cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/ky7cvcj3mk
title: Hydrothermal_Niobium

description: Data associated with the manuscript "Speciation of Niobium in hydrothermal fluids". "01_XANES_EXAFS" series include the Athena, Artemis and Larch processed normalised XAS spectra data. "02_FDMNES" series include the results of FDMNES with different Ta complexes geometry. "03_Substi_Gibbs_Results" series include the substitute Nb-Cl-O complexes Gibbs Energy Results.
DOI: 10.17632/ky7cvcj3mk.1
title: Hydrothermal_Niobium

description: Data associated with the manuscript "Speciation of Niobium in hydrothermal fluids". "01_XANES_EXAFS" series include the Athena, Artemis and Larch processed normalised XAS spectra data. "02_FDMNES" series include the results of FDMNES with different Ta complexes geometry. "03_Substi_Gibbs_Results" series include the substitute Nb-Cl-O complexes Gibbs Energy Results.
DOI: 10.5281/zenodo.18247694
title: Meißen, Triebischtal-Apotheke (ca. 1924/1947)

description: Historical questionnaire/s 1924/1948 and index cards, partly selected enclosures regarding the history of a German pharmacy, catalogued via Kalliope portal (Historischer Fragebogen 1924/1948 und Karteikarten, ggf. gemeinfreie Anlagen zur Apothekengeschichte; als Katalog dient das Nachlassportal Kalliope): https://kalliope-verbund.info/DE-611-BF-70963 [Funktion: Im Findbuch anzeigen]Please note: The Kalliope catalogue entry might indicate related material in the archival folder which cannot be published due to copyright or other legal restrictions (NB: Das Katalogisat bei Kalliope kann auch auf Materialien - teils erheblichen Umfangs - verweisen, die aus archiv- oder urheberrechtlichen Gründen nicht veröffentlicht werden dürfen).
DOI: 10.5281/zenodo.18247693
title: Meißen, Triebischtal-Apotheke (ca. 1924/1947)

description: Historical questionnaire/s 1924/1948 and index cards, partly selected enclosures regarding the history of a German pharmacy, catalogued via Kalliope portal (Historischer Fragebogen 1924/1948 und Karteikarten, ggf. gemeinfreie Anlagen zur Apothekengeschichte; als Katalog dient das Nachlassportal Kalliope): https://kalliope-verbund.info/DE-611-BF-70963 [Funktion: Im Findbuch anzeigen]Please note: The Kalliope catalogue entry might indicate related material in the archival folder which cannot be published due to copyright or other legal restrictions (NB: Das Katalogisat bei Kalliope kann auch auf Materialien - teils erheblichen Umfangs - verweisen, die aus archiv- oder urheberrechtlichen Gründen nicht veröffentlicht werden dürfen).
DOI: 10.15468/dl.tmbtwh
title: Occurrence Download

description: A dataset containing 28740 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Abramis brama",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1990",
 "Year is less than or equal to 1994"
 ]
}

 The dataset includes 28740 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009487-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w9s2za
title: Occurrence Download

description: A dataset containing 11122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lacerta agilis",
 "Country is Germany",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year 2005-2020"
 ]
}

 The dataset includes 11122 records from 93 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009489-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.es4kpe
title: Occurrence Download

description: A dataset containing 21384 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Betula papyrifera",
 "BasisOfRecord is one of (Human Observation)"
 ]
}

