cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.sj3tx9619
title: Data from: Drivers of bromeliad leaf and floral bract variation across a latitudinal gradient in the Atlantic Forest

description: Aim: Understanding the complex interaction and relative contributions of
 factors involved in species and trait diversification is crucial to gain
 insights into the evolution of Neotropical biodiversity. Here, we
 investigated the drivers of morphological variation in bromeliads along a
 latitudinal gradient in a biodiversity hotspot. Location: Atlantic Forest,
 Brazil. Taxon: A species complex in the genus Vriesea (Bromeliaceae).
 Methods: We measured shape and size variation for 208 floral bracts and
 176 leaves in individuals from 14 localities using geometric
 morphometrics. We compiled data for two chloroplast regions (matK and
 trnL-F) from 89 individuals to assess genetic diversity, population
 structure and phylogenetic relationships. We tested the influence of
 climate, altitude and genetic distance on morphological traits using
 linear statistical models. Results: Temperature seasonality is a main
 driver of floral bract shape. Together with precipitation, it also
 explains changes in leaf size across the latitudinal gradient. Shifts in
 morphological traits are correlated with genetic structure and partly
 support the recent taxonomic delimitation proposed for the species
 complex. The species started to diversify in the Pliocene ca. 5 Mya. We
 detected a phylogeographic break in species distribution into northern and
 southern clades between the Bocaina region and the southern portion of the
 Atlantic Forest. Main conclusions: We identify how geography and
 environmental changes through time shape floral bracts and leaves in
 similar ways. At highly seasonal sites with lower annual precipitation (in
 the southern subtropical portion of the Atlantic Forest), leaves are
 larger and floral bracts are wide-elliptic, making them better suited for
 increased water accumulation. In contrast, at less seasonal sites (in the
 tropical north, where rainfall is more abundant and temperatures are
 higher), leaves are narrower and floral bracts are lanceolate-shaped,
 facilitating water drainage. The biogeographical break we identified
 suggests a role of tectonic activity and climatic oscillations in
 promoting species divergence and diversification.
description: Plants were collected in nature. Floral bracts and leaves of
 individuals were scanned. All data generated or analysed are included in
 supplementary files. Complete information on methods is detailed in the
 main manuscript.
description: - Definition of variables and explanation of data in the Excel
 file. - Two folders of images of the structures
 analysed in this manuscript (Floral bract images and leaf
 images).
DOI: 10.15468/dl.m6dr6t
title: Occurrence Download

description: A dataset containing 17522335 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bryophyta"
 ]
}

 The dataset includes 17522335 records from 2749 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001900-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hrvh24
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Argentina",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Stillingia salpingadenia"
 ]
}

 The dataset includes 7 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007843-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48436/sed9k-vtc72
title: SDOstreamclust: Stream Clustering Robust to Concept Drift - Evaluation Tests

description: SDOstreamclust Evaluation Tests

conducted for the paper: Stream Clustering Robust to Concept Drift. Please refer to:



Iglesias Vazquez, F., Konzett, S., Zseby, T., & Bifet, A. (2025). Stream Clustering Robust to Concept Drift. In 2025 International Joint Conference on Neural Networks (IJCNN) (pp. 1–10). IEEE. https://doi.org/10.1109/IJCNN64981.2025.11227664


Context and methodology

SDOstreamclust is a stream clustering algorithm able to process data incrementally or per batches. It is a combination of the previous SDOstream (anomaly detection in data streams) and SDOclust (static clustering). SDOstreamclust holds the characteristics of SDO algoritmhs: lightweight, intuitive, self-adjusting, resistant to noise, capable of identifying non-convex clusters, and constructed upon robust parameters and interpretable models. Moreover, it shows excellent adaptation to concept drift 

In this repository, SDOclust is evaluated with 165 datasets (both synthetic and real) and compared with CluStream, DBstream, DenStream, StreamKMeans.

