A framework for evaluating semantic metadata

Yuangui Lei; Victoria Uren; Enrico Motta

doi:10.1145/1298406.1298431

A framework for evaluating semantic metadata

Yuangui Lei
, Victoria Uren
, Enrico Motta

Open University

Research output: Chapter in Book/Published conference output › Conference publication

21 Citations (SciVal)

Abstract

Because poor quality semantic metadata can destroy the effectiveness of semantic web technology by hampering applications from producing accurate results, it is important to have frameworks that support their evaluation. However, there is no such framework developedto date. In this context, we proposed i) an evaluation reference model, SemRef, which sketches some fundamental principles for evaluating semantic metadata, and ii) an evaluation framework, SemEval, which provides a set of instruments to support the detection of quality problems and the collection of quality metrics for these problems. A preliminary case study of SemEval shows encouraging results.

Original language	English
Title of host publication	K-CAP '07 - proceedings of the 4th international conference on Knowledge capture
Editors	Derek Sleeman, Ken Barker
Place of Publication	New York, NY (US)
Publisher	ACM
Pages	135-142
Number of pages	8
ISBN (Print)	978-1-59593-643-1
DOIs	https://doi.org/10.1145/1298406.1298431
Publication status	Published - 28 Oct 2007
Event	4th International Conference on Knowledge Capture - Whistler, BC, Canada Duration: 28 Oct 2007 → 31 Oct 2007

Conference

Conference	4th International Conference on Knowledge Capture
Abbreviated title	K-CAP'07
Country/Territory	Canada
City	Whistler, BC
Period	28/10/07 → 31/10/07

Access to Document

10.1145/1298406.1298431

Cite this

@inproceedings{6807b8415b5d4b92bdaa5c5d3f7d06b0,

title = "A framework for evaluating semantic metadata",

abstract = "Because poor quality semantic metadata can destroy the effectiveness of semantic web technology by hampering applications from producing accurate results, it is important to have frameworks that support their evaluation. However, there is no such framework developedto date. In this context, we proposed i) an evaluation reference model, SemRef, which sketches some fundamental principles for evaluating semantic metadata, and ii) an evaluation framework, SemEval, which provides a set of instruments to support the detection of quality problems and the collection of quality metrics for these problems. A preliminary case study of SemEval shows encouraging results.",

author = "Yuangui Lei and Victoria Uren and Enrico Motta",

year = "2007",

month = oct,

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doi = "10.1145/1298406.1298431",

language = "English",

isbn = "978-1-59593-643-1",

pages = "135--142",

editor = "Derek Sleeman and Ken Barker",

booktitle = "K-CAP '07 - proceedings of the 4th international conference on Knowledge capture",

publisher = "ACM",

address = "United States",

note = "4th International Conference on Knowledge Capture, K-CAP'07 ; Conference date: 28-10-2007 Through 31-10-2007",

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T1 - A framework for evaluating semantic metadata

AU - Lei, Yuangui

AU - Uren, Victoria

AU - Motta, Enrico

PY - 2007/10/28

Y1 - 2007/10/28

N2 - Because poor quality semantic metadata can destroy the effectiveness of semantic web technology by hampering applications from producing accurate results, it is important to have frameworks that support their evaluation. However, there is no such framework developedto date. In this context, we proposed i) an evaluation reference model, SemRef, which sketches some fundamental principles for evaluating semantic metadata, and ii) an evaluation framework, SemEval, which provides a set of instruments to support the detection of quality problems and the collection of quality metrics for these problems. A preliminary case study of SemEval shows encouraging results.

AB - Because poor quality semantic metadata can destroy the effectiveness of semantic web technology by hampering applications from producing accurate results, it is important to have frameworks that support their evaluation. However, there is no such framework developedto date. In this context, we proposed i) an evaluation reference model, SemRef, which sketches some fundamental principles for evaluating semantic metadata, and ii) an evaluation framework, SemEval, which provides a set of instruments to support the detection of quality problems and the collection of quality metrics for these problems. A preliminary case study of SemEval shows encouraging results.

UR - http://dl.acm.org/citation.cfm?doid=1298406.1298431

U2 - 10.1145/1298406.1298431

DO - 10.1145/1298406.1298431

M3 - Conference publication

SN - 978-1-59593-643-1

SP - 135

EP - 142

BT - K-CAP '07 - proceedings of the 4th international conference on Knowledge capture

A2 - Sleeman, Derek

A2 - Barker, Ken

PB - ACM

CY - New York, NY (US)

T2 - 4th International Conference on Knowledge Capture

Y2 - 28 October 2007 through 31 October 2007

ER -

A framework for evaluating semantic metadata

Abstract

Conference

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