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2018-12-19
Fovea-centered OCT images of adult healthy retina
Résultats de recherche
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2019-05-09
Data for 598 private landowners analyzed to investigate the effect of participation in two different conservation incentive programs on invasive species management. Presented in: Drescher, M., Epstein, G., Warriner, K. & Rooney, R. An Investigation of the Effects of Conservation Incentive Programs on Management of Invasive Species by Private Landowners. Conservation Science and Practice (accepted).
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2021-05-01
Wearable-sensor data with merged and separate freezing of gait episodes.
Walking trials with participants with Parkinson’s disease.
Contains inertial measurement unit (IMU) and plantar-pressure based features.
Suited for freeze detection and prediction in Parkinson’s disease.
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2021-01-26
This dataset is composed of several training and validation datasets used to develop the pedestrian bridge (PED), asphalt (ASH), and building wall (BW) scale estimators described in the paper, "Learning‐based image scale estimation using surface textures for quantitative visual inspection of regions‐of‐interest". The texture patch images are stored in indexed subfolders, where each subfolder contains patches corresponding to a distinct texture area. Each subfolders contain patches collected from different scenes of the structure-of-interest, and thus subfolders either minorly or do not share textures taken from the same location. The texture patches are 850X850 pixels and are taken at various standoff distances from the structure, ranging roughly from 0.2m-3m. Note that the images are taken parallel to the surface. A csv file contains the file names of the texture patches and their corresponding image scales.
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2021-04-12
Grounded: The Impact of the COVID-19 Pandemic on the People of the Canadian Air Travel Industry details the stories of the people whose lives have been turned upside down by the changes that have occurred in the world of aviation since March 2020. The project aimed to answer the research question of, "how has the COVID-19 pandemic impacted the lives of employees, passengers, and other people connected to the Canadian air travel industry?”
The files in this dataset contain the de-identified transcriptions of five interviews completed as part of this project. The interviews were completed between January and March of 2021 and discussed the preceding year.
The interviews formed the basis for a public webpage which is linked as the publication link below.
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2020-03-16
Tab. S3. (Supplementary Material). Physicochemical properties of peat samples collected for the microcosm experiment. DOC – dissolved organic carbon (mg g-1), EC – electrical conductivity (µS cm-1), WT – water table (cm); short chain fatty acid ions and inorganic ions (µg g-1 of dry peat). MP – potential rates of methane production; MO – potential rates of methane oxidation. Depth zones: A (0-10 cm below the WT), B (0-10 cm above the WT), C (10-20 cm below the WT).
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2013-01-27
N/A
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2013-03-05
N/A
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2022-01-28
Processed Community Earth System Model (CESM) output from an ensemble of experiments simulated for the study "On the Linearity of External Forcing Response in Solar Geoengineering Experiments." Currently in review at Geophysical Research Letters. Model output is in netCDF format and only consists of variables used for analysis in the study.
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2017-10-13
Maple worksheets and data for weak orders on 4 by 4 and 4 by 5 products.
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2020-05-23
This includes data used for generating figures in the article "Ultrastable monodisperse polymer glass formed by physical vapour deposition".
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2013-01-27
N/A
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2013-01-27
N/A
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2013-10
N/A
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2013-01-27
N/A
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2013-08
This survey monitors wellbeing among residents of the City of Kingston, Ontario who are without housing or are precariously housed. Drawing upon the CIW-Kingston, Frontenac, Lennox
& Addington Community Wellbeing Survey, and focusing on a vulnerable population group, the survey is a joint initiative of the Canadian Index of Wellbeing in partnership with the Community Foundation for Kingston & Area and KFL&A Public Health. Additional community partners who contributed to the development and administration of the survey include the Kingston Poverty Reduction Group, people with lived experience of poverty, the local shelter/hot meals program, and the City of Kingston. The su
rvey was administered at community shelters during a one week period of targeted implementation. Respondents were supported, as needed, to complete the survey by individuals with lived experience of poverty. These individuals had been provided with basic training on how to support survey completion. The primary objectives of this survey are to (a) gather data on the wellbeing of vulnerable or at risk residents which could be monitored over time; and, (b) to provide information on specific aspects of their wellbeing that could be used to inform policy issues and community action. The purpose of the survey is to better understand subjective perceptions of wellbeing of r
esidents in the City of Kingston who are without housing or precariously housed. The survey provides information based on eight domains of wellbeing, as identified by the Canadian Index of Wellbeing: Community Vitality, Democratic Engagement, Environment, Education, Healthy Populations, Leisure and Culture, Living Standards, and Time Use. The questionnaire collected additional information about dental health, emergency preparedness, and numerous socio-economic characteristics.
