"Big data and the new phenomenon open data are closely related but they're not the same. Open data brings a perspective that can make big data more useful, more democratic, and less threatening. While big data is defined by size, open data is defined by its use. Big data is the term used to describe very large, complex, rapidly-changing datasets. But those judgments are subjective and dependent on technology: today's big data may not seem so big in a few years when data analysis and computing technology improve. Open data is accessible public data that people, companies, and organisations can use to launch new ventures, analyse patterns and trends, make data-driven decisions, and solve complex problems. All definitions of open data include two basic features: the data must be publicly available for anyone to use, and it must be licensed in a way that allows for its reuse. Open data should also be relatively easy to use, although there are gradations of "openness". And there's general agreement that open data should be available free of charge or at minimal cost."
Issues and developments related to IP, AI, and OM, examined in the IP and tech ethics graduate courses I teach at the University of Pittsburgh School of Computing and Information. My Bloomsbury book "Ethics, Information, and Technology", coming in Summer 2025, includes major chapters on IP, AI, OM, and other emerging technologies (IoT, drones, robots, autonomous vehicles, VR/AR). Kip Currier, PhD, JD
Thursday, April 17, 2014
Big data and open data: what's what and why does it matter?; Guardian, 4/15/14
Joel Gurin, Guardian; Big data and open data: what's what and why does it matter? :
Subscribe to:
Post Comments (Atom)
No comments:
Post a Comment