📜 BRIDGE-Open Dataset The BRIDGE-Open dataset is an open-access subset of the datasets used by the BRIDGE benchmark. This dataset includes the 55 tasks of the open-access datasets that can be released to the public. Each dataset should be used in accordance with the license of its original release (the source of each dataset is listed at our BRIDGE paper, Supplementary Section 5.)

Due to privacy and security considerations of clinical data, regulated-access datasets can not… See the full description on the dataset page: https://huggingface.co/datasets/YLab-Open/BRIDGE-Open.

The Open Database of Healthcare Facilities (ODHF) is a collection of open data containing the names, types, and locations of health facilities across Canada. It is released under the Open Government License - Canada. The ODHF compiles open, publicly available, and directly-provided data on health facilities across Canada. Data sources include regional health authorities, provincial, territorial and municipal governments, and public health and professional healthcare bodies. This database aims to provide enhanced access to a harmonized listing of health facilities across Canada by making them available as open data. This database is a component of the Linkable Open Data Environment (LODE).

Pt204_C_n_461 Pt204_C_n_472 Pt204_C_n_474 Pt204_C_n_490 Pt204_C_n_518 Pt204_C_n_519 Pt204_C_n_529 Pt204_C_n_535 Pt204_C_n_546 Pt204_C_n_547 Pt204_C_n_557 Pt227_C_n_2175 Pt227_C_n_2178 Pt227_C_n_2194 Pt227_C_n_2200 Pt227_C_n_2208 Pt227_C_n_2209 Pt227_C_n_2213 Pt227_C_n_2215 Pt227_C_n_2217 Pt227_C_n_2218 Pt227_C_n_2219 Pt227_C_n_2239 Pt227_C_n_2262 Pt227_C_n_2326 Pt227_C_n_2333 Pt227_C_n_2338 Pt227_C_n_2339 input_2D input_3D Pt227_C_n_2340 Pt227_C_n_2364 Pt227_C_n_2369 Pt227_C_n_2370 Pt227_C_n_2372 Pt227_C_n_2373 Pt227_C_n_2374 Pt227_C_n_2375 Pt227_C_n_2376 Pt227_C_n_2377 Pt227_C_n_2378 Pt227_C_n_2408 Pt227_C_n_2409 Pt227_C_n_2410 Pt227_C_n_2411 input_2D input_3D Pt227_C_n_2413 Pt227_C_n_2414 Pt227_C_n_2459 Pt227_C_n_2473 Pt227_C_n_2479 Pt227_C_n_2480 Pt230_C_n_0 Pt230_C_n_10 Pt230_C_n_101 Pt230_C_n_11 Pt230_C_n_123 Pt230_C_n_145 Pt230_C_n_181 Pt230_C_n_19 Pt230_C_n_20 Pt230_C_n_220 Pt230_C_n_25 Pt230_C_n_252 Pt230_C_n_255 Pt230_C_n_258 Pt230_C_n_259 input_2D input_3D Pt230_C_n_280 Pt230_C_n_281 Pt230_C_n_284 Pt230_C_n_290 Pt230_C_n_293 Pt230_C_n_300 Pt230_C_n_301 Pt230_C_n_306 Pt230_C_n_307 Pt230_C_n_308 Pt230_C_n_37 Pt230_C_n_43 Pt230_C_n_78 Pt230_C_n_80 Pt253_PD_n_3447 Pt253_PD_n_3450 Pt253_PD_n_3452 Pt253_PD_n_3482

According to the World Health Organisation, the number of mental disorder patients, especially depression patients, has grown rapidly and become a leading contributor to the global burden of disease. However, the present common practice of depression diagnosis is based on interviews and clinical scales carried out by doctors, which is not only labour-consuming but also time-consuming. One important reason is due to the lack of physiological indicators for mental disorders. With the rising of tools such as data mining and artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. However, good quality physiological data for mental disorder patients are hard to acquire. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and audio data from clinically depressed patients and matching normal controls. All our patients were carefully diagnosed and selected by professional psychiatrists in hospitals. The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications. The 128-electrodes EEG signals of 53 subjects were recorded as both in resting state and under stimulation; the 3-electrode EEG signals of 55 subjects were recorded in resting state; the audio data of 52 subjects were recorded during interviewing, reading, and picture description. We encourage other researchers in the field to use it for testing their methods of mental-disorder analysis.

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yashraizada/yelp-open-dataset-checkin dataset hosted on Hugging Face and contributed by the HF Datasets community

This publication contains open dataset for the journal publication "Systematic Mapping Study on Requirements Engineering for Regulatory Compliance of Software Systems".

The dataset contains the data extracted from 280 selected primary studies.

The dataset includes the following data:

study metadata (title, venue, publication year, authors, authors’ affiliation, abstract);

challenges to regulatory compliance (direct excerpts from studies);

categories of challenges to compliance;

principles and practices (direct excerpts from text);

categories of principles and practices;

types of automation of principles and practices;

involved stakeholders (direct excerpts from studies);

categories of involved stakeholders;

phase of the principle and practice life cycle for which involvement of stakeholders was considered;

SDLC process areas covered by the study;

regulations considered in the study;

fields of regulations that were considered;

domains of application that were considered;

assessment of rigor and relevance of the study.

This dataset contains key characteristics about the data described in the Data Descriptor A structured open dataset of government interventions in response to COVID-19. Contents:

    1. human readable metadata summary table in CSV format


    2. machine readable metadata file in JSON format

Safe Open

## Overview

Safe Open is a dataset for object detection tasks - it contains Safe Open annotations for 644 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).

