On extending the knowledge sharing practices in scientific collaboration to the semantic web

The internet has greatly facilitated scientific collaborations to efficaciously share their analytic knowledge. The impending semantic web promises to dispense with some of the human effort by making the shared knowledge accessible to machines on a semantic basis; giving rise to the connotation of webifying artificial intelligence (AI) for doing reasoning of science, if unchecked, could turn into another pipe-dream. In practise, as exemplified in this paper, it requires considerable effort to put the shared knowledge in common. Therefore, we stress the need to adopt a realistic attitude when extending the knowledge sharing practices in scientific collaboration to the semantic web. Drawing ideas from previous studies in academic communities, supported by our analysis about knowledge sharing in the case study domain of Experimental High- Energy Physics (EHEP), and acknowledging the limitation of AI, we advocate pursuing a pragmatic approach that emphasises the sharing of the analytic knowledge of a domain which is employed in computation, not cognition. Further, we highlight that it is suffice to focus on the directively and paradigmatically shared knowledge in a scientific collaboration