cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr300726
title: Replication Package for: The Her in Inheritance: How Marriage Matching Has Always Mattered, Quebec 1800–1970
title: Archival Version

description: <p class="editor-paragraph" dir="ltr"><span style="white-space: pre-wrap;">Replication Package for: The Her in Inheritance: How Marriage Matching Has Always Mattered, Quebec 1800–1970</span></p>
DOI: 10.3886/icpsr300726.v1
title: Replication Package for: The Her in Inheritance: How Marriage Matching Has Always Mattered, Quebec 1800–1970
title: Version 1

description: <p class="editor-paragraph" dir="ltr"><span style="white-space: pre-wrap;">Replication Package for: The Her in Inheritance: How Marriage Matching Has Always Mattered, Quebec 1800–1970</span></p>
DOI: 10.15468/dl.u5ew3f
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Living Specimen)",
 "TaxonKey is Nilssonia leithii"
 ]
}

 The dataset includes 27 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005681-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48579/pro/3cgsug
title: Replication data for: Fig 8.14, Bottom, Submergers vs nonsubmergers, WTPDs, 21 Nov 2025

description: FILE DESCRIPTION Keywords: alarm call, submerger vs nonsubmerger, WTPDs File name = Fig 8.14, Bottom, Submergers vs nonsubmergers, WTPDs, 21 Nov 2025 Date = 10 April 2019 = date of creation for this file These data are from WTPDs at the Arapaho National Wildlife Refuge from 2006 through 2012 292/956 WTPD submergers = 30.54 % DID give alarm call 664/956 WTPD submergers = 69.46% DID give alarm call 804/1536 WTPD NON-submergers = 52.34 % DID give alarm call 732/1536 WTPD NON-submergers = 47.66% DID give alarm call Variable = Frequency = number of observations of calling or non-calling for each class of WTPD All data were summarized by Judy, and checked by Judy and John TWO TIMES File name = Fig 8.14, Bottom, Submergers vs nonsubmergers, WTPDs, 21 Nov 2025 For statistical analysis, I did a 2x2 chi-square test These data used for Fig 8.14, Bottom, in Hoogland 2026. This file ready for longterm storage on 04 June 2025. Counts for this file come from study of alarm call raw data sheets. I considered data from the same prairie dog on the same day and on different days and in different years to be independent. Data in this file represents SUMMATION OF UPD DATA FROM ALL YEARS Variable = Frequency = number of observations of calling or non-calling for WTPDs that did and did not submerge during experiments with the moving stuffed badger Submerger = 1 = prairie dog DID submerge Submerger = 2 = prairie dog did NOT submerge Alarm call = 1 = prairie dog DID give alarm call Alarm call = 2 = prairie dog did NOT give alarm call
DOI: 10.11588/duerer.online.69245366829e4
title: Eingangshalle im Erdgeschoss des Dürer-Hauses, https://d-nb.info/gnd/1207789984
DOI: 10.15468/dl.94nw6g
title: Occurrence Download

description: A dataset containing 582 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "GadmGid is COL.15.13_2",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 582 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005682-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48579/pro/4ogivl
title: Replication data for: Fig 8.14, Bottom, Submergers vs nonsubmergers, UPDs, 21 Nov 2025

description: FILE DESCRIPTION Keywords: alarm calls, submergers vs nonsubmergers, UPDs Filename = Fig 8.14, Bottom, Submergers vs nonsubmergers, UPDs, 21 Nov 2025 OLD file name = UPDs, Submerge, 23 Sept 2019 These numbers checked TWO TIMES at creation of old file name 458/2978 of UPD submergers = 15.38% DID give alarm call in response to experimental badger 2520/2978 of UPD submergers = 84.62% did NOT give alarm call in response to experimental badger 1067/2436 of UPD NON-submergers = 43.80% DID give alarm call in response to experimental badgers 1369/2436 of UPD NON-submergers = 56.20% DID NOT give alarm call in response to experimental badgers Data in this file represents SUMMATION OF UPD DATA FROM ALL YEARS Variable = Frequency = number of observations of calling or non-calling for UPDs that did and did not submerge during experiments with the moving stuffed badger Submerger = 1 = prairie dog DID submerge Submerger = 2 = prairie dog did NOT submerge Alarm call = 1 = prairie dog DID give alarm call Alarm call = 2 = prairie dog did NOT give alarm call For statistical analysis, I did a 2x2 chi-square test These data used for Fig 8.14, Bottom, in Hoogland 2026. This file ready for longterm storage on 04 June 2025. Counts for this file come from study of alarm call raw data sheets. Filename = Fig 8.14, Bottom, Submergers vs nonsubmergers, UPDs, 04 June 2025 I considered data from the same prairie dog on the same day and on different days and in different years to be independent.
DOI: 10.15468/dl.zgnduw
title: Occurrence Download

