cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1285/i22402772a6p229
title: La lezione di un maestro. In ricordo di Aldo Mazzacane
DOI: 10.18712/nsd-nsd3219-v1
title: Labour Force Survey 2021, 1st Quarter

description: Statistics Norway established the Labor Force Survey (LFS) in 1972, and it has been conducted quarterly ever since. The LFS measures the population's participation in the labor market and provides comprehensive information on unemployment, employment, people outside the labor force, temporary employees, underemployed and other subgroups that are not captured by register-based statistics. This makes the LFS one of the most important sources of information about conditions in the Norwegian labor market.

Right from the start, the aim has been to ensure that the survey is comparable with similar surveys internationally. Today, the LFS is designed in accordance with the EU's statistical regulations to ensure consistent and comparable European statistics. The LFS data contains long time series, and although there have been some breaks in the time series due to changes in the questionnaire and data collection, the most central variables have been continuously included since the start. This makes it possible to present time series data for the employed, unemployed and people outside the labor force all the way back to 1972.

From 2020 to 2021, a significant break in the time series was necessary due to the implementation of a new framework regulation for European social statistics. The production system was revised in full, with changes in sampling, weighting, use of register data, and a new questionnaire, several changes were made to modernize and streamline data collection.

The dataset consists of a single quarter, along with a quarterly weight. The dataset should be used for a quarterly average rather than an annual distribution. If an annual average is desired, separate datasets are available.
DOI: 10.18712/nsd-nsd3220-v1
title: Labour Force Survey 2021, 2nd Quarter

description: Statistics Norway established the Labor Force Survey (LFS) in 1972, and it has been conducted quarterly ever since. The LFS measures the population's participation in the labor market and provides comprehensive information on unemployment, employment, people outside the labor force, temporary employees, underemployed and other subgroups that are not captured by register-based statistics. This makes the LFS one of the most important sources of information about conditions in the Norwegian labor market.

Right from the start, the aim has been to ensure that the survey is comparable with similar surveys internationally. Today, the LFS is designed in accordance with the EU's statistical regulations to ensure consistent and comparable European statistics. The LFS data contains long time series, and although there have been some breaks in the time series due to changes in the questionnaire and data collection, the most central variables have been continuously included since the start. This makes it possible to present time series data for the employed, unemployed and people outside the labor force all the way back to 1972.

From 2020 to 2021, a significant break in the time series was necessary due to the implementation of a new framework regulation for European social statistics. The production system was revised in full, with changes in sampling, weighting, use of register data, and a new questionnaire, several changes were made to modernize and streamline data collection.

The dataset consists of a single quarter, along with a quarterly weight. The dataset should be used for a quarterly average rather than an annual distribution. If an annual average is desired, separate datasets are available.
DOI: 10.18712/nsd-nsd3221-v1
title: Labour Force Survey 2021, 3rd Quarter

description: Statistics Norway established the Labor Force Survey (LFS) in 1972, and it has been conducted quarterly ever since. The LFS measures the population's participation in the labor market and provides comprehensive information on unemployment, employment, people outside the labor force, temporary employees, underemployed and other subgroups that are not captured by register-based statistics. This makes the LFS one of the most important sources of information about conditions in the Norwegian labor market.

Right from the start, the aim has been to ensure that the survey is comparable with similar surveys internationally. Today, the LFS is designed in accordance with the EU's statistical regulations to ensure consistent and comparable European statistics. The LFS data contains long time series, and although there have been some breaks in the time series due to changes in the questionnaire and data collection, the most central variables have been continuously included since the start. This makes it possible to present time series data for the employed, unemployed and people outside the labor force all the way back to 1972.

From 2020 to 2021, a significant break in the time series was necessary due to the implementation of a new framework regulation for European social statistics. The production system was revised in full, with changes in sampling, weighting, use of register data, and a new questionnaire, several changes were made to modernize and streamline data collection.

The dataset consists of a single quarter, along with a quarterly weight. The dataset should be used for a quarterly average rather than an annual distribution. If an annual average is desired, separate datasets are available.
DOI: 10.1285/i22402772a6p235
title: Recensioni e Segnalazioni
DOI: 10.1285/i22402772a6p237
title: Cesare Letta, Simonetta Segenni (cur.), Roma e le sue province. Dalla prima guerra punica a Diocleziano
DOI: 10.15468/dl.mupe34
title: Occurrence Download

description: A dataset containing 332384 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Florida Keys Reef Visual Census 2008"
 ]
}