 The dataset includes 21384 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009490-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15139/s3/uhlygv
title: Data Management and Sharing Plan for: Collaborative Research: RESEARCH-PGR NSF-SNSF: Comparative high-resolution analysis of transcription factor binding sites in plant organ formation

description: The Data Management and Sharing Plan describes the scientific data to be generated and/or used in the research and outlines a strategy for managing and sharing project data.
description: Data Management and Sharing Plan
DOI: 10.5281/zenodo.18247766
title: Baccharis rufescens Spreng. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.5281/zenodo.18247767
title: Baccharis rufescens Spreng. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.17632/rkbw676zf2.2
title: Videos and files for image analysis

description: Time-lapse live-cell imaging datasets and associated image analysis files.
DOI: 10.17632/d65x5skg84
title: Electofilia y cierre de alternativas electorales: fidelidad partidista declarada y evidencia con microdatos del CIS sobre voto alternativo y congruencia recuerdo × intención (España, 2023–2024)

description: Electofilia y cierre de alternativas electorales: fidelidad partidista declarada y evidencia con microdatos del CIS sobre voto alternativo y congruencia recuerdo × intención (España, 2023–2024).

AUTOR: José Javier Miranda Mayo

Este artículo propone y documenta un indicador observable en encuesta para capturar un patrón de cierre explícito de alternativas bajo un escenario contrafactual: la electofilia o declaración de que no existe ningún partido alternativo aceptable cuando el partido preferido no pudiera ser votado (código 9993 en el ítem de voto alternativo del CIS, P12/P16R). El objetivo es (1) cuantificar su prevalencia en dos barómetros del CIS y (2) describir su relación con el recuerdo de voto y la intención de voto, así como sus correlatos sociodemográficos mediante modelos logísticos ponderados. El manuscrito se mantiene deliberadamente descriptivo y no infiere mecanismos psicológicos ni consecuencias normativas. Se reportan prevalencias ponderadas con intervalos de confianza aproximados, cruces recuerdo×intención y resultados de modelos, preservando los universos elegibles definidos por el cuestionario del CIS y explicitando limitaciones de validez y de inferencia asociadas al filtrado y al diseño muestral. Por ello, las asociaciones reportadas deben interpretarse como patrones descriptivos y no como estimaciones causales.

ALGUNAS CITAS

“Este estudio utiliza microdatos reales del CIS para medir una forma estricta de electofilia o fidelidad partidista declarada basada en el voto alternativo (código 9993). En dos barómetros consecutivos, aproximadamente entre el 10% y el 12% de las personas a quienes se formula la pregunta declara no contemplar ningún otro partido.” (Miranda Mayo, J. J., 2026)

“cuando un segmento del electorado declara no contemplar alternativas incluso bajo un supuesto contrafactual, el castigo electoral ante evaluaciones negativas o transgresiones normativas podría volverse menos probable.” (Miranda Mayo, J. J., 2026)

Artículo completo en: https://www.evaluacionderiesgoslaborales.com/noticia.php?idnot=47
DOI: 10.17632/d65x5skg84.1
title: Electofilia y cierre de alternativas electorales: fidelidad partidista declarada y evidencia con microdatos del CIS sobre voto alternativo y congruencia recuerdo × intención (España, 2023–2024)

description: Electofilia y cierre de alternativas electorales: fidelidad partidista declarada y evidencia con microdatos del CIS sobre voto alternativo y congruencia recuerdo × intención (España, 2023–2024).

AUTOR: José Javier Miranda Mayo

Este artículo propone y documenta un indicador observable en encuesta para capturar un patrón de cierre explícito de alternativas bajo un escenario contrafactual: la electofilia o declaración de que no existe ningún partido alternativo aceptable cuando el partido preferido no pudiera ser votado (código 9993 en el ítem de voto alternativo del CIS, P12/P16R). El objetivo es (1) cuantificar su prevalencia en dos barómetros del CIS y (2) describir su relación con el recuerdo de voto y la intención de voto, así como sus correlatos sociodemográficos mediante modelos logísticos ponderados. El manuscrito se mantiene deliberadamente descriptivo y no infiere mecanismos psicológicos ni consecuencias normativas. Se reportan prevalencias ponderadas con intervalos de confianza aproximados, cruces recuerdo×intención y resultados de modelos, preservando los universos elegibles definidos por el cuestionario del CIS y explicitando limitaciones de validez y de inferencia asociadas al filtrado y al diseño muestral. Por ello, las asociaciones reportadas deben interpretarse como patrones descriptivos y no como estimaciones causales.