description: A dataset containing 206 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Brachybotrys paridiformis",
 "Year 1950-2025"
 ]
}

 The dataset includes 206 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005683-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48579/pro/na8zzy
title: Replication data for: Fig 8.14, Bottom, Submergers vs nonsubmergers, GPDs, 21 Nov 2025

description: FILE DESCRIPTION Keywords: alarm calls, submergers vs nonsubmergers, GPDs Filename = Fig 8.14, Bottom, Submergers vs nonsubmergers, GPDs, 21 Nov 2025 OLD file name = GPDs, Submerge, 23 Sept 2019 These numbers checked TWO TIMES at creation of old file name 194/1290 of GPD submergers = 15.04% DID give alarm call in response to experimental badger 1096/1290 of GPD submergers = 84.96% did NOT give alarm call in response to experimental badger 947/2872 of GPD NON-submergers = 32.97% DID give alarm call in response to experimental badgers 1925/2872 of GPD NON-submergers = 67.03% DID NOT give alarm call in response to experimental badgers Data in this file represents SUMMATION OF GPD DATA FROM ALL YEARS Variable = Frequency = number of observations of calling or non-calling for GPDs that did and did not submerge during experiments with the moving stuffed badger Submerger = 1 = prairie dog DID submerge Submerger = 2 = prairie dog did NOT submerge Alarm call = 1 = prairie dog DID give alarm call Alarm call = 2 = prairie dog did NOT give alarm call For statistical analysis, I did a 2x2 chi-square test These data used for Fig 8.14, Bottom, in Hoogland 2026. This file ready for longterm storage on 03 June 2025. I considered data from the same prairie dog in different years to be independent. Counts for this file come from study of alarm call raw data sheets. Filename = Fig 8.14, Bottom, Submergers vs nonsubmergers, GPDs, 21 Nov 2025 I considered data from the same prairie dog on the same day and on different days and in different years to be independent.
DOI: 10.17632/wb2w5hpth3
title: Modeling extreme nitrogen isotope variability in diamond

description: Supplementary material and figures data
DOI: 10.17632/wb2w5hpth3.2
title: Modeling extreme nitrogen isotope variability in diamond

description: Supplementary material and figures data
DOI: 10.5281/zenodo.17699761
title: Code and data for paper entitled 'Physically Guided GAN-Based Super Resolution of Buoy Observations for Internal Solitary Waves'

description: Code and data for paper entitled 'Physically Guided GAN-Based Super Resolution of Buoy Observations for Internal Solitary Waves'
DOI: 10.5281/zenodo.17699760
title: Code and data for paper entitled 'Physically Guided GAN-Based Super Resolution of Buoy Observations for Internal Solitary Waves'

description: Code and data for paper entitled 'Physically Guided GAN-Based Super Resolution of Buoy Observations for Internal Solitary Waves'
DOI: 10.48579/pro/mdqfnf
title: Replication data for: Fig 8.14, Bottom, Submergers vs nonsubmergers, BTPDs, 21 Nov 2025