This repository is framed within the research on the following domains: algorithm evaluation, stream clustering, unsupervised learning, machine learning, data mining, streaming data analysis. Datasets and algorithms can be used for experiment replication and for further evaluation and comparison.

Docker

A Docker version is also available in: https://hub.docker.com/r/fiv5/sdostreamclust

Technical details

Experiments are conducted in Python v3.8.14. The file and folder structure is as follows:- [algorithms] contains a script with functions related to algorithm configurations.



 [data] contains datasets in ARFF format.

 [results] contains CSV files with algorithms' performances obtained from running the "run.sh" script (as shown in the paper).

"dependencies.sh" lists and installs python dependencies.

"pysdoclust-stream-main.zip" contains the SDOstreamclust python package. 

"README.md" shows details and intructions to use this repository.

"run.sh" runs the complete experiments.

"run_comp.py"for running experiments specified by arguments.

"TSindex.py" implements functions for the Temporal Silhouette index.


Note: if codes in SDOstreamclust are modified, SWIG (v4.2.1) wrappers have to be rebuilt and SDOstreamclust consequently reinstalled with pip. 

License

The CC-BY license applies to all data generated with MDCgen. All distributed code is under the GPLv3+  license.
DOI: 10.48436/xh0w2-q5x18
title: SDOstreamclust: Stream Clustering Robust to Concept Drift - Evaluation Tests

description: SDOstreamclust Evaluation Tests

conducted for the paper: Stream Clustering Robust to Concept Drift. Please refer to:



Iglesias Vazquez, F., Konzett, S., Zseby, T., & Bifet, A. (2025). Stream Clustering Robust to Concept Drift. In 2025 International Joint Conference on Neural Networks (IJCNN) (pp. 1–10). IEEE. https://doi.org/10.1109/IJCNN64981.2025.11227664


Context and methodology

SDOstreamclust is a stream clustering algorithm able to process data incrementally or per batches. It is a combination of the previous SDOstream (anomaly detection in data streams) and SDOclust (static clustering). SDOstreamclust holds the characteristics of SDO algoritmhs: lightweight, intuitive, self-adjusting, resistant to noise, capable of identifying non-convex clusters, and constructed upon robust parameters and interpretable models. Moreover, it shows excellent adaptation to concept drift 

In this repository, SDOclust is evaluated with 165 datasets (both synthetic and real) and compared with CluStream, DBstream, DenStream, StreamKMeans.

This repository is framed within the research on the following domains: algorithm evaluation, stream clustering, unsupervised learning, machine learning, data mining, streaming data analysis. Datasets and algorithms can be used for experiment replication and for further evaluation and comparison.

Docker

A Docker version is also available in: https://hub.docker.com/r/fiv5/sdostreamclust

Technical details

Experiments are conducted in Python v3.8.14. The file and folder structure is as follows:- [algorithms] contains a script with functions related to algorithm configurations.



 [data] contains datasets in ARFF format.

 [results] contains CSV files with algorithms' performances obtained from running the "run.sh" script (as shown in the paper).

"dependencies.sh" lists and installs python dependencies.

"pysdoclust-stream-main.zip" contains the SDOstreamclust python package. 

"README.md" shows details and intructions to use this repository.

"run.sh" runs the complete experiments.

"run_comp.py"for running experiments specified by arguments.

"TSindex.py" implements functions for the Temporal Silhouette index.


Note: if codes in SDOstreamclust are modified, SWIG (v4.2.1) wrappers have to be rebuilt and SDOstreamclust consequently reinstalled with pip. 

