Data-driven biology, typified by the Human Genome Project, has produced an enormous amount of experimental data, including data on genomes, transcriptomes, proteomes, interactomes, and phenomes. The next pursuit in genome science concentrates on elucidating relations among the data. Key to understanding these relations are bio-networks that incorporate information on protein-protein interactions, metabolic pathways, signal transduction pathways, and gene regulatory networks. Development of these bio-networks, however, requires biomedical knowledge of life phenomena in order to add biological interpretations. In this sense, data creation and knowledge creation play complementary roles in the development of genome science. As for knowledge creation, Ikujiro Nonaka proposed the importance of "ba", that is, a time and place in which people share knowledge and work together as a community. Grid computing offers great potential to extend the concept of "ba" to networks, especially in terms of deepening the understanding and use of bio-networks by means of sharing explicit knowledge represented by ontology, mathematical simulation models and bioinformatics workflows.