Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. The problem of designing data integration systems is important in current real world applications, and is characterized by a number of issues that are interesting from a theoretical point of view. This document presents on overview of the material to be presented in a tutorial on data integration. The tutorial is focused on some of the theoretical issues that are relevant for data integration. Special attention will be devoted to the following aspects: modeling a data integration application, processing queries in data integration, dealing with inconsistent data sources, and reasoning on queries.

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Data integration: a theoretical perspective

XML is quickly becoming the de facto standard for data exchange over the Internet. This is creating a new set of data management requirements involving XML, such as the need to store and query XML documents. Researchers have proposed using relational database systems to satisfy these requirements by devising ways to "shred" XML documents into relations, and translate XML queries into SQL queries over these relations. However, a key issue with such an approach, which has largely been ignored in the research literature, is how (and whether) the ordered XML data model can be efficiently supported by the unordered relational data model. This paper shows that XML's ordered data model can indeed be efficiently supported by a relational database system. This is accomplished by encoding order as a data value. We propose three order encoding methods that can be used to represent XML order in the relational data model, and also propose algorithms for translating ordered XPath expressions into SQL using these encoding methods. Finally, we report the results of an experimental study that investigates the performance of the proposed order encoding methods on a workload of ordered XML queries and updates.

http://db.ucsd.edu/static/cse232b-archive/papers/tatarinov02.pdf

Storing and querying ordered XML using a relational database system

XML is a versatile markup language, capable of labeling the information content of diverse data sources including structured and semi-structured documents, relational databases, and object repositories. A query language that uses the

XQuery 1.0 : An XML Query Language

The collection of digital information by governments, corporations, and individuals has created tremendous opportunities for knowledge- and information-based decision making. Driven by mutual benefits, or by regulations that require certain data to be published, there is a demand for the exchange and publication of data among various parties. Data in its original form, however, typically contains sensitive information about individuals, and publishing such data will violate individual privacy. The current practice in data publishing relies mainly on policies and guidelines as to what types of data can be published and on agreements on the use of published data. This approach alone may lead to excessive data distortion or insufficient protection. Privacy-preserving data publishing (PPDP) provides methods and tools for publishing useful information while preserving data privacy. Recently, PPDP has received considerable attention in research communities, and many approaches have been proposed for different data publishing scenarios. In this survey, we will systematically summarize and evaluate different approaches to PPDP, study the challenges in practical data publishing, clarify the differences and requirements that distinguish PPDP from other related problems, and propose future research directions.

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Privacy-preserving data publishing: A survey of recent developments

The problem of answering queries using views is to find efficient methods of answering a query using a set of previously defined materialized views over the database, rather than accessing the database relations. The problem has recently received significant attention because of its relevance to a wide variety of data management problems. In query optimization, finding a rewriting of a query using a set of materialized views can yield a more efficient query execution plan. To support the separation of the logical and physical views of data, a storage schema can be described using views over the logical schema. As a result, finding a query execution plan that accesses the storage amounts to solving the problem of answering queries using views. Finally, the problem arises in data integration systems, where data sources can be described as precomputed views over a mediated schema. This article surveys the state of the art on the problem of answering queries using views, and synthesizes the disparate works into a coherent framework. We describe the different applications of the problem, the algorithms proposed to solve it and the relevant theoretical results.

/pdf/answering-queries-using-views-a-survey-4aug5icc6d.pdf

Answering queries using views: A survey

An important application of XML is the interchange of electronic data (EDI) between multiple data sources on the Web. As XML data proliferates on the Web, applications will need to integrate and aggregate data from multiple source and clean and transform data to facilitate exchange. Data extraction, conversion, transformation, and integration are all well-understood database problems, and their solutions rely on a query language. We present a query language for XML, called XML-QL, which we argue is suitable for performing the above tasks. XML-QL is a declarative, `relational complete' query language and is simple enough that it can be optimized. XML-QL can extract data from existing XML documents and construct new XML documents.

A query language for XML

Systems for managing and querying semistructured-data sources often store data in proprietary object repositories or in a tagged-text format. We describe a technique that can use relational database management systems to store and manage semistructured data. Our technique relies on a mapping between the semistructured data model and the relational data model, expressed in a query language called STORED. When a semistructured data instance is given, a STORED mapping can be generated automatically using data-mining techniques. We are interested in applying STORED to XML data, which is an instance of semistructured data. We show how a document-type-descriptor (DTD), when present, can be exploited to further improve performance.

http://pike.psu.edu/classes/ist597/2003-fall/papers/deutsch98storing.pdf

Storing semistructured data with STORED

XML-QL: A Query Language for XML

We revisit the standard chase procedure, studying its properties and applicability to classical database problems. We settle (in the negative) the open problem of decidability of termination of the standard chase, and we provide sufficient termination conditions which are strictly less over-conservative than the best previously known. We investigate the adequacy of the standard chase for checking query containment under constraints, constraint implication and computing certain answers in data exchange, gaining a deeper understanding by separating the algorithm from its result. We identify the properties of the chase result that are essential to the above applications, and we introduce the more general notion of F-universal model set, which supports query and constraint languages that are closed under a class F of mappings. By choosing F appropriately, we extend prior results to existential first-order queries and ∀∃-firstorder constraints. We show that the standard chase is incomplete for finding universal model sets, and we introduce the extended core chase which is complete, i.e. finds an F-universal model set when it exists. A key advantage of the new chase is that the same algorithm can be applied for all mapping classes F of interest, simply by modifying the set of constraints given as input. Even when restricted to the typical input in prior work, the new chase supports certain answer computation and containment/implication tests in strictly more cases than the incomplete standard chase.

http://db.ucsd.edu/wp-content/uploads/pdfs/302.pdf

The chase revisited

We formalize and study business process systems that are centered around "business artifacts", or simply "artifacts". Artifacts are used to represent (real or conceptual) key business entities, including both their data schema and lifecycles. The lifecycle of an artifact type specifies the possible sequencings of services that can be applied to an artifact of this type as it progresses through the business process. The artifact-centric approach was introduced by IBM, and has been used to achieve substantial savings when performing business transformations.In this paper, artifacts carry attribute records and internal state relations (holding sets of tuples) that services can consult and update. In addition, services can access an underlying database and can introduce new values from an infinite domain, thus modeling external inputs or partially specified processes described by pre-and-post conditions. The lifecycles associate services to the artifacts using declarative, condition-action style rules.We consider the problem of statically verifying whether all runs of an artifact system satisfy desirable correctness properties expressed in a first-order extension of linear-time temporal logic. We map the boundaries of decidability for the verification problem and provide its complexity. The technical challenge to static verification stems from the presence of data from an infinite domain, yielding an infinite-state system. While much work has been done lately in the verification community on model checking specialized classes of infinite-state systems, the available results do not transfer to our framework, and this remains a difficult problem. We identify an expressive class of artifact systems for which verification is nonetheless decidable. The complexity of verification is PSPACE-complete, which is no worse than classical finite-state model checking.This investigation builds upon previous work on verification of data-driven Web services and ASM transducers, while addressing significant new technical challenges raised by the artifact model.

http://db.ucsd.edu/artifacts/pubs/324.pdf

Alin Deutsch

Papers

A query language for XML

Storing semistructured data with STORED

XML-QL: A Query Language for XML

The chase revisited

Automatic verification of data-centric business processes