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 15years, 1,000times more information will exist in the digital world than the amount that exists today.
Daniel Acuna
School of Information Studies (iSchool)Assistant Professor will be contributing to the newest thinking about that big data issueas an invited speaker attheinauguralsymposium of the newly created. He’ll be travelingto Japan to speak at the 2019meeting and presenthis work. Theevent takes place March 20 atTohukuUniversity in Sendai.
Thesymposiumprovides an interdisciplinary forum for researchers who examine the future of information and communication technologies and research platforms associated withYotta-scale data science.Yottascale is described as the largestdecimal unit prefix in the metric system(to date), or a septillion. It’s written as a 1 followedby 24 zeroes.
Conference organizersaim 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 thathis work in the field that he calls “the science of science” was interesting to conference organizers, and that scientists at the newly created institutewant to understand systematic approaches to create new knowledge through funding incentives, collaborationand impact.
“Newinstitutesthatsupportknowledgecreationusuallyaimfor‘transformative research,’novel,high-risk research withthepotential torevolutionize a field.One of my current projectsasks the question of what is the right level of riskthat wouldmaximize 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 () and peer review (). 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.
