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

description: A dataset containing 408485 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bryopsidales"
 ]
}

 The dataset includes 408485 records from 884 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007691-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ajggz5
title: Occurrence Download

description: A dataset containing 1455763 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "GadmGid is one of (ISR, PSE)",
 "Year 1000-2018"
 ]
}

 The dataset includes 1455763 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007679-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14470/sa879454
title: Northern Finland Seismological Network

description: Sodankylä geophysical observatory (SGO) has operated in Sodankylä in northern Finland since 1913. SGO was originally founded by the Finnish Academy of Science and Letters. Now it takes care of national and international duties studying the space and geoenvironment as an independent research organisation in the University of Oulu. SGO performs long-term measurements, builds instruments, innovates and maintains domestic and international measurements, and performs research from these measurements. The seismic observations at SGO started in Sodankylä 1956. In 2005-2006 SGO seismic stations were updated to broadband instrumentation and connected to GEOFON data center. Today, the number of seismic stations has increased to 9. The stations have Streckeisen STS-2 or Nanometrics Trillium PA/PH broadband sensors. 3 of the stations are so called Posthole stations located in borehole 5-22 m below surface. The rest of the stations are located on the surface or in a more traditional type of vault. Data acquisition systems are either Earth Data PS6-24 digitisers and PC with Seiscomp or Nanometrics Centaurs. The continuous waveform data are collected at 100 Hz sampling frequency. The data are available from GEOFON data center. Further information about instrumentation can be found at the Institute’s web site (https://www.sgo.fi/). Waveform data are available from the GEOFON data centre, under network code FN, and arefully open.
DOI: 10.15468/dl.kuhj5v
title: Occurrence Download

description: A dataset containing 2741 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Monitoreo de la Red de Parcelas Forestales Permanente al Suroriente de Boyacá en Jurisdicción de Corpochivor"
 ]
}

 The dataset includes 2741 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007740-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17711879
title: CRRC Omnibus Survey (2019-2025) on Georgia

description: CRRC Omnibus Survey Omnibus surveys combine questions from different organizations and researchers into a single survey. This enables data collection at significantly reduced costs compared with commissioning an entire survey. CRRC Georgia offers a quarterly omnibus survey. CRRC's Omnibus has an achieved sample size of 1,200 respondents, is conducted using live telephone interviewing, and is nationally representative, excluding populations living in territories affected by military conflict (South Ossetia and Abkhazia).

The CRRC Omnibus Survey in Georgia, as outlined in the codebook, is a wide-ranging public opinion survey that explores key aspects of Georgian society, including employment, income, religion, media consumption, political preferences, and trust in institutions. Conducted regularly, it gathers data on whether people are employed, their income levels, religious service attendance, how often and through which channels they access news (especially TV and internet), and their attitudes toward political parties, leaders, and the country's direction. The survey enables long-term tracking of public attitudes and behaviors and includes demographic and attitudinal filters to ensure accurate, representative insights.

The files include 24 waves of datasets in STATA, SPSS and CSV. 

New in this version: English translations of the questionnaires for the 3rd and 9th–15th waves have been added.
description: Published on Discuss Data, https://discuss-data.net/dataset/e6c0d8b6-1233-402a-a033-818c5ff0022c/
description: Method(s) of data collection: Cati (Computer-Assisted Telephone Interviews), Face-To-Face Survey, Quantitative Survey
DOI: 10.5281/zenodo.17711880
title: CRRC Omnibus Survey (2019-2025) on Georgia

description: CRRC Omnibus Survey Omnibus surveys combine questions from different organizations and researchers into a single survey. This enables data collection at significantly reduced costs compared with commissioning an entire survey. CRRC Georgia offers a quarterly omnibus survey. CRRC's Omnibus has an achieved sample size of 1,200 respondents, is conducted using live telephone interviewing, and is nationally representative, excluding populations living in territories affected by military conflict (South Ossetia and Abkhazia).

The CRRC Omnibus Survey in Georgia, as outlined in the codebook, is a wide-ranging public opinion survey that explores key aspects of Georgian society, including employment, income, religion, media consumption, political preferences, and trust in institutions. Conducted regularly, it gathers data on whether people are employed, their income levels, religious service attendance, how often and through which channels they access news (especially TV and internet), and their attitudes toward political parties, leaders, and the country's direction. The survey enables long-term tracking of public attitudes and behaviors and includes demographic and attitudinal filters to ensure accurate, representative insights.

The files include 24 waves of datasets in STATA, SPSS and CSV. 

