Data Interlocking: Coupling analytics to the data
Yousef Kowsar, Harriet Dashnow, Andrew Lonie
2014 IEEE/ACM 7TH INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING (UCC) | IEEE | Published : 2014
'Big data' analytics can be defined by the requirement for flexible, high throughput computational analysis methods applied to large, heterogeneous datasets. We propose an architectural approach to 'big data' challenges in which the movement of data is minimized, and analysis methods are implemented on the data as portable services. We term this approach 'data interlocking'. We demonstrate the feasibility of this approach through a domain specific implementation of a data interlocking architecture, in which an on-demand computational workbench provides portable high-throughput analysis methods to large genomic datasets on cloud infrastructure.