Abstract

Increasingly, advances in biomedical research are the result of combining and analyzing heterogeneous data types from different sources, spanning genomic, proteomic, imaging, and clinical data. Yet despite the proliferation of data-driven methods, tools to support the integration and management of large collections of data for purposes of data driven discovery are scarce, leaving scientists with ad hoc and inefficient processes. The scientific process could benefit significantly from lightweight methods for data integration that allow for exploratory, incrementally refined integration of heterogeneous data. In this paper, we address this problem by introducing a new asset management based approach designed to support continuous integration of biomedical data. We describe the system and our experiences using it in the context of several scientific applications.

Date

November 3, 2025

Authors

Robert E Schuler, Carl Kesselman, Karl Czajkowski

Conference

Data Integration in the Life Sciences: 10th International Conference, DILS 2014, Lisbon, Portugal, July 17-18, 2014. Proceedings 10

Pages

1-15

Publisher

Springer International Publishing