Dataset

This dataset was created by Joost Luijben

Released under Apache 2.0

Contents

Context A Large dataset of Audio MNIST, 30000 audio samples of spoken digits (0-9) of 60 different speakers.

Content data (audioMNIST)

• The dataset consists of 30000 audio samples of spoken digits (0-9) of 60 folders and 500 files each and 500 noisy files with -8 SNR.
• There is one directory per speaker holding the audio recordings.
• Additionally "audioMNIST_meta.txt" provides meta information such as gender or age of each speaker. Acknowledgements Here's the original git repo for the project. Also here's the not noisy dataset. Inspiration A noisy audio dataset was missing.

About this dataset

Context

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

Content

The dataset constitues the following three datasets

• Kiawah Island, SC Age Group Population Dataset: A complete breakdown of Kiawah Island age demographics from 0 to 85 years, distributed across 18 age groups
• Kiawah Island, SC Age Cohorts Dataset: Children, Working Adults, and Seniors in Kiawah Island - Population and Percentage Analysis
• Kiawah Island, SC 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 Film dataset is a large collection of audio files with full metadata, including chords, instrumentation, key, tempo, and timestamps. This dataset is designed for machine learning applications and serves as a reliable resource for generative AI music, Music Information Retrieval (MIR), and source separation. With an emphasis on expanding machine learning attempts, the dataset allows researchers to delve into the complexities of film music, enabling the development of algorithms capable of generating creative compositions that genuinely represent the emotive nuances of various genres.

Film music, an essential component of cinematic storytelling, plays an important role in increasing spectator engagement and emotional resonance. Composers work collaboratively with filmmakers to create music that enhance visual aspects, set the tone, and reinforce story themes.

Training models on this cinema dataset allows researchers to better grasp and mimic these artistic details, extending the bounds of AI-generated music and contributing to advances in MIR and source separation.

Sokic Detection

## Overview

Sokic Detection is a dataset for computer vision tasks - it contains Sokic annotations for 259 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 [MIT license](https://creativecommons.org/licenses/MIT).

This dataset is about books. It has 1 row and is filtered where the author is Paul Rostand. It features 7 columns including author, publication date, language, and book publisher.

This dataset is about books. It has 1 row and is filtered where the book is Electronic commerce and business communications. It features 7 columns including author, publication date, language, and book publisher.

Generally speaking, the stakes are people, property, activities, cultural or environmental heritage elements, threatened by a hazard and likely to be affected or damaged by it. The sensitivity of an issue to a hazard is called “vulnerability”. This object class brings together all the issues that have been addressed in the RPP study. An issue is a dated object whose consideration depends on the purpose of the RPP and its vulnerability to the hazards studied. A PPR issue can therefore be considered (or not) depending on the type or types of hazard being addressed. These elements form the basis of knowledge of the land cover necessary for the development of the RPP, in or near the study area, at the time of the analysis of the issues. The data on issues represent a (figible and non-exhaustive) photograph of assets and individuals exposed to hazards at the time of the development of the risk prevention plan. This data is not updated after approval of the RPP. In practice they are no longer used: the issues are recalculated as necessary with up-to-date data sources.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national filewith no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent dataset, or they can be combined to cover the entire nation. The Area Hydrography Shapefile contains the geometry and attributes of both perennial and intermittent area hydrography features, including ponds, lakes, oceans, swamps (up to the U.S. nautical three-mile limit), glaciers, and the area covered by large rivers, streams, and/or canals that are represented as double-line drainage. Single-line drainage water features can be found in the Linear Hydrography Shapefile (LINEARWATER.shp). Linear water features includes single-line drainage water features and artificial path features, where they exist, that run through double-line drainage features such as rivers, streams, and/or canals, and serve as a linear representation of these features.

Time series data for the statistic Exports_Denmark_to_Dominica. Indicator Definition:Goods, Value of Exports, Free on board (FOB), US DollarsThe indicator "Goods, Value of Exports, Free on board (FOB), US Dollars" stands at 0.1013 Million as of 05/31/2025. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -52.50 percent compared to the value the year prior.The 1 year change in percent is -52.50.The 3 year change in percent is 446.06.The 5 year change in percent is 5,133.18.The 10 year change in percent is 708.80.The Serie's long term average value is 0.0579 Million. It's latest available value, on 05/31/2025, is 74.91 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 11/30/2021, to it's latest available value, on 05/31/2025, is +18,311.27%.The Serie's change in percent from it's maximum value, on 04/30/2009, to it's latest available value, on 05/31/2025, is -91.37%.

StreamGaze Dataset

StreamGaze is a comprehensive streaming video benchmark for evaluating MLLMs on gaze-based QA tasks across past, present, and future contexts.

  📁 Dataset Structure

streamgaze/ ├── metadata/ │ ├── egtea.csv # EGTEA fixation metadata │ ├── egoexolearn.csv # EgoExoLearn fixation metadata │ └── holoassist.csv # HoloAssist fixation metadata │ ├── qa/ │ ├── past_gaze_sequence_matching.json │ ├──… See the full description on the dataset page: https://huggingface.co/datasets/danaleee/StreamGaze.

MyTiles2023

## Overview

MyTiles2023 is a dataset for object detection tasks - it contains Whitefly annotations for 1,088 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).

