Data exchange and schema mappings in open and closed worlds

In the study of data exchange one usually assumes an open-world semantics, making it possible to extend instances of target schemas. An alternative closed-world semantics only moves ‘as much data as needed’ from the source to the target to satisfy constraints of a schema mapping. It avoids some of the problems exhibited by the open-world semantics, but limits the expressivity of schema mappings. Here we propose a mixed approach: one can designate different attributes of target schemas as open or closed, to combine the additional expressivity of the open-world semantics with the better behavior of query answering in closed worlds. We define such schema mappings, and show that they cover a large space of data exchange solutions with two extremes being the known open and closed-world semantics. We investigate the problems of query answering and schema mapping composition, and prove two trichotomy theorems, classifying their complexity based on the number of open attributes. We find conditions under which schema mappings compose, extending known results to a wide range of closed-world mappings. We also provide results for restricted classes of queries and mappings guaranteeing lower complexity.     

Data integration with uncertainty

This paper reports our first set of results on managing uncertainty in data integration. We posit that data-integration systems need to handle uncertainty at three levels and do so in a principled fashion. First, the semantic mappings between the data sources and the mediated schema may be approximate because there may be too many of them to be created and maintained or because in some domains (e.g., bioinformatics) it is not clear what the mappings should be. Second, the data from the sources may be extracted using information extraction techniques and so may yield erroneous data. Third, queries to the system may be posed with keywords rather than in a structured form. As a first step to building such a system, we introduce the concept of probabilistic schema mappings and analyze their formal foundations. We show that there are two possible semantics for such mappings: by-table semantics assumes that there exists a correct mapping but we do not know what it is; by-tuple semantics assumes that the correct mapping may depend on the particular tuple in the source data. We present the query complexity and algorithms for answering queries in the presence of probabilistic schema mappings, and we describe an algorithm for efficiently computing the top-k answers to queries in such a setting. Finally, we consider using probabilistic mappings in the scenario of data exchange.     

Semantic integration in Xyleme: a uniform tree-based approach

Xyleme is a huge warehouse integrating XML data of the Web. Xyleme considers a simple data model with data trees and tree types for describing the data sources, and a simple query language based on tree queries with boolean conditions. The main components of the data model are a mediated schema modeled by an abstract tree type, as a view of a set of tree types associated with actual data trees, called concrete tree types, and a mapping expressing the connection between the mediated schema and the concrete tree types. The first contribution of this paper is formal: we provide a declarative model-theoretic semantics for Xyleme tree queries, a way of checking tree query containment, and a characterization of tree queries as a composition of branch queries. The other contributions are algorithmic and handle the potentially huge size of the mapping relation which is a crucial issue for semantic integration and query evaluation in Xyleme. First, we propose a method for pre-evaluating queries at compile time by storing some specific meta-information about the mapping into map translation tables. These map translation tables summarize the set of all the branch queries that can be generated from the mediated schema and the set of all the mappings. Then, we propose different operators and strategies for relaxing queries which, having an empty map translation table, will have no answer if they are evaluated against the data. Finally, we present a method for semi-automatically generating the mapping relation.     

On the finite controllability of conjunctive query answering in databases under open-world assumption

In this paper we study queries over relational databases with integrity constraints (ICs). The main problem we analyze is OWA query answering, i.e., query answering over a database with ICs under open-world assumption. The kinds of ICs that we consider are inclusion dependencies and functional dependencies, in particular key dependencies; the query languages we consider are conjunctive queries and unions of conjunctive queries. We present results about the decidability of OWA query answering under ICs. In particular, we study OWA query answering both over finite databases and over unrestricted databases, and identify the cases in which such a problem is finitely controllable, i.e., when OWA query answering over finite databases coincides with OWA query answering over unrestricted databases. Moreover, we are able to easily turn the above results into new results about implication of ICs and query containment under ICs, due to the deep relationship between OWA query answering and these two classical problems in database theory. In particular, we close two long-standing open problems in query containment, since we prove finite controllability of containment of conjunctive queries both under arbitrary inclusion dependencies and under key and foreign key dependencies. The results of our investigation are very relevant in many research areas which have recently dealt with databases under an incomplete information assumption: e.g., data integration, data exchange, view-based information access, ontology-based information systems, and peer data management systems.     

基于模式集成语义的查询处理

在采用面向对象模型作为公共数据模型的多数据库系统中，基于模式集成语义的查询处理不仅要实现针对集成模式查询到针对输出模式查询的转换，而且要从语义上尽可能减少回答用户查询所需数据，保证对象引用的正确性.为了达到这个目标,提出了一些新的概念及基于模式集成语义的查询处理规则和路径表达式的查询处理方法.     

