Data science is hot. That’s good news for workers with data science skills. It also means organizations competing to hire data scientists need to understand how to recruit talent that will solve their data science challenges and contribute to creating a productive and diverse workforce. Continue reading
As organizational and societal decisions become more data-driven academic institutions, industry, and government officials continuously identify data literacy as an important skillset for individuals currently in and entering the workforce. Unfortunately, a dearth of qualified data literate employees exists producing a need for effective data science education and training for undergraduates. Continue reading
The South Hub continually identifies opportunities to expose students and professionals to data science. For example, the South Hub awarded five student’s registration fellowships through the SNAP-DS program, “Stimulating New Activities and Projects in Data Science,” to attend the Young CEOs Business Summit’s (YCBS) 2018 Annual Summit in Atlanta. The South Hub developed the SNAP-DS program to provide travel support, student stipends, or registration fellowships for students to attend data-related workshops, conferences, and projects, such as the Young CEO’s Business Summit, that expose students to data science and the ways data science can better societies and businesses. Continue reading
In November 2017, the National Science Foundation’s Big Data Innovation Hubs sponsored a workshop in Versailles, France to discuss the formation of public-private partnerships in big data research among institutions in the United States and the European Union. Organized in conjunction with the Big Data Value Association, the PICASSO Project, and Inria, the workshop was the first of its kind to bring together international big data experts representing government, industry, and academia. Continue reading
Earlier this year, the South Big Data Hub partnered with Microsoft Research to offer researchers in the South Hub region the opportunity to apply for cloud credits on Azure, the comprehensive cloud services platform offered through Microsoft. The opportunity was designed to provide cloud computing resources to support data-intensive research projects.
Each day countless devices—from monitors in hospitals to diagnostic tests to Fitbits—capture huge amounts of health data. That data could change how patients and doctors interact, how diseases are diagnosed and treated, and the amount of control individuals have over their health outcomes.
But there’s a catch, says Wendy Nilsen, PhD, program director of the Smart and Connected Health Initiative at the National Science Foundation.
The data is plentiful, Nilsen acknowledged. The challenge, she said, is how to make that data easier to use, how to standardize it so it can be analyzed, how to scale it, keep it safe, and how to account for external factors such as the environment or a person’s genome.
Nilsen discussed these challenges and how to address them in a roundtable discussion hosted by the South Big Data Hub on October 14. Nilsen’s talk, titled “Smart Health and Our Future” provides an overview of the challenges that must be addressed as well as the ultimate goal: A system where patients use data to take more control of their health and where healthcare practitioners can use data from multiple sources to improve diagnoses and health outcomes.
To view the presentation slides, click here.
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
By 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
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?
The American Association for Advancement of Science (AAAS) Science & Technology Policy Fellowship Big Data Affinity Group, in collaboration with the South Big Data Hub, West Big Data Hub, and The National Consortium for Data Science, are making this Friday’s data visualization and storytelling event available for virtual attendees. To learn more about the event, visit the website or read our earlier blog post announcing the event.
Data-Driven Storytelling: A Deep Dive into Visualization Techniques
July 14 | 9:00 AM – Noon ET | WebCast
Join the Webcast: http://bit.ly/datavizwebex
Event Number: 641 886 660 | Event password: dataviz