28 datasets found
  1. Number of U.S. pet owning households by species 2024

    • statista.com
    • itunite.ru
    • +1more
    Updated Jun 24, 2025
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    Statista (2025). Number of U.S. pet owning households by species 2024 [Dataset]. https://www.statista.com/statistics/198095/pets-in-the-united-states-by-type-in-2008/
    Explore at:
    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    An estimated ** million households in the United States owned at least one dog according to a 2024/25 pet owners survey, making them the most widely owned type of pet across the U.S. at this time. Cats and freshwater fish ranked in second and third places, with around ** million and ** million households owning such pets, respectively. Freshwater vs. salt water fish Freshwater fish spend most or all their lives in fresh water. Fresh water’s main difference to salt water is the level of salinity. Freshwater fish have a range of physiological adaptations to enable them to live in such conditions. As the statistic makes clear, Americans keep a large number of freshwater aquatic species at home as pets. American pet owners In 2023, around ** percent of all households in the United States owned a pet. This is a decrease from 2020, but still around a ** percent increase from 1988. It is no surprise that as more and more households own pets, pet industry expenditure has also witnessed steady growth. Expenditure reached over *** billion U.S. dollars in 2022, almost a sixfold increase from 1998. The majority of pet product sales are still made in brick-and-mortar stores, despite the rise and evolution of e-commerce in the United States.

  2. cats_vs_dogs

    • huggingface.co
    • tensorflow.org
    • +1more
    Updated May 23, 2024
    + more versions
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    Microsoft (2024). cats_vs_dogs [Dataset]. https://huggingface.co/datasets/microsoft/cats_vs_dogs
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 23, 2024
    Dataset authored and provided by
    Microsofthttp://microsoft.com/
    License

    https://choosealicense.com/licenses/unknown/https://choosealicense.com/licenses/unknown/

    Description

    Dataset Card for Cats Vs. Dogs

      Dataset Summary
    

    A large set of images of cats and dogs. There are 1738 corrupted images that are dropped. This dataset is part of a now-closed Kaggle competition and represents a subset of the so-called Asirra dataset. From the competition page:

    The Asirra data set Web services are often protected with a challenge that's supposed to be easy for people to solve, but difficult for computers. Such a challenge is often called a CAPTCHA… See the full description on the dataset page: https://huggingface.co/datasets/microsoft/cats_vs_dogs.

  3. d

    Data from: Human preferences for dogs and cats in China: the current...

    • search.dataone.org
    • datadryad.org
    Updated Dec 18, 2024
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    Zhang Xu; He Yuansi; Yang Shuai; Wang Daiping (2024). Human preferences for dogs and cats in China: the current situation and influencing factors of watching online videos and pet ownership [Dataset]. http://doi.org/10.5061/dryad.qfttdz0rr
    Explore at:
    Dataset updated
    Dec 18, 2024
    Dataset provided by
    Dryad Digital Repository
    Authors
    Zhang Xu; He Yuansi; Yang Shuai; Wang Daiping
    Description

    Dogs and cats have become the most important and successful pets through long-term domestication. People keep them for various reasons, such as their functional roles or for physical or psychological support. However, why humans are so attached to dogs and cats remains unclear. A comprehensive understanding of the current state of human preferences for dogs and cats and the potential influential factors behind it is required. Here, we investigate this question using two independent online datasets and anonymous questionnaires in China. We find that current human preferences for dog and cat videos are relatively higher than for most other interests, with video plays ranking among the top three out of fifteen interests. We also find genetic variations, gender, age, and economic development levels notably influence human preferences for dogs and cats. Specifically, dog and cat ownership are significantly associated with parents’ pet ownership of dogs and cats (Spearman’s rank correlation c..., , , # Human preferences for dogs and cats in China: the current situation and influencing factors of watching online videos and pet ownership

    https://doi.org/10.5061/dryad.qfttdz0rr

    This dataset contains three CSV data files, each corresponding to one of the three parts described in the study.

    Description of the data and file structure

    **“1, bilibili.csv†**: contains data extracted from the Bilibili website. Each row in the dataset represents yearly data for each popular channel. Missing data are indicated with NA.

    • ID:Â The serial number for each video, ranging from 1 to 167368.
    • year: The year the video was published on the website, from 2009 to 2021.
    • Videourl:Â The URL of the video.
    • plays:Â The total number of plays for the video.
    • likes: The total number of likes for the video.
    • sort: The ranking of the video in terms of play count among all popular videos in its channel for that year.
    • channelID: The I...
  4. Cats & Dogs

    • kaggle.com
    Updated May 7, 2025
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    Simon Weckert (2025). Cats & Dogs [Dataset]. https://www.kaggle.com/datasets/simonweckert/cats-and-dogs
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 7, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Simon Weckert
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    In this competition, you'll write an algorithm to classify whether images contain either a dog or a cat. This is easy for humans, dogs, and cats. Your computer will find it a bit more difficult.

    https://www.ethosvet.com/wp-content/uploads/cat-dog-625x375.png" alt="">

    The Asirra data set

    Web services are often protected with a challenge that's supposed to be easy for people to solve, but difficult for computers. Such a challenge is often called a CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) or HIP (Human Interactive Proof). HIPs are used for many purposes, such as to reduce email and blog spam and prevent brute-force attacks on web site passwords.

