cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.12761322
title: Underwater images collected by an Autonomous Surface Vehicle in Hermitage, Réunion - 2024-06-28

description: This dataset was collected by an Autonomous Surface Vehicle in Hermitage, Réunion - 2024-06-28. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
description: The Plancha project is co-financed by the Prefecture of Reunion as part of a 2019-2022 convergence and transformation contract, measure 3.3.1.1
DOI: 10.5281/zenodo.11204953
title: Underwater images collected by an Autonomous Surface Vehicle in Tessier, Réunion - 2024-05-15

description: This dataset was collected by an Autonomous Surface Vehicle in Tessier, Réunion - 2024-05-15. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
description: The Plancha project is co-financed by the Prefecture of Reunion as part of a 2019-2022 convergence and transformation contract, measure 3.3.1.1
DOI: 10.15468/dl.uqckn3
title: Occurrence Download

description: A dataset containing 11218 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Canna indica L.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 11218 records from 447 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007520-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.saqyp4
title: Occurrence Download

description: A dataset containing 4204 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Theobroma L.",
 "HasCoordinate is true",
 "Country is Colombia"
 ]
}

 The dataset includes 4204 records from 134 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007521-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.86jnbh
title: Occurrence Download

description: A dataset containing 312 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Capromys pilorides (Say, 1822))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 312 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007522-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3hkh7j
title: Occurrence Download

description: A dataset containing 7061 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Festuca idahoensis Elmer"
 ]
}

 The dataset includes 7061 records from 169 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007586-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.35080/data.h.2020.p21
title: Integration of Borehole Data and 3D Geological Modeling of the Huangling Area on the Southern Margin of the Ordos Basin Based on joint Coal-Uranium Explorations
title: 鄂尔多斯盆地南缘黄陵地区煤铀兼探钻孔数据集成与三维地质模型构建

description: The  Huangling  area  on  the  southern  margin  of  the  Ordos  Basin  boasts  great potential for uranium mineralization. China Geological Survey has organized and implemented 3D geological survey of the uranium-bearing rock series in this area to seek prospecting target areas of in-situ leachable sandstone-hosted uranium deposits. During the survey, the data of the coalfield boreholes were developed and utilized again to determine exploration areas under the guidance  of  new  ideas  of  joint  coal-uranium  explorations  and  joint  petroleum-uranium explorations.  As  a  result,  the  data  of  354  coalfield  boreholes  (49  potential  sandstone-hosted uranium  ore  boreholes)  and  21  verified  uranium  ore  boreholes  (16  industrial  uranium mineralization boreholes) were acquired and a database was created accordingly. Furthermore, a thematic result atlas and a 3D geologic model were established, which mainly constitute the database. The thematic result atlas includes the isoline maps of stratum thickness, sand body thickness, the burial depth of the roof and floor, sand content and radioactive anomalies of the uranium-bearing  rock  series.  Therefore,  the  database  will  provide  active  support  and  service for the exploration and development of uranium deposits.
description: 鄂尔多斯盆地南缘黄陵地区铀成矿前景良好。中国地质调查局在该地区组织实施了含铀岩系三维地质调查工作，以寻找可地浸砂岩型铀矿找矿靶区为目标，采用“煤铀兼探”、“油铀兼探”的新思路，对煤田钻孔资料进行“二次开发利用”，开展勘查选区研究，完成了354口煤田钻孔（其中筛选出潜在砂岩型铀矿（化）孔49口）和21口铀矿验证钻孔（其中工业矿（化）孔16口）的数据采集建库，在此基础上建立了专题成果图集及三维地质模型。该数据库主要由含铀岩系地层厚度等值线图、砂体厚度等值线图、顶底板埋深等值线图、含砂率等值线图、放射性异常等值线图等专题成果图集和三维地质结构模型组成，为铀矿勘探开发提供了有利支撑和服务作用。
DOI: 10.6084/m9.figshare.28374080.v1
title: Figure 1C, S1A, S1B, S1E, S1F