New in this version: English translations of the questionnaires for the 3rd and 9th–15th waves have been added.
description: Published on Discuss Data, https://discuss-data.net/dataset/e6c0d8b6-1233-402a-a033-818c5ff0022c/
description: Method(s) of data collection: Cati (Computer-Assisted Telephone Interviews), Face-To-Face Survey, Quantitative Survey
DOI: 10.15468/dl.yxa72w
title: Occurrence Download

description: A dataset containing 2741 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Monitoreo de la Red de Parcelas Forestales Permanente al Suroriente de Boyacá en Jurisdicción de Corpochivor"
 ]
}

 The dataset includes 2741 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007741-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.byghe5
title: Occurrence Download

description: A dataset containing 1187963 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Africa",
 "Country is Namibia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 1187963 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007673-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17293369
title: A Taxonomy of Business Models for Data Intermediaries

description: Background:  Both the rising dominance of large platforms in data markets and the increasing exchange of personal data among organizations within data ecosystems have led to significant asymmetries, as individuals have limited control over data-related decisions and restricted access to the value generated from data use. Scholars have called for data intermediaries to help address these asymmetries, yet little research has examined how their business models function within data ecosystems that facilitate personal data exchange.  

Aim: This study investigates the key characteristics and archetypes of business models of data intermediaries in data ecosystems that facilitate the exchange of personal data. 

Method: Using Nickerson’s taxonomy methodology and the Al-Debei business model ontological structure, a comprehensive taxonomy of data intermediary business models is developed. Hierarchical clustering is then applied to identify distinct archetypes.

Results: The research develops a taxonomy of data intermediary business models in data ecosystems centered on personal data exchange and derives archetypes through hierarchical clustering. The identified taxonomy dimensions clarify how these business models operate and create value within personal data ecosystems from a network-level business model perspective. Based on this framework, eight archetypes are identified, illustrating how data intermediaries prioritize interests of different ecosystem actors.

Dataset: This dataset contains:



A summary of the 107 cases analyzed in this research, and how the researchers mapped the dimensions and characteristics from the taxonomy onto these cases.

Definitions of the dimensions and characteristics in the taxonomy.

A cross-table analysis showing how frequently the dimensions and characteristics appear in the eight identified archetypes.
DOI: 10.5281/zenodo.17293370
title: A Taxonomy of Business Models for Data Intermediaries

description: Background:  Both the rising dominance of large platforms in data markets and the increasing exchange of personal data among organizations within data ecosystems have led to significant asymmetries, as individuals have limited control over data-related decisions and restricted access to the value generated from data use. Scholars have called for data intermediaries to help address these asymmetries, yet little research has examined how their business models function within data ecosystems that facilitate personal data exchange.  

Aim: This study investigates the key characteristics and archetypes of business models of data intermediaries in data ecosystems that facilitate the exchange of personal data. 

Method: Using Nickerson’s taxonomy methodology and the Al-Debei business model ontological structure, a comprehensive taxonomy of data intermediary business models is developed. Hierarchical clustering is then applied to identify distinct archetypes.

Results: The research develops a taxonomy of data intermediary business models in data ecosystems centered on personal data exchange and derives archetypes through hierarchical clustering. The identified taxonomy dimensions clarify how these business models operate and create value within personal data ecosystems from a network-level business model perspective. Based on this framework, eight archetypes are identified, illustrating how data intermediaries prioritize interests of different ecosystem actors.

Dataset: This dataset contains:



A summary of the 107 cases analyzed in this research, and how the researchers mapped the dimensions and characteristics from the taxonomy onto these cases.

Definitions of the dimensions and characteristics in the taxonomy.

A cross-table analysis showing how frequently the dimensions and characteristics appear in the eight identified archetypes.
DOI: 10.15468/dl.ekc8uc
title: Occurrence Download

description: A dataset containing 81580 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Calopteryx haemorrhoidalis, Stylurus flavipes, Onychogomphus uncatus, Leucorrhinia dubia, Epitheca bimaculata, Aeshna juncea)",
 "Geometry POLYGON((-5.2 43.7, 4 41.9, 8.5 41.9, 8.5 41.2, 10 41.2, 10 43.4, 8.5 43.4, 8.5 49, 2.5 51.2, -5.2 49.5, -5.2 43.7))"
 ]
}

 The dataset includes 81580 records from 962 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007718-251120083545085/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/12039855
title: Daftar Pengadilan Indonesia
DOI: 10.15468/dl.v4kwfe
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Hemigalus derbyanus (Gray, 1837))",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016063-250525065834625/datasets/export for details.
DOI: 10.15468/dl.zsvdds
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Hemigalus derbyanus (Gray, 1837))",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016064-250525065834625/datasets/export for details.
DOI: 10.15468/dl.7n3uza
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Hemigalus derbyanus (Gray, 1837))",
 "Country is one of (American Samoa, Australia, Christmas Island, Cocos (Keeling) Islands, Cook Islands, Fiji, French Polynesia, Guam, Heard Island and McDonald Islands, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Caledonia, New Zealand, Niue, Norfolk Island, Northern Mariana Islands, Palau, Papua New Guinea, Pitcairn, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, United States Minor Outlying Islands, Vanuatu, Wallis and Futuna)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016065-250525065834625/datasets/export for details.
DOI: 10.15468/dl.umzf7q
title: Occurrence Download

description: A dataset containing 36448 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Streptomyces Waksman & Henrici, 1943"
 ]
}