    Asirra (Animal Species Image Recognition for Restricting Access) is a HIP that works by asking users to identify photographs of cats and dogs. This task is difficult for computers, but studies have shown that people can accomplish it quickly and accurately. Many even think it's fun! Here is an example of the Asirra interface:

    Asirra is unique because of its partnership with Petfinder.com, the world's largest site devoted to finding homes for homeless pets. They've provided Microsoft Research with over three million images of cats and dogs, manually classified by people at thousands of animal shelters across the United States. Kaggle is fortunate to offer a subset of this data for fun and research. Image recognition attacks

    While random guessing is the easiest form of attack, various forms of image recognition can allow an attacker to make guesses that are better than random. There is enormous diversity in the photo database (a wide variety of backgrounds, angles, poses, lighting, etc.), making accurate automatic classification difficult. In an informal poll conducted many years ago, computer vision experts posited that a classifier with better than 60% accuracy would be difficult without a major advance in the state of the art. For reference, a 60% classifier improves the guessing probability of a 12-image HIP from 1/4096 to 1/459. State of the art

    The current literature suggests machine classifiers can score above 80% accuracy on this task [1]. Therfore, Asirra is no longer considered safe from attack. We have created this contest to benchmark the latest computer vision and deep learning approaches to this problem. Can you crack the CAPTCHA? Can you improve the state of the art? Can you create lasting peace between cats and dogs?

    Submission Format

    Your submission should have a header. For each image in the test set, predict a label for its id (1 = dog, 0 = cat):

    id,label 1,0 2,0 3,0 etc...

  5. 5-Day Data Challenge Sign-Up Survey Responses

    • kaggle.com
    Updated Dec 13, 2017
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    Rachael Tatman (2017). 5-Day Data Challenge Sign-Up Survey Responses [Dataset]. https://www.kaggle.com/rtatman/5day-data-challenge-signup-survey-responses/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 13, 2017
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Rachael Tatman
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context:

    This dataset contains survey responses to a survey that people could complete when they signed up for the 5-Day Data Challenge.

    On December 12, 2017 survey responses for the second 5-Day Data Challenge were added. For this version of the challenge, participants could sign up for either an intro version or a more in-depth regression challenge.

    Content:

    The optional survey included four multiple-choice questions:

    1. Have you ever taken a course in statistics?
    • Yep
    • Yes, but I've forgotten everything
    • Nope
    1. Do you have any previous experience with programming?
    • Nope
    • I have a little bit of experience
    • I have quite a bit of experience
    • I have a whole lot of experience
    1. What's your interest in data science?
    • Just curious
    • It will help me in my current job
    • I want to get a job where I use data science
    • Other
    1. Just for fun, do you prefer dogs or cat?
    • Dogs 🐶
    • Cats 🐱
    • Both 🐱🐶
    • Neither 🙅

    In order to protect privacy, the data has been shuffled (so there’s no temporal order to the responses) and a random 2% of the data has been removed (so even if you know that someone completed the survey, you cannot be sure that their responses are included in this dataset). In addition, all incomplete responses have been removed, and any text entered in the “other” free response field has been replaced with the text “other”.

    Acknowledgements:

    Thanks to everyone who completed the survey! :)

    Inspiration:

    • Is there a relationship between how much programming experience someone has and why they’re interested in data science?
    • Are more experienced programmers more likely to have taken statistics?
    • Do people tend to prefer dogs, cats, both or neither? Is there a relationship between what people prefer and why they’re interested in data science?
  6. R

    Cat&dog&people Dataset

    • universe.roboflow.com
    zip
    Updated Feb 12, 2023
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    tagasugi-shinsuge (2023). Cat&dog&people Dataset [Dataset]. https://universe.roboflow.com/tagasugi-shinsuge/cat-dog-people-dqyva/dataset/7
    Explore at:
    zipAvailable download formats
    Dataset updated
    Feb 12, 2023
    Dataset authored and provided by
    tagasugi-shinsuge
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Cats Bounding Boxes
    Description

    Cat&dog&people

    ## Overview
    
    Cat&dog&people is a dataset for object detection tasks - it contains Cats annotations for 612 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  7. R

    Cat Dog Spider Pumpkin Hooman Dataset

    • universe.roboflow.com
    zip
    Updated Jan 13, 2023
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    Peter Guhl (2023). Cat Dog Spider Pumpkin Hooman Dataset [Dataset]. https://universe.roboflow.com/peter-guhl-de1vy/cat-dog-spider-pumpkin-hooman/dataset/4
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jan 13, 2023
    Dataset authored and provided by
    Peter Guhl
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Pumpkins Bounding Boxes
    Description

    Started out as a pumpkin detector to test training YOLOv5. Now suffering from extensive feature creep and probably ending up as a cat/dog/spider/pumpkin/randomobjects-detector. Or as a desaster.

