cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.3jtazg
title: Occurrence Download

description: A dataset containing 1396 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lepidium campestre",
 "Country is Canada",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1396 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022824-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vts436
title: Occurrence Download

description: A dataset containing 387 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Argythamnia desertorum"
 ]
}

 The dataset includes 387 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022823-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/p9lsb9
title: Time-dependent approach to the X-ray photoemission problem

description: Supplementary data for the work available at: 
https://doi.org/10.48550/arXiv.2502.11317 (2025)
DOI: 10.15468/dl.pz5j5z
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lepidium campestre",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022825-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17047145
title: Regression-Ready dataset for: The Impact of the 2022 Energy Crisis on UK Electricity System Prices

description: This dataset accompanies the thesis “The Impact of the 2022 Energy Crisis on UK Electricity System Prices: A Commodity Market Analysis.” It provides a regression-ready panel of daily observations for the UK electricity system price and its key explanatory variables over the 2021–2023 period. Variables include Brent crude oil prices, Dutch TTF natural gas prices, GBP/USD exchange rates, Geopolitical Risk Index (GPR/GRI), Economic Policy Uncertainty Index (EPU) and FTSE All-Share Index (FTAS).

The dataset has been fully cleaned, standardized, and formatted to support multiple linear regression and robustness checks. It is designed to enable replication of the thesis results and further exploration of commodity–electricity linkages during the 2022 energy crisis.

By making this dataset openly available, the research supports transparency, reproducibility, and innovation at the intersection of energy economics and financial technology (Fintech), where advanced analytics and market modeling are increasingly used for decision-making.
DOI: 10.5281/zenodo.17047146
title: Regression-Ready dataset for: The Impact of the 2022 Energy Crisis on UK Electricity System Prices

description: This dataset accompanies the thesis “The Impact of the 2022 Energy Crisis on UK Electricity System Prices: A Commodity Market Analysis.” It provides a regression-ready panel of daily observations for the UK electricity system price and its key explanatory variables over the 2021–2023 period. Variables include Brent crude oil prices, Dutch TTF natural gas prices, GBP/USD exchange rates, Geopolitical Risk Index (GPR/GRI), Economic Policy Uncertainty Index (EPU) and FTSE All-Share Index (FTAS).

The dataset has been fully cleaned, standardized, and formatted to support multiple linear regression and robustness checks. It is designed to enable replication of the thesis results and further exploration of commodity–electricity linkages during the 2022 energy crisis.

By making this dataset openly available, the research supports transparency, reproducibility, and innovation at the intersection of energy economics and financial technology (Fintech), where advanced analytics and market modeling are increasingly used for decision-making.
DOI: 10.5066/p13vzbte
title: Water temperature, air temperature, sensor depth, and select flow and temperature metrics. Data from water year 2020 for the Stormwater Action Monitoring Puget Small Streams Project

description: These data were collected as part of the Stormwater Action Monitoring (SAM) program's Puget Small Streams (PSS) status and trends program (https://ecology.wa.gov/regulations-permits/reporting-requirements/stormwater-monitoring/stormwater-action-monitoring/sam-status-and-trends/puget-small-streams). The data presented here were collected from 29 sites during water year 2020 for water temperature, air temperature, and sensor depth. Sensor depth was used as a surrogate for water depth and represents the arbitrary depth of water above the sensor location in the water column. Data were collected at 15-minute intervals from October 2019 until September 2020 using Hobo U20L-04 sensors that simultaneously measured temperature and pressure. All data were analyzed and approved following USGS continuous data processing procedures.

Sensor depth data was used as a surrogate for stream stage in order to calculate three flow metrics: (1) the fraction of time that flow exceeded the annual mean (TQmean), (2) the Richards-Baker Index of flashiness (RBI), and (3) the annual tally of wet-season day-to-day flow reversals following methods outlined in Booth and Konrad (2017). In addition to these flow metrics, continuous temperature data was used to calculate the 7-day average daily maximum (7DADmax) temperature at each monitoring site. Included in this data release are the final approved continuous data, the input and output files used to calculate the metrics in R, and two html files showing the R code and process used to make these calculations.

