Lawrence Berkeley National Laboratory
Multi-source data analysis challenges
- Author(s): Uselton, S
- Ahrens, J
- Bethel, W
- Treinish, L
- State, A
- et al.
Published Web Locationhttps://doi.org/10.1145/288216.288380
The factors making multi-source data analysis pervasive in the near future are: ease and cost effectiveness of digital data acquisition; fidelity, detail and practicality of computational simulations; and networks that make data from many sources accessible to a single user or application. Bringing data from multiple sources together is much more powerful than using each source separately, and computer systems can provide support for users in situations where they would be overwhelmed by volume or complexity without the support. However, multi-source data analysis still face challenges in the Accelerated Strategic Computing Initiative, geosciences, atmospheric sciences, medicine, and aerospace engineering design, and these challenges are presented.