The world already faces a glut of data, and the repository of online information constantly increases in size. Scientists who study the issue say that in the next 15 years, 1,000 times more information will exist in the digital world than the amount that exists today.
School of Information Studies (iSchool) Assistant Professor Daniel Acuna will be contributing to the newest thinking about that big data issue as an invited speaker at the inaugural symposium of the newly created Advanced Institute for Yotta Informatics. He’ll be traveling to Japan to speak at the 2019 meeting and present his work. The event takes place March 20 at Tohuku University in Sendai.
The symposium provides an interdisciplinary forum for researchers who examine the future of information and communication technologies and research platforms associated with Yotta-scale data science. Yotta scale is described as the largest decimal unit prefix in the metric system (to date), or a septillion. It’s written as a 1 followed by 24 zeroes.
Conference organizers aim to identify and develop new interdisciplinary academic fields that deal with both quantity and quality of information, establish a research platform for interdisciplinary science and technology, and identify new interdisciplinary academic fields that deal with both quantity and quality of information, among other goals. Attendees will be looking at the problem of extracting value and knowledge from enormous volumes of information, focusing on the disciplines of artificial intelligence, the Internet of Things, information security, and high-speed broadband communication technology.
Acuna says that his work in the field that he calls “the science of science” was interesting to conference organizers, and that scientists at the newly created institute want to understand systematic approaches to create new knowledge through funding incentives, collaboration and impact.
“New institutes that support knowledge creation usually aim for ‘transformative research,’ novel, high-risk research with the potential to revolutionize a field. One of my current projects asks the question of what is the right level of risk that would maximize future impact,” he adds.
Acuna’s research involves harnessing vast datasets about scientific activities and applying machine learning and artificial intelligence to uncover rules that make publication, collaboration, and funding decisions more successful.
He has created tools to improve literature search (eileen.io) and peer review (pr.scienceofscience.org). He has had a deep interest in understanding human decision-making and mimicking human semi-optimal strategies with algorithms. A long-term goal, he says, is to teach computers to learn from humans and enhance human decision-making through the use of machine learning and artificial intelligence.