IndVal = 0.707) for coastal fog oases.
DOI: 10.17632/pyh4w9srs7
title: Large Language Models and the Labour Market: Spatial Evidence from Job Ads

description: This is the database for the following article: Baranyai, E., Granát, M., Szepesi, M. (2026) Large Language Models and the Labour
Market: Spatial Evidence from Job Ads.

Despite the rapid rise of large language models (LLMs) and their implications for productivity and employment, little is known about how exposure to LLMs varies within and across countries. Understanding these patterns matters because technology spillovers are often geographically localised, and regional disparities can affect domestic and international labour market flows, long-term growth, social cohesion, and political stability. Using geolocated, task-level data from all job advertisements on Hungarys largest online job portal, we apply an LLM-based mapping approach to estimate job exposure. Extrapolating to the national labour market, we find Hungarys average LLM exposure to be 8%, substantially lower than estimates for the United States. This gap is partly explained by Hungarys higher share of physically intensive occupations and lower prevalence of office-based roles. Job-level exposure rarely exceeds 30%, suggesting that LLMs primarily complement rather than replace tasks. Spatial variation in exposure is driven mainly by industry composition, with higher exposure in urban areas and associations with current demographic characteristics and historical economic development. These findings highlight regions and sectors where productivity gains from LLM adoption may arise and where targeted education and employment policies could support workforce adjustment.
DOI: 10.17632/pyh4w9srs7.1
title: Large Language Models and the Labour Market: Spatial Evidence from Job Ads

description: This is the database for the following article: Baranyai, E., Granát, M., Szepesi, M. (2026) Large Language Models and the Labour
Market: Spatial Evidence from Job Ads.

Despite the rapid rise of large language models (LLMs) and their implications for productivity and employment, little is known about how exposure to LLMs varies within and across countries. Understanding these patterns matters because technology spillovers are often geographically localised, and regional disparities can affect domestic and international labour market flows, long-term growth, social cohesion, and political stability. Using geolocated, task-level data from all job advertisements on Hungarys largest online job portal, we apply an LLM-based mapping approach to estimate job exposure. Extrapolating to the national labour market, we find Hungarys average LLM exposure to be 8%, substantially lower than estimates for the United States. This gap is partly explained by Hungarys higher share of physically intensive occupations and lower prevalence of office-based roles. Job-level exposure rarely exceeds 30%, suggesting that LLMs primarily complement rather than replace tasks. Spatial variation in exposure is driven mainly by industry composition, with higher exposure in urban areas and associations with current demographic characteristics and historical economic development. These findings highlight regions and sectors where productivity gains from LLM adoption may arise and where targeted education and employment policies could support workforce adjustment.
DOI: 10.17632/j72cwhshsd
title: Research on the lag effect of rainfall erosivity in southern China: relevant Data

description: This dataset constitutes critical data for research into the lag effect of rainfall erosion potential in southern China, primarily comprising rainfall erosion potential data calculated from daily rainfall amounts, alongside various climatic index data.
DOI: 10.17632/j72cwhshsd.1
title: Research on the lag effect of rainfall erosivity in southern China: relevant Data

description: This dataset constitutes critical data for research into the lag effect of rainfall erosion potential in southern China, primarily comprising rainfall erosion potential data calculated from daily rainfall amounts, alongside various climatic index data.
DOI: 10.17632/j3yk2kkkkz
title: Long-term population dynamics of a human-associated colonial raptor: case of Lesser Kestrel Falco naumanni

description: Breeding biology data used in article
DOI: 10.17632/j3yk2kkkkz.1
title: Long-term population dynamics of a human-associated colonial raptor: case of Lesser Kestrel Falco naumanni

description: Breeding biology data used in article
DOI: 10.17632/jgfkz6493p
title: UzThemeLex Dataset: An Uzbek Thematic Lexicon for Domain Terminology and Weakly Supervised NER

description: UzThemeLex is a curated Uzbek-language thematic lexicon dataset designed for domain terminology mining and weakly supervised named entity recognition (NER). The release contains 4,945 unique terminological entries organized into 3 top-level domains (Agronomy, Economics and Business, Law and Governance) and 30 subcategories. Each entry provides the Uzbek term in Latin script, a normalized form for matching, a paraphrased Uzbek definition, domain and subcategory labels, provenance pointers to authoritative sources, and lightweight quality-control signals (heuristic confidence score, review flag, ambiguity flag). Optional fields include aliases and example sentences.

The dataset is distributed in multiple formats to support both manual inspection and machine processing. It includes a flat CSV file and a multi-sheet Excel workbook, together with a data dictionary that documents all columns and label sets. For training and pipeline integration, the release also provides JSON/JSONL exports, taxonomy metadata, and ready-to-use pattern files for dictionary-based tagging and weak supervision (e.g., spaCy EntityRuler patterns). A validation script is included to help users verify schema consistency and detect formatting issues (e.g., residual Cyrillic characters and apostrophe normalization).

