cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive6139.20251217.10
title: Tepidiphilus margaritifer Manaia et al. 2003 emend. Poddar et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0074196.10fu
title: SH0074196.10FU

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: 10.13145/bacdive6140.20241212.9.2
title: Annwoodia aquaesulis (Wood and Kelly 1995) Boden et al. 2017

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6140.20251217.10
title: Annwoodia aquaesulis (Wood and Kelly 1995) Boden et al. 2017

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0074197.10fu
title: SH0074197.10FU

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/sh0074198.10fu
title: SH0074198.10FU

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: 10.13145/bacdive6141.20241212.9.2
title: Thiobacillus denitrificans (ex Beijerinck 1904) Kelly and Harrison 1989 emend. Kelly and Wood 2000

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6141.20251217.10
title: Thiobacillus denitrificans (ex Beijerinck 1904) Kelly and Harrison 1989 emend. Kelly and Wood 2000

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6142.20241212.9.2
title: Thiobacillus denitrificans (ex Beijerinck 1904) Kelly and Harrison 1989 emend. Kelly and Wood 2000

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive6142.20251217.10
title: Thiobacillus denitrificans (ex Beijerinck 1904) Kelly and Harrison 1989 emend. Kelly and Wood 2000

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0074199.10fu
title: SH0074199.10FU

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: 10.13145/bacdive6143.20250331.9.3
title: Thiobacillus denitrificans (ex Beijerinck 1904) Kelly and Harrison 1989 emend. Kelly and Wood 2000

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0074200.10fu
title: SH0074200.10FU

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: 10.5281/zenodo.15240436
title: Data of Thread Lines
DOI: 10.5281/zenodo.15240437
title: Data of Thread Lines
DOI: 10.5281/zenodo.13968831
title: Meteorological Data from Chios: May 2024 Baseline Measurements for the MUSICA Project

description: May 2024 – Chios (Chiostown)

Introduction

The present meteorological data is collected from the weather station in Chiostown, located in Chios, and is published on the Zenodo platform for open access. The station is positioned at an elevation of 32 meters, and the data includes measurements of temperature, rainfall, wind speed, and wind direction, covering the period from May 1st to May 31st, 2024.

Purpose

These measurements are conducted as part of the MUSICA project, which aims to monitor climate changes in the Chiostown area and the broader region of Chios. The data for May 2024 captures the transition from spring to early summer, offering insights into the warming trend and dry conditions typical for the region during this period.

Content

The files include:



Date and time of recording: For accurate time tracking of the data.

Temperature: Daily average, maximum, and minimum temperatures in degrees Celsius (°C).

Rainfall: Daily rainfall in millimeters (mm).

Wind speed: Average and maximum daily wind speed in kilometers per hour (km/h).

Wind direction: The prevailing wind direction of the day.


Data Highlights for May 2024



Highest temperature: 28.8°C, recorded on May 19th, 2024, at 18:20.

Lowest temperature: 12.3°C, recorded on May 15th, 2024, at 05:00.

Total rainfall: 1.2 mm, with the highest daily rainfall of 1.19 mm recorded on May 11th, 2024.

Highest wind speed: 56.3 km/h, recorded on May 27th, 2024, at 10:40.


Data Usage

The data is free to use. Users are welcome to download, analyze, and utilize the data for personal, educational, or research purposes, as well as for developing applications and tools that contribute to understanding and addressing weather and climate phenomena
DOI: 10.5281/zenodo.14029134
title: Phase Space Files of a Liac HWL linac

description: A set of phase-space files (PSFs) calculated with penEasy 2020 for the Liac HWL mobile accelerator (S.I.T.). This version includes PSFs for various applicator diameters at energies of 6, 8, 10, and 12 MeV.

C8B0_12MeV stands for applicator with a diameter of 8 cm, a 0º bevel ending and simulated with a beam energy of 12 MeV.

