cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14163171
title: Global spending on zoonotic surveillance programs: a country-scale dataset based on USAspending

description: This dataset provides detailed information on U.S. federal spending for the cost of zoonotic disease monitoring and surveillance programs. Data are gathered from the USAspending.gov database, an open data source that allows to track how federal money is allocated and spent across various countries. We retrieved information  at country-level over the period 2008-2023 for more than 130 countries.

Our aim was to estimate the total yearly spending from US-based organisations on zoonotic disease surveillance worldwide. Hence, we focussed on programs related to zoonotic disease monitoring and surveillance funded by the following agencies: Centers for Disease Control and Prevention (CDC), U.S. Agency for International Development (USAID) and Bureau of Global Health, Security and Diplomacy.

The dataset consists on:

(i) country code;

(ii) country name;

(iii) fiscal year;

(iv) Recipient ($), which is the total amount of funds allocated to a given country in a specific year, referring to the legal business addresses of organizations that are awarded with federal contracts, grants or financial assistance; 

(v) Performance ($), which is the total amount of funds associated with the country, specifying the local where most of the work takes place, e.g. for a manufacturing contract this indicates the main place where items are produced; 

(vi) Spending ($), which is the sum of recipient and performance funds for a country for each available year. 

This dataset can serve as a valuable resource not only for researchers, but also for decision-makers as it supports the analysis of federal spending patterns. Despite the data account for U.S. spending for (excluding extranational spending of other big investors, such as the European Union), they are produced based on a consistent approach providing comparable information among years and countries. The usefulness and applicability of this dataset is indeed manifold: it can be used for examining the trends in funding distribution and outcomes, assessing the effectiveness of spending policies, and analyzing the outcome of investment programs over time. Likewise, analysis of trends in spending can be crucial to improve public services, such as healthcare, by identifying gaps and weaknesses, which may lead to the identification of more targeted actions for reducing the risk of zoonotic disease. Moreover, these data can be exploited to forecast economic trends and identify areas which are underfunded and might require future investment.
DOI: 10.5281/zenodo.15682268
title: Global spending on zoonotic surveillance programs: a country-scale dataset based on USAspending

description: This dataset provides detailed information on U.S. federal spending for the cost of zoonotic disease monitoring and surveillance programs. Data are gathered from the USAspending.gov database, an open data source that allows to track how federal money is allocated and spent across various countries. We retrieved information  at country-level over the period 2008-2023 for more than 130 countries.

Our aim was to estimate the total yearly spending from US-based organisations on zoonotic disease surveillance worldwide. Hence, we focussed on programs related to zoonotic disease monitoring and surveillance funded by the following agencies: Centers for Disease Control and Prevention (CDC), U.S. Agency for International Development (USAID) and Bureau of Global Health, Security and Diplomacy.

The dataset consists on:

(i) country code;

(ii) country name;

(iii) fiscal year;

(iv) Recipient ($), which is the total amount of funds allocated to a given country in a specific year, referring to the legal business addresses of organizations that are awarded with federal contracts, grants or financial assistance; 

(v) Performance ($), which is the total amount of funds associated with the country, specifying the local where most of the work takes place, e.g. for a manufacturing contract this indicates the main place where items are produced; 

(vi) Spending ($), which is the sum of recipient and performance funds for a country for each available year. 

This dataset can serve as a valuable resource not only for researchers, but also for decision-makers as it supports the analysis of federal spending patterns. Despite the data account for U.S. spending for (excluding extranational spending of other big investors, such as the European Union), they are produced based on a consistent approach providing comparable information among years and countries. The usefulness and applicability of this dataset is indeed manifold: it can be used for examining the trends in funding distribution and outcomes, assessing the effectiveness of spending policies, and analyzing the outcome of investment programs over time. Likewise, analysis of trends in spending can be crucial to improve public services, such as healthcare, by identifying gaps and weaknesses, which may lead to the identification of more targeted actions for reducing the risk of zoonotic disease. Moreover, these data can be exploited to forecast economic trends and identify areas which are underfunded and might require future investment.
DOI: 10.48328/tudatalib-1814
title: Künstliche Intelligenz im Studium - Eine quantitative Studie zur Nutzung KI-basierter Tools durch Studierende und Lehrende (Jahr: 2025)

