Paper/Poster/Presentation Title
Keywords
semantic web, social media, networked learning, diffusion of innovations, technology adoption
Location
Session A6: Semantics, Metadata and Ontologies of Natural Systems
Start Date
19-6-2014 9:00 AM
End Date
19-6-2014 10:20 AM
Abstract
A key challenge in modeling of complex natural systems is identifying and integrating models and tools that are relevant, but were not developed for the targeted purpose. Modeling resources are proliferating, along with emerging technologies designed to enable discovery and integration of data and models. The goal of the Virtual Learning Commons (VLC) is to improve awareness and understanding of emerging methodologies and technologies, facilitate individual and group evaluation of these for innovative uses, and trace the impact of innovations across research communities. The VLC is funded by the U.S. National Science Foundation, and will be released in 2014. The VLC is a Web-based social bookmarking site with support for semantic analysis of content. It makes use of Web 2.0 (Social Web) and Web 3.0 (Semantic Web) approaches to enable discovery of potentially relevant model and tool innovations, and networked learning about their function. It is founded on well-developed models of technology adoption and diffusion of innovation. Expected outcomes from the VLC project are:
- Improved dissemination of emerging models and tools across disciplines and institutions using Semantic Web approaches;
- Better support for community learning using social and networked learning approaches; and
- New methods for capturing the provenance (trace) of innovations from creators, to interested researchers, to users, based on the new provenance standard PROV-O.
The VLC project is significant because across the globe, decision makers are calling for better translation of research products into impacts. The VLC provides a 21st century approach towards innovation, enabling better sharing and reuse of models and tools in a wider variety of research contexts.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Other Civil and Environmental Engineering Commons
The Virtual Learning Commons (VLC): Enabling Sharing and Innovation for Flexible, Responsive Solutions
Session A6: Semantics, Metadata and Ontologies of Natural Systems
A key challenge in modeling of complex natural systems is identifying and integrating models and tools that are relevant, but were not developed for the targeted purpose. Modeling resources are proliferating, along with emerging technologies designed to enable discovery and integration of data and models. The goal of the Virtual Learning Commons (VLC) is to improve awareness and understanding of emerging methodologies and technologies, facilitate individual and group evaluation of these for innovative uses, and trace the impact of innovations across research communities. The VLC is funded by the U.S. National Science Foundation, and will be released in 2014. The VLC is a Web-based social bookmarking site with support for semantic analysis of content. It makes use of Web 2.0 (Social Web) and Web 3.0 (Semantic Web) approaches to enable discovery of potentially relevant model and tool innovations, and networked learning about their function. It is founded on well-developed models of technology adoption and diffusion of innovation. Expected outcomes from the VLC project are:
- Improved dissemination of emerging models and tools across disciplines and institutions using Semantic Web approaches;
- Better support for community learning using social and networked learning approaches; and
- New methods for capturing the provenance (trace) of innovations from creators, to interested researchers, to users, based on the new provenance standard PROV-O.
The VLC project is significant because across the globe, decision makers are calling for better translation of research products into impacts. The VLC provides a 21st century approach towards innovation, enabling better sharing and reuse of models and tools in a wider variety of research contexts.