    The dataset does not fit https://docs.ultralytics.com/tutorials/training-tips-best-results/ well. There are no background images and the labeling is often only partial. Especially in the humans and pumpkin category where there are often lots of objects in one photo people apparently (and understandably) got bored and did not labe everything. And of course the images from the cat-category don't have the humans in it labeled since they come from a cat-identification model which ignored humans. It will need a lot of time to fixt that.

    Dataset used: - Cat and Dog Data: Cat / Dog Tutorial NVIDIA Jetson https://github.com/dusty-nv/jetson-inference/blob/master/docs/pytorch-cat-dog.md © 2016-2019 NVIDIA according to bottom of linked page - Spider Data: Kaggle Animal 10 image set https://www.kaggle.com/datasets/alessiocorrado99/animals10 Animal pictures of 10 different categories taken from google images Kaggle project licensed GPL 2 - Pumpkin Data: Kaggle "Vegetable Images" https://www.researchgate.net/publication/352846889_DCNN-Based_Vegetable_Image_Classification_Using_Transfer_Learning_A_Comparative_Study https://www.kaggle.com/datasets/misrakahmed/vegetable-image-dataset Kaggle project licensed CC BY-SA 4.0 - Some pumpkin images manually copied from google image search - https://universe.roboflow.com/chess-project/chess-sample-rzbmc Provided by a Roboflow user License: CC BY 4.0 - https://universe.roboflow.com/steve-pamer-cvmbg/pumpkins-gfjw5 Provided by a Roboflow user License: CC BY 4.0 - https://universe.roboflow.com/nbduy/pumpkin-ryavl Provided by a Roboflow user License: CC BY 4.0 - https://universe.roboflow.com/homeworktest-wbx8v/cat_test-1x0bl/dataset/2 - https://universe.roboflow.com/220616nishikura/catdetector - https://universe.roboflow.com/atoany/cats-s4d4i/dataset/2 - https://universe.roboflow.com/personal-vruc2/agricultured-ioth22 - https://universe.roboflow.com/sreyoshiworkspace-radu9/pet_detection - https://universe.roboflow.com/artyom-hystt/my-dogs-lcpqe - license: Public Domain url: https://universe.roboflow.com/dolazy7-gmail-com-3vj05/sweetpumpkin/dataset/2 - https://universe.roboflow.com/tristram-dacayan/social-distancing-g4pbu - https://universe.roboflow.com/fyp-3edkl/social-distancing-2ygx5 License MIT - Spiders: https://universe.roboflow.com/lucas-lins-souza/animals-train-yruka

    Currently I can't guarantee it's all correctly licenced. Checks are in progress. Inform me if you see one of your pictures and want it to be removed!

  8. d

    Quantifying prey return rates of domestic cats in the UK

    • search.dataone.org
    • data.niaid.nih.gov
    • +1more
    Updated May 3, 2025
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    Hannah Lockwood; Maren Huck (2025). Quantifying prey return rates of domestic cats in the UK [Dataset]. http://doi.org/10.5061/dryad.31zcrjdv9
    Explore at:
    Dataset updated
    May 3, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Hannah Lockwood; Maren Huck
    Description

    Non†native predators can cause great harm to natural ecosystems through competition for resources and by directly predating on native species. Domestic cats (Felis catus) predate on wild prey throughout the world and have been implicated in a number of species declines. However, in the UK, long†term, widespread research is lacking. The data provided here relate to prey returned home by pet cats in the UK over a total period of 3.5 years (ranging from one month to 3.5 years per cat). These data were collected by cat owners across the UK, noting details of the prey returned home by their cats monthly. Data were gathered upon registration regarding the age, sex, and body condition of participating cats, allowing for the analysis of the potential influence of such factors. While most cats returned 0–1 prey per month, a small minority (n = 3 cats) returned over 15 individuals monthly. It is important that true predation rates (in addition to the return rates found here) are further exp..., , , # Title of Dataset: Quantifying prey return rates of domestic cats in the UK

    [Access this dataset on Dryad](DOI: 10.5061/dryad.31zcrjdv9)

    Description of the data and file structure

    Data are presented in two files: 'Data1_prey' and 'Data2_cats'.

