Extended relational operators for statistical data manipulations in medical databases

Conventional relational database management systems fail to address three features of statistical data management in a biomedical/clinical database, namely, that (1) statistical and medical data (SMD) require a great deal of space and need to be stored in a reduced form with minimal duplication; indeed, SMD have many derived/calculated and summary statistics that make the number of attributes in a relation (i.e., a set of records) grow rapidly and dynamically; (2) most SMD have hierarchical structures that are difficult to manage using the relational data model since SMD are stored in separate relations for duplication and space considerations; and (3) the management of SMD is made easier if it is possible to reorganize relations or group data, a capability lacking in conventional relational database management systems. In this paper, we (1) introduce five extended relational operators, (lattice) NEST, (lattice) UNNEST, MERGE, SPREAD, and GEN, to reorganize relations; (2) integrate the extended operators with conventional relational algebra and introduce the concept of the lattice relational model; and (3) give applications of the extended relational operators and the lattice relational model in solving the problems of statistical data manipulation in medical databases.     

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.     

Fuzzy rough set techniques for uncertainty processing in a relational database

This paper concerns the modeling of imprecision, vagueness, and uncertainty in databases through an extension of the relational model of data: the fuzzy rough relational database, an approach which uses both fuzzy set and rough set theories for knowledge representation of imprecise data in a relational database model. The fuzzy rough relational database is formally defined, along with a fuzzy rough relational algebra for querying. Comparisons of theoretical properties of operators in this model with those in the standard relational model are discussed. An example application is used to illustrate other aspects of this model, including a fuzzy entity–relationship type diagram for database design, a fuzzy rough data definition language, and an SQL‐like query language supportive of the fuzzy rough relational database model. This example also illustrates the ease of use of the fuzzy rough relational database, which often produces results that are better than those of conventional databases since it more accurately models the uncertainty of real‐world enterprises than do conventional databases through the use of indiscernibility and fuzzy membership values. ©2000 John Wiley & Sons, Inc.     

Using Constraint Programming in Selection Operators for Constraint Databases

Constraint Databases represent complex data by means of formulas described by constraints (equations, inequations or Boolean combinations of both). Commercial database management systems allow the storage and efficient retrieval of classic data, but for complex data a made-to-measure solution combined with expert systems for each type of problem are necessary. Therefore, in the same way as commercial solutions of relational databases permit storing and querying classic data, we propose an extension of the Selection Operator for complex data stored, and an extension of SQL language for the case where both classic and constraint data need to be managed. This extension shields the user from unnecessary details on how the information is stored and how the queries are evaluated, thereby enlarging the capacity of expressiveness for any commercial database management system. In order to minimize the selection time, a set of strategies have been proposed, which combine the advantages of relational algebra and constraint data representation.     

关系模式下的XML数据存取技术研究

XML数据具有自描述性和半结构化特征,所以它能够从自身得到能够描述自己的类似于数据库的数据模式,并且对XML数据进行数据库存取。本文对利用关系模式来映射XML模式从而在关系数据库中存取XML数据的技术,进行了研究和初步应用。     

A relational approach to querying data streams

Data streams are long, relatively unstructured sequences of characters that contain information such as electronic mail or a tape backup of various documents and reports created in an office. A conceptual framework is presented, using relational algebra and relational databases, within which data streams may be queried. As information is extracted from the data streams, it is put into a relational database that may be queried in the usual manner. The database schema evolves as the user's knowledge of the content of the data stream changes. Operators are defined in terms of relational algebra that can be used to extract data from a specially defined relation that contains all or part of the data stream. This approach to querying data streams permits the integration of unstructured data with structured data. The operators defined extend the functionality of relational algebra in much the same way that the join does relative to the basic operators select, project, union, difference, and Cartesian product     

Efficient Querying and Animation of Periodic Spatio-Temporal Databases

We propose a representation of spatio-temporal objects with continuous and cyclic or acyclic periodic movements. We also describe an extended relational algebra query language for databases with such objects. We show that the new spatio-temporal databases are closed under the extended relational algebra queries, and each fixed relational algebra query can be evaluated in PTIME in the size of the input database.     