description: Der Datensatz basiert auf einer groß angelegten quantitativen Studie zum Einsatz KI-basierter Tools im Hochschulkontext. Insgesamt wurden 4.910 Studierende und 626 Hochschullehrende an deutschen Hochschulen befragt. Ziel der Untersuchung war es, Nutzungsmuster, Anwendungsbereiche, Bedenken sowie institutionelle Rahmenbedingungen im Umgang mit generativer KI aus Sicht beider Zielgruppen systematisch zu erfassen. Die Studie ist in mehrere Abschnitte gegliedert, die unterschiedliche Aspekte der Nutzung von KI-Tools im Studium und in der Lehre abbilden. In der Studierendenbefragung liegt der Fokus zunächst auf der Frage, ob und in welchem Umfang KI-Tools – wie etwa ChatGPT, DeepL oder DALL·E – bereits im Studium eingesetzt werden. Daran anschließend werden konkrete Anwendungsbereiche erfasst, z. B. zur Klärung von Verständnisfragen, für Recherchen, Übersetzungen, die Erstellung wissenschaftlicher Texte oder datengetriebene Analysen. Studierende, die keine KI-Tools nutzen, werden nach den Gründen für ihre bisherige Nichtnutzung gefragt. Weitere Abschnitte thematisieren Bedenken sowie die generelle Bereitschaft zur Nutzung solcher Tools. Ergänzend wird erfasst, ob es an den jeweiligen Hochschulen bereits Vorgaben oder Leitlinien zur Nutzung generativer KI gibt. Die Umfrage endet mit einem deskriptiven Teil mit Angaben zu Abschlussziel, Studienbereich, Bundesland, Geschlecht, Alter und Technikbereitschaft. Die Lehrendenbefragung folgt einer analogen Struktur. Der erste Hauptteil erfasst, ob und in welchem Umfang Lehrende KI-Tools in ihrer Lehrpraxis einsetzen. Nach der Erfassung genutzter Tools – ebenfalls z. B. ChatGPT, DeepL oder DALL·E – werden detaillierte Angaben zu spezifischen Lehrbereichen erhoben, in denen diese Tools verwendet werden. Bei Angabe konkreter Einsatzbereiche folgen vertiefende Fragen zur Art der Nutzung, während bei Nichtnutzung Gründe dafür abgefragt werden. Auch hier schließen sich Abschnitte zu Bedenken, Bereitschaft zur Nutzung und möglichen hochschulischen Vorgaben an. Die Umfrage endet mit Angaben zu Lehrposition, Fachbereich, Bundesland, Geschlecht, Alter sowie einer Technikbereitschaftsskala. Erste deskriptive Auswertungen zu den Studien sind zu finden unter Studierende: DOI 10.48444/h_docs-pub-533 sowie Lehrende: DOI: 10.48444/h_docs-pub-546
DOI: 10.34810/data392
title: Data for "Manufacturing Conflict Narratives in Real Madrid vs Barcelona football matches"

description: The data presented here were used to explore the media coverage of the clasico, Real Madrid vs FC Barcelona played on Dec 10, 2011. In the qualitative table (Tabla cualitativa tramas clasico 10-D.xlsx) we can find all the details about the articles on the match : the media outlet, date, hour, headline, whether the header was a quotation, and the main characters of the article. In the quantitative table (Tabla cuantitativa clasico 10-D.xlsx) we can find the the absolut numbers for the match: number of articles on Real Madrid, number of articles on FC Barcelona, and partial percentages, all sorted by media outlet. Estos datos fueron utilizados para medir la cobertura mediática del clásico Real Madrid - FC Barcelona disputado el 10 de diciembre de 2011. En la tabla cualitativa (Tabla cualitativa tramas clasico 10-D.xlsx) se detallan todos los artículos: el medio de comunicación, la fecha de la noticia, la franja horaria, el titular, si era una cita textual o no, y los protagonistas de la noticia. En la tabla cuantitativa (Tabla cuantitativa clasico 10-D.xlsx) se hallan el total de las noticias sobre el FC Barcelona, sobre el Real Madrid, sobre el clásico, y sus porcentajes respecto al total de noticias deportivas y al total de noticias en general, ordenados por diarios online.
DOI: 10.15468/dl.mpxajc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Persicaria hystricula (J.Schust.) Soják",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((15.6372 -28.0032,16.2782 -28.5786,20.509 -28.5786,20.509 -24.0715,15.4933 -24.0715,15.4945 -24.1257,16.0509 -25.6631,15.6372 -28.0032))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051005-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.29336903
title: data: Make a Guess - An experiment on Academic Performance

description: Data and do file
DOI: 10.6084/m9.figshare.29336903.v1
title: data: Make a Guess - An experiment on Academic Performance

description: Data and do file
DOI: 10.15468/dl.dhfuv9
title: Occurrence Download

description: A dataset containing 702 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Falco chicquera Daudin, 1800",
 "HasCoordinate is true",
 "Geometry POLYGON((2.676932 4.272244, 14.678014 4.272244, 14.678014 13.865923, 2.676932 13.865923, 2.676932 4.272244))"
 ]
}