description: FILE DESCRIPTION Keywords: alarm calls, submergers vs nonsubmergers, BTPDs Filename = Fig 8.14, Bottom, Submergers vs nonsubmergers, BTPDs, 21 Nov 2025 OLD file name = BTPDs, Alarm calls, submergers vs nonsubmergers, 10 April 2019 These data are from BTPDs of my first book (Hoogland, 1995) I assume all data were checked TWO TIMES, because that's what I always did for my first book 598/2255 of BTPD submergers = 26.52% DID give alarm call in response to experimental badger 1657/2255 of BTPD submergers = 73.48% % DID NOT give alarm call in response to experimental badger 688/3299 of BTPD NON-submergers = 20.85% DID give alarm call in response to experimental badgers 2611/3299 of BTPD NON-submergers = 79.15% DID NOT give alarm call in response to experimental badgers The data in this file are group BY YEAR. The summaries I provide immediately above and in figure for my new book are the SUMMATION OF DATA FROM ALL YEARS Variable = Frequency = number of observations of calling or non-calling for closest and not closest prairie dogs Submerger = 1 = prairie dog DID submerge Submerger = 2 = prairie dog did NOT submerge Alarm call = 1 = prairie dog DID give alarm call Alarm call = 2 = prairie dog did NOT give alarm call For statistical analysis, I did a 2x2 chi-square test These data used for Fig 8.14, Bottom, in Hoogland 2026. This file ready for longterm storage on 03 June 2025. I considered data from the same prairie dog in different years to be independent. Counts for this file come from study of alarm call raw data sheets. Filename = Fig 8.14, Bottom, Submergers vs nonsubmergers, BTPDs, 03 June 2025 I considered data from the same prairie dog on the same day and on different days and in different years to be independent.
DOI: 10.15468/dl.umrt9n
title: Occurrence Download

description: A dataset containing 3277 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation, Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Opuntia cespitosa"
 ]
}

 The dataset includes 3277 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005684-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/b5rpts
title: Archeologisch Bureauonderzoek aanleg MS- en LS-leiding te Exloo, gemeente Borger-Odoorn

description: BAM Infraconsult BV (“opdrachtgever”) heeft T&A Survey (“T&A”) op 9 juli 2025 schriftelijk opdracht verleend voor het uitvoeren van een archeologisch bureauonderzoek. De opdrachtgever is voornemens in Exloo een MS- en LS-leiding te realiseren. Het plangebied ligt in de bebouwde kom van Exloo in de straten Cypreslaan, Cederlaan, Thujalaan, Taxuslaan, Boslaan, Dennenlaan en Hoofdstraat. De geplande werkzaamheden betreft de aanleg van een MS- en een LS-leiding. De grootste deel van de leiding zal door middel van open ontgraving uitgevoerd worden. Er wordt een sleuf met een breedte van circa 50 cm en een diepte van 90 cm – MV aangelegd. Twee kleine stukken worden door middel van een persing met een diameter van 80 mm aangelegd.
DOI: 10.48579/pro/ynh0gd
title: Replication data for: Fig 8.14, Top, Closest vs farther for alarm callers, WTPDs, 21 Nov 2025

description: FILE DESCRIPTION Keywords: alarm calls, closest vs farther away, WTPDs Filename = Fig 8.14, TOP, Closest vs farther for alarm callers, WTPDs, 21 Nov 2025 Older date = Date of creation (I think) = 10 April 2019 These data are from WTPDs at the Arapaho National Wildlife Refuge from 2006 through 2012 413/961 of closest WTPDs = 42.98% DID give alarm call 548/961 of closest WTPDs = 57.02% DID NOT give alarm call 620/1409 of farther WTPDs = 44.00% DID give alarm call 789/1409 of farther WTPDs = 56.00% DID NOT give alarm call Variable = Frequency = number of observations of calling or non-calling for each class of WTPD All data were summarized by Judy, and checked by Judy and John TWO TIMES For statistical analysis, I did a 2x2 chi-square test These data used for Fig 8.14, Top, in Hoogland 2026. This file ready for longterm storage on 04 June 2025. I considered data from the same prairie dog in different years to be independent. Counts for this file come from study of alarm call raw data sheets. Filename = Fig 8.14, Top, Closest vs farther for alarm callers, WTPDs, 21 Nov 2025 I considered data from the same prairie dog on the same day and on different days and in different years to be independent. Variable = Frequency = number of observations of calling or non-calling for closest and not closest prairie dogs Close WTPD = 1 = closest to prairie dog Close WTPD = 2 = NOT closest to prairie dog WTPD alarm call = 1 = prairie dog DID give alarm call WTPD alarm call = 2 = prairie dog did NOT give alarm call For statistical analysis, I did a 2x2 chi-square test Counts for this file come from study of alarm call raw data sheets.
DOI: 10.48579/pro/ieaotq
title: Replication data for: Fig 8.14, top, Closest vs farther for alarm callers, UPDs, 21 Nov 2025

