For any human or nonhuman User to locate any “ instance ” (physical or virtual) within this expanded address field requires not only that it has a predictable and available location, but that the career of that thing and the history of its relations must in fact be queryable. Internet search has largely focused on the sorts of data that are publicly available at IPv4 addresses, namely web pages, but both the Internet of Things and the more comprehensive theoretical SPIME spaces suggest radically expanded search domains (and deep addresses exponentially more so). These range from the prosaic (Google “ my car keys ” to find them under the couch) to the barely fathomable ( “ search the contagion distribution of the RNA in the virus that laid me up ” ). Just as for today ’ s web pages, search providers are eager to provide more direct services built directly into query results themselves by predictively interpreting the intention of the query and providing its likely solution along with tools for the User to accomplish that intention as part of the search result. These are techniques sometimes associated with the semantic web, for which structured data are linked and associated to allow instrumental relations with other data, making the web as a whole more programmable by Users. Through various combinations of open or proprietary exigetics of data, and perhaps a sequence of application programming interfaces (APIs), a query entered as “ book me a ticket to New York ” can activate a series of secondary inquiries to calendars, banks, flight schedules, airline databases, bank accounts, and so on and, through this, initiate the cascading programming resulting in that booking. For this, to search is also to program. Such tidy consumer use cases require enormously difficult standardizations of interoperability between competitive services (not to mention beyond-Esperanto level standardization of all Users’ conceptual taxonomies). The goal of linking data into semantically relevant and accessible structures so that “ search ” would also provide more actionable results, and in turn allowing queries to program those results for specific ends, remains compelling for search engines, if less so for individual down-service-stream providers, such as airlines and banks, which see their business absorbed into a handful of search platforms. <sup>20</sup> By comparison, physical search may be based on a similar tissue of interrelation between addressable entities — in this case, a mix of physical things and data of interest — and might be a necessary condition of a really viable Internet of Things or SPIME space. The designation of semantic relations between objects, according to some disinterested (or extremely interested and capitalized) graph of addresses and their interlocking sets, might reorganize what we take to be the natural proximities of one thing to one another and introduce another map (even topology) of queryable association between them. This resulting platform might provide for the programming and counterprogramming of the resulting object landscapes and event graphs, putting them to direct use, as well as providing secondary metadata about their efficacy or accuracy. Just as most of the traffic on the Internet today is machine-to-machine, or at least machine generated, so too a semantic web of things <sup>21</sup> would be correlated less by the cognitive dispositions or instrumental intentions of human Users, but those of “ objects ” and other instances within the larger meta-assemblage all querying and programming one another without human intervention or supervision. In the hype, it ’ s easy to forget that the Internet of Things is also an Internet for Things (or for any addressable entity, however immaterial).
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Address Layer