License

The CC-BY license applies to all data generated with MDCgen. All distributed code is under the GPLv3+  license.
DOI: 10.23673/re-559
title: Financial well-being and personality

description: The data were collected as part of an online panel study in Estonia in April 2024 by the survey agency Norstat. The questionnaire was programmed in LimeSurvey and consisted of three sections. The first section included socio-demographic indicators, comprised of age, gender, education, and area of residence. Age was grouped into 5-year blocks except for the 18-19 age group. The area of residence was categorised based on indicators from the Estonian Department of Statistics. The second section off the questionnaire consisted of questions related to personality. The 20 statements validated in the Estonian National Mental Health Study (Laidra et al., 2023) are part of a more extensive personality questionnaire that was previously used in personality research. This questionnaire was developed to investigate the links between personality traits and genetics (Arumäe et al., 2025). The third section contained nine items measuring the three dimensions of FWB The final part of the questionnaire included questions about the respondents’ occupation and satisfaction with their current monetary situation (income). The study was also preregistered in the Open Science Framework (https://osf.io/t9j5s) environment. The sample consists of 1007 adults aged 18-74. The participants could complete the questionnaire in either Estonian or Russian. The sample was formed according to quotas for different socio-demographic indicators that were created in line with Estonian population statistics. This approach was chosen to create a sample that closely matches the Estonian adult resident population in terms of key demographic characteristics.
DOI: 10.15468/dl.emsfdz
title: Occurrence Download

description: A dataset containing 3807 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Dicksonia sellowiana"
 ]
}

 The dataset includes 3807 records from 226 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007844-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17286414
title: Quantifying Conversational Coherence: Empirical Evidence of Shared Informational Structure in Human Dialogue

description: This dataset contains the full materials and computational implementation used in the study “Quantifying Conversational Coherence: Empirical Evidence of Shared Informational Structure in Human Dialogue.”

It includes:





Human annotations of six natural dialogues (≈23 turns each) by five independent annotators, marking valleys (ruptures of coherence) and peaks (recoveries of coherence).




The Python script, implementing the tolerant evaluation framework described in the paper (tolerant Precision–Recall–F₁, permutation baselines, Fleiss’ κ and Light’s κ on dilated labels).




The reproducible results (valleys_peaks_final_results.xlsx) obtained from the final dataset.



Analyses were performed using pooled and window-tolerant matching (±1, ±2, ±3 turns) and 300 permutation baselines preserving per-annotator event frequencies.

All computations are fully replicable. The materials support the claim—consistent with the Theory of Informational Emergence (TIE)—that conversational coherence is not merely semantic but an emergent informational property of interactional dynamics.

Future work: A forthcoming pilot study will correlate these human agreement results with automated coherence metrics generated by TIE–Dialog, an analytical tool designed to simulate informational coherence and detect structural ruptures and recoveries in real-time conversational data.

 

Contact:

Adolfo J. Céspedes Jiménez — University of Groningen

📧 a.j.cespedes.jimenez@student.rug.nl
DOI: 10.5281/zenodo.17286413
title: Quantifying Conversational Coherence: Empirical Evidence of Shared Informational Structure in Human Dialogue

description: This dataset contains the full materials and computational implementation used in the study “Quantifying Conversational Coherence: Empirical Evidence of Shared Informational Structure in Human Dialogue.”

It includes:





Human annotations of six natural dialogues (≈23 turns each) by five independent annotators, marking valleys (ruptures of coherence) and peaks (recoveries of coherence).




The Python script, implementing the tolerant evaluation framework described in the paper (tolerant Precision–Recall–F₁, permutation baselines, Fleiss’ κ and Light’s κ on dilated labels).




The reproducible results (valleys_peaks_final_results.xlsx) obtained from the final dataset.



Analyses were performed using pooled and window-tolerant matching (±1, ±2, ±3 turns) and 300 permutation baselines preserving per-annotator event frequencies.

All computations are fully replicable. The materials support the claim—consistent with the Theory of Informational Emergence (TIE)—that conversational coherence is not merely semantic but an emergent informational property of interactional dynamics.

Future work: A forthcoming pilot study will correlate these human agreement results with automated coherence metrics generated by TIE–Dialog, an analytical tool designed to simulate informational coherence and detect structural ruptures and recoveries in real-time conversational data.