description: FILE DESCRIPTION Keywords: alarm calls, closest vs farther away, UPDs Filename: Fig 8.14, top, Closest vs farther for alarm callers, UPDs, 21 Nov 2025 OLD Filename: UPDs, Alarm calls, closest vs farther from badger, 10 April 2019 436/1876 of closest UPDs = 23.24% DID give alarm call 1440/1876 of closest UPDs = 76.76% DID NOT give alarm call 763/2575 farther UPDs = 29.63% DID give alarm call 1812/2575 of farther UPDs = 70.37% DID NOT give alarm call The summaries I provide immediately above and in Fig 8.14 for my new book are from the SUMMATION OF DATA FROM ALL YEARS Variable = Frequency = number of observations of calling or non-calling for closest and not closest prairie dogs Close prairie dog = 1 = closest to prairie dog Close prairie dog = 2 = NOT closest to prairie dog UPD alarm call = 1 = prairie dog DID give alarm call UPD alarm call = 2 = prairie dog did NOT give alarm call For statistical analysis, I did a 2x2 chi-square test These data used for Fig 8.14, Top, in Hoogland 2026. This file ready for longterm storage on 03 June 2025. I considered data from the same prairie dog in different years to be independent. Counts for this file come from study of alarm call raw data sheets. Filename: Fig 8.14, Top, Closest vs farther for alarm callers, UPDs, 21 Nov 2025 I considered data from the same prairie dog on the same day and on different days and in different years to be independent. I assume that I checked these data TWO TIMES, but I cannot find that assurance.
DOI: 10.15468/dl.dqyj57
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Living Specimen)",
 "TaxonKey is Nilssonia nigricans"
 ]
}

 The dataset includes 21 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005686-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w7g3mb
title: Occurrence Download

description: A dataset containing 373373 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Coordinate rounded, Geodetic datum invalid, Geodetic datum assumed WGS84, Coordinate reprojection suspicious, Footprint WKT mismatch, Footprint WKT invalid, Country mismatch, Country derived from coordinates, Continent coordinate mismatch, Continent country mismatch, Continent derived from coordinates, Recorded date mismatch, Recorded date invalid, Taxon match fuzzy, Taxon match higher rank, The scientific name ID was not found in the checklist, The taxon concept ID was not found in the checklist, The taxon ID was not found in the checklist, The scientific name differs on the record from that found in the checklist, Taxon match none, Depth unlikely, Elevation min max swapped, Elevation non numeric, Modified date invalid, Identified date invalid, Type status invalid, Multimedia date invalid, Multimedia URI invalid, References URI invalid, Individual count invalid, Individual count conflicts with occurrence status, Occurrence status unparsable, Occurrence status inferred from individual count)",
 "OccurrenceStatus is Present",
 "TaxonKey is Betula pubescens",
 "Year 1950-2025"
 ]
}

 The dataset includes 373373 records from 864 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005622-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48579/pro/tdabo4
title: Replication data for: Fig 8.14, Top, Closest vs farther for alarm callers, BTPDs, 21 Nov 2025

description: FILE DESCRIPTION Keywords: alarm calls, closest vs farther away, BTPDs Filename: Fig 8.14, Top, Closest vs farther for alarm callers, BTPDs, 21 Nov 2025 OLD Filename: BTPDs, Alarm calls, closest vs farther from badger, 10 April 2019 These data are from my first book (Hoogland 1995), so I assume they were checked TWO times 340/710 of closest BTPDs = 47.89% DID give alarm call 370/710 of closest BTPDs = 52.11% DID NOT give alarm call 877/2281 farther BTPDs = 38.45% DID give alarm call 1404/2281 of farther BTPDs = 61.55% DID NOT give alarm call The data in this file are grouped BY YEAR. The summaries I provide immediately above and in figure for my new book are from the SUMMATION OF DATA FROM ALL YEARS Variable = Frequency = number of observations of calling or non-calling for closest and not closest prairie dogs Close prairie dog = 1 = closest to prairie dog Close prairie dog = 2 = NOT closest to prairie dog BTPD alarm call = 1 = prairie dog DID give alarm call BTPD alarm call = 2 = prairie dog did NOT give alarm call For statistical analysis, I did a 2x2 chi-square test These data used for Fig 8.14, Top, in Hoogland 2026. This file ready for longterm storage on 03 June 2025. I considered data from the same prairie dog on the same day and on different days and years to be independent. Counts for this file come from study of alarm call raw data sheets. Filename: Fig 8.14, Top, Closest vs farther for alarm callers, BTPDs, 21 Nov 2025
DOI: 10.17632/xw8jhkrjr2
title: Hyaluronidase for Microstomia in Fibrosing Skin Disease: Systematic Review and Case Series

