Conflict resolution with data currency and consistency

Wenfei Fan, Floris Geerts, Nan Tang, Wenyuan Yu

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

This article introduces a new approach for conflict resolution: given a set of tuples pertaining to the same entity, it identifies a single tuple in which each attribute has the latest and consistent value in the set. This problem is important in data integration, data cleaning, and query answering. It is, however, challenging since in practice, reliable time stamps are often absent, among other things. We propose a model for conflict resolution by specifying data currency in terms of partial currency orders and currency constraints and by enforcing data consistency with constant conditional functional dependencies.We show that identifying data currency orders helps us repair inconsistent data, and vice versa. We investigate a number of fundamental problems associated with conflict resolution and establish their complexity. In addition, we introduce a framework and develop algorithms for conflict resolution by integrating data currency and consistency inferences into a single process and by interacting with users. We experimentally verify the accuracy and efficiency of our methods using real-life and synthetic data.

Original languageEnglish
Article number6
JournalJournal of Data and Information Quality
Volume5
Issue number1-2
DOIs
Publication statusPublished - 1 Jan 2014

Fingerprint

Data integration
Cleaning
Repair
Conflict resolution
Currency

Keywords

  • Conditional functional dependency
  • Currency constraints
  • Data cleaning

ASJC Scopus subject areas

  • Information Systems and Management
  • Information Systems

Cite this

Conflict resolution with data currency and consistency. / Fan, Wenfei; Geerts, Floris; Tang, Nan; Yu, Wenyuan.

In: Journal of Data and Information Quality, Vol. 5, No. 1-2, 6, 01.01.2014.

Research output: Contribution to journalArticle

Fan, Wenfei ; Geerts, Floris ; Tang, Nan ; Yu, Wenyuan. / Conflict resolution with data currency and consistency. In: Journal of Data and Information Quality. 2014 ; Vol. 5, No. 1-2.
@article{a62831753d4647dd909cf7e1fc4c475e,
title = "Conflict resolution with data currency and consistency",
abstract = "This article introduces a new approach for conflict resolution: given a set of tuples pertaining to the same entity, it identifies a single tuple in which each attribute has the latest and consistent value in the set. This problem is important in data integration, data cleaning, and query answering. It is, however, challenging since in practice, reliable time stamps are often absent, among other things. We propose a model for conflict resolution by specifying data currency in terms of partial currency orders and currency constraints and by enforcing data consistency with constant conditional functional dependencies.We show that identifying data currency orders helps us repair inconsistent data, and vice versa. We investigate a number of fundamental problems associated with conflict resolution and establish their complexity. In addition, we introduce a framework and develop algorithms for conflict resolution by integrating data currency and consistency inferences into a single process and by interacting with users. We experimentally verify the accuracy and efficiency of our methods using real-life and synthetic data.",
keywords = "Conditional functional dependency, Currency constraints, Data cleaning",
author = "Wenfei Fan and Floris Geerts and Nan Tang and Wenyuan Yu",
year = "2014",
month = "1",
day = "1",
doi = "10.1145/2631923",
language = "English",
volume = "5",
journal = "Journal of Data and Information Quality",
issn = "1936-1955",
publisher = "Association for Computing Machinery (ACM)",
number = "1-2",

}

TY - JOUR

T1 - Conflict resolution with data currency and consistency

AU - Fan, Wenfei

AU - Geerts, Floris

AU - Tang, Nan

AU - Yu, Wenyuan

PY - 2014/1/1

Y1 - 2014/1/1

N2 - This article introduces a new approach for conflict resolution: given a set of tuples pertaining to the same entity, it identifies a single tuple in which each attribute has the latest and consistent value in the set. This problem is important in data integration, data cleaning, and query answering. It is, however, challenging since in practice, reliable time stamps are often absent, among other things. We propose a model for conflict resolution by specifying data currency in terms of partial currency orders and currency constraints and by enforcing data consistency with constant conditional functional dependencies.We show that identifying data currency orders helps us repair inconsistent data, and vice versa. We investigate a number of fundamental problems associated with conflict resolution and establish their complexity. In addition, we introduce a framework and develop algorithms for conflict resolution by integrating data currency and consistency inferences into a single process and by interacting with users. We experimentally verify the accuracy and efficiency of our methods using real-life and synthetic data.

AB - This article introduces a new approach for conflict resolution: given a set of tuples pertaining to the same entity, it identifies a single tuple in which each attribute has the latest and consistent value in the set. This problem is important in data integration, data cleaning, and query answering. It is, however, challenging since in practice, reliable time stamps are often absent, among other things. We propose a model for conflict resolution by specifying data currency in terms of partial currency orders and currency constraints and by enforcing data consistency with constant conditional functional dependencies.We show that identifying data currency orders helps us repair inconsistent data, and vice versa. We investigate a number of fundamental problems associated with conflict resolution and establish their complexity. In addition, we introduce a framework and develop algorithms for conflict resolution by integrating data currency and consistency inferences into a single process and by interacting with users. We experimentally verify the accuracy and efficiency of our methods using real-life and synthetic data.

KW - Conditional functional dependency

KW - Currency constraints

KW - Data cleaning

UR - http://www.scopus.com/inward/record.url?scp=84907031191&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84907031191&partnerID=8YFLogxK

U2 - 10.1145/2631923

DO - 10.1145/2631923

M3 - Article

VL - 5

JO - Journal of Data and Information Quality

JF - Journal of Data and Information Quality

SN - 1936-1955

IS - 1-2

M1 - 6

ER -