Raw dataset 1.Datasets data link (GSE6919/ GSE46602/GSE70768)： https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi

1. Datasets data link (TCGA-PRAD)： https://portal.gdc.cancer.gov/exploration?filters={"content":[{"content":{"field":"cases.primary_site","value":["pancreas"]},"op":"in"},{"content":

This file contains raw data for cameras and wearables of the ConfLab dataset.

./cameras

contains the overhead video recordings for 9 cameras (cam2-10) in MP4 files.

These cameras cover the whole interaction floor, with camera 2 capturing the

bottom of the scene layout, and camera 10 capturing top of the scene layout.

Note that cam5 ran out of battery before the other cameras and thus the recordings

are cut short. However, cam4 and 6 contain significant overlap with cam 5, to

reconstruct any information needed.

Note that the annotations are made and provided in 2 minute segments.

The annotated portions of the video include the last 3min38sec of x2xxx.MP4

video files, and the first 12 min of x3xxx.MP4 files for cameras (2,4,6,8,10),

with "x" being the placeholder character in the mp4 file names. If one wishes

to separate the video into 2 min segments as we did, the "video-splitting.sh"

script is provided.

./camera-calibration contains the camera instrinsic files obtained from

https://github.com/idiap/multicamera-calibration. Camera extrinsic parameters can

be calculated using the existing intrinsic parameters and the instructions in the

multicamera-calibration repo. The coordinates in the image are provided by the

crosses marked on the floor, which are visible in the video recordings.

The crosses are 1m apart (=100cm).

./wearables

subdirectory includes the IMU, proximity and audio data from each

participant at the Conflab event (48 in total). In the directory numbered

by participant ID, the following data are included:

1. raw audio file

2. proximity (bluetooth) pings (RSSI) file (raw and csv) and a visualization

3. Tri-axial accelerometer data (raw and csv) and a visualization

4. Tri-axial gyroscope data (raw and csv) and a visualization

5. Tri-axial magnetometer data (raw and csv) and a visualization

6. Game rotation vector (raw and csv), recorded in quaternions.

All files are timestamped.

The sampling frequencies are:

- audio: 1250 Hz

- rest: around 50Hz. However, the sample rate is not fixed

and instead the timestamps should be used.

For rotation, the game rotation vector's output frequency is limited by the

actual sampling frequency of the magnetometer. For more information, please refer to

https://invensense.tdk.com/wp-content/uploads/2016/06/DS-000189-ICM-20948-v1.3.pdf

Audio files in this folder are in raw binary form. The following can be used to convert

them to WAV files (1250Hz):

ffmpeg -f s16le -ar 1250 -ac 1 -i /path/to/audio/file

Synchronization of cameras and werables data

Raw videos contain timecode information which matches the timestamps of the data in

the "wearables" folder. The starting timecode of a video can be read as:

ffprobe -hide_banner -show_streams -i /path/to/video

./audio

./sync: contains wav files per each subject

./sync_files: auxiliary csv files used to sync the audio. Can be used to improve the synchronization.

The code used for syncing the audio can be found here:

https://github.com/TUDelft-SPC-Lab/conflab/tree/master/preprocessing/audio

cyclists

The MESSENGER GRS uncalibrated observations consist of science and instrument data collected by the GRS sensor.

This dataset is designed for training and evaluating object detection models focused on identifying various types of litter in real-world environments.

Dataset Overview:

Total Images: 1,499

Annotations: Each image is annotated with bounding boxes corresponding to different litter categories.

Classes: 59 distinct classes representing various waste items.

Dataset Split:

Training Set: 1,049 images (70%)

Validation Set: 299 images (20%)

Test Set: 151 images (10%)

Preprocessing:

Auto-Orient: Applied to ensure consistent image orientation.

Class Modification: 59 classes remapped; none dropped.

Augmentations: No augmentations were applied in this version.

This dataset is suitable for developing and testing object detection models aimed at recognizing and classifying litter in various settings, such as urban streets, parks, and natural environments. It can be instrumental in applications related to environmental monitoring, waste management, and sustainability initiatives.