The files were recorded at a position of  z=28 cm, with the linac aligned along the z-axis and the distal end of the applicator positioned at z=0. The modeled applicators consist of two sections: a common part measuring 10.5 cm in length and interchangeable bevel endings measuring 29.5 cm.

NOTE: To recreate a realistic setup, the simulation should include a PMMA cylindrical applicator with the selected inner diameter and a wall thickness of 0.5 cm. This PSFs can be rotated to simulate beveled applicators.

All files are provided in the IAEA PHSP format, including the corresponding header files, making them compatible with most Monte Carlo codes for radiation transport simulation.

Additional PSFs corresponding to applicator diameters of 7, 9 and 12 cm could not be added to this record due to data size limitations, and can be found here:https://doi.org/10.5281/zenodo.14215758
DOI: 10.5281/zenodo.14143380
title: Phase Space Files of a Liac HWL linac

description: A set of phase-space files (PSFs) calculated with penEasy 2020 for the Liac HWL mobile accelerator (S.I.T.). This version includes PSFs for various applicator diameters at energies of 6, 8, 10, and 12 MeV.

C8B0_12MeV stands for applicator with a diameter of 8 cm, a 0º bevel ending and simulated with a beam energy of 12 MeV.

The files were recorded at a position of  z=28 cm, with the linac aligned along the z-axis and the distal end of the applicator positioned at z=0. The modeled applicators consist of two sections: a common part measuring 10.5 cm in length and interchangeable bevel endings measuring 29.5 cm.

NOTE: To recreate a realistic setup, the simulation should include a PMMA cylindrical applicator with the selected inner diameter and a wall thickness of 0.5 cm. This PSFs can be rotated to simulate beveled applicators.

All files are provided in the IAEA PHSP format, including the corresponding header files, making them compatible with most Monte Carlo codes for radiation transport simulation.

Additional PSFs corresponding to applicator diameters of 7, 9 and 12 cm could not be added to this record due to data size limitations, and can be found here:https://doi.org/10.5281/zenodo.14215758
DOI: 10.6092/unibo/amsacta/7924
title: INTELLIMAN. WP5 T5-3-1. Attention-Based Cloth Manipulation from Model-free Topological Representation

description: This dataset contains data related to a novel attention-based neural architecture capable of solving a smoothing task for deformable objects, such as clothes and fabric, by means of a single robotic arm. In particular, the dataset contains the data used for the training on a model-free learning-based policy for cloth smoothing task and the script used to collect the resulting data. The data were produced in the framework of Horizon Europe INTELLIMAN project and are presented in the publication: 
K. Galassi, B. Wu, J. Perez, G. Palli and J. -M. Renders, "Attention-Based Cloth Manipulation from Model-free Topological Representation", 2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 2024, pp. 18207-18213, doi: 10.1109/ICRA57147.2024.10610241.
DOI: 10.5281/zenodo.13968830
title: Meteorological Data from Chios: May 2024 Baseline Measurements for the MUSICA Project

description: May 2024 – Chios (Chiostown)

Introduction

The present meteorological data is collected from the weather station in Chiostown, located in Chios, and is published on the Zenodo platform for open access. The station is positioned at an elevation of 32 meters, and the data includes measurements of temperature, rainfall, wind speed, and wind direction, covering the period from May 1st to May 31st, 2024.

Purpose

These measurements are conducted as part of the MUSICA project, which aims to monitor climate changes in the Chiostown area and the broader region of Chios. The data for May 2024 captures the transition from spring to early summer, offering insights into the warming trend and dry conditions typical for the region during this period.

Content

The files include:



Date and time of recording: For accurate time tracking of the data.

Temperature: Daily average, maximum, and minimum temperatures in degrees Celsius (°C).

Rainfall: Daily rainfall in millimeters (mm).

Wind speed: Average and maximum daily wind speed in kilometers per hour (km/h).

Wind direction: The prevailing wind direction of the day.


Data Highlights for May 2024



Highest temperature: 28.8°C, recorded on May 19th, 2024, at 18:20.

