Poor data quality (DQ) can have substantial social and economic impacts. Although firms are improving data quality with practical approaches and tools, their improvement efforts tend to focus narrowly on accuracy. We believe that data consumers have a much broader data quality conceptualization than IS professionals realize. The purpose of this paper is to develop a framework that captures the aspects of data quality that are important to data consumers.A two-stage survey and a two-phase sorting study were conducted to develop a hierarchical framework for organizing data quality dimensions. This framework captures dimensions of data quality that are important to data consumers. Intrinsic DQ denotes that data have quality in their own right. Contextual DQ highlights the requirement that data quality must be considered within the context of the task at hand. Representational DQ and accessibility DQ emphasize the importance of the role of systems. These findings are consistent with our understanding that high-quality data should be intrinsically good, contextually appropriate for the task, clearly represented, and accessible to the data consumer.Our framework has been used effectively in industry and government. Using this framework, IS managers were able to better understand and meet their data consumers' data quality needs. The salient feature of this research study is that quality attributes of data are collected from data consumers instead of being defined theoretically or based on researchers' experience. Although exploratory, this research provides a basis for future studies that measure data quality along the dimensions of this framework.

https://courses.washington.edu/geog482/resource/14_Beyond_Accuracy.pdf

Beyond accuracy: what data quality means to data consumers

Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mappings has been the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping.

/pdf/ontology-mapping-the-state-of-the-art-91mok9nz44.pdf

Ontology mapping: the state of the art

This paper attempts to define an object-oriented database system It describes the main features and characteristics that a system must have to qualify as an object-oriented database system

We have separated these characteristics into three groups: 
•	
Mandatory, the ones the system must satisfy in order to be termed an object-oriented database system These are complex objects, object identity, encapsulation, types or classes, inheritance, overriding combined with late binding, extensibility, computational completeness, persistence, secondary storage management, concurrency, recovery and an ad hoc query facility

•	
Optional, the ones that can be added to make the system better, but which are not mandatory These are multiple inheritance, type checking and inferencing, distribution, design transactions and versions

•	
Open, the points where the designer can make a number of choices These are the programming paradigm, the representation system, the type system, and uniformity




We have taken a position, not so much expecting it to be the final word as to erect a provisional landmark to orient further debate

The object-oriented database system manifesto

Ontology mapping is seen as a solution provider in today's landscape of ontology
research. As the number of ontologies that are made publicly available and
accessible on the Web increases steadily, so does the need for applications to use
them. A single ontology is no longer enough to support the tasks envisaged by a 
distributed environment like the Semantic Web. Multiple ontologies need to be 
accessed from several applications. Mapping could provide a common layer from which
several ontologies could be accessed and hence could exchange information in 
semantically sound manners. Developing such mapping has beeb the focus of a variety
of works originating from diverse communities over a number of years. In this
article we comprehensively review and present these works. We also provide insights
on the pragmatics of ontology mapping and elaborate on a theoretical approach for
defining ontology mapping.

https://drops.dagstuhl.de/opus/volltexte/2005/40/pdf/04391.KalfoglouYannis.Paper.40.pdf/

Ontology Mapping: The State of the Art

After more than 20 years of research and practice in software configuration management (SCM), constructing consistent configurations of versioned software products still remains a challenge. This article focuses on the version models underlying both commercial systems and research prototypes. It provides an overview and classification of different versioning paradigms and defines and relates fundamental concepts such as revisions, variants, configurations, and changes. In particular, we focus on intensional versioning, that is, construction of versions based on configuration rules. Finally, we provide an overview of systems that have had significant impact on the development of the SCM discipline and classify them according to a detailed taxonomy.