UzThemeLex can be used as (i) a domain dictionary for keyword-based classification and information extraction in Uzbek texts and (ii) a gazetteer for generating weak labels to train or fine-tune NER models. The resource is intended to support Uzbek NLP research and applied text analytics in agriculture, economics, and legal/governance domains.
DOI: 10.17632/jgfkz6493p.1
title: UzThemeLex Dataset: An Uzbek Thematic Lexicon for Domain Terminology and Weakly Supervised NER

description: UzThemeLex is a curated Uzbek-language thematic lexicon dataset designed for domain terminology mining and weakly supervised named entity recognition (NER). The release contains 4,945 unique terminological entries organized into 3 top-level domains (Agronomy, Economics and Business, Law and Governance) and 30 subcategories. Each entry provides the Uzbek term in Latin script, a normalized form for matching, a paraphrased Uzbek definition, domain and subcategory labels, provenance pointers to authoritative sources, and lightweight quality-control signals (heuristic confidence score, review flag, ambiguity flag). Optional fields include aliases and example sentences.

The dataset is distributed in multiple formats to support both manual inspection and machine processing. It includes a flat CSV file and a multi-sheet Excel workbook, together with a data dictionary that documents all columns and label sets. For training and pipeline integration, the release also provides JSON/JSONL exports, taxonomy metadata, and ready-to-use pattern files for dictionary-based tagging and weak supervision (e.g., spaCy EntityRuler patterns). A validation script is included to help users verify schema consistency and detect formatting issues (e.g., residual Cyrillic characters and apostrophe normalization).

UzThemeLex can be used as (i) a domain dictionary for keyword-based classification and information extraction in Uzbek texts and (ii) a gazetteer for generating weak labels to train or fine-tune NER models. The resource is intended to support Uzbek NLP research and applied text analytics in agriculture, economics, and legal/governance domains.
DOI: 10.17632/567r73y4mp
title: Raw data for Manuscript

description: Raw testing data
DOI: 10.17632/567r73y4mp.1
title: Raw data for Manuscript

description: Raw testing data
DOI: 10.17632/7m3jrh2c3w
title: Atypical Borrowing by Resource-based Firms: Implications for Resource Curse

description: Replication package for the paper
DOI: 10.17632/7m3jrh2c3w.1
title: Atypical Borrowing by Resource-based Firms: Implications for Resource Curse

description: Replication package for the paper
DOI: 10.17632/zw9479ybdd
title: UzNER-5Style Corpus

description: As part of the study, an annotated corpus of the Uzbek language was created for training and evaluating named entity recognition (NER) models. The corpus consists of 5,000 sentences (65,608 words) collected from various sources.

The data were compiled from the following sources:

• Legislative and official documents: Part of the data was extracted from the publicly available lex.uz database, which contains official and normative legal texts.

• Mass media sources: To enrich the corpus, materials were collected from the online news platform kun.uz and transcripts of videos from the youtube.com platform covering various topics.

• Literary sources: Excerpts from the novel “Kecha va kunduz” were selected to represent the literary style.

• Scientific sources: Texts in the scientific style were obtained from conference proceedings and academic collections.

• Synthetic data: In addition, synthetic sentences in the scientific style were generated to further diversify the corpus.

The collected data were organized according to five major functional styles: colloquial, official, scientific, literary, and publicistic. This approach ensured thematic and stylistic diversity of the corpus and enhanced the effectiveness of model training.

Data annotation was performed manually using the BIOES tagging scheme, which enables precise identification of the boundaries and types of named entities. All annotated data were reviewed and validated by Uzbek language experts to ensure accuracy and consistency.
DOI: 10.17632/zw9479ybdd.1
title: UzNER-5Style Corpus

description: As part of the study, an annotated corpus of the Uzbek language was created for training and evaluating named entity recognition (NER) models. The corpus consists of 5,000 sentences (65,608 words) collected from various sources.

The data were compiled from the following sources:

• Legislative and official documents: Part of the data was extracted from the publicly available lex.uz database, which contains official and normative legal texts.

• Mass media sources: To enrich the corpus, materials were collected from the online news platform kun.uz and transcripts of videos from the youtube.com platform covering various topics.

• Literary sources: Excerpts from the novel “Kecha va kunduz” were selected to represent the literary style.

• Scientific sources: Texts in the scientific style were obtained from conference proceedings and academic collections.

• Synthetic data: In addition, synthetic sentences in the scientific style were generated to further diversify the corpus.

The collected data were organized according to five major functional styles: colloquial, official, scientific, literary, and publicistic. This approach ensured thematic and stylistic diversity of the corpus and enhanced the effectiveness of model training.

