cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25375/uct.25828264
title: Ship Hull Vinyl Dataset

description: An inside sweet water tank at the Institute for Maritime Technology (IMT) in Cape Town was used to take a controlled underwater dataset using a prototype sensor rig - 24 October 2023. The target scene is a life-sized photomosaic of the side of a commercial ship hull that IMT had previously taken when the ship was last in dry dock. The photomosaic is printed onto a large vinyl tarpaulin and hung along the side of the tank.<br><br>Because the tank platform is 1m from the surface of the water, two 3m PVC pipes were used to manoeuvre the rig through the water, seen below. The rig is moved horizontally along the side of the platform facing the vinyl surface. Marks were placed on the PVC pipes as a visual aid to keep the rig at a relatively constant depth when moving horizontally. Once at the end of the vinyl, the rig is lowered directly downward to the next marked depth and moved horizontally back along the platform, creating a square ‘C’ shape. The data collection starts at 0.5m depth and returns at 1m depth.<br>We provide the data in the form of ROS bags. The data is supplied in two formats: raw and pre-processed. The raw data has not been edited. The pre-processed data has been synchronized and images have been stereo rectified and undistorted. With the ROS bags we also include the stereo camera and stereo-inertial (camera-IMU) calibration output files in yaml format.The original calibration data for camera and stereo-inertial calibrations are also included in ROS bag format so that users can perform their own calibrations if desired. On the sister GitHub, in the Meta Data folder, we detail the data collection method in a PDF for contextual understanding of the dataset and provide the data sheets of the sensors used along with supporting code.
DOI: 10.25375/uct.25828264.v3
title: Ship Hull Vinyl Dataset

description: An inside sweet water tank at the Institute for Maritime Technology (IMT) in Cape Town was used to take a controlled underwater dataset using a prototype sensor rig - 24 October 2023. The target scene is a life-sized photomosaic of the side of a commercial ship hull that IMT had previously taken when the ship was last in dry dock. The photomosaic is printed onto a large vinyl tarpaulin and hung along the side of the tank.<br><br>Because the tank platform is 1m from the surface of the water, two 3m PVC pipes were used to manoeuvre the rig through the water, seen below. The rig is moved horizontally along the side of the platform facing the vinyl surface. Marks were placed on the PVC pipes as a visual aid to keep the rig at a relatively constant depth when moving horizontally. Once at the end of the vinyl, the rig is lowered directly downward to the next marked depth and moved horizontally back along the platform, creating a square ‘C’ shape. The data collection starts at 0.5m depth and returns at 1m depth.<br>We provide the data in the form of ROS bags. The data is supplied in two formats: raw and pre-processed. The raw data has not been edited. The pre-processed data has been synchronized and images have been stereo rectified and undistorted. With the ROS bags we also include the stereo camera and stereo-inertial (camera-IMU) calibration output files in yaml format.The original calibration data for camera and stereo-inertial calibrations are also included in ROS bag format so that users can perform their own calibrations if desired. On the sister GitHub, in the Meta Data folder, we detail the data collection method in a PDF for contextual understanding of the dataset and provide the data sheets of the sensors used along with supporting code.
DOI: 10.25375/uct.25828264.v2
title: Ship Hull Vinyl Dataset

description: An inside sweet water tank at the Institute for Maritime Technology (IMT) in Cape Town was used to take a controlled underwater dataset using a prototype sensor rig. The target scene is a life-sized photomosaic of the side of a commercial ship hull that IMT had previously taken when the ship was last in dry dock. The photomosaic is printed onto a large vinyl tarpaulin and hung along the side of the tank.<br><br>Because the tank platform is 1m from the surface of the water, two 3m PVC pipes were used to manoeuvre the rig through the water, seen below. The rig is moved horizontally along the side of the platform facing the vinyl surface. Marks were placed on the PVC pipes as a visual aid to keep the rig at a relatively constant depth when moving horizontally. Once at the end of the vinyl, the rig is lowered directly downward to the next marked depth and moved horizontally back along the platform, creating a square ‘C’ shape. The data collection starts at 0.5m depth and returns at 1m depth.<br>We provide the data in the form of ROS bags. The data is supplied in three formats: raw, pre-processed and enhanced. The raw data has not been edited. The pre-processed data has been synchronized and images have been stereo rectified and undistorted. The enhanced data has been pre-processed and the images have additionally been enhanced with a CLAHE filter and dehazing, for improved underwater feature detection. With the ROS bags we also include the stereo camera and stereo-inertial (camera-IMU) calibration output files in yaml format.The original calibration data for camera and stereo-inertial calibrations are also included in ROS bag format so that users can perform their own calibrations if desired. On the sister GitHub, in the Meta Data folder, we detail the data collection method in a PDF for contextual understanding of the dataset and provide the data sheets of the sensors used along with supporting code.
DOI: 10.15468/dl.z6sfkz
title: Occurrence Download

description: A dataset containing 202517 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Plantago major subsp. major)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 202517 records from 715 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090342-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yxcyj9
title: Occurrence Download

description: A dataset containing 1018 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aglaia odorata Lour., Aglaia odorata subsp. microphyllina C.DC., Aglaia odorata var. chaudocensis (Pierre) Pellegr., Aglaia odorata var. microphyllina C.DC., Aglaia odorata var. odorata)"
 ]
}

