In semistructured databases there is no schema fixed in advance. To provide the benefits of a schema in such environments, we introduce DataGuides: concise and accurate structural summaries of semistructured databases. DataGuides serve as dynamic schemas, generated from the database; they are useful for browsing database structure, formulating queries, storing information such as statistics and sample values, and enabling query optimization. This paper presents the theoretical foundations of DataGuides along with an algorithm for their creation and an overview of incremental maintenance. We provide performance results based on our implementation of DataGuides in the Lore DBMS for semistructured data. We also describe the use of DataGuides in Lore, both in the user interface to enable structure browsing and query formulation, and as a means of guiding the query processor and optimizing query execution.

This paper is an attempt at laying the foundations for the classification of queries on relational data bases according to their structure and their computational complexity. Using the operations of composition and fixpoints, a Z--// hierarchy of height w 2, called the fixpoint query hierarchy, is defined, and its properties investigated. The hierarchy includes most of the queries considered in the literathre including those of Codd and Aho and Ullman

A temporal database contains time-varying data. In a real-time database transactions have deadlines or timing constraints. In this paper we review the substantial research in these two heretofore separate research areas. We first characterize the time domain, then investigate temporal and real-time data models. We evaluate temporal and real-time query languages along several dimensions. Temporal and real-time DBMS implementation is examined. We conclude with a summary of the major accomplishments of the research to date, and list several research questions that should be addressed next. Keywords: object-oriented database, relational databases, query language, temporal data model, time-constrained database, transaction time, user-defined time, valid time 1 Introduction Time is an important aspect of all real-world phenomena. Events occur at specific points in time; objects and the relationships among objects exist over time. The ability to model this temporal dimension of the real worl...

System R is a database management system which provides a high level relational data interface. The system provides a high level of data independence by isolating the end user as much as possible from underlying storage structures. The system permits definition of a variety of relational views on common underlying data. Data control features are provided, including authorization, integrity assertions, triggered transactions, a logging and recovery subsystem, and facilities for maintaining data consistency in a shared-update environment. This paper contains a description of the overall architecture and design of the system. At the present time the system is being implemented and the design evaluated. We emphasize that System R is a vehicle for research in database architecture, and is not planned as a product.

This paper describes the design and implementation of PESTO (Portable Explorer of STructured Objects), a user interface that supports browsing and querying of object databases. PESTO allows users to navigate the relationships that exist among objects. In addition, users can formulate complex object queries through an integrated query paradigm ("query-in-place") that presents querying as a natural extension of browsing. PESTO is designed to be portable to any object database system that supports a high-level query language; in addition, PESTO is extensible, providing hooks for specialized predicate formation and object display tools for new data types (e.g., images or text). 1 Introduction The Garlic project at the IBM Almaden Research Center [Care95] is developing a system and associated tools for managing large quantities of heterogeneous multimedia information. The goal of Garlic is to permit both traditional and multimedia data residing in a variety of existing data repositories ...

A decade of experience with research proposals as well as standardized query languages for the conventional Web and the recent emergence of query languages for the Semantic Web call for a reconsideration of design principles for Web and Semantic Web query languages. This article first argues that a new generation of versatile Web query languages is needed for solving the challenges posed by the changing Web: We call versatile those query languages able to cope with both Web and Semantic Web data expressed in any (Web or Semantic Web) markup language. This article further suggests that (well-known) referential transparency and (novel) answer-closedness are essential features of versatile query languages. Indeed, they allow queries to be considered like forms and answers like form-fillings in the spirit of the “query-by-example ” paradigm. This article finally suggests that the decentralized and heterogeneous nature of the Web requires incomplete data specifications (or “incomplete queries”) and incomplete data selections (or “incomplete answers”): the form-like query can be specified without precise knowledge of the queried data and answers can be restricted to contain only an excerpt of the queried data. 1.