/pdf/version-models-for-software-configuration-management-1tcwwh2q9y.pdf

Version models for software configuration management

Large organizations need to exchange information among many separately developed systems. In order for this exchange to be useful, the individual systems must agree on the meaning of their exchanged data. That is, the organization must ensure semantic interoperability. This paper provides a theory of semantic values as a unit of exchange that facilitates semantic interoperability betweeen heterogeneous information systems. We show how semantic values can either be stored explicitly or be defined by environments. A system architecture is presented that allows autonomous components to share semantic values. The key component in this architecture is called the context mediator, whose job is to identify and construct the semantic values being sent, to determine when the exchange is meaningful, and to convert the semantic values to the form required by the receiver.Our theory is then applied to the relational model. We provide an interpretation of standard SQL queries in which context conversions and manipulations are transparent to the user. We also introduce an extension of SQL, called Context-SQL (C-SQL), in which the context of a semantic value can be explicitly accessed and updated. Finally, we describe the implementation of a prototype context mediator for a relational C-SQL system.

/pdf/using-semantic-values-to-facilitate-interoperability-among-3qqp303is6.pdf

Using semantic values to facilitate interoperability among heterogeneous information systems

Many database applications require the storage and manipulation of different versions of data objects. To satisfy the diverse needs of these applications, current database systems support versioning at a very low level. This article demonstrates that application-independent versioning can be supported at a significantly higher level. In particular, we extend the EXTRA data model and EXCESS query language so that configurations can be specified conceptually and non-procedurally. We also show how version sets can be viewed multidimensionally, thereby allowing configurations to be expressed at a higher level of abstraction. The resulting model integrates and generalizes ideas in CAD systems, CASE systems, and temporal databases.

/pdf/versioning-and-configuration-management-in-an-object-1lus7rxt4c.pdf

Versioning and configuration management in an object-oriented data model

The use of inference rules to support intelligent data processing is an increasingly important tool in many areas of computer science. In database systems, rules are used in semantic query optimization as a method for reducing query processing costs. The savings is dependent on the ability of experts to supply a set of useful rules and the ability of the optimizer to quickly find the appropriate transformations generated by these rules. Unfortunately, the most useful rules are not always those that would or could be specified by an expert. This paper describes the architecture of a system having two interrelated components: a combined conventional/semantic query optimizer, and an automatic rule deriver.Our automatic rule derivation method uses intermediate results from the optimization process to direct the search for learning new rules. Unlike a system employing only user-specified rules, a system with an automatic capability can derive rules that may be true only in the current state of the database and can modify the rule set to reflect changes in the database and its usage pattern.This system has been implemented as an extension of the EXODUS conventional query optimizer generator. We describe the implementation, and show how semantic query optimization is an extension of conventional optimization in this context.

A method for automatic rule derivation to support semantic query optimization

Access . permissions in a data warehouse are currently managed in a separate world from the sources’ policies. The consequences are inconsistencies, slow response to change, and wasted administrative work. We present a different approach, which treats the sources’ exported tables and the warehouse as part of the same distributed database. Our main result is a way to control derived products by extending SQL grants rather than creating entirely new mechanisms. We provide a powerful, sound inference theory that derives permissions on warehouse tables (both materialized and virtual), making the system easier to administer and its applications more robust. We also propose a new permission construct suitable for views that filter data from mutually-suspicious parties.

/pdf/view-security-as-the-basis-for-data-warehouse-security-8fpghfvafx.pdf

View Security as the Basis for Data Warehouse Security

The concept of annotation from object-oriented languages is adapted to object-oriented databases. It is shown how annotations can be used to model activities such as constraint checking, default values, and triggers. Annotations also are an appropriate way to model different versioning concepts. This paper discusses three kinds of versioning—histories, revisions, and alternatives—and demonstrates how each one can be modeled effectively using annotations. The use of annotations also allows other kinds of versioning to be defined extensibly, and arbitrary combinations of versions can be handled easily.

Edward Sciore

Papers

Using semantic values to facilitate interoperability among heterogeneous information systems

Versioning and configuration management in an object-oriented data model

A method for automatic rule derivation to support semantic query optimization

View Security as the Basis for Data Warehouse Security

Using annotations to support multiple kinds of versioning in an object-oriented database system