 The dataset includes 1018 records from 93 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090389-240506114902167/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/8772657
title: ⏳ endoflife.date database (duckdb)
DOI: 10.15468/dl.wyerdb
title: Occurrence Download

description: A dataset containing 2758655 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Sweden",
 "OccurrenceStatus is Present",
 "TaxonKey is Lepidoptera",
 "Year 1775-2019"
 ]
}

 The dataset includes 2758655 records from 101 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090360-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12508664
title: Supplementary material of Investigating User Feedback from a Crowd in Requirements Management in Software Ecosystems
DOI: 10.5281/zenodo.12508665
title: Supplementary material of Investigating User Feedback from a Crowd in Requirements Management in Software Ecosystems
DOI: 10.15468/dl.ptfs6m
title: Occurrence Download

description: A dataset containing 5094 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Melochia tomentosa L.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5094 records from 187 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090390-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.khuzk9
title: Occurrence Download

description: A dataset listing the 127141 species recorded in GBIF matching the query:
{
 "PublishingCountry" : [
 "is South Africa"
 ]
}

 The dataset's 127141 records were derived from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090363-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v2esem
title: Occurrence Download

description: A dataset containing 9223951 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Living Specimen, Occurrence evidence, Fossil, Specimen)",
 "Country is China"
 ]
}

 The dataset includes 9223951 records from 1674 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090336-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.75qvw2
title: Occurrence Download

description: A dataset containing 126 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Polyclita A.C.Sm."
 ]
}

 The dataset includes 126 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015408-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.efnf48
title: Occurrence Download

description: A dataset containing 187114 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Scolytus intricatus Wood & Bright, 1992, Phymatodes testaceus (Linnaeus, 1758), Vibidia duodecimguttata (Poda, 1761), Plagionotus arcuatus (Linnaeus, 1758), Diaspidiotus ostreaeformis (Curtis, 1843), Cryptolestes ferrugineus (Stephens, 1831), Vincenzellus ruficollis (Panzer, 1794), Colydium elongatum (Fabricius, 1787), Lissodema denticolle (Gyllenhal, 1813), Uleiota planatus (Linnaeus, 1760), Taphrina carpini (Rostr.) Johanson, Armillaria tabescens (Scop.) Emel, Thaumetopoea processionea Linnaeus, 1758, Encoelia carpini Boud., Ascochyta carpinea Sacc., Ascocoryne sarcoides (Jacq.) J.W.Groves & D.E.Wilson, Anthostoma decipiens (DC.) Nitschke, Bulgaria inquinans (Pers.) Fr., Apiosporopsis carpinea (Fr.) Mariani, Amphisphaeria millepunctata (Fuckel) Petr., Bispora antennata (Pers.) E.W.Mason, Chaetosphaeria myriocarpa (Fr.) C.Booth, Ceratosporella stipitata (Goid.) S.Hughes, Diaporthe carpini (Pers.) Fuckel, Discosporina deplanata (Lib. ex Sacc.) Höhn., Encoelia glaberrima (Rehm) Kirschst., Discosia artocreas (Tode) Fr., Fusidium griseum Ditmar ex Link, Gnomonia fimbriata (Pers.) Fuckel, Melogramma campylosporum Fr., Melanconium stromaticum Corda, Mollisia ligni (Desm.) P.Karst., Melanopsamma pomiformis (Pers.) Sacc., Phaeohelotium italicum (Sacc.) Dennis, Ohleria rugulosa Fuckel, Pezicula carpinea (Pers.) Tul. ex Fuckel, Rutstroemia bolaris (Batsch) Rehm, Nitschkia grevillii (Rehm) Nannf., Diatrype disciformis (Hoffm.) Fr., Athelopsis glaucina (Bourdot & Galzin) Oberw. ex Parmasto, Hericium erinaceus (Bull.) Pers., Henningsomyces candidus (Pers.) Kuntze, Hymenochaete rubiginosa (Dicks.) Lév., Leucoagaricus ionidicolor Bellù & Lanzoni, Mycoacia nothofagi (G.Cunn.) Ryvarden, Phlebiella boidinii Tellería, Melo & M.Dueñas, Phanerochaete laevis (Fr.) J.Erikss. & Ryvarden, Peniophora laeta (Fr.) Donk, Polyporus umbellatus (Pers.) Fr., Pluteus salicinus (Pers.) P.Kumm.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 187114 records from 1469 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015407-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m6nzvq
title: Occurrence Download

description: A dataset containing 3021 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((35.25988 19.51316,142.74012 19.51316,142.74012 62.48684,35.25988 62.48684,35.25988 19.51316))",
 "Geometry POLYGON((115.91821 40.03901,116.50249 40.03901,116.50249 40.38412,115.91821 40.38412,115.91821 40.03901))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Rhopophilus pekinensis (Swinhoe, 1868)"
 ]
}