ALGUNAS CITAS

“Este estudio utiliza microdatos reales del CIS para medir una forma estricta de electofilia o fidelidad partidista declarada basada en el voto alternativo (código 9993). En dos barómetros consecutivos, aproximadamente entre el 10% y el 12% de las personas a quienes se formula la pregunta declara no contemplar ningún otro partido.” (Miranda Mayo, J. J., 2026)

“cuando un segmento del electorado declara no contemplar alternativas incluso bajo un supuesto contrafactual, el castigo electoral ante evaluaciones negativas o transgresiones normativas podría volverse menos probable.” (Miranda Mayo, J. J., 2026)

Artículo completo en: https://www.evaluacionderiesgoslaborales.com/noticia.php?idnot=47
DOI: 10.15468/dl.rhqxza
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"USA.34.97_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009491-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/93bjs843gn
title: SDG coding of museum exhibitions and monthly audience-interest indicators (TripAdvisor, visitors), Mar 2017–Sep 2025

description: This dataset contains source materials and derived data used in a monthly analysis linking SDG-related exhibition content to audience-interest indicators. The temporal coverage is March 2017 – September 2025 (103 monthly observations). The unit of observation is an exhibition (N=61) for the coding materials and a month for the analytical dataset.

Files:

exhibition codes.pdf – SDG coding for 61 exhibitions (Exhibition 1–Exhibition 61) across 17 SDGs (SDG1–SDG17) on a 0–2 scale, provided in two versions: “my code (0–2)” and “museum staff member’s code (0–2)”.

SDGs.pdf – exhibition scheduling and SDG aggregation over time:

scheduling section: exhibition list (EXHIBITION, TIME) plus an exhibition–month matrix where 1 indicates the exhibition was on display (blank cells = not on display);

aggregation section: monthly indicators for 11 SDGs (SDG3, SDG4, SDG5, SDG9, SDG10, SDG11, SDG12, SDG13, SDG15, SDG16, SDG17) including SUM of all exhibitions and, for each SDG: no. of exhibitions, mean_SDG, sum_SDG, share_SDG, mean_SDG_pos, any_SDG.

OLS.xlsx – regression-ready monthly dataset:

includes TripAdvisor_rating, TripAdvisor_reviews, log transforms (ln(reviews), ln(visitors+1)), visitors, exhibition counts (n_exhibitions, no_exhibitions), SDG indicators (mean_/sum_/share_/mean_*pos/any), and controls: COVID, open_museum, season (1 = tourist season; 0 = off-season), trend;

sheet provides an auxiliary working extract of selected SDG shares (share_SDG4 / share_SDG10 / share_SDG11 / share_SDG15 / share_SDG16).
DOI: 10.17632/93bjs843gn.1
title: SDG coding of museum exhibitions and monthly audience-interest indicators (TripAdvisor, visitors), Mar 2017–Sep 2025

description: This dataset contains source materials and derived data used in a monthly analysis linking SDG-related exhibition content to audience-interest indicators. The temporal coverage is March 2017 – September 2025 (103 monthly observations). The unit of observation is an exhibition (N=61) for the coding materials and a month for the analytical dataset.

Files:

exhibition codes.pdf – SDG coding for 61 exhibitions (Exhibition 1–Exhibition 61) across 17 SDGs (SDG1–SDG17) on a 0–2 scale, provided in two versions: “my code (0–2)” and “museum staff member’s code (0–2)”.

SDGs.pdf – exhibition scheduling and SDG aggregation over time:

scheduling section: exhibition list (EXHIBITION, TIME) plus an exhibition–month matrix where 1 indicates the exhibition was on display (blank cells = not on display);

aggregation section: monthly indicators for 11 SDGs (SDG3, SDG4, SDG5, SDG9, SDG10, SDG11, SDG12, SDG13, SDG15, SDG16, SDG17) including SUM of all exhibitions and, for each SDG: no. of exhibitions, mean_SDG, sum_SDG, share_SDG, mean_SDG_pos, any_SDG.