 The dataset includes 332384 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002857-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1285/i22402772a6p241
title: AA. VV., Civitas, Iura, Arma. Organizzazioni militari, istituzioni giuridiche e strutture sociali alle origini dell'Europa (secc. III-VIII)
DOI: 10.15468/dl.qvmb5s
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lysimachia tenella L.",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 31 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002864-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mkpvzb
title: Occurrence Download

description: A dataset containing 36439 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Europe",
 "Country is Germany",
 "DatasetKey is one of (Observation.org, Nature data from around the World, iNaturalist Research-grade Observations)",
 "Geometry MULTIPOLYGON(((6.86548 53.58472,6.87525 53.59323,6.85269 53.58997,6.86548 53.58472)),((6.90697 53.64171,6.86519 53.64111,6.89177 53.62549,6.90697 53.64171)),((7.42847 53.72019,7.43095 53.7322,7.363 53.72729,7.42847 53.72019)),((7.93436 53.78984,7.84612 53.78699,7.97826 53.77784,7.93436 53.78984)),((7.09716 53.67936,7.02698 53.68517,6.85193 53.66265,7.09716 53.67936)),((7.74407 53.78123,7.66877 53.75391,7.8147 53.78137,7.74407 53.78123)),((7.50039 53.72198,7.63118 53.74877,7.46485 53.74084,7.50039 53.72198)),((7.23404 53.72278,7.13784 53.70588,7.3462 53.71806,7.23404 53.72278)),((6.74859 53.55777,6.81207 53.60444,6.65825 53.5991,6.74859 53.55777)),((9.43322 51.65223,9.68499 51.58263,9.54286 51.36268,9.73071 51.29477,9.7934 51.40733,10.1523 51.43109,10.36861 51.5866,10.65745 51.55894,10.70089 51.64161,10.57375 51.81081,10.64837 51.95448,10.56148 52.00464,10.96407 52.05733,11.08593 52.22895,10.9821 52.34239,11.07124 52.3728,10.93402 52.46176,10.97663 52.62412,10.79673 52.71425,10.76472 52.84241,11.31472 52.87846,11.5977 53.03666,11.34063 53.05522,10.92827 53.34851,9.90638 53.41597,9.2543 53.85983,8.61431 53.88203,8.48478 53.6557,8.65225 53.60728,8.65007 53.51113,8.4921 53.47448,8.55042 53.53773,8.28775 53.61175,8.23484 53.39807,8.06933 53.46684,8.1722 53.53578,8.02894 53.70757,7.31739 53.68338,7.03333 53.54506,6.99863 53.36028,7.26432 53.3256,7.21604 53.00717,7.05426 52.64391,6.71114 52.62835,6.69774 52.48647,6.98785 52.46917,7.06374 52.24129,7.68487 52.45622,7.9902 52.3094,7.89968 52.20732,8.0087 52.11569,7.88486 52.08323,7.98094 52.03609,8.51666 52.18498,8.29693 52.45606,8.65204 52.53158,8.70909 52.39534,8.85683 52.38918,9.09462 52.49793,9.11745 52.39882,8.96362 52.27948,9.07475 52.23396,8.98499 52.19426,9.15858 52.12009,9.32397 51.85504,9.45951 51.86128,9.37885 51.73808,9.43322 51.65223),(8.48114 53.22488,8.95647 53.14765,8.97916 53.04604,8.73277 53.03627,8.48114 53.22488)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Orthoptera",
 "Year 2008-2024"
 ]
}

 The dataset includes 36439 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002866-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1285/i22402772a6p251
title: Francesco Lucrezi. Appunti di diritto ebraico - Francesco Lucrezi, Il furto di terra e di animali in diritto ebraico romano. Studi sulla "Collatio"
DOI: 10.15468/dl.h5d7t4
title: Occurrence Download

description: A dataset containing 5673 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Melbourne Water Frog Census",
 "Year 2017-2019"
 ]
}

 The dataset includes 5673 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002867-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1285/i22402772a6p260
title: Francesco Arcaria, "Quod ipsi Gallo inter gravissima crimina ab Augusto obicitur". Augusto e la repressione del dissenso per mezzo del senato agli inizi del Principato
DOI: 10.1285/i22402772a6p267
title: Luigi Capogrossi Colognesi, La costruzione del diritto privato romano
DOI: 10.5281/zenodo.14916563
title: SyMeRAD60 Synthetic & Measured FMCW Radar Data 60GHz