    Data1_prey. This file contains details of all prey returned home by the cats monitored (n=553) over a total period of 3.5 years. Cat_ID is a unique identifier for each cat and Prey_ID is as given by owners or as verified by researchers thanks to photographs provided. Taxonomic group is then given, along with whether prey were dead or alive (or not recorded), what happened to the prey which were returned alive (for example, released), and whether returned whole, part-eaten, or witnessed by owners to be eaten. Age and sex were not required, but some participants gave this information in the related 'notes' section of the data return form. As such, there are many 'NA' datapoints for age and sex fields.

    Data2_cats. This file contains data re...,

  9. R

    Swe Project 2 Dataset

    • universe.roboflow.com
    zip
    Updated Mar 26, 2025
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    SwE Project 2 (2025). Swe Project 2 Dataset [Dataset]. https://universe.roboflow.com/swe-project-2/swe-project-2/dataset/1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Mar 26, 2025
    Dataset authored and provided by
    SwE Project 2
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Dogs Cats Pikachus Drones People Bounding Boxes
    Description

    SwE Project 2

    ## Overview
    
    SwE Project 2 is a dataset for object detection tasks - it contains Dogs Cats Pikachus Drones People annotations for 2,971 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  10. Data from: Popular press portrayal of issues surrounding free-roaming...

    • figshare.com
    rtf
    Updated Sep 23, 2021
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    Elizabeth A. Gow; Joseph B. Burant; Alex O. Sutton; Nikole E. Freeman; Elora Grahame; Matthew Fuirst; Marjorie C. Sorensen; Samantha M. Knight; Hannah E. Clyde; Nathaniel J. Quarrell; Alana A. E. Wilcox; Roxan Chicalo; Stephen G. Van Drunen; David S. Shiffman (2021). Data from: Popular press portrayal of issues surrounding free-roaming domestic cats (Felis catus) [Dataset]. http://doi.org/10.6084/m9.figshare.16539942.v1
    Explore at:
    rtfAvailable download formats
    Dataset updated
    Sep 23, 2021
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Elizabeth A. Gow; Joseph B. Burant; Alex O. Sutton; Nikole E. Freeman; Elora Grahame; Matthew Fuirst; Marjorie C. Sorensen; Samantha M. Knight; Hannah E. Clyde; Nathaniel J. Quarrell; Alana A. E. Wilcox; Roxan Chicalo; Stephen G. Van Drunen; David S. Shiffman
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset is comprised of variables coded/extracted from popular press articles about domestic cats (Felis catus), which were evaluated as part of a media-content analysis. Our focus was understanding how a number of issues surrounding free-roaming (feral) cats are presented and discussed in the popular press, including: - The messengers who are quoted or referenced (e.g., cat advocates, veterinarians, naturalists, researchers) - The risks and threats to which feral cats are exposed (e.g., diseases, vehicles, predation)- The impacts feral cats have on the environment, native wildlife (e.g., via predation), and threats they pose to human health (e.g., via disease transmission)- The potential strategies and tools used to manage feral cat populations and their impacts (e.g., trap-neuter-release, bylaws, public education)We used the Lexis Nexus search engine to conduct a systemic search for English-language popular print media, including news articles and bulletins, opinion-editorials, and other public notices (e.g., classifieds) published between 1990 and 2018 (see Search Terms in READ_ME file and Methods: Search in the referenced article). Using a code book we developed (see Questions Coded From Articles in READ_ME), we evaluated each article based on whether they conveyed a variety of different messages. In total, the dataset is comprised of 796 articles, with the bulk (~95%) of articles from the United States and Canada. Most of the people interviewed ("messengers") were from non-governmental organizations, mainly from cat-welfare or cat-rights groups. Researchers, shelter organizations, veterinarians, and groups that differ on how to resolve issues surrounding free-roaming cats were rarely interviewed. Most articles focused on cat welfare issues and the management strategies of euthanasia or trap-neuter-release (TNR), whereas less than one-third of the articles acknowledged that cats have any impact on wildlife or the broader environment.See READ_ME file for a full list of variable definitions.

  11. C

    Young people and children's questionnaires to know about the help and...

