cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5284/1137115
title: Site Images and GIS Data from an Archaeological Evaluation at Moore's Farm, Fowlmere Road, Foxton, Cambridgeshire, July 2024

description: This collection comprises site images and GIS data from an archaeological evaluation at Moore's Farm, Fowlmere Road, Foxton, Cambridgeshire. The works were carried out by Cotswold Archaeology in July 2024. Despite the site's location within a prehistoric, Roman and medieval agricultural landscape denoted by extensive crop marks, only one archaeological feature in the form of a pit was recorded within the trenches. No datable material was recovered from the pit or from any of the topsoil and subsoil layers encountered.
DOI: 10.5281/zenodo.17427471
title: DS.HERG_RVIZ_Rosbag_Subject1.01

description: Gesture-based control of the bucket on a UR5 robotic arm, visualized in RViz, with three participants performing unloading gestures.
DOI: 10.5281/zenodo.17427472
title: DS.HERG_RVIZ_Rosbag_Subject1.01

description: Gesture-based control of the bucket on a UR5 robotic arm, visualized in RViz, with three participants performing unloading gestures.
DOI: 10.5281/zenodo.17431748
title: Accessions_PX365743_to_PX365874_and_PX381351_to_PX381463

description: Datasets corresponding to GenBank accession numbers PX365743 to PX365874 and PX381351 to PX381463
DOI: 10.5281/zenodo.17431749
title: Accessions_PX365743_to_PX365874_and_PX381351_to_PX381463

description: Datasets corresponding to GenBank accession numbers PX365743 to PX365874 and PX381351 to PX381463
DOI: 10.15468/dl.3mvx9w
title: Occurrence Download

description: A dataset containing 136322 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Asterias rubens"
 ]
}

 The dataset includes 136322 records from 405 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054287-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17396219
title: ETLR - Extruded Tunnel Lining Regeneration

description: The dataset contains the results of a full-scale testing campaign for the ETLR project. The project investigated a slip-forming methodology for the refurbishment of existing tunnels using extrudable steel fibre-reinforced concrete (SFRC). This technology provides an innovative framework for the maintenance of highway and railway tunnels.

The dataset contains the results of four experimental tests performed on four full-scale mock-ups replicating a motorway tunnel lining, which were constructed using this technology and tested under load conditions that simulate the relevant action combinations for tunnel linings in the intended scenarios. For each test, the measurements of 7 actuators are collected, along with the records of 7 sensors monitoring the displacement field of the tunnel mock-up. 

Both symmetric and non-symmetric loading combinations were examined, including a sequential loading case to assess accumulated damage and residual bearing capacity. The structural tests were conducted at the ELSA laboratory of the European Commission, Joint Research Centre in Ispra under the Framework of access to the Joint Research Centre Physical Research Infrastructures of the European Commission.
DOI: 10.5281/zenodo.17396220
title: ETLR - Extruded Tunnel Lining Regeneration

description: The dataset contains the results of a full-scale testing campaign for the ETLR project. The project investigated a slip-forming methodology for the refurbishment of existing tunnels using extrudable steel fibre-reinforced concrete (SFRC). This technology provides an innovative framework for the maintenance of highway and railway tunnels.

The dataset contains the results of four experimental tests performed on four full-scale mock-ups replicating a motorway tunnel lining, which were constructed using this technology and tested under load conditions that simulate the relevant action combinations for tunnel linings in the intended scenarios. For each test, the measurements of 7 actuators are collected, along with the records of 7 sensors monitoring the displacement field of the tunnel mock-up. 

Both symmetric and non-symmetric loading combinations were examined, including a sequential loading case to assess accumulated damage and residual bearing capacity. The structural tests were conducted at the ELSA laboratory of the European Commission, Joint Research Centre in Ispra under the Framework of access to the Joint Research Centre Physical Research Infrastructures of the European Commission.
DOI: 10.5281/zenodo.17223516
title: Supporting data for thermomechanical modelling of clamping force in power transformer in operation

description: Supporting data for paper on thermomechanical modelling of clamping force in transformers (to be published).If you use this data in your work, please cite the paper once it is published.

Dataset from on-line direct monitoring of transformer temperatures and clamping force for 2024 for 40 MVA ONAN transformer in operation in the south of Norway. The dataset contains operating parameters (Voltage, Current), transformer temperatures and clamping force measurements required to validate transformer clamping force models.In addition, the calculated temperatures and changes in clamping force are available in a separate file.Note that there are some gaps in the data, due to technical issues and special operations.

