The 2018 International Conference on Biological Ontologies (a special focus event in the annual ICBO series) aims to foster discussion, exchange, and innovation in research and development in the areas of biomedical ontology (including plants, agriculture, environment and biomes, as well as human health and disease). Researchers and professionals from all areas of biology, medicine, ecology, computer science, mathematics, text-mining, BIG-data analytics and related fields are invited to share their knowledge and experience. The theme of the joint meeting is "Ontologies for Health, Food, Nutrition and Environment: A partnership with BIG-Data and Analytics".
At the conference participants will present their work on applied aspects of ontologies and demonstrate innovative ontology-driven solutions for all areas of healthcare and life sciences including plant biology, agriculture, ecology, and the atmospheric and ocean sciences. We plan on inviting innovation development talks.
The biology, bioinformatics and medical areas have seen a deluge of data in recent times from digital record keeping, samples, methods, observations, imaging, sensors, genotyping, phylogenomics, phenotyping and -omics studies. More recently the improved understanding of the microbiome and of its associations with the environment and with other organisms has contributed greatly to this growth. While the generation of Big Data is already successfully driving scientific research, providing the needed metadata (data annotating the BIG data) is still a major challenge in the life sciences areas. For example, life scientists in all areas are mining BIG data either to make novel discoveries or to confirm existing results. However, our ability to draw the inferences needed for discovery depends on the quality of the reference and sample annotations (metadata descriptions) of data derived from assays of genotypes, molecular functions, phenotypes, pathotypes, environments, and treatments. Ontologies, a refined set of well-defined and structured controlled vocabularies, provide consistency and quality in metadata annotation. As the role of ontologies expands, Natural Language Processing (NLP) and data mining methods are being used increasingly for information extraction into the more structured and meaningful forms which ontologies allow.