 The dataset includes 3021 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015401-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n87jqw
title: Occurrence Download

description: A dataset containing 3402 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Singapore",
 "OccurrenceStatus is Present",
 "TaxonKey is Sciuridae"
 ]
}

 The dataset includes 3402 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015406-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dr8dwn
title: Occurrence Download

description: A dataset containing 4529 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((74.16657 25.27208,137.83343 25.27208,137.83343 50.72792,74.16657 50.72792,74.16657 25.27208))",
 "Geometry POLYGON((115.87723 40.01109,116.68221 40.01109,116.68221 40.47703,115.87723 40.47703,115.87723 40.01109))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pterorhinus davidi Swinhoe, 1868"
 ]
}

 The dataset includes 4529 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015403-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15495869
title: ocean model bathymetry on eORCA12 grid derived from GEBCO2021

description: Ocean model bathymetry on the eORCA12 grid (nominal 1/12 degree horizontal resolution), derived from the GEBCO2021 dataset. Also included is a file containing the grid and land-sea mask information required to reproduce the bathymetry. Details of the process used to derive the bathymetry are here:

https://github.com/JMMP-Group/GLOBAL_BATHYMETRY
DOI: 10.5281/zenodo.15495870
title: ocean model bathymetry on eORCA12 grid derived from GEBCO2021

description: Ocean model bathymetry on the eORCA12 grid (nominal 1/12 degree horizontal resolution), derived from the GEBCO2021 dataset. Also included is a file containing the grid and land-sea mask information required to reproduce the bathymetry. Details of the process used to derive the bathymetry are here:

https://github.com/JMMP-Group/GLOBAL_BATHYMETRY
DOI: 10.15131/shef.data.29135327
title: Mine locations and footprints in sub Saharan Africa

description: These data we devised and used in the following papersAhmed, A.I., Massam, M.R., Bryant, R.G. and Edwards, D.P., 2025. How much deforestation in sub-Saharan Africa has been caused by mining?. <i>Biological Conservation</i>, <i>304</i>, p.111040. https://doi.org/10.1016/j.biocon.2025.111040Ahmed, A.I., Bryant, R.G. and Edwards, D.P., 2021. Where are mines located in sub Saharan Africa and how have they expanded overtime?. <i>Land Degradation & Development</i>, <i>32</i>(1), pp.112-122. 10.1002/ldr.3706The mine database and mine footprint data (an *xlxs file and a zipped *shp file) include a combination of mine data for sub-saharan africa (e.g. location, commodity, mine operator, and active dates) from sources outlined in Ahmed et al., (2021), as well from a process of manual digitising and mapping of mine footprints using high resolution remote sensing data. The methods used to generate this initial suite of information are outlined in Ahmed et al., (2021). A sub-set of these mine locations were used in Ahmed et al. (2025) to study the impacts of these mine operations on deforestation.
DOI: 10.15131/shef.data.29135327.v1
title: Mine locations and footprints in sub Saharan Africa

description: These data we devised and used in the following papersAhmed, A.I., Massam, M.R., Bryant, R.G. and Edwards, D.P., 2025. How much deforestation in sub-Saharan Africa has been caused by mining?. <i>Biological Conservation</i>, <i>304</i>, p.111040. https://doi.org/10.1016/j.biocon.2025.111040Ahmed, A.I., Bryant, R.G. and Edwards, D.P., 2021. Where are mines located in sub Saharan Africa and how have they expanded overtime?. <i>Land Degradation & Development</i>, <i>32</i>(1), pp.112-122. 10.1002/ldr.3706The mine database and mine footprint data (an *xlxs file and a zipped *shp file) include a combination of mine data for sub-saharan africa (e.g. location, commodity, mine operator, and active dates) from sources outlined in Ahmed et al., (2021), as well from a process of manual digitising and mapping of mine footprints using high resolution remote sensing data. The methods used to generate this initial suite of information are outlined in Ahmed et al., (2021). A sub-set of these mine locations were used in Ahmed et al. (2025) to study the impacts of these mine operations on deforestation.
DOI: 10.6084/m9.figshare.29135609
title: Trilford, Harris and Cuda. 2025. The Islands of Occupied Palestine: Analyzing the Urbicide and Spatial Disruption of the Israeli Apartheid Wall in the West Bank through Space Syntax Analysis Case Studies of Qalqilya and Abu Dis. Depthmap Models