The dataset is split into files for the measured sensor data and the calculated values from the model:

Barug2025_sensordata.csv:Voltage [kV], Current [A], Ambient [degC], Top oil [degC], Bottom oil [degC], Mid-spot HV [degC], Mid-spot LV [degC], Hot-spot HV [degC], Hot-spot LV [degC], Clamping force [kN], Clamping pressure [MPa]

Barug2025_calculated.csv:Top oil (calculated) [degC], Bottom oil (calculated) [degC], HV average (calculated) [degC], LV average (calculated) [degC], Core average (calculated) [degC],, Clamping force change (calculated) [kN]

The clamping force is is measured by sensors under the blocks on top of the windings. For more information on monitoring methodology, see:Madshaven, Inge, et al. "On-line direct clamping pressure monitoring of power transformer windings." 2022 7th International Advanced Research Workshop on Transformers (ARWtr). IEEE, 2022. DOI: 10.23919/ARWtr54586.2022.9959909.

Detailed description of modelling methodology will be available in full paper.

This dataset was developed in the DynaLoad project, a Knowledge-building Project for Industry supported by The Research Council of Norway (RCN) under the RCN contract 319289. The DynaLoad consortium consists of SINTEF Energy, Norwegian University of Science and Technology (NTNU), Royal Institute of Technology (KTH), Weidmann Electrical Technology, Electricité de France (EDF), Elvia AS, Kolektor Etra, Siemens Energy, Statkraft Energy, Statnett SF, and SP Energy Networks.
DOI: 10.5281/zenodo.17223514
title: Supporting data for thermomechanical modelling of clamping force in power transformer in operation

description: Supporting data for paper on thermomechanical modelling of clamping force in transformers (to be published).If you use this data in your work, please cite the paper once it is published.

Dataset from on-line direct monitoring of transformer temperatures and clamping force for 2024 for 40 MVA ONAN transformer in operation in the south of Norway. The dataset contains operating parameters (Voltage, Current), transformer temperatures and clamping force measurements required to validate transformer clamping force models.In addition, the calculated temperatures and changes in clamping force are available in a separate file.Note that there are some gaps in the data, due to technical issues and special operations.

The dataset is split into files for the measured sensor data and the calculated values from the model:

Barug2025_sensordata.csv:Voltage [kV], Current [A], Ambient [degC], Top oil [degC], Bottom oil [degC], Mid-spot HV [degC], Mid-spot LV [degC], Hot-spot HV [degC], Hot-spot LV [degC], Clamping force [kN], Clamping pressure [MPa]

Barug2025_calculated.csv:Top oil (calculated) [degC], Bottom oil (calculated) [degC], HV average (calculated) [degC], LV average (calculated) [degC], Core average (calculated) [degC],, Clamping force change (calculated) [kN]

The clamping force is is measured by sensors under the blocks on top of the windings. For more information on monitoring methodology, see:Madshaven, Inge, et al. "On-line direct clamping pressure monitoring of power transformer windings." 2022 7th International Advanced Research Workshop on Transformers (ARWtr). IEEE, 2022. DOI: 10.23919/ARWtr54586.2022.9959909.

Detailed description of modelling methodology will be available in full paper.

This dataset was developed in the DynaLoad project, a Knowledge-building Project for Industry supported by The Research Council of Norway (RCN) under the RCN contract 319289. The DynaLoad consortium consists of SINTEF Energy, Norwegian University of Science and Technology (NTNU), Royal Institute of Technology (KTH), Weidmann Electrical Technology, Electricité de France (EDF), Elvia AS, Kolektor Etra, Siemens Energy, Statkraft Energy, Statnett SF, and SP Energy Networks.
DOI: 10.5281/zenodo.15622583
title: MBDD2025: A Deep Learning-Oriented Dataset for Diverse Building Defect Detection from UAV Images

description: MBDD2025 is a large-scale dataset of building surface defects collected by UAV imagery. It is designed for object detection and classification tasks in intelligent building inspection. The dataset covers a wide range of structural types and defect categories, making it suitable for deployment in diverse real-world scenarios.
DOI: 10.5281/zenodo.15622584
title: MBDD2025: A Deep Learning-Oriented Dataset for Diverse Building Defect Detection from UAV Images