    • dataverse.csuc.cat
    pdf, tsv, txt
    Updated Jul 26, 2023
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    Maria Carme Montserrat Boada; Maria Carme Montserrat Boada (2023). Young people and children's questionnaires to know about the help and support they have received during the COVID-19 pandemic [Dataset]. http://doi.org/10.34810/data722
    Explore at:
    tsv(36561), pdf(295823), tsv(350257), pdf(319909), txt(9386), pdf(248698), pdf(333728), pdf(283404), pdf(235217)Available download formats
    Dataset updated
    Jul 26, 2023
    Dataset provided by
    CORA.Repositori de Dades de Recerca
    Authors
    Maria Carme Montserrat Boada; Maria Carme Montserrat Boada
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    These questionnaires correspond to one of the methodological phases of the research project "Resilient children, youth and communities: identifying and analysing social and educational practices from a multidimensional and intersectional perspective to address the pandemic”. The purpose of quizzes is to know about the experiences or programs that were carried out in the town or city to help children and young people face the COVID pandemic, especially during the time of confinement, and also, if they participated in helping other people. The questionnaires had questions corresponding to the 5 dimensions of resilience analysis Community education derived from the theoretical framework of research. They are the instrument to analyse the intersectionality between groups and the cross-cutting nature of resilience. This dataset includes: (1) Youngsters and children questionnaires (26 and 27 questions). There are closed (dichotomous, multiple choice, Likert scale according to or frequency and a satisfaction scale of 11 points) and open questions recoded to enter them in the spss (RE). There are adapted versions of them in order to make them accessible, both versions can be found in this dataset in pdf format, all of them are in catalan and the questionnaires for elder than 18 can be found also in spanish. (2) The data frame in spss (statistic program) format, with the children's answers to the questionnaire (a total of 1216 answers) and the youngsters' answers to the questionnaire (a total of 115 answers).

  12. AI Face with Mask, without mask and non huma

    • kaggle.com
    Updated Nov 16, 2020
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    Md Hasibul Huq (2020). AI Face with Mask, without mask and non huma [Dataset]. https://www.kaggle.com/mdhasibulhuq/ai-face-with-mask-without-mask-and-non-huma/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 16, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Md Hasibul Huq
    Description

    Context

    The dataset we had to create for our academic project.

    Content

    Here we have Human and nonhuman data set. In the human dataset, it is again divided into 2 more categories. they are face with mask and face without mask.

    Acknowledgements

    Dataset collected from various sources. https://www.kaggle.com/ayushimishra2809/face-mask-detection?select=train.csv https://www.kaggle.com/moltean/fruits https://www.kaggle.com/aliasgartaksali/human-and-non-human https://www.kaggle.com/c/dogs-vs-cats

    Inspiration

  13. R

    Model 20 Dataset

    • universe.roboflow.com
    zip
    Updated Dec 7, 2022
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    HakunaMatata (2022). Model 20 Dataset [Dataset]. https://universe.roboflow.com/hakunamatata/model-20/dataset/1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Dec 7, 2022
    Dataset authored and provided by
    HakunaMatata
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Cat Squirrel People Bounding Boxes
    Description

    Model 20

    ## Overview
    
    Model 20 is a dataset for object detection tasks - it contains Cat Squirrel People annotations for 1,037 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  14. u

    Data from: SGS-LTER Long-Term Monitoring Project: Small Mammals on Trapping...

    • agdatacommons.nal.usda.gov
    • s.cnmilf.com
    • +4more
    bin
    Updated Feb 13, 2024
    + more versions
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    Paul Stapp (2024). SGS-LTER Long-Term Monitoring Project: Small Mammals on Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1994 -2006, ARS Study Number 118 [Dataset]. http://doi.org/10.6073/pasta/2e311b4e40fea38e573890f473807ba9
    Explore at:
    binAvailable download formats
    Dataset updated
    Feb 13, 2024
    Dataset provided by
    Colorado State University
    Authors
    Paul Stapp
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Nunn, Colorado, United States
    Description

    This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83452. Small mammals (rabbits, rodents) are integral components of semiarid ecosystems because of their roles as consumers of plants, seeds and arthropods, as soil disturbance agents, and as food for raptors, snakes and mammalian carnivores. Because of their vagility and intermediate trophic position, populations of small mammals may track changes in vegetation and the abiotic environment that may result from shifts in land-use and other anthropogenic disturbances. However, these populations are variable over space and time, and their response to environmental changes may not be immediately apparent given their behavioral flexibility and relatively long life-spans and generation times. Patterns in the distribution and abundance of small mammals thus may simultaneously reflect and affect the stability of the shortgrass-steppe ecosystem. Long-term studies of population and community dynamics therefore are needed to fully understand the role of small mammals in grassland ecosystems. In 1994, we implemented a sampling scheme to monitor long-term changes in relative abundance of small mammals in representative habitats of shortgrass steppe. We live-trapped nocturnal rodents twice each year (spring, late summer) on trapping webs in upland prairie (GRASS) and saltbush-dominated (SHRUB) habitats. Three 3.14-ha webs were established in each habitat. Each web had 124 Sherman traps, which were spaced 10-m apart on 12 100-m spokes, with 30 degrees between spokes. Four traps were set in the center of the web. Traps were set for four consecutive nights in each trapping session. Traps are baited with a mix of peanut butter and oats, set in the evening and checked (and closed) at dawn. We recorded sex, age and weight upon first capture of all individuals. In the early years of the study, individuals were batch-marked (Sharpie colored felt markers) to distinguish recaptures from new individuals, providing the minimum information necessary to use distance-sampling methods to estimate density. Most nocturnal species are now usually marked with aluminum ear tags, although we continue to mark very small (pocket mice) or small-eared (voles) species only with felt pens. For ear-tagged animals, we distinguish new captures (N) from individuals marked during previous sessions (old, O), versus those that are recaptured (R) on 2nd, 3rd or 4th nights of a trapping session. The location of one trapping web was changed from 13NE (1994-1997) to 13SW (1998- present) because of concerns about intensive cattle use in the pasture, as well as activity of CPER Site Manager’s cats. Resources in this dataset:Resource Title: Website Pointer to html file. File Name: Web Page, url: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sgs&identifier=137 Webpage with information and links to data files for download