This dataset is a compilation of address point data for the City of Tempe. The dataset contains a point location, the official address (as defined by The Building Safety Division of Community Development) for all occupiable units and any other official addresses in the City. There are several additional attributes that may be populated for an address, but they may not be populated for every address. Contact: Lynn Flaaen-Hanna, Development Services Specialist Contact E-mail Link: Map that Lets You Explore and Export Address Data Data Source: The initial dataset was created by combining several datasets and then reviewing the information to remove duplicates and identify errors. This published dataset is the system of record for Tempe addresses going forward, with the address information being created and maintained by The Building Safety Division of Community Development.Data Source Type: ESRI ArcGIS Enterprise GeodatabasePreparation Method: N/APublish Frequency: WeeklyPublish Method: AutomaticData Dictionary

Open-Domain-Oral-Disease-QA-Dataset

  Dataset Details





  Dataset Description

This dataset is meticulously designed to evaluate the diagnostic capabilities of Large Language Models (LLMs) in the domain of oral disease. We currently offer a suite of evaluation datasets encompassing models such as GPT-3.5, GPT-4, Palm2, and Llama2-70B. More data is under reviewed. This dataset is meticulously designed to evaluate the diagnostic capabilities of Large Language Models… See the full description on the dataset page: https://huggingface.co/datasets/Lines/Open-Domain-Oral-Disease-QA-Dataset.

damien-johnston/open-data-project dataset hosted on Hugging Face and contributed by the HF Datasets community

Number and percentage of persons for mental health indicators, by age group and sex.

The California Health and Human Services Agency (CHHS) has launched its Open Data Portal initiative in order to increase public access to one of the State’s most valuable assets – non-confidential health and human services data. Its goals are to spark innovation, promote research and economic opportunities, engage public participation in government, increase transparency, and inform decision-making. "Open Data" describes data that are freely available, machine-readable, and formatted according to national technical standards to facilitate visibility and reuse of published data.

A simulated dataset of silicon pixel clusters produced by charged particles (pions), where the particle kinematics are taken from fitted tracks in CMS Run 2 data. The interaction of the charged particles with a 100 micron thick silicon pixel detector is simulated using a time-sliced version of PixelAV. The pixel detector is taken to be a 21x13 array of pixels with 50x12.5 micron pitch, situated 30mm from the particle's origin point. The detector is immersed in a 3.8T magnetic field parallel to the sensor x coordinate.

Positively and negatively charged particles are saved in the directories positive-charge and negative-charge, respectively. Truth properties of each particle are saved in the labels files, which include columns x-entry, y-entry, z-entry, n_x, n_y, n_z, number_eh_pairs, y-local, pt, cotAlpha, cotBeta, y-midplane, x-midplane. The particle impact point on the sensor surface is described by (x-entry, y-entry), and the impact point at the mid-plane of the sensor is (x-midplane, y-midplane). These impact points are in units of microns. The track direction is given by (n_x, n_y, n_z). The number of electron-hole pairs created in the silicon is number_eh_pairs. The y distance in mm between the center of the 21x13 pixel array and the center of a flat module is denoted by y-local (see included diagram). The particle transverse momentum ($p_T$) in GeV is stored in the pt variable, with the sign indicating the sign of the particle charge. The angle of incidence in the x-z plane is described by cotAlpha, and the angle of incidence in the y-z plane (the bending plane of the magnetic field) is described by cotBeta.

The deposited charge per pixel per time slice is saved in the recon files. Reshaping each line as (8,13,21) gives the three dimensional cluster in (time, y, x). Each slice in time corresponds to a window of 200 ps.

The combination of all files with index 16800+ yield a physical distribution. Files with lower indices are flattened at low $p_T$.

RS: People Practicing Open Defecation: Rural: % of Rural Population data was reported at 0.163 % in 2015. This records an increase from the previous number of 0.150 % for 2014. RS: People Practicing Open Defecation: Rural: % of Rural Population data is updated yearly, averaging 0.069 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 0.163 % in 2015 and a record low of 0.025 % in 2004. RS: People Practicing Open Defecation: Rural: % of Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Serbia – Table RS.World Bank: Health Statistics. People practicing open defecation refers to the percentage of the population defecating in the open, such as in fields, forest, bushes, open bodies of water, on beaches, in other open spaces or disposed of with solid waste.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).; Weighted Average;

The different data sets of point features related to food that we used for the different tasks in our user study. The data was extracted from the Yelp Open Dataset.

UAV Open Dataset Of Rice Paddies Detection

## Overview

UAV Open Dataset Of Rice Paddies Detection is a dataset for semantic segmentation tasks - it contains Stressed Rice Seedling annotations for 1,200 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 dataset from the Alpha SETup (ASET) for publication in preparation: 'New upper limits for beta-delayed fission probabilities of 230,232Fr and 230,232,234Ac'

Includes the data analysed for results given in the publication from the LOI216 experimental campaign at ISOLDE (CERN).

This resource shows all Open datasets available on Lincolnshire Open Data. All the Open datasets are listed with some brief key details about them (such as update schedule and licensing). Open datasets are available using the Search tools on the site. The datasets are also shown in themed Groups (see Groups link at the top of the webpage). Open datasets also have Tags (relevant words) that can be clicked to show datasets with that Tag. The Open Datasets register shows the latest information at the time of publication, and is updated monthly. For any enquiries please contact the Open Data team at opendata@lincolnshire.gov.uk .