description: AbstractSpatial networks and street infrastructures are analyzed as orchestrated architectures of violence weaponized by the Israeli Occupation’s Apartheid Wall as a tool for urbicide in the West Bank of the Occupied Palestinian Territories. Utilizing space syntax analysis, this study reveals how the Wall alters urban spatial configurations, mobility and accessibility, contributing to the discourse on urbicide by uncovering the systemic, covert spatial violence often overshadowed by overt military actions.Space syntax analysis has been applied to other partitioned cities, such as Berlin, Belfast, and Beirut, demonstrating how division lines control movement. This method is used to map the street networks of two West Bank sites with and without the Wall: Qalqilya and Abu Dis. These sites, selected for their urban disruption and data availability from GEOMOLG and OpenStreetMap exemplify varying degrees of division and spatial violence.Qalqilya's near-complete encirclement by the Wall highlights severe isolation, drastically reducing accessible routes and severing economic and social links. Abu Dis faces disconnect from Jerusalem, impacting essential access to healthcare, education, and employment. The study underscores the Wall's contribution to urbicide by diminishing urban vitality and resilience.
DOI: 10.6084/m9.figshare.29135609.v1
title: Trilford, Harris and Cuda. 2025. The Islands of Occupied Palestine: Analyzing the Urbicide and Spatial Disruption of the Israeli Apartheid Wall in the West Bank through Space Syntax Analysis Case Studies of Qalqilya and Abu Dis. Depthmap Models

description: AbstractSpatial networks and street infrastructures are analyzed as orchestrated architectures of violence weaponized by the Israeli Occupation’s Apartheid Wall as a tool for urbicide in the West Bank of the Occupied Palestinian Territories. Utilizing space syntax analysis, this study reveals how the Wall alters urban spatial configurations, mobility and accessibility, contributing to the discourse on urbicide by uncovering the systemic, covert spatial violence often overshadowed by overt military actions.Space syntax analysis has been applied to other partitioned cities, such as Berlin, Belfast, and Beirut, demonstrating how division lines control movement. This method is used to map the street networks of two West Bank sites with and without the Wall: Qalqilya and Abu Dis. These sites, selected for their urban disruption and data availability from GEOMOLG and OpenStreetMap exemplify varying degrees of division and spatial violence.Qalqilya's near-complete encirclement by the Wall highlights severe isolation, drastically reducing accessible routes and severing economic and social links. Abu Dis faces disconnect from Jerusalem, impacting essential access to healthcare, education, and employment. The study underscores the Wall's contribution to urbicide by diminishing urban vitality and resilience.
DOI: 10.15468/dl.ygahrk
title: Occurrence Download

description: A dataset containing 12492 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((115.72595 39.95471,116.73617 39.95471,116.73617 40.61946,115.72595 40.61946,115.72595 39.95471))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Passer montanus (Linnaeus, 1758)"
 ]
}

 The dataset includes 12492 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015388-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tu3ujn
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{
 "and" : [
 "RecordedBy is Chiovenda, E.",
 "Year 1895-1921"
 ]
}

 The dataset includes 74 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015391-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14968860
title: PANDORA Database

description: This repository contains the latest update to the PANDORA template database, including pMHCI, pMHCII and reversed-pMHCII templates.

PANDORA is an anchor-restrained modelling pipeline for generating peptide-MHC structures.

GitHub Repository

Software Documentation

 

Publications:



Rademaker, D.T., Parizi, F.M., Vreeswijk, M. van, Eerden, S., Marzella, D.F., Xue, L.C., 2025. Bidirectional Peptide Conformation Prediction for MHC Class II using PANDORA. https://doi.org/10.1101/2024.11.04.621877



 

Parizi, F.M., Marzella, D.F., Ramakrishnan, G., ‘T Hoen, P.A.C., Karimi-Jafari, M.H., Xue, L.C., 2023. PANDORA v2.0: Benchmarking peptide-MHC II models and software improvements. Front. Immunol. 14, 1285899. https://doi.org/10.3389/fimmu.2023.1285899

 


Marzella, D.F., Parizi, F.M., Tilborg, D.V., Renaud, N., Sybrandi, D., Buzatu, R., Rademaker, D.T., ‘T Hoen, P.A.C., Xue, L.C., 2022. PANDORA: A Fast, Anchor-Restrained Modelling Protocol for Peptide: MHC Complexes. Front. Immunol. 13, 878762. https://doi.org/10.3389/fimmu.2022.878762