OLS.xlsx – regression-ready monthly dataset:

includes TripAdvisor_rating, TripAdvisor_reviews, log transforms (ln(reviews), ln(visitors+1)), visitors, exhibition counts (n_exhibitions, no_exhibitions), SDG indicators (mean_/sum_/share_/mean_*pos/any), and controls: COVID, open_museum, season (1 = tourist season; 0 = off-season), trend;

sheet provides an auxiliary working extract of selected SDG shares (share_SDG4 / share_SDG10 / share_SDG11 / share_SDG15 / share_SDG16).
DOI: 10.5281/zenodo.18247772
title: Baccharis rufescens var. tenuifolia (DC.) Baker. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.5281/zenodo.18247773
title: Baccharis rufescens var. tenuifolia (DC.) Baker. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.17632/553rmtf894
title: Quantitative Assessment of Scholarly Impact

description: This dataset provides a fully reproducible workflow for curating publication records, mapping peer-reviewed articles to research domains, and visualizing domain-specific scientific contributions using a quantile-based scoring framework.

Publication records were initially exported from Google Scholar (Ray_citations.csv) and curated using an R-based data cleaning pipeline (GoogleScholarDataCleaning.R). Conference abstracts, meeting-only entries, and preprints (including bioRxiv, medRxiv, arXiv, and Research Square) were excluded to retain peer-reviewed journal publications only. All filtering rules are explicitly documented and reproducible.

Peer-reviewed publications were subsequently mapped to predefined research domains using rule-based keyword matching, resulting in publication_domain_map_auto.csv. Domain-specific publication counts were normalized using a quantile-based approach to derive relative contribution scores, which were then visualized in a radar chart (K12_Radar_Musculoskeletal_Rehabilitation_quantile.pdf) using a fully reproducible R script (reproduce_domain_scoring_and_radar.R).

For presentation purposes and to improve readability in proposal formatting, the exported PDF figure was additionally imported into Adobe Illustrator for minor post-processing, including adjustment of font size, label positioning, and spacing. No data values, scoring results, or graphical relationships were altered during this step. The original PDF generated directly from R is retained to ensure transparency and reproducibility.

Together, these files enable transparent reproduction of the data processing, scoring methodology, and visualization used to summarize domain-specific scientific contributions and anticipated enhancement through structured training.
DOI: 10.17632/553rmtf894.1
title: Quantitative Assessment of Scholarly Impact

description: This dataset provides a fully reproducible workflow for curating publication records, mapping peer-reviewed articles to research domains, and visualizing domain-specific scientific contributions using a quantile-based scoring framework.

Publication records were initially exported from Google Scholar (Ray_citations.csv) and curated using an R-based data cleaning pipeline (GoogleScholarDataCleaning.R). Conference abstracts, meeting-only entries, and preprints (including bioRxiv, medRxiv, arXiv, and Research Square) were excluded to retain peer-reviewed journal publications only. All filtering rules are explicitly documented and reproducible.

Peer-reviewed publications were subsequently mapped to predefined research domains using rule-based keyword matching, resulting in publication_domain_map_auto.csv. Domain-specific publication counts were normalized using a quantile-based approach to derive relative contribution scores, which were then visualized in a radar chart (K12_Radar_Musculoskeletal_Rehabilitation_quantile.pdf) using a fully reproducible R script (reproduce_domain_scoring_and_radar.R).

For presentation purposes and to improve readability in proposal formatting, the exported PDF figure was additionally imported into Adobe Illustrator for minor post-processing, including adjustment of font size, label positioning, and spacing. No data values, scoring results, or graphical relationships were altered during this step. The original PDF generated directly from R is retained to ensure transparency and reproducibility.

