Analyzing and Improving Collaborative eScience with Social Networks (eSoN 12)
Workshop to be held with IEEE e-Science 2012
Monday, 8 October 2012, Chicago, IL, USA
Social networking is profoundly changing the way that people communicate and interact on a daily basis. As eScience is inherently collaborative, social networks can serve as a vital means for supporting information and resource sharing, aiding discovery of connected individuals, improving communication between globally dispersed individuals, and even measuring scientific impact. Consequently, eScience systems are increasingly integrating social networking concepts to improve collaboration. For example researcher profiles and groups exist in publication networks, such as Google scholar and Mendeley, and eScience infrastructures, such as MyExperiment, NanoHUB and GlobusOnline all utilize social networking principles to enhance scientific collaboration. In addition to incorporating explicit social networks, eScience infrastructures can also leverage implicit social networks extracted from relationships expressed in collaborative activities (e.g. publication and grant authorship or citation networks).
Here is another IEEE paper. This one is published in the 2010 IEEE Education Engineering (EDUCON) Conference.
“Knowledge management and professional profiles in electronic systems engineering: The function of university-industry collaboration” (Subscription required.)
This paper presents a work in progress related to the knowledge and competence management techniques applicable in an electronic systems engineering company. It also discusses the role of the university-industry collaboration in the knowledge management process.
Lining Shen wrote this IEEE Conference paper, “Study on Collaborative Information Seeking Behavior for Academic Information in Web2.0 Environment” for the 2010 2nd International Symposium on Information Engineering and Electronic Commerce. (Subscription required for online access.)
With the rapid development of Internet, there is a growing development of collaboration through the Internet. In this course, Collaboration for academic information seeking always takes place due to the complex and interdisciplinary of science research task. Based on this, the paper introduces the main features of academic information. Then it carries out the motivation analysis of collaborative information seeking for academic information in the Web2.0 environment. Meanwhile, the paper puts forward its aim and establishes the collaborative information seeking behavior model. This model includes four layers: demand analysis, search services, user interaction and outcome store and presentation.