A Web page today is the result of a number of interacting components—like cascading style sheets, XML code, ad hoc database queries, and JavaScript functions. For all but the most rudimentary sites, keeping track of how these different elements interact, refer to each other, and pass data back and forth can be a time-consuming chore. Ur/Web's ability to both provide security protection and coordinate disparate Web technologies stems from two properties it shares with most full-blown programming languages, like C++ or Java. One is that it is "strongly typed." That means that any new variable that a programmer defines in Ur/Web is constrained to a particular data type. Similarly, any specification of a new function has to include the type of data the function acts on and the type of data it returns.

The forests that surround Campos do Jordao are among the foggiest places on Earth. With a canopy shrouded in mist much of time, these are the renowned cloud forests of the Brazilian state of São Paulo. It is here that researchers from the São Paulo Research Foundation—better known by its Portuguese acronym, FAPESP—have partnered with Rafael Olivier, professor of ecology at the University of Campinas, in an ambitious effort to understand the climate and ecology of these spectacular woodlands. Their aptly named Cloud Forest Project has both conservation and practical goals, as it seeks to understand how to protect one of Brazil's largest forested areas while learning to manage access to water and other natural resources more effectively.

Halloween 2013 brought real terror to an Austin, Texas, neighborhood, when a flash flood killed four residents and damaged roughly 1,200 homes. Following torrential rains, Onion Creek swept over its banks and inundated the surrounding community. At its peak, the rampaging water flowed at twice the force of Niagara Falls.Recognizing their shared interest in predicting and responding to floods, the two began collaborating on a system to bring flood forecasts and warnings down to the local level. The need was obvious: flooding claims more lives and costs more federal government money than any other category of natural disasters. A system that can predict local floods could help flood-prone communities prepare for and maybe even prevent catastrophic events like the Onion Creek deluge.