 

Contact:

Adolfo J. Céspedes Jiménez — University of Groningen

📧 a.j.cespedes.jimenez@student.rug.nl
DOI: 10.15468/dl.924swy
title: Occurrence Download

description: A dataset listing the 8 species recorded in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Heteroplacidium compactum"
 ]
}

 The dataset's 8 records were derived from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007828-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pp4kpw
title: Occurrence Download

description: A dataset containing 334 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((94.96626 5.92499,94.29736 4.90197,95.6745 3.80026,97.62217 2.12802,99.23538 -0.40985,102.08803 -4.61996,104.27178 -6.80371,105.8063 -6.23318,107.20312 -2.65262,105.23577 -0.7443,103.99635 0.49512,102.36346 1.28206,100.2584 3.13136,97.18935 5.96433,94.96626 5.92499))",
 "TaxonKey is Nephelium"
 ]
}

 The dataset includes 334 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007846-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.24403/jp.1512755
title: Nachruf auf Elmar Bickar / Frank Merken
DOI: 10.15468/dl.putxfe
title: Occurrence Download

description: A dataset containing 756 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leontopithecus rosalia"
 ]
}

 The dataset includes 756 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007845-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jfaev9
title: Occurrence Download

description: A dataset containing 2896 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Dicksonia sellowiana"
 ]
}

 The dataset includes 2896 records from 190 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007847-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17712406
title: Survey: Hydrological information needs and limitations for habitat RS-monitoring

description: Annex for Biodiversa+ Habitat Pilot subtask report: Habitat condition indicators for monitoring. (2025)

The file contains a spreadsheet of habitat monitoring survey results. In the survey, we mapped information needs and expected limitations for remote sensing (RS) -based monitoring of grassland and wetland habitats hydrological condition. The survey was answered by six pilot partners for their respective regions in the EU. 

The spreadsheet contains the following sections filled by each partner for each of the habitat types occurring in their region:





Habitat Directive Annex 1 Habitat type




Relevant season(s) for monitoring




Required time window for observations to capture ecologically relevant hydrological events in the habitat (quick- versus longer term flooding, prolonged drought periods)




Expected limitations for satellite-based monitoring (tree-cover, thick vegetation layer, high-resolution heterogeneity, small size of habitats)




Relevancy of the suggested yearly RS-indicator metrics including the following:






Moisture indices:






Yearly mean, mean of specific season, wetness minimum, wetness maximum





Inundation






Number of inundated months or weeks 




Seasonally/constantly inundated area




Ending time of flooding season





Drought frequency over multiple years
DOI: 10.5281/zenodo.17712405
title: Survey: Hydrological information needs and limitations for habitat RS-monitoring

description: Annex for Biodiversa+ Habitat Pilot subtask report: Habitat condition indicators for monitoring. (2025)

The file contains a spreadsheet of habitat monitoring survey results. In the survey, we mapped information needs and expected limitations for remote sensing (RS) -based monitoring of grassland and wetland habitats hydrological condition. The survey was answered by six pilot partners for their respective regions in the EU. 

The spreadsheet contains the following sections filled by each partner for each of the habitat types occurring in their region:





Habitat Directive Annex 1 Habitat type




Relevant season(s) for monitoring




Required time window for observations to capture ecologically relevant hydrological events in the habitat (quick- versus longer term flooding, prolonged drought periods)




Expected limitations for satellite-based monitoring (tree-cover, thick vegetation layer, high-resolution heterogeneity, small size of habitats)




Relevancy of the suggested yearly RS-indicator metrics including the following:






Moisture indices:






Yearly mean, mean of specific season, wetness minimum, wetness maximum





Inundation






Number of inundated months or weeks 




Seasonally/constantly inundated area




Ending time of flooding season





Drought frequency over multiple years
DOI: 10.15468/dl.4tx26h
title: Occurrence Download

description: A dataset containing 10274 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Ursus maritimus"
 ]
}

