The TargetMine Data Warehouse: Enhancement and Updates

Data Warehouse Maintenance under Concurrent Schema and Data Updates

Data warehouses (DW) are built by gathering information from several information sources and integrating it into one repository customized to users' needs. Recently proposed view maintenance algorithms tackle the problem of (concurrent) data updates happening at di erent autonomous ISs, whereas the EVE system addresses the maintenance of a data warehouse after schema changes of ISs. The concurr...

TargetMine, an Integrated Data Warehouse for Candidate Gene Prioritisation and Target Discovery

Prioritising candidate genes for further experimental characterisation is a non-trivial challenge in drug discovery and biomedical research in general. An integrated approach that combines results from multiple data types is best suited for optimal target selection. We developed TargetMine, a data warehouse for efficient target prioritisation. TargetMine utilises the InterMine framework, with n...

Detection and Correction of Conflicting Concurrent Data Warehouse Updates

Enhancement of a Data Warehouse Performance using Association Rules Technique

The data warehouse holds information management and turns it into meaningful management information, from which, very interesting patterns can be discovered by applying knowledge discovery process. As the update of the Data Warehouse is not too frequent, it is possible to improve query performance while storing the data retrieved by them in a cache. However, the most powerful systems have a sma...

Data warehouse enhancement: A semantic cube model approach

Many data warehouse systems have been developed recently, yet data warehouse practice is not sufficiently sophisticated for practical usage. Most data warehouse systems have some limitations in terms of flexibility, efficiency, and scalability. In particular, the sizes of these data warehouses are forever growing and becoming overloaded with data, a scenario that leads to difficulties in data m...