Object-oriented query language access to relational databases: A semantic framework for query translation

This research investigates and approach to query processing in a multidatabase system that uses an objectoriented model to capture the semantics of other data models. The object-oriented model is used to construct a global schema, defining an integrated view of the different schemas in the environment. The model is also used as a self-describing model to build a meta-database for storing information about the global schema. A unique aspect of this work is that the object-oriented model is used to describe the different data models of the multidatabase environment, thereby extending the meta database with semantic information about the local schemas. With the global and local schemas all represented in an object-oriented form, structural mappings between the global schema and each local schema are then easily supported. An object algebra then provides a query language for expressing global queries, using the structural mappings to translate object algebra queries into SQL queries over local relational schema. The advantage of using an object algebra is that the object-oriented database can be viewed as a blackboard for temporary storage of local data and for establishing relationships between different databases. The object algebra can be used to directly retrieve temporarily-stored data from the object-oriented database or to transparently retrieve data from local sources using the translation process described in this paper.     

Schema mapping and query translation in heterogeneous P2P XML databases

Peers in a peer-to-peer data management system often have heterogeneous schemas and no mediated global schema. To translate queries across peers, we assume each peer provides correspondences between its schema and a small number of other peer schemas. We focus on query reformulation in the presence of heterogeneous XML schemas, including data–metadata conflicts. We develop an algorithm for inferring precise mapping rules from informal schema correspondences. We define the semantics of query answering in this setting and develop query translation algorithm. Our translation handles an expressive fragment of XQuery and works both along and against the direction of mapping rules. We describe the HePToX heterogeneous P2P XML data management system which incorporates our results. We report the results of extensive experiments on HePToX on both synthetic and real datasets. We demonstrate our system utility and scalability on different P2P distributions.     

Answering queries using views: A survey

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. Received: 1 August 1999 / Accepted: 23 March 2001 Published online: 6 September 2001     

基于模式映射的查询计划生成算法

因特网的迅速发展使得多数据源综合集成日益重要.但是,不同数据源之间数据结构和语义的异构性导致数据集成是相当困难的.本文提出了一种基于模式映射的查询计划生成算法.该算法在正确定义映射规则的前提下,根据不同的查询条件和不同的数据源模式,自动构造查询计划,并保证结果数据满足目标模式结构与引用完整性要求.     

Logic-based query optimization for object databases

We present a technique for transferring query optimization techniques, developed for relational databases, into object databases. We demonstrate this technique for ODMG database schemas defined in ODL and object queries expressed in OQL. The object schema is represented using a logical representation (Datalog). Semantic knowledge about the object data model, e.g., class hierarchy information, relationship between objects, etc., as well as semantic knowledge about a particular schema and application domain are expressed as integrity constraints. An OQL object query is represented as a logic query and query optimization is performed in the Datalog representation. We obtain equivalent (optimized) logic queries, and subsequently obtain equivalent (optimized) OQL queries for each equivalent logic query. We present one optimization technique for semantic query optimization (SQO) based on the residue technique of U. Charavarthy et al. (1990; 1986; 1988). We show that our technique generalizes previous research on SQO for object databases. We handle a large class of OQL queries, including queries with constructors and methods. We demonstrate how SQO can be used to eliminate queries which contain contradictions and simplify queries, e.g., by eliminating joins, or by reducing the access scope for evaluating a query to some specific subclass(es). We also demonstrate how the definition of a method or integrity constraints describing the method, can be used in optimizing a query with a method     

Data Cleaning and Query Answering with Matching Dependencies and Matching Functions

Matching dependencies were recently introduced as declarative rules for data cleaning and entity resolution. Enforcing a matching dependency on a database instance identifies the values of some attributes for two tuples, provided that the values of some other attributes are sufficiently similar. Assuming the existence of matching functions for making two attribute values equal, we formally introduce the process of cleaning an instance using matching dependencies, as a chase-like procedure. We show that matching functions naturally introduce a lattice structure on attribute domains, and a partial order of semantic domination between instances. Using the latter, we define the semantics of clean query answering in terms of certain/possible answers as the greatest lower bound/least upper bound of all possible answers obtained from the clean instances. We show that clean query answering is intractable in general. Then we study queries that behave monotonically w.r.t. semantic domination order, and show that we can provide an under/over approximation for clean answers to monotone queries. Moreover, non-monotone positive queries can be relaxed into monotone queries.     