description: Fluorescence microscopy of WT <i>E. coli</i> cells uninfected or infected by phage Goslar at 10, 30 or 60 mpi. Channel 1: outer membrane (FM4-64), channel 2: All membranes (MitoTracker Green FM), channel 3: DNA (DAPI), channel 4: brightfield.
DOI: 10.6084/m9.figshare.28357829.v1
title: Figure 2A, 2B, S2A

description: Fluorescence microscopy of NT or ChmAg1 <i>E. coli</i> cells infected by phage Goslar carrying GFP-tagged phage protein gp58. Images were collected at 60 mpi. Channel 1: outer membrane (FM4-64), channel 2: all membranes (MitoTracker Green FM), channel 3: DNA (DAPI), channel 4: brightfield.
DOI: 10.6084/m9.figshare.28357829.v2
title: Figure 2A, 2B

description: Fluorescence microscopy of NT or ChmAg1 <i>E. coli</i> cells infected by phage Goslar carrying GFP-tagged phage protein gp58. Images were collected at 60 mpi. Channel 1: outer membrane (FM4-64), channel 2: all membranes (MitoTracker Green FM), channel 3: DNA (DAPI), channel 4: brightfield.
DOI: 10.6084/m9.figshare.28297403
title: Dataset Compassion Arthitis.xlsx

description: The aim of the research was to examine the roles of compassion from others, self-compassion, and rumination in explaining psychological distress in patients with arthritis.
DOI: 10.6084/m9.figshare.28297403.v1
title: Dataset Compassion Arthitis.xlsx

description: The aim of the research was to examine the roles of compassion from others, self-compassion, and rumination in explaining psychological distress in patients with arthritis.
DOI: 10.35080/data.h.2020.p20
title: Borehole Databases and 3D Geological Model of JurassicCretaceous Strata in Dongsheng Area, North Odors Basin
title: 鄂尔多斯盆地北部东胜地区侏罗系−白垩系钻孔数据库

description: The integrated application of existing borehole data has become an urgent need with further  prospecting  of  sandstone-hosted  uranium  deposits.  In  this  paper,  a  comprehensive borehole  database  of  Jurassic –Cretaceous  strata  in  Dongsheng  area  (also  referred  to  as  the Database)  was  established  under  the  guidance  of  the  new  ideas  and  methods  of “secondary development  and  utilization  of  existing  coalfield  borehole  data” and “coal-uranium  joint exploration” .  In  detail,  the  borehole  attributes  of  Dongsheng  area  were  collected.  Then  key borehole data related to coalfields and uranium deposits were successively collated, scanned, converted  into  desired  data  types,  input  into  data  tables,  and  integrated  into  databases according  to  unified  standards  and  requirements.  As  a  result,  the  Database  was  established, achieving unified management of borehole data from multiple sources. The Database consists of  three  Access  databases  and  corresponding  result  maps.  Each  of  the  Access  databases contains  eight  data  tables,  namely Basic information of a borehole, Beds based on comprehensive histograms, Beds based on lithologic description, Names and codes of strata, Data from logging curves, Configuration of logging curves, Bending degree measurement of boreholes,  etc.  These  data  tables  respectively  contain  detailed  data  of  the  lithology  from geologic records, beds, rock colors, logging curves, hydrogeological beds, borehole sampling, and bending degree measurement. According to application and practices, the Database enables a quick generation of critical basic geologic maps such as well profiles and the isoline maps of the elevations of roofs and floors, stratum thickness, sand-body thickness, and sand content of target  strata  bearing  coal  and  uranium.  This  will  increase  the  data  utilization  efficiency  and
provide critical data for the exploration and research of uranium deposits.
description: 随着砂岩型铀矿找矿工作的进一步开展，其对以往钻孔资料集成应用的需求尤为迫切。在煤田钻孔资料“二次开发利用”和“煤铀兼探”新方法、新思路的指导下，通过采集东胜地区钻孔资料属性数据，按照统一的标准和要求，将煤田、铀矿等类型的重要钻孔资料，通过整理、扫描、数据类型转换、录入和集成，建成了东胜地区侏罗系—白垩系综合钻孔数据库，实现了对多源钻孔数据的统一管理。该数据库共包含3个Access数据库和相应的成果图件。每个Access数据库均包含钻孔基本信息表、综合柱状分层表、岩性描述分层表、地层名称及代号表、地层颜色表、测井曲线数据表、测井曲线配置表和钻孔弯曲度测量数据表等8张数据表，分别详细记录了地质编录岩性信息、地层分层信息、岩石颜色信息、测井曲线信息、水文分层信息、钻孔样品采样信息、弯曲度测量信息等。通过应用实践，该钻孔数据库成果可实现连井剖面、含煤含铀目的层的顶底板标高、地层等厚图、砂体等厚图及含砂率图等重要基础地质图件的快速生成，从而提高数据的使用效率并为铀矿勘查及研究工作提供重要数据基础。
DOI: 10.6084/m9.figshare.28374134.v1
title: Figure 2C, 2D, 2E, S2B

