The drastic growth in data in the recent years, within the Agronomic sciences has brought the concept of knowledge management to the forefront. Some of the factors that contribute to this change include a) conducting high-throughput experiments have become affordable, the time spent in generating data through these experiments are minuscule when compared to its integration and analysis; b) publishing data over the web is fairly trivial and c) multiple databases exist for each type of data (i.e. ‘omics’ data) with a possible overlap or slight variation in its coverage [1, 2]. In most cases these sources remain autonomous and disconnected. Hence, efficiently managed data and the underlying knowledge in principle will make data analysis straightforward aiding in more efficient decision making. We are involved in developing methods to aid data integration and knowledge management within the domain of Agronomic sciences to improve information accessibility and interoperability. To this end, we address the challenge by pursuing several complementary research directions towards: distributed, heterogeneous data integration.
Goble, C. and Stevens, R. (2008) State of the nation in data integration for bioinformatics. Journal of Biomedical Informatics, 41(5), 687-693.
Antezana, E., et al. (2009) Biological knowledge management: the emerging role of the Semantic Web technologies.Brief. in Bioinformatics,10(4), 392-407.