Microsoft Research Open Data Project lays down evolving standards for data access and reproducible research

Microsoft Research has announced that it will be adopting the Open Use of Data Agreement (O-UDA) data for several datasets that the company offers. 

The Open Use of Data Agreement (O-UDA) is intended to make it easier for individuals and organizations that want to share data to do so, with minimal requirements for users and no restrictions on use. The O-UDA is complemented by the Computational Use of Data Agreement (C-UDA), an agreement intended for situations where a specific data use scenario is desirable or required.

It is not appropriate for datasets that include any data that might include materials subject to privacy laws (such as the GDPR or HIPAA) or other unlicensed third-party materials. 

The O-UDA meets the open definition: it does not impose any restriction with respect to the use or modification of data other than ensuring that attribution and limitation of liability information is passed downstream. In the research context, this implies that users of the data need to cite the corresponding publication with which the data is associated. This aids in findability and reusability of data, an important tenet in the FAIR guiding principles for scientific data management and stewardship.

Microsoft recognizes that in certain cases, datasets useful for AI and research analysis may not be able to be fully “open” under the O-UDA. For example, they may contain third-party copyrighted materials, such as text snippets or images, from publicly available sources. 

The law permits their use for research, so following the principle that research data should be “as open as possible, as closed as necessary,” Microsoft developed the Computational Use of Data Agreement (C-UDA) to make data available for research while respecting other interests. The software giant will prefer the O-UDA where possible, but perceives the C-UDA as a useful tool for ensuring that researchers continue to have access to important and relevant datasets.

Microsoft researcher John Krumm and collaborators collected GPS data from 21 people who carried a GPS receiver in the Seattle area. Users who provided their data agreed to it being shared as long as certain geographic regions were deleted. 

This work covers key research on privacy preservation of GPS data as evidenced in the corresponding paper, “Exploring End User Preferences for Location Obfuscation, Location-Based Services, and the Value of Location,” which was accepted at the Twelfth ACM International Conference on Ubiquitous Computing (UbiComp 2010). The paper has been cited 147 times, including for research that builds upon this work to further the field of preservation of geo-privacy for location-based services providers.

Another example dataset is that of labeled hand images and video clips collected by researchers Eyal Krupka, Kfir Karmon, and others. The research addresses an important computer vision and machine learning problem that deals with developing a hand-gesture-based interface language. 

The data was recorded using depth cameras and has labels that cover joints and fingertips. The two datasets included are FingersData, which contains 3,500 labeled depth frames of various hand poses, and GestureClips, which contains 140 gesture clips (100 of these contain labeled hand gestures and 40 contain non-gesture activity). 

The research associated with this dataset is available in the paper “Toward Realistic Hands Gesture Interface: Keeping it Simple for Developers and Machines,” which was published in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems.

Finally, the FigureQA dataset generated by researchers Samira Ebrahimi Kahou, Adam Atkinson, Adam Trischler, Yoshua Bengio and collaborators, introduces a visual reasoning task for research that is specific to graphical plots and figures. 

Microsoft Research Open Data project was conceived from the start to reflect Microsoft Research’s commitment to fostering open science and research and to achieve this without compromising the ethics of collecting and sharing data. The company aims to make it easier for researchers to maintain provenance of data while having the ability to reference and build upon it.

QliqSOFT post-acute visit management app offers business-enhancing delivery-data for hospice and home healthcare agencies

QliqSOFT has launched on Monday VisitPath, its home health nurse distress notification-enabled mobile care-delivery app designed to provide hospice and post-acute business administration with data that improves business and patient outcomes. Additionally, Visit Path puts safety in the hands of the home health nurse. 

The Visit Path web-based administrator’s dashboard integrates with GPS-enabled smart devices to ensure patient care delivery is optimized, on time and recorded. This, along with the ability to manage unscheduled and after-hours visits, improves patient and home health nurse satisfaction, patient outcomes, billing accuracy and a digital record that prevents ensures government reimbursements are never penalized.

As a real-time, GPS-enabled care management delivery solution, Visit Path verifies where and when a hospice or home health field nurse is on duty, begins service for a client, when they complete service and when they are off duty. This verification of service is the basis for accurate, compliant billing. The administrator's dashboard is a window into ROI.

With a focus on home health, hospice, and other post-acute verticals, QliqSOFT is excited to share the news of Visit Path to coincide with the National Hospice and Palliative Care Organization’s (NHPCO) annual Interdisciplinary Conference.

“This app is a good solution for hospice and home healthcare agencies that want more insight into their care delivery data to reduce costs and improve their business outcomes," says QliqSOFT founder and CEO Krishna Kurapati. “Additionally, the distress notification provides safety and security for nurses while visiting homes and if they should run into trouble while in transit between visits.”

“We wanted to provide hospice and home healthcare agencies with a product that gives them real-time knowledge of completed patient visits activity to help them better manage their field staff,” Krishna added.