description: The SiMeRAD60 dataset is based on the AWR6843ISK radar system, a MIMO FMCW radar from Texas Instruments. It operates at a center frequency of 60 GHz, with a frequency slope of 79.8 MHz per microsecond and a total bandwidth of 3.99 GHz. The system captures 128 ADC samples per chirp at a sampling rate of 11.648 MSa/s, and each radar frame consists of 32 chirps.The signal processing pipeline computes the range spectrum using a 128-point FFT along the fast-time axis and a 32-point FFT across the chirps to extract Doppler information. Static clutter removal mitigates interference from stationary objects. The radar transmits chirps with an idle time of 50 microseconds and an ADC valid start time of 7 microseconds, operating with a ramp time of 50 microseconds and a frequency sweep frame periodicity of 200 milliseconds.The SiMeRAD60 dataset comprises 3,324 measured Range-Doppler (RD) maps and 10,890 synthetic RD maps. Each RD map contains up to two randomly moving human targets in a parking garage. The synthetic dataset was generated using a digital twin of the environment and the radar sensor to simulate radar wave propagation, reflections, and noise characteristics.The measured and synthetic datasets include targets with diverse motion patterns, considering multipath propagation effects. The measured data is manually labeled to provide ground truth annotations, ensuring accurate evaluation and detection performance comparison.
DOI: 10.5281/zenodo.14916564
title: SyMeRAD60 Synthetic & Measured FMCW Radar Data 60GHz

description: The SiMeRAD60 dataset is based on the AWR6843ISK radar system, a MIMO FMCW radar from Texas Instruments. It operates at a center frequency of 60 GHz, with a frequency slope of 79.8 MHz per microsecond and a total bandwidth of 3.99 GHz. The system captures 128 ADC samples per chirp at a sampling rate of 11.648 MSa/s, and each radar frame consists of 32 chirps.The signal processing pipeline computes the range spectrum using a 128-point FFT along the fast-time axis and a 32-point FFT across the chirps to extract Doppler information. Static clutter removal mitigates interference from stationary objects. The radar transmits chirps with an idle time of 50 microseconds and an ADC valid start time of 7 microseconds, operating with a ramp time of 50 microseconds and a frequency sweep frame periodicity of 200 milliseconds.The SiMeRAD60 dataset comprises 3,324 measured Range-Doppler (RD) maps and 10,890 synthetic RD maps. Each RD map contains up to two randomly moving human targets in a parking garage. The synthetic dataset was generated using a digital twin of the environment and the radar sensor to simulate radar wave propagation, reflections, and noise characteristics.The measured and synthetic datasets include targets with diverse motion patterns, considering multipath propagation effects. The measured data is manually labeled to provide ground truth annotations, ensuring accurate evaluation and detection performance comparison.
DOI: 10.1285/i22402772a6p281
title: P. J. du Plessis, J. Cairns (Hrg.), Reassessing Legal Humanism and its Claims. Petere Fontes?
DOI: 10.15468/dl.j266hf
title: Occurrence Download

description: A dataset containing 106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Malus sylvestris Mill.",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 106 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002869-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14916733
title: raw data - Prognostic impact of histopathological features and serum inflammatory markers in patients with locally advanced gastric cancer undergoing neoadjuvant therapy
DOI: 10.5281/zenodo.14916734
title: raw data - Prognostic impact of histopathological features and serum inflammatory markers in patients with locally advanced gastric cancer undergoing neoadjuvant therapy
DOI: 10.15468/dl.qwzkqw
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Capra sibirica (Pallas, 1776)"
 ]
}

 The dataset includes 64 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002865-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1285/i22402772a6p286
title: Luigi Garofalo, Fondamenti e svolgimenti della scienza giuridica. Nuovi saggi
DOI: 10.15468/dl.hc8gmv
title: Occurrence Download

description: A dataset containing 68986 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Africa",
 "TaxonKey is Amphibia"
 ]
}

 The dataset includes 68986 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002868-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1285/i22402772a6p291
title: Taco Terpstra, Trading Communities in the Roman World: A Micro-Economic and Institutional Perspective
DOI: 10.15468/dl.yshz98
title: Occurrence Download

description: A dataset containing 70153 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (NABU|naturgucker, iNaturalist Research-grade Observations, Observation.org, Nature data from around the World, EOD – eBird Observation Dataset)",
 "GadmGid is one of (DEU.14.2_1, DEU.14.7.3_1)",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 70153 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002870-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1285/i22402772a6p295
title: Yan Thomas, Il valore delle cose
DOI: 10.1285/i22402772a6p298
title: Vincenzo Giuffrè, Divagazioni intorno al diritto romano
DOI: 10.1285/i22402772a6p315
title: Pietro Siciliani, Il carteggio familiare (1850-1914) Aa.Vv., Pietro Siciliani e Cesira Pozzolini. Filosofia e Letteratura
DOI: 10.15468/dl.hwan9u
title: Occurrence Download

description: A dataset containing 765593 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Xeno-canto - Bird sounds from around the world"
 ]
}