 The dataset includes 36448 records from 425 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016062-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17606847
title: THE ROLE OF ARTIFICIAL INTELLIGENCE IN FORENSIC PSYCHOLOGICAL EVALUATIONS: ADVANCEMENTS, CHALLENGES, AND FUTURE DIRECTIONS
DOI: 10.5281/zenodo.17606848
title: THE ROLE OF ARTIFICIAL INTELLIGENCE IN FORENSIC PSYCHOLOGICAL EVALUATIONS: ADVANCEMENTS, CHALLENGES, AND FUTURE DIRECTIONS
DOI: 10.13140/rg.2.2.35611.12322
title: A LIFELONG GIFT TO MY READERS ON RESEARCHGATE Professor of Eminence (Honorary in Physics)
DOI: 10.15468/dl.gdgt6p
title: Occurrence Download

description: A dataset containing 1891114 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Betula"
 ]
}

 The dataset includes 1891114 records from 3373 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032720-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15282169
title: Understanding Technical Debt through the Lens of IT Professionals: An Empirical Investigation

description:     Technical debt refers to the long-term costs and challenges arising from short-term technical decisions to accelerate software development. Effectively managing this debt remains a significant challenge in software projects, requiring strategic approaches and specific practices. This study investigates how professionals identify, track, and manage technical debt in real-world software development environments. Our mixed-methods survey of IT professionals yielded 62 valid responses from 83 total. The study explores (i) the influence of project management practices on the emergence and accumulation of technical debt; (ii) the main challenges teams face in monitoring and prioritizing debt throughout the project lifecycle; (iii) professionals’ perceptions of technical debt impacts on software quality attributes; and (iv) the strategies and artifacts most commonly used to handle debt. Our findings reveal that while awareness of technical debt is widespread, many teams lack effective prevention or mitigation processes. Participants identified poor scope definition, deadline pressure, and inadequate documentation as primary causes. Key quality attributes affected include maintainability, reliability, and efficiency. Despite these challenges, professionals emphasized the relevance of culture, communication, and the adoption of structured artifacts—such as code reviews and refactoring tasks—for effective management. The study highlights the need for stronger client involvement and institutional support to enhance technical debt practices and promote long-term software sustainability.
DOI: 10.5281/zenodo.15282170
title: Understanding Technical Debt through the Lens of IT Professionals: An Empirical Investigation

description:     Technical debt refers to the long-term costs and challenges arising from short-term technical decisions to accelerate software development. Effectively managing this debt remains a significant challenge in software projects, requiring strategic approaches and specific practices. This study investigates how professionals identify, track, and manage technical debt in real-world software development environments. Our mixed-methods survey of IT professionals yielded 62 valid responses from 83 total. The study explores (i) the influence of project management practices on the emergence and accumulation of technical debt; (ii) the main challenges teams face in monitoring and prioritizing debt throughout the project lifecycle; (iii) professionals’ perceptions of technical debt impacts on software quality attributes; and (iv) the strategies and artifacts most commonly used to handle debt. Our findings reveal that while awareness of technical debt is widespread, many teams lack effective prevention or mitigation processes. Participants identified poor scope definition, deadline pressure, and inadequate documentation as primary causes. Key quality attributes affected include maintainability, reliability, and efficiency. Despite these challenges, professionals emphasized the relevance of culture, communication, and the adoption of structured artifacts—such as code reviews and refactoring tasks—for effective management. The study highlights the need for stronger client involvement and institutional support to enhance technical debt practices and promote long-term software sustainability.
DOI: 10.5517/ccdc.csd.cc2mls23
title: CCDC 2431115: Experimental Crystal Structure Determination

description: Related Article: Alexey A. Konnov, Anton D. Lisyutkin, Dmitry B. Vinogradov, Amina A. Nazarova, Alla N. Pivkina, Leonid L. Fershtat|2025|Org.Lett.|27|3795|doi:10.1021/acs.orglett.5c01074
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2lpdtj
title: CCDC 2403858: Experimental Crystal Structure Determination

description: Related Article: Fáinché Murphy, Alan R. Kennedy, Catherine E. Weetman|2025|Dalton Trans.|54|6038|doi:10.1039/D5DT00379B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2mls34
title: CCDC 2431116: Experimental Crystal Structure Determination

description: Related Article: Alexey A. Konnov, Anton D. Lisyutkin, Dmitry B. Vinogradov, Amina A. Nazarova, Alla N. Pivkina, Leonid L. Fershtat|2025|Org.Lett.|27|3795|doi:10.1021/acs.orglett.5c01074
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.hy346p
title: Occurrence Download

description: A dataset containing 215 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is one of (Russian Federation, Mongolia, Kazakhstan, China)",
 "Geometry POLYGON((70.41133 37.69793,106.45923 37.69793,106.45923 57.21129,70.41133 57.21129,70.41133 37.69793))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ovis ammon (Linnaeus, 1758)",
 "Year 1980-2025"
 ]
}

 The dataset includes 215 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001533-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/bby-xm8-58k
title: Eleocharis mamillata (H.Lindb.) H.Lindb.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/ez6-58k-ty2
title: Subularia aquatica L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/nge-8mq-jh0
title: Myagrum perfoliatum L.

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.