Raw Dataset for the 1X World Model Sammpling Challenge. Download with: huggingface-cli download 1x-technologies/worldmodel_raw_data --repo-type dataset --local-dir data

  Train/Val v2.0

The training dataset is shareded into 100 independent shards. The definitions are as follows:

video_{shard}.mp4: Raw video with a resolution of 512x512. segment_idx_{shard}.bin - Maps each frame i to its corresponding segment index. You may want to use this to separate non-contiguous frames from… See the full description on the dataset page: https://huggingface.co/datasets/1x-technologies/world_model_raw_data.

This data set consists of raw data collected during the Titan radio occultation of Voyager 1 in November 1980 plus ancillary files that might be useful in analysis of those data. The raw data are sampled voltage outputs from receivers tuned to the Voyager carrier frequencies at both S-band and X-band during the occultations. The data have been reduced to give profiles of atmospheric temperature and pressure as a function of height above the surface on both the ingress and egress sides of Titan and to make a marginal detection of an ionosphere.

44 sheets of data, each sheet representing a table from the database that stores the information. The order of the sheets is based on the sequence of reporting forms for the Financial Transactions Report.

Component(raw)

## Overview

Component(raw) is a dataset for object detection tasks - it contains Component OMCZ annotations for 526 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).

Dataset Card for Dataset Name

This dataset card aims to be a base template for new datasets. It has been generated using this raw template.

  Dataset Details





  Dataset Description

Curated by: [More Information Needed] Funded by [optional]: [More Information Needed] Shared by [optional]: [More Information Needed] Language(s) (NLP): [More Information Needed] License: [More Information Needed]

  Dataset Sources [optional]

Repository: [More… See the full description on the dataset page: https://huggingface.co/datasets/OmThakur/Raw-Dave.

Basic raw materials 1:200 000 contains geoscientific data relating to basic raw material resources including clay, limesand, limestone, hard rock aggregate, sand and gravel. Show full description

The Cassini LGA Radio Science Titan Gravity Science Experiment (TIGR19) Raw Data Archive is a time-ordered collection of radio science raw data acquired on March 16, 2015, during the Cassini Extended Extended Mission.

This is the raw normalized RAW sensor signals captured using our PXI 4464 ADC system. This dataset contains audio data recorded from a reference microphone GRAS 46BE and alongside other air based and contact based sensors.

A complete list of live websites using the raw.githack.com technology, compiled through global website indexing conducted by WebTechSurvey.

Repository Description

This repository provides access to NeoVault, a structured data hub for postural, physiological, and medical data of neonates. NeoVault offers both a web interface and a Raw dataset for retrieving movement datasets collected from preterm infants.

• NeoVault Web Interface: https://conversational.ugr.es/neovault
• Raw Dataset Repository: https://github.com/bihut/neovault-database

The raw dataset includes positional data (x, y, z coordinates) and physiological parameters (heart rate, oxygen saturation) recorded from neonatal intensive care units (NICUs). These datasets are publicly available to support research in neonatal movement quantification and computational healthcare analysis.

For more details on data access, please refer to the NeoVault documentation.

The raw data files for generating the figures in the paper.

Plant invasions likely impact entire arthropod communities but most research focuses either on insect controls or select target plant species. In Western Montana, USA, vegetation and arthropod communities were compared between intermountain grassland habitats uninvaded by spotted knapweed (Centaurea stoebe) and habitats corresponding with increasing levels of invasion. Arthropods were sampled using a diverse array of sampling methods. Arthropod data were analyzed both at the community and trophic level. Native plant species richness and percent cover values were significantly different between uninvaded and invaded habitats, but no differences were observed in plant diversity and evenness. Invasion by C. stoebe did not reduce arthropod morphospecies diversity estimates. Overall arthropod abundance however and proportional abundance by trophic level were significantly influenced by extent of invasion. Arthropod detritivores, predators, and biological control herbivores were positively re...

Raw data derived from DELM, DBN, DNN, ELM prediction errors, which was used for comparison and selection of different algorithm, applied for Fig 8

Over the course of 24 hours, we collected raw (Photoplethysmography (PPG), Acceleration, and Gyro) and processed (steps, calories, sleep, HR, HRV, SPO2, Respiratory Rate, R-R) data samples. Biostrap approaches health insights from a data-driven perspective. Our clinical-grade hardware enables users to accurately track SpO2, HRV, RHR, and a variety of other biometrics with confidence.

This bundle contains raw data from the Alpha Particle X-ray Spectrometer on Mars Exploration Rover 1 (Opportunity).