Please see the file readme.txt for information about the data Lithium-ion (Li-ion) batteries are the most popular energy storage technology in consumer electronics and electric vehicles and are increasingly applied in stationary storage systems. Yet, concerns about safety and reliability remain major obstacles, which must be addressed in order to improve the acceptance of this technology. The gradual degradation of Li-ion cells over time lies at the heart of this problem. Time, usage and environmental conditions lead to performance deterioration and cell failures, which, in rare cases, can be catastrophic due to fires or explosions. The physical and chemical mechanisms responsible for degradation are numerous, complex and interdependent. Our understanding of degradation and failure of Li-ion cells is still very limited and more limited yet are reliable and practical methods for the detection and prediction of these phenomena. This dataset contains the results of long term cycling of 8 lithium-ion cells in our lab in Oxford. The full details are given in the readme.txt file.

The Oxford-IIIT pet dataset is a 37 category pet image dataset with roughly 200 images for each class. The images have large variations in scale, pose and lighting. All images have an associated ground truth annotation of breed and species. Additionally, head bounding boxes are provided for the training split, allowing using this dataset for simple object detection tasks. In the test split, the bounding boxes are empty.

To use this dataset:

import tensorflow_datasets as tfds

ds = tfds.load('oxford_iiit_pet', split='train')
for ex in ds.take(4):
 print(ex)

See the guide for more informations on tensorflow_datasets.

Oxford

## Overview

Oxford is a dataset for object detection tasks - it contains Pets annotations for 3,601 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).

The ont-open-data registry provides reference sequencing data from Oxford Nanopore Technologies to support, 1) Exploration of the characteristics of nanopore sequence data. 2) Assessment and reproduction of performance benchmarks 3) Development of tools and methods. The data deposited showcases DNA sequences from a representative subset of sequencing chemistries. The datasets correspond to publicly-available reference samples (e.g. Genome In A Bottle reference cell lines). Raw data are provided with metadata and scripts to describe sample and data provenance.

Notice The Oxford Multimotion Dataset (OMD) may be temporarily unavailable for parts of 2025 while it is moved to a new hosting service. This website will be updated with new links once the data is available at its new location.

Oxford-IIIT Pet Dataset

Images from The Oxford-IIIT Pet Dataset. Only images and labels have been pushed, segmentation annotations were ignored.

Homepage: https://www.robots.ox.ac.uk/~vgg/data/pets/

License: Same as the original dataset.

Dataset Card for "oxford-flowers"

More Information needed

About this dataset

Context

The dataset tabulates the Oxford population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Oxford across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Oxford was 22,078, a 0.34% increase year-by-year from 2022. Previously, in 2022, Oxford population was 22,004, a decline of 0.33% compared to a population of 22,077 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Oxford increased by 2,874. In this period, the peak population was 22,091 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Oxford is shown in this column.
• Year on Year Change: This column displays the change in Oxford population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Oxford Population by Year. You can refer the same here

The Oxford-IIIT Pet Dataset

  Description

A 37 category pet dataset with roughly 200 images for each class. The images have a large variations in scale, pose and lighting. This instance of the dataset uses standard label ordering and includes the standard train/test splits. Trimaps and bbox are not included, but there is an image_id field that can be used to reference those annotations from official metadata. Website: https://www.robots.ox.ac.uk/~vgg/data/pets/… See the full description on the dataset page: https://huggingface.co/datasets/timm/oxford-iiit-pet.

256 Object Detection Oxford

## Overview

256 Object Detection Oxford is a dataset for object detection tasks - it contains Car Zfvy annotations for 1,795 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).

About this dataset

Context

The dataset tabulates the Oxford population by age. The dataset can be utilized to understand the age distribution and demographics of Oxford.

Content

The dataset constitues the following three datasets

• Oxford, IA Age Group Population Dataset: A complete breakdown of Oxford age demographics from 0 to 85 years, distributed across 18 age groups
• Oxford, IA Age Cohorts Dataset: Children, Working Adults, and Seniors in Oxford - Population and Percentage Analysis
• Oxford, IA Population Pyramid Dataset: Age Groups, Male and Female Population, and Total Population for Demographics Analysis

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

The Oxford Internet Survey, 2019 (OxIS 2019) is a representative survey of British internet use in 2019. Data were collected via in-home interviews with respondents. It includes both internet users and non-users. The dataset contains almost 700 variables measuring internet activities, attitudes and effects.

Further information about the OxIS, including publications, is available from the Oxford Internet Surveys webpages.

Users should note the data are only available in Stata format.

This study is Open Access. It is freely available to download and does not require UK Data Service registration.

About this dataset

Context

The dataset tabulates the Oxford population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Oxford. The dataset can be utilized to understand the population distribution of Oxford by age. For example, using this dataset, we can identify the largest age group in Oxford.

Key observations

The largest age group in Oxford, NC was for the group of age 60 to 64 years years with a population of 740 (8.32%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Oxford, NC was the 80 to 84 years years with a population of 201 (2.26%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Oxford is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Oxford total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Oxford Population by Age. You can refer the same here

The Oxford Buildings Dataset consists of 5062 images collected from Flickr by searching for particular Oxford landmarks. The collection has been manually annotated to generate a comprehensive ground truth for 11 different landmarks, each represented by 5 possible queries. This gives a set of 55 queries over which an object retrieval system can be evaluated.

https://www.robots.ox.ac.uk/%7Evgg/data/pets/pet_annotations.jpg" alt="Example Annotations">

About this Dataset

The Oxford Pets dataset (also known as the "dogs vs cats" dataset) is a collection of images and annotations labeling various breeds of dogs and cats. There are approximately 100 examples of each of the 37 breeds. This dataset contains the object detection portion of the original dataset with bounding boxes around the animals' heads.

Origin

This dataset was collected by the Visual Geometry Group (VGG) at the University of Oxford.

The Oxford Flowers 102 dataset is a consistent of 102 flower categories commonly occurring in the United Kingdom. Each class consists of between 40 and 258 images. The images have large scale, pose and light variations. In addition, there are categories that have large variations within the category and several very similar categories.

The dataset is divided into a training set, a validation set and a test set. The training set and validation set each consist of 10 images per class (totalling 1020 images each). The test set consists of the remaining 6149 images (minimum 20 per class).

Note: The dataset by default comes with a test size larger than the train size. For more info see this issue.

To use this dataset:

import tensorflow_datasets as tfds

ds = tfds.load('oxford_flowers102', split='train')
for ex in ds.take(4):
 print(ex)

See the guide for more informations on tensorflow_datasets.

https://storage.googleapis.com/tfds-data/visualization/fig/oxford_flowers102-2.1.1.png" alt="Visualization" width="500px">

This dataset provides information about the number of properties, residents, and average property values for 30th Street cross streets in Oxford, KS.

Dataset

This dataset was created by Ashay Ajbani

Contents

Graph and download economic data for Unemployment Rate in Oxford County, ME (MEOXFO7URN) from Jan 1990 to Jun 2025 about Oxford County, ME; ME; unemployment; rate; and USA.

The Oxford dataset is a standard benchmark for evaluating local image descriptors, it features images under various conditions with keypoint matches.