Time series data for the statistic Trade_Balance_Afghanistan_with_Belarus. Indicator Definition:Goods, Value of Trade Balance, US DollarsThe indicator "Goods, Value of Trade Balance, US Dollars" stands at -0.5316 Million as of 5/31/2025, the lowest value since 5/31/2024. Regarding the One-Year-Change of the series, the current value constitutes an decrease of -0.0208 Million compared to the value the year prior.The Serie's long term average value is -0.284 Million. It's latest available value, on 5/31/2025, is -0.247 Million lower, compared to it's long term average value.The Serie's change from it's minimum value, on 1/31/2021, to it's latest available value, on 5/31/2025, is +0.932 Million.The Serie's change from it's maximum value, on 1/31/1993, to it's latest available value, on 5/31/2025, is -0.7539 Million.

About this dataset

Context

The dataset tabulates the Nome median household income by race. The dataset can be utilized to understand the racial distribution of Nome income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Nome, AK median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Nome, AK (2021, in 2022 inflation-adjusted dollars)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Nome median household income by race. You can refer the same here

A shapefile of the extent of irrigated agricultural fields which includes an attribute table of the irrigated acreage for the period between January and December 2020 was compiled for Alachua, Baker, Bradford, Columbia, Dixie, Gilchrist, Hamilton, Jefferson, Lafayette, Levy, Madison, Suwannee, Taylor, and Union Counties, Florida. These counties are fully or partially within the Suwannee River Water Management District boundaries. Attributes for each polygon that represents a field include a general or specific crop type, irrigation system, and primary water source for irrigation.

Current-Deferred-Revenue Time Series for Ichia Technologies Inc. Ichia Technologies, Inc., together with its subsidiaries, manufactures, processes, and trades in components and materials for electronics, home appliances, electronical engineering, electrical equipment, communications, and computers in the United States, Europe, and Asia. The company offers conductive silicone elastomers, plastic keys, keyboard assemblies, input devices, and flexible printed circuit boards; rubber and plastic keypads; single sided, double sided, and multi-layer FPC boards; and plastic, silicon rubber, and plastic + silicon rubber modules. It is also involved in various investment businesses; import and export of domestic and foreign products; and agency, distribution, tender, and quotation business. Ichia Technologies, Inc. was founded in 1983 and is headquartered in Taoyuan City, Taiwan.

This is the offical huggingface repository for MMP-2K: A BENCHMARK MULTI-LABELED MACRO PHOTOGRAPHY IMAGE QUALITY ASSESSMENT DATABASE

  More information please refer to github

MMP-2k is a novel benchmark Image Quality Assessment (IQA) database for Macro Photography (MP) images. Each image within MMP-2k has a MOS and a quality report consisting of an overall quality description and distortion annotations.

  Files in MMP-2k

A metadata.csv file in which each image id… See the full description on the dataset page: https://huggingface.co/datasets/MMP-2k/MMP-2k.

The NASA Earth Exchange Global Daily Downscaled Projections CMIP6 (NEX-GDDP-CMIP6; https://doi.org/10.7917/OFSG3345) project provides high-resolution, daily climate projections derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The archive was developed by NASA Earth Exchange (NEX) by downscaling coarse-resolution CMIP6 global climate model (GCM) outputs using the daily Bias Correction/Spatial Disaggregation (BCSD) technique. It includes nine variables at a 0.25° × 0.25° (~25 km) spatial resolution, covering the historical period 1950–2014 and future projections from 2015–2100 under four Shared Socioeconomic Pathways (SSPs): SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. (Please note that variable and scenario availability are model-dependent.)

This set contains downscaled CMIP6 output derived from the MRI-ESM2-0 model, including the CMIP historical experiment and the ScenarioMIP SSP 1.2-6, 2.4-5, 3.7-0, and 5-8.5 experiments.

The MCD43D51 Version 6.1 Bidirectional Reflectance Distribution Function and Albedo (BRDF/Albedo) Black-Sky Albedo dataset is produced daily using 16 days of Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data at 30 arc second (1,000 meter (m)) resolution. Data are temporally weighted to the ninth day which is reflected in the Julian date in the file name. This Climate Modeling Grid (CMG) product covers the entire globe for use in climate simulation models. Due to the large file size, each MCD43D product contains just one data layer. MCD43D42 through MCD43D61 are the albedo products of the MCD43D BRDF/Albedo product suite. There are 10 black-sky albedo and 10 white-sky albedo layers representing MODIS bands 1 through 7 and the visible, near-infrared (NIR), and shortwave bands. The black-sky albedo (directional hemispherical reflectance) is defined as albedo in the absence of a diffuse component and is a function of solar zenith angle. White-sky albedo (bihemispherical reflectance) is defined as albedo in the absence of a direct component when the diffuse component is isotropic. Users are urged to use the band specific quality flags to isolate the highest quality full inversion results for their own science applications as described in the User Guide.MCD43D51 is the black-sky albedo for the MODIS shortwave broadband. Known Issues For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.Improvements/Changes from Previous Versions The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017.* A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).

This dataset contains water temperature, salinity, and others taken by CTD from NOAA Ship David Starr Jordan, NOAA Ship McArthur II, and others in the Northeast Pacific Ocean (limit-180) and TOGA Area - Pacific from 1996-07-22 to 2010-12-07. Data were collected using standard Sea-Bird SBE-9plus CTD, to 1000m or to 10m of bottom depth. Conductivity, temperature, pressure, and dissolved oxygen sensor calibrations were adjusted by Sea-Bird recommended procedures when possible. Details are in metadata documents. Each cast is represented by two text files: a header file (hdr) and data file (asc).