Data annotation was performed manually using the BIOES tagging scheme, which enables precise identification of the boundaries and types of named entities. All annotated data were reviewed and validated by Uzbek language experts to ensure accuracy and consistency.
DOI: 10.15468/dl.mjp8xf
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryconexodon juruenae",
 "DecimalLatitude is not null",
 "DecimalLongitude is not null"
 ]
}

 The dataset includes 68 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004153-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/8b3fd45kp6
title: ClassTrim

description: The experiment dataset is organized into two main folders: ClassTrim and baseline.

The ClassTrim folder contains all raw experimental data produced by our proposed model. It includes detailed execution records, refactoring recommendations, and intermediate results generated during the experiments.

The baseline folder contains the complete records of how the baseline tools were executed, along with the refactoring results produced by each baseline approach. 

Each folder is accompanied by a dedicated README.md file that precisely explains the directory structure, file formats, and the semantics of each data file.

At the top level of the dataset, experiment-result.xlsx and baseline.xlsx provide summarized results derived from the raw data. These two files aggregate all experimental outcomes and serve as the direct data source for the tables reported in the paper.
DOI: 10.17632/8b3fd45kp6.1
title: ClassTrim

description: The experiment dataset is organized into two main folders: ClassTrim and baseline.

The ClassTrim folder contains all raw experimental data produced by our proposed model. It includes detailed execution records, refactoring recommendations, and intermediate results generated during the experiments.

The baseline folder contains the complete records of how the baseline tools were executed, along with the refactoring results produced by each baseline approach. 

Each folder is accompanied by a dedicated README.md file that precisely explains the directory structure, file formats, and the semantics of each data file.

At the top level of the dataset, experiment-result.xlsx and baseline.xlsx provide summarized results derived from the raw data. These two files aggregate all experimental outcomes and serve as the direct data source for the tables reported in the paper.
DOI: 10.15468/dl.yzqjy3
title: Occurrence Download

description: A dataset containing 759 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Pleurodema thaul"
 ]
}

 The dataset includes 759 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004154-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cjdhu4
title: Occurrence Download

description: A dataset containing 40 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryconexodon trombetasi",
 "DecimalLatitude is not null",
 "DecimalLongitude is not null"
 ]
}

 The dataset includes 40 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004155-260208012135463/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/14789804
title: BITCOIN Historical Datasets 2018-2026 Binance API
DOI: 10.5281/zenodo.18575880
title: Complex homes, complex lives: how macrophytes' structural complexity shapes taxonomic and functional diversity in periphytic ciliate communities.
DOI: 10.5281/zenodo.18575881
title: Complex homes, complex lives: how macrophytes' structural complexity shapes taxonomic and functional diversity in periphytic ciliate communities.
DOI: 10.25919/y883-wg60
title: Parkes observations for project P1054 semester 2025OCTS_17

description: With this proposal we ask time to continue our timing follow-up campaign of pulsars discovered with the MeerKAT telescope. Fourtyfour sources have been discovered in targeted observations of Fermi unidentified point sources, two towards Supernova Remnants, 26 in the Magellanic Clouds, 106 in Globular Clusters and 87 in a survey of the Galactic plane. A large fraction of the new discoveries are recycled pulsars (including a few relativistic systems, a pulsar with a planetary companion and several 'spider' binaries), or young pulsars. Timing observations have an essential role in exploiting the full potential of any pulsar discovery, allowing for the precise measurement of rotational, astrometric and orbital parameters which, in turn, give us powerful tools to improve our understanding of the physics in extreme environments as well as of the population of neutron stars as a whole. The UWL receiver of the Parkes telescope is a sensitive, versatile instrument that is allowing us to successfully time these new sources, in the bright-end of TRAPUM discoveries.
DOI: 10.25919/gpmd-y354
title: Parkes observations for project P1165 semester 2025OCTS_06

description: We recently discovered two new pulsars J1849+1001 (35.1 ms) and J1839+0543 (57.9 ms) in a FAST pulsar survey at intermediate Galactic latitudes (PT2020_0141). Follow-up timing observations show that they are in circular orbits with massive companions. This suggests that PSR J1849+1001 and J1839+0543 can be classified as the intermediate-mass binary pulsar (IMBP). Their massive companions also make them promising systems to measure "Post-Keplerian" parameters through pulsar timing. These Parkes observations will be combined with regular timing observations with FAST or MeerKAT to measure "Post-Keplerian" parameters and then measure both neutron star and companion masses.
DOI: 10.15468/dl.wrv2u5
title: Occurrence Download

description: A dataset containing 95650 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erysiphe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 95650 records from 329 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004109-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4vhdgr
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryconops disruptus",
 "DecimalLatitude is not null",
 "DecimalLongitude is not null"
 ]
}

 The dataset includes 30 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004157-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.