The task of increasing the efficiency of database queries has recieved considerable attention. In this paper we describe the improvement of queries expressed as list comprehensions in a lazy functional language. The database literature identifies four algebraic and two implementation-based improvement strategies. For each strategy we show an equivalent improvement for queries expressed as list comprehensions. This means that welldeveloped database algorithms that improve queries using several of these strategies can be emulated to improve comprehension queries. We are also able to improve queries which require greater power than that provided by the relational algebra. Most of the improvements entail transforming a simple, inefficient query into a more complex, but more efficient form. We illustrate each improvement using examples drawn from the database literature. 1 Introduction The functional programming community is often accused of being too inward looking. Functional languages a...

QURSED enables the development of web-based query forms and reports (QFRs) that query and report semistructured XML data, i.e., data that are characterized by nesting, irregularities and structural variance. The query aspects of a QFR are captured by its query set specification, which formally encodes multiple parameterized condition fragments and can describe large numbers of queries. The run-time component of QURSED produces XQuery-compliant queries by synthesizing fragments from the query set specification that have been activated during the interaction of the end-user with the QFR. The design-time component of QURSED, called QURSED Editor, semi-automates the development of the query set specification and its association with the visual components of the QFR by translating visual actions into appropriate query set specifications. We describe QURSED and illustrate how it accommodates the intricacies that the semistructured nature of the underlying database introduces. We specifically focus on the formal model of the query set specification, its generation via the QURSED Editor and its coupling with the visual aspects of the web-based form and report. 1.

Syntax Q = fT N jEg E = E EjE Ej:EjT 2 RjA!Aj9T : R:Ej8T : R:E A = N jBjT [N ] op =! j ? j j j 6= j = 5.3 Semantic Domains T uple = List V al V al = Num+Bool + Unb Unb = T ide X Num Dbase = RIde ! Set T uple Env = T Ide ! T uple 5.4 Semantic Functions 5.4.1 j : Nmls ! V al Not specified 5.4.2 fi : Bools ! V al Not specified 5.4.3 Q : Query ! Dbase ! SetT uple Q[jfT N jEgj] ffi = fae[jT j]j ae 2 E[jEj] ffi fT ! unbtuplegg where unbtuple = null [jT j] j[jN j] 5.4.4 E : Exp ! Dbase ! Env ! Set Env E[jE 0 E 1 j] ffi ae = fae 1 jae 0 2 (E[jE 0 j]ffiae) ae 1 2 (E[jE 1 j]ffiae 0 )g E[jE 0 E 1 j] ffi ae = fae 0 jae 0 2 (E[jE 0 j]ffiae) ae 0 2 (E[jE 1 j]ffiae)g E[j:Ej] ffi ae = f ilter (E[jEj]ffiae) = OE ae E[jT 2 Rj] ffi ae = (unbtuple? ae[jT j] !fae \Phi fT 7! vgj v 2 ffi[jRj]g; f ilter (ae[jT j] 2 ffi[jRj]) ae) E[jA 0 ! A 1 j] ffi ae = \Theta [j!j] (A[jA 0 j]ae) (A[jA 1 j]ae) ae E[j9T : R:Ej] ffi ae = fae 1 jv 2 ffi[jRj] ae 1 2 (E[jEj] ffi ae \Phi fT 7! vg)g E[j8T : R:E...

The magnitude of data available on the web prompts the need for an easy to use query interface that enables users to integrate data from multiple web sources in an intelligent fashion. Past work in the area of databases has resulted in different query interface systems that simplify query formulation. While these approaches reduce the user’s effort to compose queries, the user is still required to pick data sources to use and the interaction is not guaranteed to yield a non-empty result set. We introduce a novel approach that exploits the structure of the relational data source(s) to formulate a set of constraints. These constraints are used in conjunction with partial plans to produce an intelligent query interface that (a) does not require the user to know details about data sources or existing values (b) suggests valid inputs to the user (c) creates consistent queries that always return values. ACM Classification Keywords