Booth, D. and C.P. Konrad. 2017. Hydrologic metrics for status-and trend monitoring in urban and urbanizing watersheds. Hydrological processes 31: 4507-4519. https://doi.org/10.1002/hyp.11369

Note: Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
DOI: 10.15468/dl.fnm4uz
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Crossocheilus langei)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022826-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17047972
title: 296-Isle of Secrets covers A
DOI: 10.5281/zenodo.17047973
title: 296-Isle of Secrets covers A
DOI: 10.7288/v4/magic/20328
title: Magnetic Mineralogy in Lunar Mare Basalts and Implications for Paleointensity Retrieval (Dataset)

description: Paleomagnetic, rock magnetic, or geomagnetic data found in the MagIC data repository from a paper titled: Magnetic Mineralogy in Lunar Mare Basalts and Implications for Paleointensity Retrieval
DOI: 10.15468/dl.pjup3n
title: Occurrence Download

description: A dataset containing 168 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lepidium campestre",
 "Country is Czechia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 168 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022829-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17047830
title: Literature review dataset (2016-2025) on "Artificial Intelligence" & "aging workforce". WOS and SCOPUS databases

description: Literature review dataset (2016-2025) on "Artificial Intelligence" & "aging workforce". WOS and SCOPUS databases

The objective of this study was to characterize scientific production through a literature review on Artificial Intelligence and the aging workforce in economics and management sciences available on Web of Science and Scopus. To this end, bibliometric analysis techniques and the tools Bibliometrix, VOSviewer were used.

 
description: Enerieth Lozano Mejía

Affiliation: Universidad del Valle, Faculty of Management Sciences, Tuluá, Colombia.

 Email: enerieth.lozano@correounivalle.edu.co

Orcid: https://orcid.org/0000-0001-6267-9539

MBA, Universidad Nacional de Colombia. 

Professor, Universidad del Valle, Tuluá campus. 

Research group: Science, Action, and Development (CAD).

 

Diana Anyeli Perdomo

Affiliation: Universidad del Valle, Faculty of Management Sciences, Tuluá, Colombia.

Email: perdomo.diana@correounivalle.edu.co

Orcid: https://orcid.org/0000-0003-0157-1123 

MBA, Universidad Nacional de Colombia. 

Professor, Universidad del Valle, Tuluá campus. 

Research group: Science, Action, and Development (CAD).

 

Alejandro Pérez y Soto Domínguez

Affiliation: Universidad Nacional de Colombia, Department of Agricultural Sciences, Faculty of Agricultural Sciences, Palmira, Colombia.

Email: aperezy@unal.edu.co

Orcid: https://orcid.org/0000-0001-5190-5297

Ph.D. in Economics and Philosophy, University of Almería.

Professor, National University of Colombia, Palmira campus.
description: 1. Bibliography compilation

 

Database: Scopus , SCImago Journal Rank (SJR), Web of Science (WoS) Journal Citation Reports (JCR)

 

•Equation:

•(Scopus = TITLE-ABS-KEY and in WoS = Abstract) "olders workers" OR aging OR agein. 

•(Scopus = TITLE-ABS-KEY and in WoS = Abstract) AND "artificial intelligence" OR "generative IA" OR digitalization OR automation OR "deep learning" OR "machine learning" OR "big data".

•(TITLE) AND  labour OR labor OR work OR job OR workforce.

 



•Total initial search: 
Scopus n= 142 and Wos n= 296

 

2. Literature processing



•Duplicate articles = 13

•Refinement by area of knowledge: Scopus (Business, Management, and Accounting) OR (Economics, Econometrics, and Finance) WoS (Economics OR Management OR Business OR Corporate Finance)

•No limit on document types: “article, review; advance access, editorial material, book chapter, conference paper, book”

•No language limit

•

•Publication period:

   10 years (2016-2025)

•Scopus= 41 and Wos= 37

 

Total publications n=78

 

3. Results and conclusions



Bibliometric analysis

Software selection: VOSviewer and Bibliometrix
DOI: 10.5281/zenodo.17047831
title: Literature review dataset (2016-2025) on "Artificial Intelligence" & "aging workforce". WOS and SCOPUS databases

description: Literature review dataset (2016-2025) on "Artificial Intelligence" & "aging workforce". WOS and SCOPUS databases

The objective of this study was to characterize scientific production through a literature review on Artificial Intelligence and the aging workforce in economics and management sciences available on Web of Science and Scopus. To this end, bibliometric analysis techniques and the tools Bibliometrix, VOSviewer were used.

 
description: Enerieth Lozano Mejía

Affiliation: Universidad del Valle, Faculty of Management Sciences, Tuluá, Colombia.

