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  • Neighborhood Effects: Food Environment

    Work
    Creator: Data Driven Detroit, Gomez-Lopez, Iris N., Goodspeed, Robert, Okullo, Dolorence, Veinot, Tiffany C., and Yan, Xiang (Jacob)
    Description: The food environment is: 1) The physical presence of food that affects a person’s diet; 2) A person’s proximity to food store locations; 3) The distribution of food stores, food service, and any physical entity by which food may be obtained; or 4) A connected system that allows access to food. (Source: https://www.cdc.gov/healthyplaces/healthtopics/healthyfood/general.htm) Data included here concern: 1) Food access; and 2) Liquor access. Spatial Coverage for most data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area, Michigan, USA. See exception for grocery store data below.
  • Dataset for Understanding the benefit, risk and cost relationship for patients in the emergency department

    Work
    Creator: Meurer, William
    Description: Full analytical dataset with labels in SPSS
  • ENVIREM: ENVIronmental Rasters for Ecological Modeling version 1.0

    Work
    Creator: Jordan B. Bemmels and Pascal O. Title
    Description: The ENVIREM dataset v1.0 is a set of 16 climatic and 2 topographic variables that can be used in modeling species' distributions. The strengths of this dataset include their close ties to ecological processes, and their availability at a global scale, at several spatial resolutions, and for several time periods. The underlying temperature and precipitation data that went into their construction comes from the WorldClim dataset (www.worldclim.org), and the solar radiation data comes from the Consortium for Spatial Information (www.cgiar-csi.org). The data are compatible with and expand the set of variables from WorldClim v1.4 (www.worldclim.org). For more information, please visit the project website: envirem.github.io
  • Data and code files for Bing and Wittkopp MBE submission 11/22/16

    Work
    Creator: Yang, Bing and Wittkopp, Patricia J
    Description: Datafiles and code described in accompanying MS, currently in review
  • Effects of Age-Associated Regional Changes in Aortic Stiffness on Human Hemodynamics Revealed by Computational Modeling

    Work
    Creator: Figueroa, C. Alberto
    Description: Magnetic resonance angiography (MRA) of the aorta of a 30 yo healthy volunteer, segmented and discretized using the software CRIMSON (www.crimson.software). Additionally, models corresponding to virtually-aged aortic geometries at ages: 40, 60, and 75.
  • Michigan Indoor Corridor Dataset

    Work
    Creator: Tsai, Grace and Kuipers, Benjamin
    Description: ******Michigan Indoor Corridor 2012 Dataset****** This dataset is made available for research purpose only. Please contact Grace Tsai(gstsai@umich.edu) for any questions or comments. This dataset was used to produce the results in our IROS 2012 paper. If you use the data, please cite the following reference in your publications related to this work: Grace Tsai and Benjamin Kuipers Dynamic Visual Understanding of the Local Environment for an Indoor Navigating Robot International Conference on Intelligent Robots and Systems (IROS'12) October 2012 The dataset contains 4 video sequences acquired with camera mounted on a wheeled vehicle. The camera was set-up so that there was zero tilt and roll angle with respect to the ground. The camera has a fixed height (0.47 m) with the ground throughout the video. The intrinsic parameters of the cameras are: Focal length fc = [ 1389.182714 1394.598277 ] Principal point cc = [ 672.605430 387.235803 ] The distortion of the camera has been corrected. For each video sequences, an estimated camera pose in each frame of the video is provided in the file pose.txt. Each line in the file looks like: <frame index> <x (pose)> <y (pose)> <theta (pose)> Note the camera poses provided here are estimated by using an occupancy grid mapping algorithm with a laser range finder to obtain the robot pose. The dataset provides a ground truth labeling for all the pixels every 10 frames for each video. The labels of each frame is stored as a 2D matrix in a .mat file. The filename of each .mat file corresponds to the image frame. The labels can be interpreted as followed: -2 -> ceiling plane -1 -> ground plane >0 -> walls The labels of the walls are illustrated in a .pdf figure. Note the figure is only a illustration graph, not an actual floor plan.
  • Pre-Hospital Midazolam for Treatment of Status Epilepticus Before and After the Rapid Anticonvulsant Medication Prior to Arrival Trial (RAMPART): A National Observational Cohort Study

    Work
    Creator: Shtull-Leber, Eytan
    Description: We present the SAS code used to conduct the data manipulation and analysis for our research on pre-hopsitla midazolam use before and after RAMPART.
  • Data Supplement: Self-Confirming Price-Prediction Strategies for Simultaneous One-Shot Auctions

    Work
    Creator: Wellman, Michael P.
    Description: For each game: - file in JSON format with raw payoff data - text file with game-theoretic analysis results
  • Neighborhood Effects : Community Characteristics and Health in Metropolitan Detroit

    Creator: Yan, Xiang (Jacob), Veinot, Tiffany C, Data Driven Detroit, Clarke, Phillipa J., Goodspeed, Robert, Gomez-Lopez, Iris N., and Okullo, Dolorence
    Description: This collection was produced as part of the project, “A ‘Big Data’ Approach to Understanding Neighborhood Effects in Chronic Illness Disparities.” The Investigators for the project are Tiffany Veinot, Veronica Berrocal, Phillipa Clarke, Robert Goodspeed, Daniel Romero, and VG Vinod Vydiswaran from the University of Michigan. The study took place from 2015-2016, with funding from the University of Michigan’s Social Sciences Annual Institute, MCubed, and the Sloan and Moore Foundations. Contact: Tiffany Veinot, MLS, PhD Office: 3443 North Quad Phone: 734/615-8281 Email: tveinot@umich.edu
  • Neighborhood Effects Active Living Resources

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    Creator: Data Driven Detroit, Reference USA, City of Detroit, Veinot, Tiffany C., and ESRI
    Description: Active living resources include spaces and organizations that facilitate physical activity, including 1) park land, 2) recreation areas (including parks, golf courses, amusement parks, beaches and other recreational landmarks); and 3) recreation centers (including gyms, dancing instruction, martial arts instruction, bowling centers, yoga instruction, sports clubs, fitness programs, golf course, pilates instruction, personal trainers, swimming pools, skating rinks, etc.) Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.