Title :
Model-based Tagging: Promoting Access to Online Texts on Complex Systems for Interdisciplinary Learning
Author :
Vattam, Swaroop ; Goel, Ashok K.
Author_Institution :
Design & Intell. Lab., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
The task of biologically inspired design requires designers to access, understand, and apply knowledge of biological systems. One common source for obtaining this kind of knowledge is scholarly biology articles accessed from online libraries and bibliographic databases (e.g., Web of Science, Google Scholar). However, our studies show that such online information environments do not adequately support this kind of interdisciplinary research. Designers need more help with both accessing relevant biology articles and understanding the biological systems that are described in those articles. In this paper, we present Biologue, a social citation cataloging system that uses model-based tagging to address these challenges.
Keywords :
Internet; computer aided instruction; database management systems; social networking (online); Google Scholar; Web of Science; bibliographic databases; biological systems; biologically inspired design; biologue; complex systems; interdisciplinary learning; model-based tagging; online information environments; online libraries; online texts; scholarly biology articles; social citation cataloging system; Biological system modeling; Biological systems; Context; Context modeling; Information services; Tagging; Biologically inspired design; complex systems; digital libraries; functional models; interdisciplinary learning; interdisciplinary research; tagging;
Conference_Titel :
Advanced Learning Technologies (ICALT), 2011 11th IEEE International Conference on
Conference_Location :
Athens, GA
Print_ISBN :
978-1-61284-209-7
Electronic_ISBN :
2161-3761
DOI :
10.1109/ICALT.2011.118