基于Oracle XML DB的XML存取技术研究

XML近来已成为Web上数据表示与交换的标准,而由此带来的一个亟需解决的问题就是XML数据在关系数据库中如何存储与管理。以Oracle数据库为例,简要介绍了Oracle XML DB技术,并用实例说明如何利用这种技术将XML和关系数据库联系起来,实现对XML文档的存取。     

Variable independence in constraint databases

In this paper, we study constraint databases with variable independence conditions (vics). Such databases occur naturally in the context of temporal and spatiotemporal database applications. Using computational geometry techniques, we show that variable independence is decidable for linear constraint databases. We also present a set of rules for inferring vics in relational algebra expressions. Using vics, we define a subset of relational algebra that is closed under restricted aggregation.     

An algebraic evaluation method for deduction in incomplete data bases

Strategies used in deductive data bases try as far as possible to replace deduction in Horn clause theories T_S by evaluation of relational algebra formulas in a set of ground atoms. In this paper we extend the relational algebra in order to take into account incomplete databases where incompleteness is represented by Skolem constants. We first define the notion of the extended model EM, similar to the Herbrand model, which is associated to a given theory T_S. Specific satisfiability conditions applied to EM define the link between provability in T_S and satisfiability in EM. Then we define an extended relational algebra to compute every ground instance of a given formula. It is shown that this algebra is always sound, and complete for a particular class of formulas which is not too restrictive.     

ESTIMATING NULL VALUES IN THE DISTRIBUTED RELATIONAL DATABASES ENVIRONMENT

To estimate nullvalues in relational database systems is an important research topic. In Chen and Yeh (1997) a method for estimating null values in relational database systems was presented. In Chen and Chen (1997) a method for fuzzy query translation for information in the distributed relational databases environment was presented. In this article, the works of Chen and Chen (1997) and Chen and Yeh (1997) are extended to propose a method for estimating null values in the distributed relational databases environment. The proposed method provides a useful way to estimate incomplete data when the relations stored in a failed server cannot be accessed in the distributed relational databases environment.     

多级安全数据库的语义

在含有多重实例的多级安全数据库中，各个用户都有其自身信赖的数据集合。本文提出了将多级安全数据库映射成为多个数据库，各个用户在其信赖的数据库上进行操作的思想，文章讨论了不同安全级用户所信赖的数据库之间的关系，介绍了一种新的安全的关系代数运算及相应的查询表示方法。     

Ultrawrap: SPARQL execution on relational data

The Semantic Web’s promise of web-wide data integration requires the inclusion of legacy relational databases,¹ i.e. the execution of SPARQL queries on RDF representation of the legacy relational data. We explore a hypothesis: existing commercial relational databases already subsume the algorithms and optimizations needed to support effective SPARQL execution on existing relationally stored data. The experiment is embodied in a system, Ultrawrap, that encodes a logical representation of the database as an RDF graph using SQL views and a simple syntactic translation of SPARQL queries to SQL queries on those views. Thus, in the course of executing a SPARQL query, the SQL optimizer uses the SQL views that represent a mapping of relational data to RDF, and optimizes its execution. In contrast, related research is predicated on incorporating optimizing transforms as part of the SPARQL to SQL translation, and/or executing some of the queries outside the underlying SQL environment.Ultrawrap is evaluated using two existing benchmark suites that derive their RDF data from relational data through a Relational Database to RDF (RDB2RDF) Direct Mapping and repeated for each of the three major relational database management systems. Empirical analysis reveals two existing relational query optimizations that, if applied to the SQL produced from a simple syntactic translations of SPARQL queries (with bound predicate arguments) to SQL, consistently yield query execution time that is comparable to that of SQL queries written directly for the relational representation of the data. The analysis further reveals the two optimizations are not uniquely required to achieve a successful wrapper system. The evidence suggests effective wrappers will be those that are designed to complement the optimizer of the target database.     

Hybrid query execution engine for large attributed graphs

Graphs are widely used for modeling complicated data such as social networks, bibliographical networks and knowledge bases. The growing sizes of graph databases motivate the crucial need for developing powerful and scalable graph-based query engines. We propose a SPARQL-like language, G-SPARQL, for querying attributed graphs. The language enables the expression of different types of graph queries that are of large interest in the databases that are modeled as large graph such as pattern matching, reachability and shortest path queries. Each query can combine both structural predicates and value-based predicates (on the attributes of the graph nodes/edges). We describe an algebraic compilation mechanism for our proposed query language which is extended from the relational algebra and based on the basic construct of building SPARQL queries, the Triple Pattern. We describe an efficient hybrid Memory/Disk representation of large attributed graphs where only the topology of the graph is maintained in memory while the data of the graph are stored in a relational database. The execution engine of our proposed query language splits parts of the query plan to be pushed inside the relational database (using SQL) while the execution of other parts of the query plan is processed using memory-based algorithms, as necessary. Experimental results on real and synthetic datasets demonstrate the efficiency and the scalability of our approach and show that our approach outperforms native graph databases by several factors.     