Together, these files enable transparent reproduction of the data processing, scoring methodology, and visualization used to summarize domain-specific scientific contributions and anticipated enhancement through structured training.
DOI: 10.17632/23p45538y2
title: BacteArte XII: Interdisciplinary Art and Science Event Memory

description: This dataset documents BacteArte 2024, a Colombian national interdisciplinary event that integrated biotechnology, art, and STEM education, held on October 26, 2024, at the Universidad de Santander (UDES), Bucaramanga, Colombia. The event was organized by the Bacteriology and Clinical Laboratory Program of UDES, with the support of Fundación Eureka Soluciones, as part of an initiative focused on science communication, education, and innovative learning practices.

BacteArte 2024 brought together 152 students from 10 Colombian universities, creating a national space for collaboration among students and educators interested in bioart, biotechnology, and creative scientific expression. The central component of the event was an exhibition inspired by the microscopic world, featuring agar-based biological artworks created using genetically modified Escherichia coli expressing chromogenic and fluorescent recombinant proteins. These artworks explored microbial growth, color expression, and artistic interpretation under controlled biosecurity conditions.

In addition to agar-based bioart, the event included complementary artistic categories such as scientific photography, painting, and other artistic expressions, expanding the scope of the exhibition beyond biological media. The exhibition was installed in public spaces within the university campus, facilitating broad engagement with the academic community.

The dataset compiles photographic and audiovisual documentation of the artworks, educational resources (including a biosecurity guide and a training course), participant and institutional metadata, certificates, and dissemination materials. All data were collected with prior authorization from participants and managed according to ethical and institutional guidelines.

This dataset serves as the official archival record of BacteArte 2024 and supports the documentation, preservation, and reuse of interdisciplinary educational practices at the intersection of biotechnology, bioart, and STEM education.
DOI: 10.17632/23p45538y2.1
title: BacteArte XII: Interdisciplinary Art and Science Event Memory

description: This dataset documents BacteArte 2024, a Colombian national interdisciplinary event that integrated biotechnology, art, and STEM education, held on October 26, 2024, at the Universidad de Santander (UDES), Bucaramanga, Colombia. The event was organized by the Bacteriology and Clinical Laboratory Program of UDES, with the support of Fundación Eureka Soluciones, as part of an initiative focused on science communication, education, and innovative learning practices.

BacteArte 2024 brought together 152 students from 10 Colombian universities, creating a national space for collaboration among students and educators interested in bioart, biotechnology, and creative scientific expression. The central component of the event was an exhibition inspired by the microscopic world, featuring agar-based biological artworks created using genetically modified Escherichia coli expressing chromogenic and fluorescent recombinant proteins. These artworks explored microbial growth, color expression, and artistic interpretation under controlled biosecurity conditions.

In addition to agar-based bioart, the event included complementary artistic categories such as scientific photography, painting, and other artistic expressions, expanding the scope of the exhibition beyond biological media. The exhibition was installed in public spaces within the university campus, facilitating broad engagement with the academic community.

The dataset compiles photographic and audiovisual documentation of the artworks, educational resources (including a biosecurity guide and a training course), participant and institutional metadata, certificates, and dissemination materials. All data were collected with prior authorization from participants and managed according to ethical and institutional guidelines.

This dataset serves as the official archival record of BacteArte 2024 and supports the documentation, preservation, and reuse of interdisciplinary educational practices at the intersection of biotechnology, bioart, and STEM education.
DOI: 10.15468/dl.cjmu9b
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"IND.26.30_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009492-260108223611665/datasets/export for details.
DOI: 10.17632/c8mw46jf3z
title: Impact of a UV-C multiemitter disinfection system on hospital environmental bioburden and inactivation of clinically relevant pathogens

description: Data set of Impact of a UV-C multiemitter disinfection system on hospital environmental bioburden and inactivation of clinically relevant pathogens