 The dataset includes 765593 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002862-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1285/i22402772a6p322
title: Emilio Minniti, Lo stato d'eccezione
DOI: 10.1285/i22402772a6p325
title: Christian Baldus, Massimo Miglietta, Gianni Santucci, Emanuele Stolfi (cur.), Dogmengeschichte und historische Individualität der römischen Juristen. Storia dei dogmi e individualità storica dei giuristi romani
DOI: 10.34808/0abb-f491
title: Calibration images under different lighting conditions vol. 1
DOI: 10.13135/ela-339
title: Honours for Phyleus of Oinoe [secretary to the Council and the People], and his associates
DOI: 10.15468/dl.em26vg
title: Occurrence Download

description: A dataset containing 69 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Malvella sherardiana (L.) Jaub. & Spach",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 69 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002871-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1285/i22402772a6p340
title: Guido D'Agostino, Ferrando d'Aragona duca di Calabria e Viceré di Valenza (ultimo mancato re aragonese di Napoli). Il racconto di una vita (1488-1550)
DOI: 10.1285/i22402772a6p346
title: Libri pervenuti alla redazione
DOI: 10.15468/dl.m7s5dd
title: Occurrence Download

description: A dataset containing 23047 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Zostera marina L., Zostera noltii Hornem.)",
 "Year 2010-2025"
 ]
}

 The dataset includes 23047 records from 184 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002872-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14916762
title: Knife vs Pistol Detection

description: Description:







This Knife vs Pistol Detection was created to develop a robust machine learning model capable of differentiating between knives and pistols in images. The primary goal is to aid in object recognition tasks, particularly in security applications where identifying potential weapons is crucial.

 







Download Dataset

 









Dataset Structure

The dataset is divided into four key folders, each containing images meant for both training and evaluation of machine learning models:



Knife: Contains images specifically focused on knives. These are used to train the knife recognition model.

eval_Knife: Designed for evaluating the knife detection model’s accuracy and its ability to make reliable predictions.

Pistol: Contains images of pistols, design to train the model in distinguishing pistols from other objects.

eval_Pistol: Use to test and evaluate the pistol detection model, ensuring that it can effectively predict pistol-related outcomes.


Additional Features



Image Variations: The dataset includes various angles, lighting conditions, and backgrounds to ensure robustness in diverse real-world scenarios.

Data Augmentation: To improve model generalization, data augmentation techniques such as rotation, scaling, and cropping can be apply to simulate different environments.

Annotation Files: The dataset includes label annotations, providing bounding boxes around the objects (knife or pistol) within each image, facilitating precise object localization tasks.

Use Case Examples: This dataset is particularly suited for applications in airport security, automate surveillance systems, and law enforcement technologies where accurate weapon detection is critical.


This dataset is sourced from Kaggle.
DOI: 10.5281/zenodo.14916761
title: Knife vs Pistol Detection

description: Description:







This Knife vs Pistol Detection was created to develop a robust machine learning model capable of differentiating between knives and pistols in images. The primary goal is to aid in object recognition tasks, particularly in security applications where identifying potential weapons is crucial.

 







Download Dataset

 









Dataset Structure

The dataset is divided into four key folders, each containing images meant for both training and evaluation of machine learning models:



Knife: Contains images specifically focused on knives. These are used to train the knife recognition model.

eval_Knife: Designed for evaluating the knife detection model’s accuracy and its ability to make reliable predictions.

Pistol: Contains images of pistols, design to train the model in distinguishing pistols from other objects.

eval_Pistol: Use to test and evaluate the pistol detection model, ensuring that it can effectively predict pistol-related outcomes.


Additional Features



Image Variations: The dataset includes various angles, lighting conditions, and backgrounds to ensure robustness in diverse real-world scenarios.

Data Augmentation: To improve model generalization, data augmentation techniques such as rotation, scaling, and cropping can be apply to simulate different environments.

Annotation Files: The dataset includes label annotations, providing bounding boxes around the objects (knife or pistol) within each image, facilitating precise object localization tasks.

Use Case Examples: This dataset is particularly suited for applications in airport security, automate surveillance systems, and law enforcement technologies where accurate weapon detection is critical.


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

description: A dataset containing 44 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Capricornis milneedwardsii David, 1869"
 ]
}

 The dataset includes 44 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002874-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.