An overview of semistructured data

Research on semistructured data started from the observation that much of today's electronic dat a does not conform to traditional relational, or object oriented data models . Several applications store their data in non-standard data formats ; legacy systems . structured documents . like HTML or SGML etc . Another instance is the integration of heterogeneous data sources : often these sources belong to external organizations . or partners . not under the application's control, and thei r structure is only partially known. and may change without notice . Data in these applications could be modeled as an object-oriented data . but its structure is irregular : some objects may have missing attributes . others may have multiple occurrences of the same attribute . the same attribut e may have different types in different objects, semantically related information may be represented differently in various objects . Data with these characteristics has been called semistructured data . Recent research has aimed at extending database management techniques to semistructure d data. The result of this work is a new paradigm in databases . complementing the relational an d object-oriented one. The new model has been applied to a. few research prototypes, like dat a integration [PGMW95 . PAGM96] . Web site management [FFK +98] . general-purpose management of semistructured data [QRS + 95 . AQUIt 97, MAG + 97], and data conversion [SCJK98] . Other research work has addressed query language design [AQM + 97. BDHS96a. PAGM96 . FFLS97a . FFLS97b] schema specification [BDFS97. MS99 . DGM98. BM99] . schema extraction [NUWC97 . BDFS97 . GW97 . NAM97], optimizations [AV97b, Suc96 . Suc97 . FS98. MW97] . indexing [MWA+98 . NIS99] . as well as formal aspects [AV97a, AV97b . MM97 . FLS98] . The interested reader may wan t to consult the tutorials by Abiteboul [Abi97] and Bunernan [Bun97] . In the traditional relational paradigm a database is modeled as a finite . first order structure . The first order vocabulary, i .e . the names and arities of the relations of that structure models th e database schema (the list of all table names and their attributes), and first order logic, or highe r logic formulae model queries . Database theory is related to both finite model theory and descriptiv e complexity. It makes no sense however to talk about finite structures or formulae without fixing the vocabulary first . In semistructured databases we do not have an a priory schema, hence no vocabulary . One way to model semistructured databases is to represent them as graphs . Thus. the vocabulary is fixed once and forever to be that of graphs . The real schema of a given database instance is now

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