The Globus Data Grid architecture provides a scalable infrastructure for the management of storage resources and data that are distributed across Grid environments. These services are designed to support a variety of scientific applications, ranging from high-energy physics to computational genomics, that require access to large amounts of data (terabytes or even petabytes) with varied quality of service requirements. By layering on a set of core services, such as data transport, security, and replica cataloging, one can construct various higher-level services. In this paper, we discuss the design and implementation of a high-level replica selection service that uses information regarding replica location and user preferences to guide selection from among storage replica alternatives. We first present a basic replica selection service design, then show how dynamic information collected using Globus information service capabilities concerning storage system properties can help improve and optimize the selection process. We demonstrate the use of Condor's ClassAds resource description and matchmaking mechanism as an efficient tool for representing and matching storage resource capabilities and policies against application requirements.