PSU researchers awarded $1 million federal grant to develop ‘open knowledge network’
A $1 million grant from the National Science Foundation will help Portland State provide better information to agencies that manage wildfires, water quality and biodiversity conservation.
The grant will pay to conduct user needs assessments and develop prototype technologies to support an “open knowledge network,” which builds the framework behind search engines and online platforms. Companies like Google, Apple and Amazon use these systems to provide search results that are more tailored to the search question. For example, the system can help identify the difference between the noun “building” and the verb “building” and provides additional related levels of information based on the search.
Sean Gordon, a research assistant professor with PSU’s Institute for Sustainable Solutions, will lead a team of 13 researchers and practitioners from 10 different institutions and organizations collectively focused on spatial decision support systems.
Spatial decision support systems combine computer mapping and algorithms to help people make decisions. Google Maps, for example, uses these systems to build the most efficient routes from one place to another.
“The proliferation of online mapping technologies has greatly increased access to and utility of these kinds of tools, and a logical next step is increasing our ability to find the appropriate data and tools for your problem and link these together for more complex analyses,” Gordon said.
The team will focus on three applied case studies — management of wildland fire, water quality and biodiversity conservation — and develop automated methods to collect and share relevant information.
With wildfires, for example, the utilities may need to shut off electricity in a localized area, as seen recently in California as PG&E turned off power for more than 2 million residents in an attempt to minimize fire damage.
Utilities have to make decisions that consider a medley of factors, including the location of customers, transmission lines, and fire risks based on the impact of bad weather and what the local landscape looks like.
“The idea is to make this information better related and easier for people to navigate when they have these kinds of complicated questions or complicated tasks that they have to carry out,” Gordon said.
After the first phase of the project, researchers intend to submit a proposal for up to $5 million in additional NSF funding for fuller implementation of the prototypes developed in phase 1.