  15. b

    People involved in accidents managed by the Police in the city of Barcelona

    • opendata-ajuntament.barcelona.cat
    • datos.gob.es
    • +1more
    Updated Nov 19, 2015
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    Gerència de Seguretat i Prevenció (2015). People involved in accidents managed by the Police in the city of Barcelona [Dataset]. https://opendata-ajuntament.barcelona.cat/data/dataset/accidents-persones-gu-bcn
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    Dataset updated
    Nov 19, 2015
    Authors
    Gerència de Seguretat i Prevenció
    Area covered
    Barcelona
    Description

    List of people who have been involved in an accident managed by the Police in the city of Barcelona have suffered some type of injury ( slightly wounded, serious injuries or death). It includes a description of the person ( driver, passenger or pedestrian), sex, age, vehicle associated person if the cause was pedestrian.

  16. Warrior Cats The Prophecy Begins, Name mentions

    • kaggle.com
    Updated Jul 23, 2021
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    Robert Zheng (2021). Warrior Cats The Prophecy Begins, Name mentions [Dataset]. https://www.kaggle.com/sirbobthemarvelous/warrior-cats-the-prophecy-begins-name-mentions/code
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 23, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Robert Zheng
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    So a while ago I wanted to check out if I can provably show off Riverclan's lack of presence in The Broken Code and it somehow spiralled into a data collecting frenzy.

    Content

    I've used the 6 books of The Prophecy Begins and individually searched up every character's name, And Tree, and recorded the amount of times their name comes up in each book.

    Acknowledgements

    I mean this was just me using Control-F to search a bunch of ebooks to collect data so I can safely say this was all me

    Inspiration

    Honestly this all probably wouldn't have happened if it weren't for my good friend Snow and the online creator Moonkitti, so props to them.

  17. R

    Argusnight Dataset

    • universe.roboflow.com
    zip
    Updated Jun 24, 2023
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    Argus (2023). Argusnight Dataset [Dataset]. https://universe.roboflow.com/argus/argusnight/dataset/1
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    zipAvailable download formats
    Dataset updated
    Jun 24, 2023
    Dataset authored and provided by
    Argus
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Cats People Skunks Bugs Bounding Boxes
    Description

    ArgusNight

    ## Overview
    
    ArgusNight is a dataset for object detection tasks - it contains Cats People Skunks Bugs annotations for 1,799 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  18. u

    Data from: Dataset from: Exaptation and vulnerability to introduced mammal...

    • portalinvestigacio.uib.cat
    • dataone.org
    • +2more
    Updated 2023
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    Capó, Miquel; Perez-Barrales, Rocio; Cursach, Joana; Garrido, Jaume; Baraza, Elena; Rita, Juan; Capó, Miquel; Perez-Barrales, Rocio; Cursach, Joana; Garrido, Jaume; Baraza, Elena; Rita, Juan (2023). Dataset from: Exaptation and vulnerability to introduced mammal herbivores on Balearic endemic flora [Dataset]. https://portalinvestigacio.uib.cat/documentos/668fc423b9e7c03b01bd4ce2
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    Dataset updated
    2023
    Authors
    Capó, Miquel; Perez-Barrales, Rocio; Cursach, Joana; Garrido, Jaume; Baraza, Elena; Rita, Juan; Capó, Miquel; Perez-Barrales, Rocio; Cursach, Joana; Garrido, Jaume; Baraza, Elena; Rita, Juan
    Area covered
    Balearic Islands
    Description

