Hackathon part of effort to make Orlando the ‘Smartest City’

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Participants in the Orlando Smart Cities Hackathon take time out for a group photo.

By Dan Ellen

On August 26 and 27, programmers and software engineers convened in Orlando to push the boundaries of creativity, innovation, reality, and technology to build solutions and concepts that have the potential to make a difference in the Orlando community.

Called the Orlando Smart Cities Hackathon, the event aimed to support the city of Orlando in its efforts to become a smart city and also to demonstrate the city’s capabilities as it works to earn the title of “The Smartest City.” Orlando received two smart cities grant awards and is pursuing a variety of additional funding opportunities for smart cities initiatives that would help to enhance transportation citywide and beyond. In these pursuits, the city continues to move forward with building a data-driven infrastructure that will support safer, cleaner, and more efficient travel and an improved quality of life.  Continue reading

Data science education in traditional contexts: Reflections on a recent webinar

On August 28, Karl Schmitt, PhD, an assistant professor in the department of mathematics and statistics at Valparaiso University, attended the webinar Data Science Education in Traditional Contexts, hosted by the South Big Data Innovation Hub as part of its Keeping Data Science Broad: Bridging the Data Divide series. The webinar featured five speakers, including Schmitt, who is also the director of data sciences at Valparaiso. Each speaker talked about their own programs and experiences in data science education as well as some of the challenges involved in creating and implementing educational programs in a field that is still very new and in the process of being defined. Continue reading

Big data and public health: New scenes and a new state of mind

Bigdatahealthcare-3By Eun Kyong Shin

The 2017 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS 2017) was held in Washington, DC, in July, and prominent fields applying social computing techniques include public health and healthcare. In early modern epidemiology, data collection processes relied heavily on painstaking manual labor. Data on a large scale was hard to obtain and resulted from careful observation and intensive recording. Since the introduction of the internet and advances in digital communication, massive amounts of dynamic data have accumulated exponentially. Along with the digitization of medical practices and other social data collection process, the nature of scientific discovery has been fundamentally changed. Continue reading

Deep Learning to classify big data

By Sahar Tavakoli

Our brains do an expert job of classification; it happens when we recognize people from their faces, categorize an object that we see, or predict the future state of an event. Proportional to  the complexity of an input pattern, the classification can be easy (for example recognizing the difference between a cat and a dog) or difficult, such as predicting the probability of two people becoming friends in a social network. Continue reading

Visuals, storytelling help make sense of data

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Panelists discuss data visualization at a recent workshop sponsored by the South and West Big Data Hubs.

By Mark Schroeder

Throughout human history, stories have helped us make sense of sequences of events in our lives, infer cause and effect relationships, and share them with others. Just as our own memories are fallible and retelling stories can shape how we remember events, data can be fallible too. Its value is shaped by the process used to collect it and can be incomplete, incorrect, or biased in some fashion. How can we use data to gain true insights about the world and share them despite these challenges?

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Mobile Health Workshop sparks ideas for future research

by Wenbin Zhang

Wenbin ZhangAs a first-year PhD student in information systems, I have been working on mobile health (mHealth) related research since the start of my PhD program. The growth of mHealth has facilitated better and instantaneous health communication, which was not previously possible. The capabilities of mHealth platforms promise to enhance healthcare quality and assist people in achieving healthy lifestyles at reduced costs. Attending the mHealth workshop organized by the South Big Data Hub and the National Consortium for Data Science (NCDS), located at the Renaissance Computing Institute (RENCI) deepened my understanding of mHealth, simply by having the chance to listen to and participate in intense discussions with an interdisciplinary group of mHealth and technology experts. Continue reading

Developing Standards for Mobile Health

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Attendees at the mHealth conference discuss key issues, including mHealth standards, at a breakout session.

By Alex Cheng

I was honored to have the opportunity to attend the Mobile Health (mHealth) conference sponsored by the South Big Data Innovation Hub and the National Consortium for Data Science as a third-year graduate student in biomedical informatics at Vanderbilt University. My research focuses on using mHealth technology to improve the efficiency of outpatient clinic operations and the quality of care for patients.  Continue reading

Can wearable devices lead to better health outcomes?

Reflections on the South BD Hub mHealth Workshop

By Chenzhang Bao

mhealth-phone-e1498589419307.jpgIn recent years, mobile health (mHealth) has become one of the most popular health care movements for patients and providers. Consumers have embraced the use of mHealth applications in their daily lives through wearable devices, and use these apps to monitor their exercise routines, heartbeats, and sleep quality. The use of mHealth apps is critical for research into new mechanisms designed to improve the quality of patient engagement; a factor that has previously been hard to measure or even unobservable to providers. One important research question looks at the relationship between patients’ usage of mHealth devices, their engagement in their own health and the future health outcomes. Continue reading

Microsoft Research looks back at a year of successful collaboration with the Big Data Hubs

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Vani Mandava of Microsoft Research (far right), with leaders of the Big Data Hubs, from left to right: Fen Zhao, NSF program coordinator; Lea Shanley, South Hub; Melissa Cragin, Midwest Hub; Rene Baston, Northeast Hub; Meredith Lee, West Hub; and Renata Rawlings-Goss, South Hub.

Microsoft Research understands that taking full advantage of big data and new data technologies requires more than developing new tools and technologies. To paraphrase Vani Mandava, director of data science for the research arm of the tech giant, it requires cross-disciplinary research that extends well beyond computer science, and collaboration among domain science experts, computing and data science specialists, and industry leaders in technology and other verticals.

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Shifting the paradigm of care via mHealth

mHealth-3By Ashley C. Griffin

The South Big Data Innovation Hub and the National Consortium for Data Science (NCDS), in collaboration with the Institute for the Future and 10X Collective, held a workshop that brought together a diverse body of experts to identify and prioritize research challenges in data science and IoT cyberinfrastructure.

The workshop participants thoughtfully assessed a wide array of mobile health (mhealth) applications to address health disparities and their environmental influences within the research, legal, policy, environment, and clinical settings. Within the clinical setting, participants identified shifting the point of care to the patient using mHealth technologies as a key priority.  Continue reading