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2018-12-19
Fovea-centered OCT images of adult retina diagnosed with Macular Hole
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2013-03-05
N/A
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2020-11-16
<p><b>Data Owner</b>: Y. Aussat, S. Keshav</p>
<p><b>Data File</b>: 32.8 MB zip file containing the data files and description</p>
<p><b>Data Description</b>: This dataset contains daylight signals collected over approximately 200 days in four unoccupied offices in the Davis Center building at the University of Waterloo. Thus, these measure the available daylight in the room. Light levels were measured using custom-built light sensing modules based on the Omega Onion microcomputer with a light sensor. An example of the module is shown in the file sensing-module.png in this directory.</p>
<p>Each sensing module is named using four hex digits. We started all modules on August 30, 2018, which corresponds to minute 0 in the dataset. However, the modules were not deployed immediately. Below are the times when we started collecting the light data in each office and corresponding sensing module names.</p>
<p><b>Office number</b> <b>Devices</b> <b>Start time</b></p>
<p>DC3526 af65, b02d September 6, 2018, 11:00 am</p>
<p>DC2518 afa7 September 6, 2018, 11:00 am</p>
<p>DC2319 af67, f073 September 21, 2018, 11:00 am</p>
<p>DC3502 afa5, b969 September 21, 2018, 11:00 am</p>
<p>Moreover, due to some technical problems, the initial 6 days for offices 1 and 2 and initial 21 days for offices 3 and 4 are dummy data and should be ignored.</p>
<p>Finally, there were two known outages in DC during the data collection process: </p>
<ul>
<li>from 00:00 AM to 4:00 AM on September 17, 2018 </li>
<li>from 11:00pm on 10/9/2018 until 7:45am on October 10, 2018 </li>
</ul>
<p>We stopped collecting the data around 2:45 pm on May 16, 2019. Therefore, we have 217 uninterrupted days of clean collected data from October 11, 2018 to May 15, 2019. </p>
<p>To take care of these problems, we have provided a python script process-lighting-data.ipynb that extracts clean data from the raw data. Both raw and processed data are provided as described next.</p>
<p><b>Raw data</b>: Raw data folder names correspond to the device names. The light sensing modules log (minute_count, visible_light, IR_light) every minute to a file. Here, minute 0 corresponds to August 30, 2018. Every 1440 minutes (i.e., 1 day) we saved the current file, created a new one, and started writing to it. The filename format is {device_name}_{starting_minute}. For example Omega-AF65_28800.csv is data collected by Omega-AF65, starting at minute 28800. A metadata file can also be found in each folder with the details of the log file structure. </p>
<p><b>Processed data</b>: The folder named ‘processed_data’ contains the processed data, which results from running the python script. Each file in this directory is named after the device ID, for example af65.csv stores the processed data of the device Omega-AF65. The columns in this file are: </p>
<ul>
<li><b>Minutes</b>: Consecutive minute of the experiment </li>
<li><b>Illum</b>: Illumination level (lux)</li>
<li><b>Min_from_midnight</b>: Minutes from midnight of the current day</li>
<li><b>Day_of_exp</b>: Count of the day number starting from October 11, 2018</li>
<li><b>Day_of_year</b>: Day of the year</li>
</ul>
<p><b>Funding</b>: The Natural Sciences and Engineering Research Council of Canada (NSERC) </p>
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2021-04-29
This data is the simulated crushing performance of 9568 different aluminum crush rails, with different shapes, under axial and 20-degree oblique dynamic impact loading.
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