    Aim: How introduced mammal herbivores affect insular flora is still under study. Also, disentangling which particular traits, that plants might develop from exaptations, are functional to avoid herbivory remains mainly unknown. This study aims to assess if the flora of continental islands with historic native herbivores has exapted to the introduction of new mammal herbivores and to predict the potential vulnerability of endemic species from islands where mammal herbivores have not been introduced yet. Location: Balearic Islands Taxon: 96 Balearic endemic plant species Methods: We investigated whether the endemic flora on continental islands maintains functional traits that resist introduced mammal herbivores by analysing the chemical and morphological traits related to plant resistance of five individuals per species (n=480). Also, we measured plant-size variables to assess plant escape strategies. Overall, we combined these traits with the accessibility to goats. Predictive models were generated for species that inhabit islands where goats have not been introduced to assess their potential vulnerability. Results: Endemic species may defend against new herbivores (e.g., goats) if they contain highly toxic compounds (alkaloids, glycosides, coumarins), spinescent and urticating structures, or specific plant architecture (low plant size, high specific leaf area). If such traits are absent, the species may become extinct—unless they inhabit areas inaccessible to goats. On continental islands, some endemic species are expected to resist the introduction of herbivores, while others may be significantly affected. Main conclusions: Part of the endemic flora may have previously adapted to ancient herbivores on the islands. Even though the ancient connection with the mainland, these traits may allow the plants to resist the presence of introduced herbivores. However, non-exapted species could be threatened by the introduction of non-native ungulates.

  19. n

    Data from: On the use of genome-wide data to model and date the time of...

    • data.niaid.nih.gov
    • search.dataone.org
    • +1more
    zip
    Updated Jun 8, 2021
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    Jo Howard-McCombe; Daniel Ward; Andrew Kitchener; Dan Lawson; Helen Senn; Mark Beaumont (2021). On the use of genome-wide data to model and date the time of anthropogenic hybridisation: an example from the Scottish wildcat [Dataset]. http://doi.org/10.5061/dryad.z34tmpgdj
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    zipAvailable download formats
    Dataset updated
    Jun 8, 2021
    Dataset provided by
    Royal Zoological Society of Scotland
    National Museums Scotland
    University of Bristol
    Authors
    Jo Howard-McCombe; Daniel Ward; Andrew Kitchener; Dan Lawson; Helen Senn; Mark Beaumont
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Scotland
    Description

    While hybridisation has long been recognised as an important natural phenomenon in evolution, the conservation of taxa subject to introgressive hybridisation from domesticated forms is a subject of intense debate. Hybridisation of Scottish wildcats and domestic cats is a good example in this regard. We develop a modelling framework to determine the timescale of introgression using approximate Bayesian computation (ABC). Applying the model to ddRAD-seq data from 129 individuals, genotyped at 6,546 loci, we show that a population of wildcats genetically distant from domestic cats is still present in Scotland. These individuals are found almost exclusively within the captive breeding program. Most wild-living cats sampled were introgressed to some extent. The demographic model predicts high levels of gene-flow between domestic cats and Scottish wildcats (13% migrants per generation) over a short timeframe, the posterior mean for the onset of hybridisation (T1) was 3.3 generations (~10 years) before present. Though the model had limited power to detect signals of ancient admixture, we find evidence that significant recent hybridisation may have occurred subsequent to the founding of the captive breeding population (T2). The model consistently predicts T1 after T2, estimated here to be 19.3 generations (~60 years) ago, highlighting the importance of this population as a resource for conservation management. Additionally, we evaluate the effectiveness of current methods to classify hybrids. We show that an optimised 35 SNP panel is a better predictor of the ddRAD-based hybrid score in comparison with a morphological method.

    Methods This study represents a new bioinformatic analysis of the sequence reads produced by Senn et al. (2019) (Dryad, Dataset, https://doi.org/10.5061/dryad.1s04tj3), incorporating an additional 51 captive and two wild individuals, as well as the original 76 samples. Sequence reads were generated using the Illumina MiSeq Platform, as described in Senn et al. (2019). As per Senn et al. (2019) reads were demultiplexed by barcode and quality filtered using the STACKS v2.1 module, process_radtags. Demultiplexed reads were trimmed to 135bp and concatenated into a single read file per individual.

    Sequence reads were aligned using BWA to the Felis catus reference genome v9.0 (GCF_000181335.3). Mapped reads were processed using STACKS (Catchen et al., 2013). In STACKs a minimum of three reads were required to form a ‘stack’. We allowed multiple SNPs per read, the mean number of SNPs per read across the final dataset was 1.6. Variants were filtered using a minimum allele frequency of 0.05 and maximum proportion of heterozygous individuals of 0.7, treating the three sample sources (domestic, wild-living, and captive) as separate populations.

