Scope

DILS provides a forum for the discussion of challenges and technical solutions to address data integration and knowledge management in the life sciences. The advent of “Semantic Web” and “Big Data” in literally every domain within the area, coming from high-throughput analytical techniques, large clinical data repositories, biomedical literature and online resources, throw up exciting new opportunities accompanied with key challenges to be addressed.

Topics of interest include, but are not limited to:

• Life Science Data Modelling
• "Big Data" infrastructure
• Data integration systems
• Data models and standards
• Ontology and its evolution
• Architectures and data management techniques
• Analysing, Indexing, and Querying Life Sciences Datasets
• Linked Open Data
• Machine Learning
• Query formulation, processing and optimization
• Annotating, Matching, and Sharing Life Sciences Datasets
• Data annotation and maintenance
• Ontology and Schema Matching
• Privacy and Provenance of Life Sciences Datasets
• Ethical, legal and social issues
• Data owner sensitive data sharing
• Privacy-preserving data integration and management
• Sharing, updating and propagating data