Ontological Multidimensional Data Models and Contextual Data Quality

Author:

Bertossi Leopoldo1,Milani Mostafa2

Affiliation:

1. Carleton University

2. McMaster University

Abstract

Data quality assessment and data cleaning are context-dependent activities. Motivated by this observation, we propose the Ontological Multidimensional Data Model (OMD model), which can be used to model and represent contexts as logic-based ontologies. The data under assessment are mapped into the context for additional analysis, processing, and quality data extraction. The resulting contexts allow for the representation of dimensions , and multidimensional data quality assessment becomes possible. At the core of a multidimensional context, we include a generalized multidimensional data model and a Datalog ± ontology with provably good properties in terms of query answering . These main components are used to represent dimension hierarchies, dimensional constraints, and dimensional rules and define predicates for quality data specification. Query answering relies on and triggers navigation through dimension hierarchies and becomes the basic tool for the extraction of quality data. The OMD model is interesting per se beyond applications to data quality. It allows for a logic-based and computationally tractable representation of multidimensional data, extending previous multidimensional data models with additional expressive power and functionalities.

Funder

NSERC Discovery

NSERC Strategic Network on Business Intelligence

Publisher

Association for Computing Machinery (ACM)

Subject

Information Systems and Management,Information Systems

Reference91 articles.

1. S. Abiteboul R. Hull and V. Vianu. 1995. Foundations of Databases. Addison-Wesley. S. Abiteboul R. Hull and V. Vianu. 1995. Foundations of Databases. Addison-Wesley.

2. Disjunctive datalog with existential quantifiers: Semantics, decidability, and complexity issues

3. Magic-Sets for Datalog with Existential Quantifiers

4. Contextualization as an independent abstraction mechanism for conceptual modeling

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3