    PLINK v1.9 (Chang et al., 2015) and VCFtools v1.15 (Danecek et al., 2011) were used to filter data from STACKs. Specifically, this led to the removal of individuals with >30% missing data and stringent subsequent filtering of loci to remove all sites with missing data. Closely related individuals were identified using IBD estimates calculated by PLINK, corrected to account for admixture using the method described by Morrison (2013). Corrected IBD estimates were used as input for PRIMUS (Staples et al., 2014) which uses genetic data to reconstruct pedigrees up to third degree relatives. Individuals were then removed from the dataset to limit relatedness.

  20. Dataset related to: "Effectiveness of pulmonary rehabilitation in...

    • zenodo.org
    • data.niaid.nih.gov
    Updated Dec 13, 2022
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    Michele Vitacca; Michele Vitacca; Mara Paneroni; Mara Paneroni; Antonio Spanevello; Piero Ceriana; Bruno Balbi; Beatrice Salvi; Beatrice Salvi; Nicolino Ambrosino; Nicolino Ambrosino; Antonio Spanevello; Piero Ceriana; Bruno Balbi (2022). Dataset related to: "Effectiveness of pulmonary rehabilitation in individuals with Chronic Obstructive Pulmonary Disease according to inhaled therapy: The Maugeri study" [Dataset]. http://doi.org/10.5281/zenodo.7385401
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    Dataset updated
    Dec 13, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Michele Vitacca; Michele Vitacca; Mara Paneroni; Mara Paneroni; Antonio Spanevello; Piero Ceriana; Bruno Balbi; Beatrice Salvi; Beatrice Salvi; Nicolino Ambrosino; Nicolino Ambrosino; Antonio Spanevello; Piero Ceriana; Bruno Balbi
    Description

    We provide the raw data used for the following article:

    Vitacca M, Paneroni M, Spanevello A, Ceriana P, Balbi B, Salvi B, Ambrosino N. Effectiveness of pulmonary rehabilitation in individuals with Chronic Obstructive Pulmonary Disease according to inhaled therapy: The Maugeri study. Respir Med. 2022 Oct;202:106967. doi: 10.1016/j.rmed.2022.106967.

    ABSTRACT

    Background and aim: Real-life studies report discordant prescribing of inhaled triple therapy (TT) among individuals
    with COPD. Guidelines recommend pulmonary rehabilitation (PR) for persistent breathlessness and/or
    exercise limitation. This real-life study aimed to assess the effects of in-patient PR in individuals under TT as
    compared to other inhaled therapies (no TT).
    Methods: Multicentric, retrospective analysis of data from individuals admitted to in-hospital PR. Baseline
    characteristics were recorded and lung function was assessed. Outcome measures were: 6-min walking test
    (6MWT: primary outcome), Medical Research Council (MRC) scale for dyspnoea, and COPD assessment test
    (CAT).
    Results: Data of pre and post program 6MWT of 1139 individuals were available. Pulmonary rehabilitation
    resulted in significant improvement in 6MWT in both groups, however, the effect size (by 54.3 ± 69.7 vs 42.5 ±
    64.2 m, p = 0.004) and proportion of individuals reaching the minimal clinically important difference (MCID) of
    6MWT (64.2%, vs 54.3%, p = 0.001) were higher in TT group. Both groups significantly improved also the other
    outcome measures. The significant independent predictors of reaching the MCID of 6MWT were hospital provenience,
    TT use, and high eosinophils count.
    Conclusion: Pulmonary rehabilitation results in significant benefits in individuals with COPD irrespective of the
    use of TT. However, individuals under TT report larger benefits in exercise tolerance than those under no TT.

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Statista (2025). Number of U.S. pet owning households by species 2024 [Dataset]. https://www.statista.com/statistics/198095/pets-in-the-united-states-by-type-in-2008/
Organization logo

Number of U.S. pet owning households by species 2024

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17 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 24, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

An estimated ** million households in the United States owned at least one dog according to a 2024/25 pet owners survey, making them the most widely owned type of pet across the U.S. at this time. Cats and freshwater fish ranked in second and third places, with around ** million and ** million households owning such pets, respectively. Freshwater vs. salt water fish Freshwater fish spend most or all their lives in fresh water. Fresh water’s main difference to salt water is the level of salinity. Freshwater fish have a range of physiological adaptations to enable them to live in such conditions. As the statistic makes clear, Americans keep a large number of freshwater aquatic species at home as pets. American pet owners In 2023, around ** percent of all households in the United States owned a pet. This is a decrease from 2020, but still around a ** percent increase from 1988. It is no surprise that as more and more households own pets, pet industry expenditure has also witnessed steady growth. Expenditure reached over *** billion U.S. dollars in 2022, almost a sixfold increase from 1998. The majority of pet product sales are still made in brick-and-mortar stores, despite the rise and evolution of e-commerce in the United States.

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