cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18110882
title: Fleet-Level Autonomous Drone Logistics Dataset

description: The dataset captures fleet-level operational telemetry of autonomous drone logistics collected from a large-scale port-centric logistics environment operating under continuous, real-world conditions. The data span a period from March 3, 2022, to August 3, 2025, recorded at a 10-minute temporal resolution, reflecting sustained day-to-day logistics activity across multiple operational seasons, weather regimes, and workload intensities. The dataset is structured as a multivariate time-series, where each record represents the instantaneous state of an active drone within a coordinated fleet, along with contextual information describing tasks, infrastructure load, environmental conditions, and inter-drone interactions.

Operational measurements include drone kinematics and energy states, task and delivery context, fleet coordination indicators, port infrastructure utilization, environmental and temporal conditions, and safety-related risk signals. These features are derived from onboard flight controllers, fleet coordination middleware, port infrastructure monitoring systems, and environmental sensing units routinely deployed in modern intelligent logistics hubs. The dataset reflects naturally imbalanced operational patterns, such as peak-hour congestion, rare safety events, uneven zone utilization, and long-tailed energy consumption behaviors, which are characteristic of real logistics environments.

In addition to raw operational features, the dataset provides fleet-level learning targets that quantify coordination effectiveness and system stress. These include the Fleet Coordination Efficiency Index (FCEI), Airspace Stress Index (ASI), and Coordination-Induced Energy Savings (CIES), enabling direct investigation of how coordinated decision-making influences efficiency, safety, and sustainability at scale. An estimated time-of-arrival variable is also included as an auxiliary benchmark signal.

The dataset is released in CSV format with clearly defined feature semantics and temporal ordering, making it suitable for regression-based learning, temporal modeling, and coordination analysis in intelligent logistics research. It is publicly shared via Zenodo to support reproducibility, benchmarking, and future extensions in autonomous logistics and industrial cyber–physical systems research
DOI: 10.5281/zenodo.18110390
title: larentia_rosei_spades_01.fasta.gz
DOI: 10.5281/zenodo.18110391
title: larentia_rosei_spades_01.fasta.gz
DOI: 10.15468/dl.p45zxv
title: Occurrence Download

description: A dataset containing 166 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Venezuela (Bolivarian Republic of), Colombia)",
 "Geometry POLYGON((-79.44641 0.16166,-58.57838 0.16166,-58.57838 11.75842,-79.44641 11.75842,-79.44641 0.16166))",
 "HasCoordinate is true",
 "TaxonKey is one of (Hyphessobrycon sweglesi, Megalamphodus sweglesi, Magalamphodus sweglesi)"
 ]
}

 The dataset includes 166 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069928-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h9rsbs
title: Occurrence Download

description: A dataset containing 12735 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hesperia comma",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1970",
 "Country is one of (Italy, Switzerland, Germany, Austria, Slovenia, France)"
 ]
}

 The dataset includes 12735 records from 181 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069929-251120083545085/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/14357105
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.hnmd2c
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cicer yamashitae",
 "Year is greater than or equal to 1000"
 ]
}

 The dataset includes 19 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069932-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ky7nu
title: Occurrence Download

description: A dataset containing 583835 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Setophaga nigrescens",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((-180 -90, 180 -90, 180 90, -180 90, -180 -90))"
 ]
}

 The dataset includes 583835 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069919-251120083545085/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/14357128
title: Balochi Language to English Translation Dataset
DOI: 10.15468/dl.2qzecn
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gegenes pumilio",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1970",
 "Country is one of (Italy, Switzerland, Germany, Austria, Slovenia, France)"
 ]
}

 The dataset includes 29 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069933-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jsk6aw
title: Occurrence Download

description: A dataset containing 6306 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Zerynthia polyxena",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1970",
 "Country is one of (Italy, Switzerland, Germany, Austria, Slovenia, France)"
 ]
}

