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To support advanced applications, this paper proposes a resource space model for aggregation query on subspaces defined by a range within the partial order on the coordinate trees representing each dimension, where each point in the subspace contains resources aggregated along the paths of the partial order relations on the coordinate trees and the aggregated resources at each point can be measured, ranked and selected by applications. To efficiently locate non-empty points in a large subspace, an approach to generating graph index is proposed to build partial order relations on coordinates of dimensions to enable a subspace query to reach non-empty points through indexing links and aggregate resources along indexing paths to their super points. 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To efficiently locate non-empty points in a large subspace, an approach to generating graph index is proposed to build partial order relations on coordinates of dimensions to enable a subspace query to reach non-empty points through indexing links and aggregate resources along indexing paths to their super points. 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