1. A method for identifying relationships between information objects and first digital resources, the method comprising: building a graph of information objects retrieved from a database, wherein each information object comprises structured text, data, and metadata representing an entity in digital form, said entity being one of: name, taxon, exemplar, practitioner, or nomos, each information object is identified by at least one persistent globally unique identifier, wherein said persistent globally unique identifier resolves to a service or a second digital resource encoding said structured text, data, and metadata for said information object, said graph comprises a set of information objects and relations among said information objects, each relation linking a pair of information objects, each said pair comprising entities of type: name-name, name-taxon, taxon-taxon, taxon-exemplar, exemplar-exemplar, nomos-taxon, practitioner-name, practitioner-taxon, practitioner-exemplar, or practitioner-nomos, and each said pair including a relation representing one of: synonymy, homonymy, orthographic variation, equivalence, membership, supertype, or subtype, new relations among said information objects are inferred based on a set of encoded rules, and the information objects in said graph may be traversed over said relations; searching within parsed data of a first digital resource for occurrences of name-like-strings, comprising at least one of the following steps searching within the parsed data for specialized formatting, searching within the parsed data for a string satisfying a regular expression, analyzing the parsed data using a grammar constructed for a class of name, performing a text search within the parsed data against a reference list of names, or performing a text search within the parsed data to identify a string having at least one of a known prefix or suffix used in a terminology, for each name-like-string identified in the parsed data: creating metadata marking an exact location in the parsed data of the occurrence of said name-like-string, obtaining a first persistent globally unique identifier of an information object by matching said name-like-string against the names or labels of entities, wherein said entities are represented as information objects stored in a repository, and wherein each information object is identified by a unique identifier, retrieving a first information object from said graph, wherein said first persistent globally unique identifier is identical to a second persistent globally unique identifier that identifies said first information object; analyzing said graph, wherein the analysis traverses said graph from said first information object over said relations to identify a plurality of information objects related to said first information object, and retrieves a second information object from among the information objects comprising said graph; obtaining from said second information object a third persistent globally unique identifier, creating a new relationship associating said second information object with the first digital resource, wherein said relationship comprises said third persistent globally unique identifier for said information object, a content identifier for said digital resource, and metadata about said association, and storing said relationship in a database, wherein each information object identifier is one of a Digital Object Identifier (DOI), a Handle, an Archival Resource Key (ARK), a Persistent Uniform Resource Locator (PURL), a Universal Unique Identifier (UUID), a Globally Unique Identifier (GUID), or a Life Sciences Identifier (LSID), and wherein said digital resource may be uniquely identified by at least one content identifier comprising a Digital Object Identifier (DOI), a Handle, an Archival Resource Key (ARK), a Persistent Uniform Resource Locator (PURL), a Universal Unique Identifier (UUID), a Globally Unique Identifier (GUID), or a Uniform Resource Identifier (URI), wherein said metadata about the association comprises at least one of said name-like-string, said exact location of said name-like-string in said parsed data, a number of occurrences of said second information object in the first digital resource, and a number of times said second information object is accessed from its relationship with the first digital resource.