Database Reference
In-Depth Information
INTRODUCTION
The goal of data integration is to enable rapid development of new applications requiring information
from multiple sources (Haas, 2007). Data integration consists in combining data from different sources
into a unified format (Bernstein & Haas, 2008). There is a number of different research fields relevant to
data integration. Among them we can distinguish: identification of the best data sources to use, cleansing
and standardizing data coming from these sources, dealing with uncertainty and tracing data provenance,
the way of querying diverse sources and optimizing queries and execution plans. Integration activities
cover any form of data reuse, such as exchanging data between different application's databases, trans-
lating data for business-to-business e-commerce, and providing access to structured data and documents
via a Web portal (Bernstein & Haas, 2008).
A variety of architectural approaches can be used to deal with the problem of data integration. The
most popular is the
materialized integration
realized by means of
data warehouse
that consolidates
data from multiple sources. Other approaches use paradigm of
virtual integration
. While warehouses
materialize the integrated data, virtual data integration offers a mediated schema against which users
can pose queries. The query is translated into queries on the data sources and results of those queries are
merged so that it appears to have come from a single integrated database (Miller et al., 2000, Pankowski
& Hunt, 2005). In a peer-to-peer (P2P) data integration the role of the mediated schema can play schema
of any peer database. Then the user issues a query against an arbitrarily chosen peer and expects that the
answer will include relevant data stored in all P2P connected data sources. The data sources are related by
means of XML
schema mappings
. A query must be propagated to all peers in the system along semantic
paths of mappings and reformulated accordingly. The partial answers must be merged and sent back to
the user's peer (Madhavan & Halevy, 2003; Pankowski, 2008c; Tatarinov & Halevy, 2004).
Much work has been done on data integration systems both with a mediated (global) schema and
in P2P architecture, where the schema of any peer can play the role of the mediated schema (Arenas
& Libkin, 2005; Madhavan & Halevy, 2003; Melnik et al., 2005, Yu & Popa, 2004). There is also a
number of systems built in P2P data integration paradigm (Koloniari & Pitoura, 2005), notably Piazza
(Tatarinov et al., 2003), PeerDB (Ooi et al., 2003). In these works the focus was on overcoming syn-
tactic heterogeneity and schema mappings were used to specify how data structured under one schema
(the source schema) can be transformed into data structured under another schema (the target schema)
(Fagin et al., 2004; Fuxman et al., 2006). Some attention has been paid to the question of how schema
constraints influence the query propagation.
This chapter describes formal foundations and some algorithms used for XML data integration in
P2P system. Schemas of XML data are described by means of a class of tree-pattern formulas, like in
(Arenas & Libkin, 2005). These formulas are used to define both schema mappings and queries. In
contrast to (Arenas & Libkin, 2005), except for schemas we use tree-pattern formulas also to specify
constraints (functional dependencies) over schemas. Schemas, mappings, queries and constraints are
specified in a uniform way as a class of tree-pattern formulas. Thanks to this, we are able to translate
high-level specifications into XQuery programs. We also discuss the problem of query propagation be-
tween peers. We show how mutual relationships between schema constraints and queries can influence
both propagation of queries and merging of answers. Taking into account such interrelationships may
improve both, efficiency of the system and information content included in answers. We show in brief
how the issues under consideration have been implemented in 6P2P system (
SixP2P
,
Semantic Integra-
tion of XML data in P2P environment
).