Temporal data exchange

Data exchange is the problem of transforming data that is structured under a source schema into data structured under another schema, called the target schema, so that both the source and target data satisfy the relationship between the schemas. Many applications such as planning, scheduling, medical and fraud detection systems, require data exchange in the context of temporal data. Even though the formal framework of data exchange for relational database systems is well-established, it does not immediately carry over to the settings of temporal data, which necessitates reasoning over unbounded periods of time.In this work, we study data exchange for temporal data. We first motivate the need for two views of temporal data: the concrete view, which depicts how temporal data is compactly represented and on which the implementations are based, and the abstract view, which defines the semantics of temporal data as a sequence of snapshots. We first extend the chase procedure for the abstract view to have a conceptual basis for the data exchange for temporal databases. Considering non-temporal source-to-target tuple generating dependencies and equality generating dependencies, the chase algorithm can be applied on each snapshot independently. Then we define a chase procedure (called c-chase) on concrete instances and show the result of c-chase on a concrete instance is semantically aligned with the result of chase on the corresponding abstract instance. In order to interpret intervals as constants while checking if a dependency or a query is satisfied by a concrete database, we will normalize the instance with respect to the dependency or the query. To obtain the semantic alignment, the nulls (which are introduced by data exchange and model incompleteness) in the concrete view are annotated with temporal information. Furthermore, we show that the result of the concrete chase provides a foundation for query answering. We define naïve evaluation on the result of the c-chase and show it produces certain answers.     

Relaxed Notions of Schema Mapping Equivalence Revisited

Recently, two relaxed notions of equivalence of schema mappings have been introduced, which provide more potential of optimizing schema mappings than logical equivalence: data exchange (DE) equivalence and conjunctive query (CQ) equivalence. In this work, we systematically investigate these notions of equivalence for mappings consisting of s-t tgds and target egds and/or target tgds. We prove that both CQ- and DE-equivalence are undecidable and so are some important optimization tasks (like detecting if some dependency is redundant). However, we also identify an important difference between the two notions of equivalence: CQ-equivalence remains undecidable even if the schema mappings consist of s-t tgds and target dependencies in the form of key dependencies only. In contrast, DE-equivalence is decidable for schema mappings with s-t tgds and target dependencies in the form of functional and inclusion dependencies with terminating chase property.     

Answering constraint-based mining queries on itemsets using previous materialized results

In recent years, researchers have begun to study inductive databases, a new generation of databases for leveraging decision support applications. In this context, the user interacts with the DBMS using advanced, constraint-based languages for data mining where constraints have been specifically introduced to increase the relevance of the results and, at the same time, to reduce its volume. In this paper we study the problem of mining frequent itemsets using an inductive database. We propose a technique for query answering which consists in rewriting the query in terms of union and intersection of the result sets of other queries, previously executed and materialized. Unfortunately, the exploitation of past queries is not always applicable. We then present sufficient conditions for the optimization to apply and show that these conditions are strictly connected with the presence of functional dependencies between the attributes involved in the queries. We show some experiments on an initial prototype of an optimizer which demonstrates that this approach to query answering is viable and in many practical cases it drastically reduces the query execution time.     

语义缓存的聚集查询匹配研究

为提高海量数据库系统的查询效率,围绕海量数据库系统中的聚集查询技术,把通常应用于小型数据库查询的语义缓存技术拓展到海量数据库的聚集查询中．首先研究了面向聚集查询的语义缓存形式化描述,在此基础上讨论了利用缓存处理查询的条件并对查询匹配进行了分类,提出并实现了包含匹配判定算法和相交匹配判定算法,最后给出了相应的实验结果．在某大型实际工程中的应用表明上述判定算法是有效的．     

The Piazza peer data management system

Intuitively, data management and data integration tools are well-suited for exchanging information in a semantically meaningful way. Unfortunately, they suffer from two significant problems: They typically require a comprehensive schema design before they can be used to store or share information and they are difficult to extend because schema evolution is heavyweight and may break backward compatibility. As a result, many small-scale data sharing tasks are more easily facilitated by nondatabase-oriented tools that have little support for semantics. The goal of the peer data management system (PDMS) is to address this need: We propose the use of a decentralized, easily extensible data management architecture in which any user can contribute new data, schema information, or even mappings between other peers' schemes. PDMSs represent a natural step beyond data integration systems, replacing their single logical schema with an interlinked collection of semantic mappings between peers' individual schemas. This paper describes-several aspects of the Piazza PDMS, including the schema mediation formalism, query answering and optimization algorithms, and the relevance of PDMSs to the semantic Web.     

Tractable XML data exchange via relations

We consider data exchange for XML documents: given source and target schemas, a mapping between them, and a document conforming to the source schema, construct a target document and answer target queries in a way that is consistent with the source information. The problem has primarily been studied in the relational context, in which data-exchange systems have also been built. Since many XML documents are stored in relations, it is natural to consider using a relational system for XML data exchange. However, there is a complexity mismatch between query answering in relational and in XML data exchange. This indicates that to make the use of relational systems possible, restrictions have to be imposed on XML schemas and mappings, as well as on XML shredding schemes. We isolate a set of five requirements that must be fulfilled in order to have a faithful representation of the XML data-exchange problem by a relational translation. We then demonstrate that these requirements naturally suggest the in-lining technique for data-exchange tasks. Our key contribution is to provide shredding algorithms for schemas, documents, mappings and queries, and demonstrate that they enable us to correctly perform XML data-exchange tasks using a relational system.