description: MBDD2025 is a large-scale dataset of building surface defects collected by UAV imagery. It is designed for object detection and classification tasks in intelligent building inspection. The dataset covers a wide range of structural types and defect categories, making it suitable for deployment in diverse real-world scenarios.
DOI: 10.25345/c50p0x43t
title: MassIVE MSV000099580 - DIA-MS Analysis of MDA-MB-231 Cells derived small extracellular vesicles with EGLN1 Knockdown Under Normoxic and Hypoxic Conditions
title: This dataset contains DIA-mass spectrometry data of MDA-MB-231 cells derived small extracellular vesicles under different conditions: N-231-shNC_sEVs refers to small extracellular vesicles derived from MDA-MB-231 cells with control shRNA treatment under nomorxic condition (21% oxygen); H-231-shNC_sEVs refers to small extracellular vesicles derived from MDA-MB-231 cells with control shRNA treatment under normoxic condition; H-231-shEGLN1_sEVs refers to small extracellular vesicles derived from MDA-MB-231 cells with EGLN1 shRNA treatment under hypoxic condition (1% oxygen). The files include raw mass spectrometry data.
DOI: 10.15468/dl.rdncx2
title: Occurrence Download

description: A dataset containing 36101 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bodianus rufus"
 ]
}

 The dataset includes 36101 records from 167 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054330-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n6gum2
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Timouria saposhnikowii"
 ]
}

 The dataset includes 11 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054331-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8bur8a
title: Occurrence Download

description: A dataset containing 2629 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Data on medicinal plants of Benin"
 ]
}

 The dataset includes 2629 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054333-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g2mn5j
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhodamnia waigeoensis"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054332-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zv3za2
title: Occurrence Download

description: A dataset containing 2629 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Data on medicinal plants of Benin"
 ]
}

 The dataset includes 2629 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054334-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yuf62m
title: Occurrence Download

description: A dataset containing 13144 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (Australian Platypus Conservancy, cPlatypus, iNaturalist Research-grade Observations, NSW BioNet Atlas, Victorian Biodiversity Atlas, WildNet - Queensland Wildlife Data, ALA species sightings and OzAtlas, ACT Wildlife Atlas)",
 "Issue is one of (Coordinate rounded, Geodetic datum assumed WGS84, Continent derived from coordinates, Institution match none, Collection match none, Institution match fuzzy, Collection match fuzzy)",
 "PublishingOrg is one of (3c5e4331-7f2f-4a8d-aa56-81ece7014fc8, abfcc93c-8ce7-4cb1-b6c8-2e26291909db, ef66652d-3cc3-4140-b268-a07d1e53441b, a4ee8241-94f8-40b8-8c47-31aaf9430c90, 96835ce2-d3af-4f6e-af81-faa0c7576fa4)",
 "TaxonKey is Ornithorhynchus anatinus",
 "Year 1990-2025"
 ]
}

 The dataset includes 13144 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054335-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ub86mz
title: Occurrence Download

description: A dataset containing 58139 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aurelia aurita"
 ]
}

 The dataset includes 58139 records from 312 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054294-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1070298.10fu
title: SH1070298.10FU

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/sh1070300.10fu
title: SH1070300.10FU

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/sh1070302.10fu
title: SH1070302.10FU

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/sh1070306.10fu
title: SH1070306.10FU

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/sh1070309.10fu
title: SH1070309.10FU

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/sh1070312.10fu
title: SH1070312.10FU

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/sh1070315.10fu
title: SH1070315.10FU

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: 10.6084/m9.figshare.31042234
title: CO word analysis dataset

description: Raw dataset of bibliometric analysis describing computational workflow in landscape architecture and architecture with focus on evironmental parameters. This study investigates the scope of computational design and environmental parameter integration within landscape architecture and planning. Employing a structured scoping review and scientometric co-word analysis of literature published between 2010 and 2025, the research maps relationships between spatial scales, environmental metrics, and digital workflows. The results indicate a significant bias toward the built environment, where BIM/BEM and parametric tools are predominantly used for energy and comfort optimisation at the building and urban block levels. Conversely, ecological and hydrological systems are largely relegated to analytical roles within GIS frameworks rather than serving as active drivers for design optimisation. The findings highlight a critical gap in computational tools for green-blue infrastructure, which currently hinders the effective integration of landscape parameters into BIM/BEM simulation and further application in Life Cycle Assessments (LCA).