 There are two prominent suggestions in the literature. The first, originally suggested by Suppes (1962 [1969]), is that data models are the target-end structures represented by models. This approach faces a question whether we should be satisfied with an account of scientific representation that precludes phenomena being represented (see Bogen and Woodward (1988) for a discussion of the distinction between data and phenomena, and Brading and Landry (2006) for a discussion of the distinction in the context of scientific representation). Van Fraassen (2008) has addressed this problem and argues for a pragmatic resolution: in the context of use, there is no pragmatic difference between representing phenomena and data extracted from it (see Nguyen 2016 for a critical discussion). The alternative approach locates the target-end structure in the target system itself. One version of this approach sees structures as being instantiated in target systems. This view seems to be implicit in many versions of the semantic view, and it is explicitly held by authors arguing for a structuralist answer to the problem of the applicability of mathematics (Resnik 1997; Shapiro 1997). This approach faces underdetermination issues in that the same target can instantiate different structures. The issue can be seen as arising due to there being alternative descriptions of the system (Frigg 2006) or because a version of “Newman’s Objection” also bites in the current context (Newman 1928; see Ainsworth 2009 and Ketland 2004 for further discussion). A more radical version simply identifies targets with structures (Tegmark 2008). This approach is highly revisionary in particular when considering target systems like populations of breeding rabbits or economies. So the question remains for any structuralist account of scientific representation: where are the required target-end structures to be found?