 Email: enerieth.lozano@correounivalle.edu.co

Orcid: https://orcid.org/0000-0001-6267-9539

MBA, Universidad Nacional de Colombia. 

Professor, Universidad del Valle, Tuluá campus. 

Research group: Science, Action, and Development (CAD).

 

Diana Anyeli Perdomo

Affiliation: Universidad del Valle, Faculty of Management Sciences, Tuluá, Colombia.

Email: perdomo.diana@correounivalle.edu.co

Orcid: https://orcid.org/0000-0003-0157-1123 

MBA, Universidad Nacional de Colombia. 

Professor, Universidad del Valle, Tuluá campus. 

Research group: Science, Action, and Development (CAD).

 

Alejandro Pérez y Soto Domínguez

Affiliation: Universidad Nacional de Colombia, Department of Agricultural Sciences, Faculty of Agricultural Sciences, Palmira, Colombia.

Email: aperezy@unal.edu.co

Orcid: https://orcid.org/0000-0001-5190-5297

Ph.D. in Economics and Philosophy, University of Almería.

Professor, National University of Colombia, Palmira campus.
description: 1. Bibliography compilation

 

Database: Scopus , SCImago Journal Rank (SJR), Web of Science (WoS) Journal Citation Reports (JCR)

 

•Equation:

•(Scopus = TITLE-ABS-KEY and in WoS = Abstract) "olders workers" OR aging OR agein. 

•(Scopus = TITLE-ABS-KEY and in WoS = Abstract) AND "artificial intelligence" OR "generative IA" OR digitalization OR automation OR "deep learning" OR "machine learning" OR "big data".

•(TITLE) AND  labour OR labor OR work OR job OR workforce.

 



•Total initial search: 
Scopus n= 142 and Wos n= 296

 

2. Literature processing



•Duplicate articles = 13

•Refinement by area of knowledge: Scopus (Business, Management, and Accounting) OR (Economics, Econometrics, and Finance) WoS (Economics OR Management OR Business OR Corporate Finance)

•No limit on document types: “article, review; advance access, editorial material, book chapter, conference paper, book”

•No language limit

•

•Publication period:

   10 years (2016-2025)

•Scopus= 41 and Wos= 37

 

Total publications n=78

 

3. Results and conclusions



Bibliometric analysis

Software selection: VOSviewer and Bibliometrix
DOI: 10.5281/zenodo.17045518
title: Supplementary material for "Strong impact of the recent Highly Pathogenic Avian Influenza panzootic on population dynamics of a long-lived bird"

description: R code and data to reproduce all the analyses presented in the paper. There are seven files:



Code_HPAI.R - Code to run the model with data from 1993 to 2024 (i.e., including HPAI panzootic outbreaks) + projections until 2034

data_hpai.RData - Necessary data to run the model with data from 1993 to 2024 (i.e., including HPAI panzootic outbreaks) + projections until 2034

pva_hpai.RData – Results of the model with data from 1993 to 2024 (i.e., including HPAI panzootic outbreaks) + projections until 2034

Code_NoHPAI.R - Code to run the model with data from 1993 to 2020 (i.e., excluding HPAI panzootic outbreaks) + projections until 2034

data_nohpai.RData - Necessary data to run the model with data from 1993 to 2020 (i.e., excluding HPAI panzootic outbreaks) + projections until 2034

pva_nohpai.RData - Results of the model with data from 1993 to 2020 (i.e., excluding HPAI panzootic outbreaks) + projections until 2034

Plots_Publish.R – Code to run the plots that appear in the manuscript. The code runs with the .RData results files (numbers 3 and 6). 