description: Fluorescence microscopy of NT and ChmAg1 <i>E. coli</i> cells uninfected or infected by phage Goslar. Images were collected at 60 mpi. Channel 1: outer membrane (FM4-64), channel 2: all membranes (MitoTracker Green FM), channel 3: DNA (DAPI), channel 4: brightfield.
DOI: 10.6084/m9.figshare.28355900.v1
title: Figure 2F, S2C, S2D, S2E

description: Fluorescence microscopy of NT-EV, ChmAg1-EV, NT-ChmA* or ChmAg1-ChmA* <i>E. coli </i>cells infected by phage Goslar. Images were collected at 60 mpi. Channel 1: outer membrane (FM4-64), channel 2: all membranes (MitoTracker Green FM), channel 3: DNA (DAPI), channel 4: brightfield.
DOI: 10.6084/m9.figshare.28374200.v1
title: Figure 3E, 3F, S3C

description: Fluorescence microscopy of NT and ChmAg1 <i>E. coli</i> cells infected by phage Goslar carrying GFP-tagged phage vRNAP subunit gp196. Images were collected at 60 mpi. Channel 1: Outer membrane (FM4-64), channel 2: GFP-tagged gp196, channel 3: DNA (DAPI), channel 4: brightfield.
DOI: 10.15468/dl.vmeud8
title: Occurrence Download

description: A dataset containing 11728 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is United States of America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Poa pratensis L."
 ]
}

 The dataset includes 11728 records from 214 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007523-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28355900
title: Figure 2F, S3B-C

description: Fluorescence microscopy of NT-EV, ChmAg1-EV, NT-ChmA* or ChmAg1-ChmA* <i>E. coli </i>cells infected by phage Goslar. Images were collected at 60 mpi. Channel 1: outer membrane (FM4-64), channel 2: all membranes (MitoTracker Green FM), channel 3: DNA (DAPI), channel 4: brightfield.
DOI: 10.6084/m9.figshare.28355900.v3
title: Figure 2F, S3B-C

description: Fluorescence microscopy of NT-EV, ChmAg1-EV, NT-ChmA* or ChmAg1-ChmA* <i>E. coli </i>cells infected by phage Goslar. Images were collected at 60 mpi. Channel 1: outer membrane (FM4-64), channel 2: all membranes (MitoTracker Green FM), channel 3: DNA (DAPI), channel 4: brightfield.
DOI: 10.6084/m9.figshare.28355900.v2
title: Figure 2F

description: Fluorescence microscopy of NT-EV, ChmAg1-EV, NT-ChmA* or ChmAg1-ChmA* <i>E. coli </i>cells infected by phage Goslar. Images were collected at 60 mpi. Channel 1: outer membrane (FM4-64), channel 2: all membranes (MitoTracker Green FM), channel 3: DNA (DAPI), channel 4: brightfield.
DOI: 10.35080/data.h.2020.p19
title: Dataset of Boreholes Drilled in the Coalfield of Wucaiwan Area in Eastern Margin of Junggar Basin, Xinjiang
title: 新疆准噶尔盆地东缘五彩湾地区煤田钻孔数据集