 The dataset includes 702 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051008-250525065834625/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/12195049
title: FORGE-IK-2025
DOI: 10.5281/zenodo.15681962
title: MLRS Net

description: Description:

MLRSNet is a multi-label high spatial resolution remote sensing dataset designed for semantic scene understanding. It offers diverse perspectives of the world captured from satellites, comprising high spatial resolution optical satellite images. The dataset contains 109,161 remote sensing images, meticulously annotated into 46 categories, with each category holding between 1,500 to 3,000 sample images. Each image maintains a fixed size of 256×256 pixels, featuring various pixel resolutions ranging from approximately 10 meters to 0.1 meters.

Download Dataset

Each image in MLRSNet is tagged with several of 60 predefined class labels, with the number of labels per image varying between 1 and 13. This comprehensive labeling enables the dataset to support multiple applications, including multi-label based image classification, multi-label based image retrieval, and image segmentation. MLRSNet thus serves as a valuable resource for advancing research and development in remote sensing and related fields.

This dataset is sourced from Kaggle.
DOI: 10.5281/zenodo.15681963
title: MLRS Net

description: Description:

MLRSNet is a multi-label high spatial resolution remote sensing dataset designed for semantic scene understanding. It offers diverse perspectives of the world captured from satellites, comprising high spatial resolution optical satellite images. The dataset contains 109,161 remote sensing images, meticulously annotated into 46 categories, with each category holding between 1,500 to 3,000 sample images. Each image maintains a fixed size of 256×256 pixels, featuring various pixel resolutions ranging from approximately 10 meters to 0.1 meters.

Download Dataset

Each image in MLRSNet is tagged with several of 60 predefined class labels, with the number of labels per image varying between 1 and 13. This comprehensive labeling enables the dataset to support multiple applications, including multi-label based image classification, multi-label based image retrieval, and image segmentation. MLRSNet thus serves as a valuable resource for advancing research and development in remote sensing and related fields.

This dataset is sourced from Kaggle.
DOI: 10.15468/dl.p6gjvt
title: Occurrence Download

description: A dataset containing 1356 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "TaxonKey is Styphnolobium japonicum (L.) Schott"
 ]
}

 The dataset includes 1356 records from 157 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051010-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ebq44z
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Persicaria hystricula (J.Schust.) Soják",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((15.4784 -23.4046,15.4933 -24.0715,20.509 -24.0715,20.509 -24.0455,20.0952 -23.5072,19.9968 -23.017,19.7843 -22.5405,19.1988 -21.8785,18.5972 -21.5447,17.8859 -21.3993,17.1626 -21.4805,16.5332 -21.7596,16.1257 -22.0882,15.8234 -22.4662,15.606 -22.8993,15.4784 -23.4046))"
 ]
}

 The dataset includes 10 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051012-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b58znb
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Virola malmei A.C.Sm."
 ]
}

 The dataset includes 22 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051015-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jppv7t
title: Occurrence Download

description: A dataset containing 3465 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((18.90951 47.38527,19.11603 47.38516,19.1933 47.38527,19.1933 47.61919,18.90951 47.61919,18.90951 47.38527))",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Anas platyrhynchos Linnaeus, 1758, Ardea cinerea Linnaeus, 1758, Fulica atra Linnaeus, 1758)"
 ]
}