Instructions: Download all files in the same folder and set it as a working directory. Thecode is set to find and load the data from the working directory.
description: Since 2020, the spread of a new Highly Pathogenic Avian Influenza virus (HPAIV-H5N1) has triggered the most severe wildlife panzootic ever recorded, with suspected population crashes in hundreds of species. Yet, no study has evaluated the demographic mechanisms underlying these declines. We used Integrated Population Models and population forecasts to evaluate the demographic impact of HPAIV-H5N1 on a long-lived species population, the peregrine falcon in the Netherlands. We found drastic declines in adult survival – the key driver of population dynamics in long-lived species – along with a sudden ~25% decline in breeding pairs over consecutive panzootic years. Population projections predict recovery to pre-panzootic levels not before 2030. Our findings illustrate how the new HPAIV panzootic can generate unprecedentedly strong, long-lasting population impacts in long-lived species. This raises major concerns about the viability of the many species affected by the panzootic and calls for a global-scale conservation response.
DOI: 10.5066/p1bdpxkz
title: Grammar transformations of topographic feature type annotations of the U.S. to structured graph data

description: These data were used to examine grammatical structures and patterns within a set of geospatial glossary definitions. Objectives of our study were to analyze the semantic structure of input definitions, use this information to build triple structures of RDF graph data, upload our lexicon to a knowledge graph software, and perform SPARQL queries on the data. Upon completion of this study, SPARQL queries were proven to effectively convey graph triples which displayed semantic significance. These data represent and characterize the lexicon of our input text which are used to form graph triples. These data were collected in 2024 by passing text through multiple Python programs utilizing spaCy (a natural language processing library) and its pre-trained English transformer pipeline. Before data was processed by the Python programs, input definitions were first rewritten as natural language and formatted as tabular data. Passages were then tokenized and characterized by their part-of-speech, tag, dependency relation, dependency head, and lemma. Each word within the lexicon was tokenized. A stop-words list was utilized only to remove punctuation and symbols from the text, excluding hyphenated words (ex. bowl-shaped) which remained as such. The tokens’ lemmas were then aggregated and totaled to find their recurrences within the lexicon. This procedure was repeated for tokenizing noun chunks using the same glossary definitions.
DOI: 10.5281/zenodo.17038240
title: Datasets used for eLOP
DOI: 10.15468/dl.58m86w
title: Occurrence Download

description: A dataset containing 5376460 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 1980-2024"
 ]
}

 The dataset includes 5376460 records from 2540 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0117305-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x0gz2t
title: Occurrence Download

description: A dataset containing 1574 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Kigelia africana (Lam.) Benth."
 ]
}

 The dataset includes 1574 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003068-150922153815467/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dc3g4c
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chromista",
 "DecimalLatitude is greater than 47.5172159059676",
 "DecimalLatitude is less than 49.1424753239688",
 "DecimalLongitude is greater than -119.400163016439",
 "DecimalLongitude is less than -117.453348701715"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005818-180824113759888/datasets/export for details.
DOI: 10.15468/dl.ezdbe2
title: Occurrence Download

description: A dataset containing 6551 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Biodiversidad asociada al proyecto Línea de Transmisión Santo Domingo - San Lorenzo a 110 kV, Antioquia"
 ]
}

 The dataset includes 6551 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044364-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ekkxua
title: Occurrence Download

description: A dataset containing 6036 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Curatella americana L."
 ]
}

 The dataset includes 6036 records from 264 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063623-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ptdtft
title: Occurrence Download

description: A dataset containing 2128 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Citharus linguatula (Linnaeus, 1758)"
 ]
}

 The dataset includes 2128 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049782-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.syig19
title: Occurrence Download

description: A dataset containing 5316 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Laterallus jamaicensis (Gmelin, 1789)"
 ]
}

 The dataset includes 5316 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003068-160118175350007/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fqy7fv
title: Occurrence Download

description: A dataset containing 150 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rudgea vellerea Müll.Arg."
 ]
}

 The dataset includes 150 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063644-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b4cshr
title: Occurrence Download

description: A dataset containing 91 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tillandsia recurvata (L.) L.",
 "Country is Mexico",
 "Year is greater than or equal to 2010"
 ]
}

 The dataset includes 91 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003068-160311141623029/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.akfe6a
title: Occurrence Download

description: A dataset containing 4198 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Espeletia grandiflora Humb. & Bonpl."
 ]
}

 The dataset includes 4198 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034763-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qkvz74
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dendrobium eximium Schltr."
 ]
}

 The dataset includes 34 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016869-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fpmq2a
title: Occurrence Download

description: A dataset containing 1503 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Abudefduf vaigiensis (Quoy & Gaimard, 1825)"
 ]
}

 The dataset includes 1503 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003068-160509122628363/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bdjeeh
title: Occurrence Download

description: A dataset containing 243 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Vachellia grandicornuta (Gerstner) Seigler & Ebinger"
 ]
}

 The dataset includes 243 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0335720-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.