Lowest temperature: 12.3°C, recorded on May 15th, 2024, at 05:00.

Total rainfall: 1.2 mm, with the highest daily rainfall of 1.19 mm recorded on May 11th, 2024.

Highest wind speed: 56.3 km/h, recorded on May 27th, 2024, at 10:40.


Data Usage

The data is free to use. Users are welcome to download, analyze, and utilize the data for personal, educational, or research purposes, as well as for developing applications and tools that contribute to understanding and addressing weather and climate phenomena
DOI: 10.5281/zenodo.14266880
title: Meteorological Data from Chios: May 2024 Baseline Measurements for the MUSICA Project

description: May 2024 – Chios (Chiostown)

Introduction

The present meteorological data is collected from the weather station in Chiostown, located in Chios, and is published on the Zenodo platform for open access. The station is positioned at an elevation of 32 meters, and the data includes measurements of temperature, rainfall, wind speed, and wind direction, covering the period from May 1st to May 31st, 2024.

Purpose

These measurements are conducted as part of the MUSICA project, which aims to monitor climate changes in the Chiostown area and the broader region of Chios. The data for May 2024 captures the transition from spring to early summer, offering insights into the warming trend and dry conditions typical for the region during this period.

Content

The files include:



Date and time of recording: For accurate time tracking of the data.

Temperature: Daily average, maximum, and minimum temperatures in degrees Celsius (°C).

Rainfall: Daily rainfall in millimeters (mm).

Wind speed: Average and maximum daily wind speed in kilometers per hour (km/h).

Wind direction: The prevailing wind direction of the day.


Data Highlights for May 2024



Highest temperature: 28.8°C, recorded on May 19th, 2024, at 18:20.

Lowest temperature: 12.3°C, recorded on May 15th, 2024, at 05:00.

Total rainfall: 1.2 mm, with the highest daily rainfall of 1.19 mm recorded on May 11th, 2024.

Highest wind speed: 56.3 km/h, recorded on May 27th, 2024, at 10:40.


Data Usage

The data is free to use. Users are welcome to download, analyze, and utilize the data for personal, educational, or research purposes, as well as for developing applications and tools that contribute to understanding and addressing weather and climate phenomena
DOI: 10.5281/zenodo.13486162
title: Mobilising marine biodiversity data: a new malacological dataset of Italian records (Mollusca)

description: The location and palaeoceanographic history of the Mediterranean Sea make it a biodiversity hotspot, prompting extensive studies in this region. However, despite the marine biodiversity of this area is apparently widely studied, a large amount of distributional data for Mediterranean taxa is still unpublished or scattered in various sources and formats, causing severe limitations to their potential reuse. This emerges as a particularly thorny issue for highly biodiverse and neglected taxa, such as invertebrates. The mobilisation of these frozen data through a process of standardisation and georeferencing could potentially support biodiversity research and conservation. The aim of this work is to provide a standardised pipeline to integrate these dispersed data, focusing on the Italian waters of the Mediterranean Sea and using molluscs as target taxa. Data were gathered from two main sources: published literature and Natural History Collections. The harmonisation process involved three key steps: 1) terminology and structure standardisation, 2) taxonomy updating and 3) georeferencing. Our efforts yielded over 44000 standardised records of mollusc species from Italian seawaters. These records encompassed primary biodiversity data from newly digitised specimens owned by 11 different institutions and private collectors, as well as secondary biodiversity data extracted from 311 published studies.
DOI: 10.25824/redu/hbs6e6
title: Comprehensive analysis of deflazacort oxidative degradation: insights into novel degradation products and mechanisms

description: Dados brutos de RMN e HPLC para o trabalho "Comprehensive analysis of deflazacort oxidative degradation: Insights into novel degradation products and mechanisms"
DOI: 10.5281/zenodo.14266378
title: Dataset [ref. paper "Predictive modeling of drivers' brake reaction time through machine learning methods"]
DOI: 10.5281/zenodo.14266379
title: Dataset [ref. paper "Predictive modeling of drivers' brake reaction time through machine learning methods"]
DOI: 10.5281/zenodo.14266883
title: ConnectionChecker: Results for Cultural Heritage Datasets

description: ConnectionChecker: Results for Cultural Heritage Datasets. We have evaluated two datasets of CH domain:

1.A subset of the dataset Persons of National Library of Netherlands with 3,000,000 triples, 698,527 entities, and 535,407 owl:sameAs relationships.