 The dataset includes 6306 records from 168 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069934-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/yvxpw7
title: Replication Data for: Ideology, Local-Level Policymaking, and International Governmental Organizations

description: A growing literature at the intersection of international relations, public policy, and comparative politics has explored the role that International Governmental Organizations (IGOs) play in influencing domestic policymaking. This literature is grounded in a commonly shared theoretical expectation that policymakers will perceive IGOs as neutral and technocratic purveyors of expert information. Based on this expectation, scholars have assumed that policymakers are likely to employ recommendations from IGOs when making decisions. In this research note, we examine this assumption through an analysis of original survey data on U.S. mayors’ responses to COVID-19-related guidance from the World Health Organization (WHO). In contrast to dominant theoretical expectations, we find that mayoral likelihood of considering WHO recommendations in policymaking and of trusting WHO-provided information was largely a function of ideology, an effect that remains after incorporating the interactive effect of Trump vote share.
DOI: 10.6073/pasta/4a7ada57b8f17e5d929f5db80573d7a1
title: Water Quality Data (Grab Samples) from the Taylor Slough, just outside Everglades National Park (FCE), for August 1998 to November 2006

description: Water quality samples are being collected using ISCO autosamplers at all wetland sites (that is, all sites except TS/Ph-9, 10, and 11). The autosamplers contain 24 1L bottles. Water is sampled by programming the autosamplers to take composite samples once every 3 days. These samples are a composite of four 250mL subsamples drawn every 18 hours (a sampling scheme that captures a dawn, noon, dusk, and midnight sample in every three day composite). The samples are collected every 3-4 weeks and analyzed for total phosphorus (TP), total nitrogen (TN), and salinity. When sites are visited to collect these samples, we also collect a grab sample that is immediately put on ice. A portion of these grab samples is filtered through a Whatman GF/F filter immediately upon return to the lab, and the filtered samples are analyzed for inorganic nutrients such as NO2-, NO3-, NH4+, SRP, and DOC. The unfiltered fraction of these grab samples is analyzed for TP, TN, and TOC. We use these montly grab samples to generate relationships between TP and SRP, and between TN and NO2- + NO3- + NH4+. Dissolved nutrients are measured using standard rapid flow analyzer (RFA) techniques. TP is analyzed with a modified Solorzano and Sharp (1980) technique. TN is measured with an Antec TN analyzer, TOC and DOC are quantified on a Shimadzu TOC Analyzer, and salinity is measured with a YSI conductivity meter. In addition to the regular water quality monitoring, we use the rain level actuators at all freshwater sites to trigger water sampling after rain events exceed a given threshold of duration and/or intensity. As currently programmed, when the threshold of = 2.5 cm of rain per hour is passed, the autosampler at that site collects a 1L sample every 15 minutes after the threshold has been reached and remains (previous to 2003- the autosampler was programmed to collect 500mL of water every 30 minutes while the threshold was being met). Rain event samples are collected, retrieved, and analyzed like out composite water quality samples.
DOI: 10.15468/dl.m3mmsx
title: Occurrence Download

description: A dataset containing 51981 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ochlodes sylvanus",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1970",
 "Country is one of (Italy, Switzerland, Germany, Austria, Slovenia, France)"
 ]
}

 The dataset includes 51981 records from 488 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069931-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ta4zt4
title: Occurrence Download

description: A dataset containing 516 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Zerynthia cassandra",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1970",
 "Country is one of (Italy, Switzerland, Germany, Austria, Slovenia, France)"
 ]
}

 The dataset includes 516 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069936-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p14j5arh
title: Land Use and Climate Covariate Values for Hexagon Tiles in the Central and Mississippi Flyways Between 1970-2019

description: This data release contains a csv file of hexagon-tile specific summaries of several land use and climate variables that have been produced using R scripts. The hexagon tile grid spans the entire USA-portion of the Central and Mississippi Migratory Flyways and data has been extracted for the years 1979-2019.
DOI: 10.15468/dl.wru9pd
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cicer uludereensis"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069937-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tjteqy
title: Occurrence Download

description: A dataset containing 5661 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Zerynthia rumina",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1970",
 "Country is one of (Italy, Switzerland, Germany, Austria, Slovenia, France)"
 ]
}

 The dataset includes 5661 records from 166 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069938-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ud67jc
title: Occurrence Download

description: A dataset containing 405334 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tephritidae"
 ]
}

 The dataset includes 405334 records from 877 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069927-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0209441.10fu
title: SH0209441.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0209442.10fu
title: SH0209442.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0209443.10fu
title: SH0209443.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0209444.10fu
title: SH0209444.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0209445.10fu
title: SH0209445.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0209446.10fu
title: SH0209446.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0209447.10fu
title: SH0209447.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0209448.10fu
title: SH0209448.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0209449.10fu
title: SH0209449.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.