 The dataset includes 10274 records from 157 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007850-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25420/britishmuseum.30649247
title: Guide to the Dataset

description: Document outlining team member roles, project background and significance, level of endangerment, fieldwork approach, overview of assets, structure of documentation records, equipment and software, acknowledgements, references.
DOI: 10.25420/britishmuseum.30649247.v1
title: Guide to the Dataset

description: Document outlining team member roles, project background and significance, level of endangerment, fieldwork approach, overview of assets, structure of documentation records, equipment and software, acknowledgements, references.
DOI: 10.25420/britishmuseum.30649208.v1
title: Artist Bảo extended interview transcript (Vietnamese)

description: Transcript of Artist Bảo's extended interview with Co-I Phạm Thanh Thôi (Vietnamese). Topics include his artistic training, mentor, career trajectory, family life, Vietnam's advertising industry, his future plans and hopes for the profession.
DOI: 10.25420/britishmuseum.30649211
title: Artist Bảo extended interview transcript (English)

description: Transcript of Artist Bảo's extended interview with Co-I Phạm Thanh Thôi (English). Topics include his artistic training, mentor, career trajectory, family life, Vietnam's advertising industry, his future plans and hopes for the profession.
DOI: 10.25420/britishmuseum.30649211.v1
title: Artist Bảo extended interview transcript (English)

description: Transcript of Artist Bảo's extended interview with Co-I Phạm Thanh Thôi (English). Topics include his artistic training, mentor, career trajectory, family life, Vietnam's advertising industry, his future plans and hopes for the profession.
DOI: 10.25420/britishmuseum.30649208
title: Artist Bảo extended interview transcript (Vietnamese)

description: Transcript of Artist Bảo's extended interview with Co-I Phạm Thanh Thôi (Vietnamese). Topics include his artistic training, mentor, career trajectory, family life, Vietnam's advertising industry, his future plans and hopes for the profession.
DOI: 10.25420/britishmuseum.30648572
title: Transcript of interview and discussion with Artist Thuyên's customer Mr Quang (English)

description: Transcript of Co-I Phạm Thanh Thôi interviewing Artist Thuyên's customer Mr Quang, the group surveying objects in Mr Quang's nostalgia café and discussing the trend for handpainted signs (English).
DOI: 10.25420/britishmuseum.30648572.v1
title: Transcript of interview and discussion with Artist Thuyên's customer Mr Quang (English)

description: Transcript of Co-I Phạm Thanh Thôi interviewing Artist Thuyên's customer Mr Quang, the group surveying objects in Mr Quang's nostalgia café and discussing the trend for handpainted signs (English).
DOI: 10.25420/britishmuseum.30648569
title: Transcript of interview and discussion with Artist Thuyên's customer Mr Quang (Vietnamese)

description: Transcript of Co-I Phạm Thanh Thôi interviewing Artist Thuyên's customer Mr Quang, the group surveying objects in Mr Quang's nostalgia café and discussing the trend for handpainted signs (Vietnamese).
DOI: 10.25420/britishmuseum.30648569.v1
title: Transcript of interview and discussion with Artist Thuyên's customer Mr Quang (Vietnamese)

description: Transcript of Co-I Phạm Thanh Thôi interviewing Artist Thuyên's customer Mr Quang, the group surveying objects in Mr Quang's nostalgia café and discussing the trend for handpainted signs (Vietnamese).
DOI: 10.25420/britishmuseum.30648410
title: Uncle Nghĩa interview transcript (Vietnamese)

description: Transcript of Uncle Nghĩa's interview (Vietnamese). He discusses his artistic training, working for Ho Chi Minh City’s Department of Culture and Information, the development of Vietnam's advertising industry following economic reform and the current trend of Old Saigon-style signboards.