Heterogeneous computing platforms constitute a challenging execution environment for distributed applications. This paper presents a ?systems? view of effective platform usage, by demonstrating the need for application software to be continuously ?aware? of the resources currently available on their underlying heterogeneous computing platforms. Our approach to the implementation of resource awareness is one that (1) provides a ?thin? middleware layer of resource aware services that permit applications to react to changes in resource availability and resources to be managed in accordance with application needs, and that (2) develops compiler- and application-level techniques for dynamic ?service morphing?, the goal being to make it easy for application-level services to adjust to runtime changes in application needs or in platform resources. The specific results presented in this paper are focused on large-data applications, for which the IQ-Services ?morphing? layer implements the data manipulations necessary to permit wide-area interactive or multimedia applications to proceed smoothly despite variations in underlying computing and network resources. IQ-Services interact with the systems layer via dynamic performance attributes, and end-to-end implementations of such attributes also enable clients to interact with servers. This results in a cooperative approach to data management for the large-data applications targeted by our research. We present and experiment with sample IQ-Services implemented for a wide-area collaboration in which multiple end users utilize different graphical views of the data being produced by a scientific simulation. The testbed used in experiments is comprised of high end machines connected via a local area backbone, remote machines connected via the Internet, and ?home? machines connected via a DSL link. Experimental results demonstrate substantial performance improvements attained by coordinating network-level with service-level adaptations of the data being transported and by permitting end users to dynamically deploy and use application-specific services for manipulating data in ways suitable for their current needs.