PRINCIPLES OF BIG DATA

Coding, as used in the context of unstructured textual data, is the process of tagging terms with an identifier code that corresponds to a synonymous term listed in a standard nomenclature(seeGlossaryitem,Identifier).Forexample,amedicalnomenclaturemightcontainthe term renal cell carcinoma, a type of kidney cancer, attaching a unique identifier code for the term, such as “C9385000.” There are about 50 recognized synonyms for “renal cell carcinoma.” A few of these synonyms and near-synonyms are listed here to show that a single concept can be expressed many different ways, including adenocarcinoma arising from kidney, adenocarcinoma involving kidney, cancer arising from kidney, carcinoma of kidney, 4 1. PROVIDING STRUCTURE TO UNSTRUCTURED DATA Grawitz tumor, Grawitz tumour, hypernephroid tumor, hypernephroma, kidney adenocarcinoma, renal adenocarcinoma, and renal cell carcinoma. All of these terms could be assigned the same identifier code, “C9385000.” The process of coding a text document involves finding all the terms that belong to a specific nomenclature and tagging the term with the corresponding identifier code. A nomenclature is a specialized vocabulary, usually containing terms that comprehensively cover a well-defined and circumscribed area (see Glossary item, Vocabulary). For example, there may be a nomenclature of diseases, or celestial bodies, or makes and models of automobiles. Some nomenclatures are ordered alphabetically. Others are ordered by synonymy,wherein allsynonymsandplesionyms(near-synonyms,seeGlossaryitem,Plesionymy) are collected under a canonical (i.e., best or preferred) term. Synonym indexes are always corrupted by the inclusion of polysemous terms (i.e., terms with multiple meanings; see Glossary item, Polysemy). In many nomenclatures, grouped synonyms are collected under a code (i.e., a unique alphanumeric string) assigned to all of the terms in the group (see Glossary items, Uniqueness, String). Nomenclatures have many purposes: to enhance interoperability and integration, to allow synonymous terms to be retrieved regardless of which specific synonym is entered as a query, to support comprehensive analyses of textual data, to express detail, to tag information in textual documents, and to drive down the complexity of documents by uniting synonymous terms under a common code. Sets of documents held in more than one Big Data resource can be harmonized under a nomenclature by substituting or appending a nomenclature code to every nomenclature term that appears in any of the documents.