description: Junggar Basin in Xinjiang is an important home to reservoirs of energy and mineral resources such as oil, gas, and coal in China. In this paper, a dataset of 20 boreholes drilled in the coalfield of Wucaiwan area that lies in the eastern margin of Junggar Basin (also referred to as the Dataset) was established based on secondary development and exploitation of existing borehole  materials.  In  other  words,  the  Dataset  was  established  by  extracting  important information  from  existing  materials  of  the  boreholes  such  as  coordinates  and  elevation  of boreholes,  thickness  and  color  of  strata  discovered,  and  data  from  interpretation  of  logging curves. It consists of Excel database files of 20 boreholes. Each database file is comprised of 10  worksheets,  namely Basic information of boreholes, Lithological beds based on logging interpretation, Beds based on geological record histogram, Beds based on comprehensive histogram, Lithological beds of boreholes, Names and codes of strata, Colors of beds, Configuration oflogging curves, Data from logging curves, and Data dictionary. The data in the  Dataset  can  be  read  using  software  developed  by  Xi'an  Shiwen  Software  Co.,  Ltd.  (also referred to as Shiwen software) to plot 3D stereograms of stratigraphic sedimentary. This will help  achieve  a  more  intuitive  understanding  of  the  spatial  distribution  and  3D  geological structures of sandstone bodies in Wucaiwan area and thus is significant for the research of the sedimentary environment in this area.
description: 新疆准噶尔盆地是中国油气、煤炭等能源矿产的重要储集场所。本次研究对搜集到的准噶尔盆地东缘五彩湾地区20个煤田钻孔资料进行二次开发利用，通过提取钻孔坐标、高程、地层分层厚度、颜色、测井曲线解译数据等重要信息，重新建立了钻孔数据集。数据集共包含20个钻孔资料的Excel数据库型数据，每个Excel数据库由“钻孔基本信息”、“测井解释岩性分层”、“地质编录柱状分层”、“综合柱状信息”、“钻孔岩性分层”、“地层名称及代号表”、“地层颜色”、“测井曲线配置”、“测井曲线数据”、“数据字典”等10个工作表组成。利用石文软件可读取数据集信息，绘制地层沉积三维立体图，该成果能够对准噶尔盆地东缘五彩湾地区砂体的空间展布、三维地质结构等提供更加直观的认识，对研究准噶尔盆地东缘五彩湾地区的沉积环境具有重要意义。
DOI: 10.6084/m9.figshare.28374134.v2
title: Figure 2C

description: Fluorescence microscopy of NT and ChmAg1 <i>E. coli</i> cells uninfected or infected by phage Goslar. Images were collected at 60 mpi. Channel 1: outer membrane (FM4-64), channel 2: all membranes (MitoTracker Green FM), channel 3: DNA (DAPI), channel 4: brightfield.
DOI: 10.15468/dl.e3dups
title: Occurrence Download

description: A dataset containing 72722 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Misumena Latreille, 1804"
 ]
}

 The dataset includes 72722 records from 821 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007518-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1049904.10fu
title: SH1049904.10FU

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/sh1049908.10fu
title: SH1049908.10FU

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/sh1049909.10fu
title: SH1049909.10FU

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.31041973
title: Additional file 1 of Strike-slip faulting and hydrothermal alteration in a Proterozoic rapakivi batholith: implications for reservoir formation and geothermal exploration in crystalline cratons—Part 1

description: Additional file 1
DOI: 10.6084/m9.figshare.31041973.v1
title: Additional file 1 of Strike-slip faulting and hydrothermal alteration in a Proterozoic rapakivi batholith: implications for reservoir formation and geothermal exploration in crystalline cratons—Part 1

description: Additional file 1
DOI: 10.6084/m9.figshare.31041979
title: Additional file 2 of Multi-centered T cell repertoire profiling identifies alterations in the immune repertoire of individuals with inflammatory bowel disease across different disease stages

description: Additional file 2. Supplementary Tables (Tables S1–S5). Excel file containing all supplementary tables, including phenotypic descriptions of the IBSEN-III, IBSEN-20, and BCBC cohorts, and lists of CD- and UC-associated TRA clonotypes.