 The dataset includes 3465 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051014-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15682334
title: Supplementary material for: Interindividual variability in flower pickiness by foraging bumblebees

description: ABSTRACT

     Pollinators navigate complex and heterogeneous “flower markets”, where floral resources vary in quality, availability, and spatial distribution. Bumblebees, as generalist foragers, visit numerous flowers during their foraging bouts, yet the factors influencing their flower choices and the individual differences in foraging behaviour remain poorly understood.  Here, we tested how bees adjust their foraging in response to different reward structures. Bombus terrestris workers completed three foraging bouts in two artificial flower environments: one simulating a favourable environment with patches alternating high- and low-quality flowers (40% vs. 20% w/w sucrose solution), and the other a challenging environment with high-quality flowers alongside unrewarded ones (40% w/w sucrose solution vs. plain water). We hypothesised that bees would improve their foraging efficiency in both environments, but more rapidly in the more extreme one, where the greater reward difference creates stronger pressure to learn quickly. In both conditions, bees increased their sucrose intake per unit time over bouts. We also observed consistent differences in flower selectivity among individuals: in the favourable environment, bees that first visited high-quality flowers focused on them and avoided low-quality ones (became “picky”), while bees that first visited low-quality flowers kept visiting both types. Despite these differences, bees across environments and pickiness levels all reached similar sucrose intake rates by the third foraging bout, either by becoming more selective, collecting more sucrose solution, or reducing time spent foraging. These findings highlight the adaptability of bee foraging and suggest that early flower experiences contribute to lasting individual differences in foraging behaviour.
DOI: 10.5281/zenodo.15682355
title: ddasfsa
DOI: 10.5281/zenodo.15682356
title: ddasfsa
DOI: 10.15468/dl.wc7v4r
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Philippines",
 "TaxonKey is Rattus tiomanicus (Miller, 1900)"
 ]
}

 The dataset includes 37 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051016-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15151/esrf-es-2142770305
title: Probing ground states in intermediate valence Yb coordination systems

description: Compounds in which integer valence states cannot be assigned, i.e. are intermediate valence, have often multiconfigurational ground states with resultant exotic magnetic properties. Such compounds are dominated by ytterbium bipyridine molecular complexes. We have now incorporated “intermediate valence” units into extended 1D chains, expected to host novel conductivity and magnetism, but for which structural analysis and magnetic measurements alone cannot confirm the presence of intermediate valency. XANES measurements are the single best method for elucidation of the valency in such compounds. XMCD measurements, however, will allow for direct measurement of not only the 4f occupation, but the element-specific magnetization, allowing elucidation of the full ground state electronic configuration. We will perform the first L3-edge XMCD measurements of two reference known intermediate valence compounds, before characterizing our 1D polymeric systems by both L3-edge XANES and XMCD.
DOI: 10.15468/dl.edtssy
title: Occurrence Download

description: A dataset containing 3373243 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is North America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Liliopsida",
 "Year 2000-2025"
 ]
}

 The dataset includes 3373243 records from 199 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050999-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q4c7bp
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Philippines",
 "TaxonKey is Crunomys melanius Thomas, 1907"
 ]
}

 The dataset includes 28 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051017-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rhuy75
title: Occurrence Download

description: A dataset containing 19631 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cedrela odorata L."
 ]
}

 The dataset includes 19631 records from 570 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051013-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.20kbq0
title: Occurrence Download

description: A dataset containing 20416 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Zomerganzen - Summering geese management and population counts in Flanders, Belgium"
 ]
}

 The dataset includes 20416 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013442-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tk7kjv
title: Occurrence Download

description: A dataset containing 763 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Ziziphus joazeiro Mart.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 763 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072114-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8nyi2c
title: Occurrence Download

description: A dataset containing 44089 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ramphocelus dimidiatus Lafresnaye, 1837"
 ]
}

 The dataset includes 44089 records from 149 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035754-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sfxw4x
title: Occurrence Download

description: A dataset containing 824831 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Ghana"
 ]
}

 The dataset includes 824831 records from 787 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001652-240130105604617/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7qaajf
title: Occurrence Download

description: A dataset containing 97 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is Guinea",
 "Country is Mali",
 "Country is Benin",
 "Country is Côte d’Ivoire",
 "Country is Liberia",
 "Country is Mauritania",
 "Country is Sierra Leone",
 "Country is Niger",
 "Country is Nigeria",
 "Country is Guinea-Bissau",
 "Country is Ghana",
 "Country is Burkina Faso",
 "Country is Togo",
 "Country is Cabo Verde",
 "Country is Senegal",
 "Country is Gambia"
 ]
 },
 "Year 1975-2020",
 "TaxonKey is Anthonotha crassifolia (Baill.) J.Léonard"
 ]
}

 The dataset includes 97 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030821-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.