/tag/hipaa

  • Ivy Secure Environment

    Ivy is a secure computing environment for researchers consisting of virtual machines (Linux and Windows). Researchers can use Ivy to process and store sensitive data with the confidence that the environment is secure and meets HIPAA, FERPA, CUI or ITAR requirements.
    Facilities Statement - Are you submitting a grant proposal and need standard information about UVA research computing environments? Get it here. Overview Ivy consists of both virtual computing environments and secure storage. In order to obtain access to either system, users must
    Submit an account request, Complete the Information Security Awareness Training, and Ensure their personal computer meets all High Security VPN requirements.

  • ACCORD

    Welcome to ACCORD (Assuring Controls Compliance of Research Data), a web-based platform which allows researchers from public universities across the state of Virginia to analyze and store their sensitive data in a central location.
    ACCORD is appropriate for de-identified PII, FERPA, de-identified HIPAA, business confidential, and other types of de-identified sensitive data
    Thanks to funding provided by the National Science Foundation (Award #: 1919667), ACCORD is available at no cost to researchers in the state of Virginia.
    Partners Listed below are our partner universities for ACCORD:
    Get Started About Learn about ACCORD.

  • ACCORD Security

    Back to Overview
    ACCORD is appropriate for de-identified PII, FERPA, de-identified HIPAA, business confidential, and other types of de-identified sensitive data. ACCORD cannot be used to process highly-restricted data such as CUI, FISMA, iTAR, and PCI data.
    Authentication ACCORD does not have its own user identity store but instead relies upon authentication via your home institution’s single sign-on tool.
    Authorization All members of a project have equal access to the data storage for that project, without sudo or root privileges.
    Closed Environments ACCORD environments have no outbound connectivity to the Internet other than approved library and tool
    repositories (PyPi, CPAN, CRAN, etc.

  • ACCORD Community Meeting - August 5, 2022

    When: Aug 5, 2022 11:00AM-3:00PM, Eastern Time (US and Canada)
    UVA is proud to sponsor a community meeting to discuss ACCORD, how far we have come and where we are headed. The event is all virtual, and you may attend any or all of the topics.
    Access the Event: Register for the Event Zoom Link You are welcome to invite colleagues to attend the Community Meeting, especially researchers who are new to ACCORD.
    Agenda 11:00 – 11:10 Welcome to ACCORD 11:10 – 12:00 Technical Overview of ACCORD 12:00 – 12:15 Break 12:15 – 12:45 Demo of ACCORD 12:45 – 1:30 Brown bag lunch with users sharing their experience 1:30 – 1:50 Breakout Room Topic Discussions Session 1 1:50 – 1:55 Switch Breakout Rooms 1:55 – 2:15 Breakout Room Topic Discussions Session 2 2:15 – 2:30 Break 2:30 – 3:00 Peek into the Future of ACCORD The same topics will be covered in the two breakout sessions so that you may attend two of the topics.

  • Service Map

    .card-body{ padding:0.6rem; } .card { background-color: #fff; border-radius: 10px; border: none; position: relative; margin-bottom: 30px; box-shadow: 0 0.46875rem 2.1875rem rgba(90,97,105,0.1), 0 0.9375rem 1.40625rem rgba(90,97,105,0.1), 0 0.25rem 0.53125rem rgba(90,97,105,0.12), 0 0.125rem 0.1875rem rgba(90,97,105,0.1); } .l-bg-cherry { background: linear-gradient(to right, #493240, #f09) !important; color: #fff; } .l-bg-blue-dark { background: linear-gradient(to right, #373b44, #4286f4) !important; color: #fff; } .l-bg-green-dark { background: linear-gradient(to right, #0a504a, #38ef7d) !important; color: #fff; } .l-bg-orange-dark { background: linear-gradient(to right, #a86008, #ffba56) !important; color: #fff; } .card .card-statistic-3 .card-icon-large .fas, .card .card-statistic-3 .card-icon-large .far, .card .card-statistic-3 .card-icon-large .fab, .card .card-statistic-3 .card-icon-large .fal { font-size: 110px; } .card .card-statistic-3 .
  • Secure Computing for Surgical Research

    RC is working with Dr. Eric Schneider to create a secure computing environment for the research of the Healthcare Surgical Outcome team. Data from this project will contain HIPAA identifiers, as well as Medicare information, and requires more security and control of data ingress/egress than projects previously hosted on the Ivy platform. After successful implementation of this project, RC will create a similar computing environment for DoD blast and traumatic brain injury data collected by Dr. Schneider before he joined UVA.
    PI: Eric Schneider (Department of Surgery)

  • Image Processing Software on Ivy Linux VM

    Pre-approved packages The following software packages are pre-approved for image processing on an Ivy Linux VM
    KNIME KNIME is open source analytics platform for data mining and pipelining.
    KNIME’s Image Processing Plugin allows users to perform common image processing
    techniques such as registration, segmentation, and feature extraction. KNIME is compatible with over 120 image file types and can be
    used alongside ImageJ.
    ImageJ ImageJ is a Java-based image processing program developed at the NIH.
    ImageJ can be used interactively through a graphical user interface or automatically with Java.
    OpenCV OpenCV is an open source library for computer vision applications.
    OpenCV includes modules for image processing, video analysis, machine learning, and much more.

  • Image Processing Software on Ivy Windows VM

    Pre-approved packages The following software packages are pre-approved for image processing on an Ivy Windows VM
    Axiovision Axiovision is software for microscopy image processing and analysis.
    Axiovision is highly configurableto meet the needs of your individual workflows.
    KNIME KNIME is open source analytics platform for data mining and pipelining.
    KNIME’s Image Processing Plugin allows users to perform common image
    processing techniques such as registration, segmentation, and feature extraction. KNIME is compatible with over 120 image file types and can be used alongside ImageJ.
    ImageJ ImageJ is a Java-based image processing program developed at the NIH.
    ImageJ can be used interactively through a graphical user interface or automatically with Java.

  • Computing Environments at UVA

    Research Computing (UVA-RC) serves as the principal center for computational resources and associated expertise at the University of Virginia (UVA). Each year UVA-RC provides services to over 433 active PIs that sponsor more than 2463 unique users from 14 different schools/organizations at the University, maintaining a breadth of systems to support the computational and data intensive research of UVA’s researchers. High Performance Computing  UVA-RC’s High Performance Computing (HPC) systems are designed with high speed networks, high performance storage, GPUs, and large amounts of memory in order to support modern compute and memory intensive programs. UVA-RC’s HPC systems are comprised of over 614 compute nodes, with a total of 20476 X86 64-bit compute cores and 240 TB total RAM.