description: Supplementary Material of Manuscript: "Hyaluronidase for Microstomia in Fibrosing Skin Disease: Systematic Review and Case Series"
DOI: 10.17632/xw8jhkrjr2.1
title: Hyaluronidase for Microstomia in Fibrosing Skin Disease: Systematic Review and Case Series

description: Supplementary Material of Manuscript: "Hyaluronidase for Microstomia in Fibrosing Skin Disease: Systematic Review and Case Series"
DOI: 10.17632/yt96x47dc7
title: RoseLeafVision: A Comprehensive Multi-Class Image Dataset for Accurate Rose Leaf Disease Detection

description: Description
Rose plant species are among the most widely used flowering plants, establishing themselves in the marketplace due to their aesthetic appeal, fragrance, as well as importance in the economy. They are also vulnerable to several diseases that can easily infect the leaves of the plants, reducing their appeal in the marketplace. In this regard, the RoseLeafVision dataset has been established.

Dataset Content
This dataset was collected from Golap Gram, Savar, Bangladesh, in July to September, 2025, where there are a total of 2,458 raw images of rose leaves collected in natural lighting conditions, although some were collected in a white background for clarity. The dataset has been categorized into five groups:
1. Black Spot: 335
2. Downy Mildew: 316
3. Dry Leaf: 712
4. Healthy Leaf: 668
5. Insect Hole: 427

After Augmentation 
The data was then augmented to a total of 12,991 pictures using rotation, shearing, zoom, flipping, as well as brightness and contrast changes. These augmentation techniques were necessary to ensure equal representation of the five classes, as the models were trained. This was in a bid to counter biased models in the classification strategies. The next step, Augmented
1. Black Spot: 2567
2. Downy Mildew: 2564
3. Dry Leaf: 2641
4. Healthy Leaf: 2634
5. Insect Hole: 2585 

Geographical Location 
All rose leaf images were collected from Golap Gram, Savar, Dhaka, a well-known rose cultivation zone in Bangladesh that naturally provides diverse leaf conditions.
Location: Golap Gram, Savar, Dhaka
Latitude: 23°48'5.808''N
Longitude: 90°19'30.4908''E

Preprocessing Steps 
1. Otsu Thresholding: separates the leaf region from the background.
2. Morphological Operations: This skips the noise and smooths the segmented leaf area.
3. Brightness Adjustment: Enhances the overall look of leaf, making images much more visible to understand.
4. CLAHE: Enhances the local contrast, more visible edge, emphasizing the disease patterns.
5. Normalization: It involves scaling pixel values to be compatible with a selected model.

Augmentation Details 
1. Rotation (±30°): Random rotation helps to make the model robust against different angle of leaf orientations.
2. Shear Transformation (0.15): It ensure slight angular distortion, allowing the model to handle shape variations.
3. Zoom (±20%): Random zoom-in and zoom-out enhance scale invariance.
4. Horizontal Flip: Flips the image left to right to increase variety in the dataset and reduce directional bias.
5. Vertical Flip: top-to-bottom flipping of images in order to enhance model generalization.
6. Fill Mode Nearest: fills no-value pixels appearing due to transformation with the nearest pixel.

Use of the Dataset
1. Perform development and benchmarking of the AI models on automated rose leaf disease detection.
2. IoT-based plant monitoring system to improve smart agriculture solutions.
3. Support research in precision agriculture field.
