Let me mention that the approach has a good foundation:
Basically information means selection within a domain (value or definition set). For comparable information the domain should be the same for all. Strictly speaking for objectivity and precision of information the uniform definition of the domain is even precondition. Therefore the global (online) definition of the domain is proposed here. It is advantageous to define an ordered domain, because this allows using numbers for addressing the elements and because nature is ordered in many respects. If the original data are ordered in multiple independent ways, we can define a domain with multiple independent numeric dimensions to reflect this. Because we want to search information in the domain, for quantification of similarity we can define a distance function or metric. Therefore we propose “Domain Spaces” (“DSs”: online defined nestable metric spaces, http://numericsearch.com/DS-Page-med.pdf ). With this searchable information can be represented in simple form as “Domain Vectors” (DVs):
URL (of common DS definition) plus sequence of numbers
Compared to words there are important advantages (objectivity, information content and concentration, range, resolution, efficiency etc.). DSs can make quantitative data searchable. They can make generally user defined information searchable. They can be used for globally uniform definition of complex information, e.g. medical findings ( http://numericsearch.com/FutureMedPoster.pdf ) . Of course we need a Web standard for DVs and DSs definitions. Though there are many possibilities for extensions, e.g. possibilities to reuse existing definitions in new definitions, we can try to make the basics as simple as possible. We can discuss this here.