Association algebra: a mathematical foundation for object-orienteddatabases

The application of the object-oriented (O-O) paradigm in the database management field has gained much attention in recent years. Several experimental and commercial O-O database management systems have become available. However, the existing O-O DBMSs still lack a solid mathematical foundation for the manipulation of O-O databases, the optimization of queries, and the design and selection of storage structures for supporting O-O database manipulations. This paper presents an association algebra (A-algebra) to serve as a mathematical foundation for processing O-O databases, which is analogous to the relational algebra used for processing relational databases. In this algebra, objects and their associations in an O-O database are uniformly represented by association patterns which are manipulated by a number of operators to produce other association patterns. Different from the relational algebra, in which set operations operate on relations with union-compatible structures, the A-algebra operators can operate on association patterns of homogeneous and heterogeneous structures. Different from the traditional record-based relational processing, the A-algebra allows very complex patterns of object associations to be directly manipulated. The pattern-based query formulation and the A-algebra operators are described. Some mathematical properties of the algebraic operators are presented together with their application in query decomposition and optimization. The completeness of the A-algebra is also defined and proven. The A-algebra has been used as the basis for the design and implementation of an object-oriented query language, OQL, which is the query language used in a prototype Knowledge Base Management System OSAM*.KBMS     

Fuzzy database query languages and their relational completenesstheorem

Two fuzzy database query languages are proposed. They are used to query fuzzy databases that are enhanced from relational databases in such a way that fuzzy sets are allowed in both attribute values and truth values. A fuzzy calculus query language is constructed based on the relational calculus, and a fuzzy algebra query language is also constructed based on the relational algebra. In addition, a fuzzy relational completeness theorem such that the languages have equivalent expressive power is proved     

Query processing over object views of relational data

This paper presents an approach to object view management for relational databases. Such a view mechanism makes it possible for users to transparently work with data in a relational database as if it was stored in an object-oriented (OO) database. A query against the object view is translated to one or several queries against the relational database. The results of these queries are then processed to form an answer to the initial query. The approach is not restricted to a ‘pure’ object view mechanism for the relational data, since the object view can also store its own data and methods. Therefore it must be possible to process queries that combine local data residing in the object view with data retrieved from the relational database. We discuss the key issues when object views of relational databases are developed, namely: how to map relational structures to sub-type/supertype hierarchies in the view, how to represent relational database access in OO query plans, how to provide the concept of object identity in the view, how to handle the fact that the extension of types in the view depends on the state of the relational database, and how to process and optimize queries against the object view. The results are based on experiences from a running prototype implementation. Edited by: M.T. ?zsu. Received April 12, 1995 / Accepted April 22, 1996     

RDB中基于RDFS的语义本体存储技术研究

资源描述框架(RDF)/资源描述框架模式(RDFS)是语义互联网架构中的技术。尽管XML/RDF数据库正迅速的发展,关系型数据库仍是目前企业级应用的首选。针对如何有效地把RDFS数据存储在关系数据库中,充分利用现有的数据库资源来管理RDFS数据,提出了一种RDB中基于RDFS的语义本体存储技术,实现了RDFS本体抽取,提出了RDFS本体的存储优化方案,提高了数据存储访问效率。     

OA系统与档案管理系统数据交换的研究与实现

Lotus Domino是当今办公自动化系统的主流开发平台之一,苏州大学的OA系统正是基于这个平台开发的。Domino自带一个非关系型数据库——文档型数据库,而苏州大学的档案管理系统的数据存储在SQL Server——关系型数据库中。因此要实现OA系统与档案管理系统的数据交换,必须要解决Domino和关系数据库的数据交换问题。本文利用ODBC实现Domino和关系数据库的互操作。     

数据树——一种用于异构数据源集成的公共数据模型

文中提出一种异构数据源集成的公共数据模型－附有元数据的数据树。数据树的元数据附在数据上，便于表达没有稳定模式的数据、自描述的数据、非结构化和半结构化的数据以及从各种异构数据源集成的数据。作为数据树操纵语言的数学基础，文中提出了数据树代数，它提供了八种操作，比关系代数具有更大的灵活性和较强的功能。