2.The dataset World War I as LOD from the Universities of Aalto and Helsinki, Finland with 47,176 triples, 11,339 entities and 547 owl:sameAs relationships.

ne can download the triples of these datasets, their metadata in CSV and VoID format, the provenance of entities and the inferred sameAs relationships. Moreover, it contains screenshots showing the produced visualizations for these datasets.

https://demos.isl.ics.forth.gr/ConnectionChecker
DOI: 10.5281/zenodo.14266884
title: ConnectionChecker: Results for Cultural Heritage Datasets

description: ConnectionChecker: Results for Cultural Heritage Datasets. We have evaluated two datasets of CH domain:

1.A subset of the dataset Persons of National Library of Netherlands with 3,000,000 triples, 698,527 entities, and 535,407 owl:sameAs relationships.

2.The dataset World War I as LOD from the Universities of Aalto and Helsinki, Finland with 47,176 triples, 11,339 entities and 547 owl:sameAs relationships.

ne can download the triples of these datasets, their metadata in CSV and VoID format, the provenance of entities and the inferred sameAs relationships. Moreover, it contains screenshots showing the produced visualizations for these datasets.

https://demos.isl.ics.forth.gr/ConnectionChecker
DOI: 10.15468/dl.x8qgtj
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Czechia",
 "TaxonKey is Vipera berus (Linnaeus, 1758)",
 "Year is 2020"
 ]
}

 The dataset includes 20 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014653-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14216467
title: Specialized and generalized non-material Nature's Contributions to People at Mount Kilimanjaro using Twitter posts.

description: This dataset was collected as part of the Kili-SES research unit, Subproject 2, Work Package 2, which focuses on understanding the elements of nature that support non-material contributions, such as aesthetic enjoyment, recreation, and spirituality. Using the NCP paradigm, non-material contributions of nature to people (NCP) were identified through an inductive approach, together with the entities of nature (EN) mentioned in Twitter posts.

This dataset builds on https://doi. org/10.5281/zenodo.14217191 by including those specific EN (and human-made features) mentioned by tourists on their Twitter posts - in order to enable evaluation of NCP-EN associations. Overview: this dataset was collected in October 2021 using the R package academictwitteR with Twitter’s official Application Programming Interface keys (API; https://developer.twitter.com/en/docs). These are publicly available Tweets targeting Mount Kilimanjaro National Park (Tanzania) and its surroundings from 10 years (April 2011 to June 2021). Data were manually filtered and cleaned to preserve tourists' Tweets of their nature experiences at Mount Kilimanjaro, Tanzania. These final dataset contains 1255 entries, and each observation represents a Tweet that contains at least one non-material nature's contributions to people (non-material NCP) and one entity of nature mentioned by an individual.Please refer to the README document to understand the data structure of this dataset, and the corresponding codes to characterize each non-material NCP as either specialized or generalized. This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Research Unit 5064: “The role of nature for human well-being in the Kilimanjaro Social-Ecological System (Kili-SES)” (Project Number 428658210).
DOI: 10.5281/zenodo.14266910
title: GMW-Greek Misspelled Words

description: This dataset contains 574,883 distinct Greek words and for each one of them it contains various misspellings, in average 4.32 misspellings per word. In total, it contains more than 3 million forms of Greek words (3,063,143). The misspelled words have been produced algorithmically. The dataset can be used for evaluating methods for approximate matching, error correction, etc.