
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.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
