research-article

Wikidata Completeness Profiling Using ProWD

Authors:

Avicenna Wisesa,

Adila Krisnadhi,

Simon RazniewskiAuthors Info & Claims

K-CAP '19: Proceedings of the 10th International Conference on Knowledge Capture

Pages 123 - 130

https://doi.org/10.1145/3360901.3364425

Published: 23 September 2019 Publication History

Abstract

Completeness is a crucial data quality aspect that deals with the question: do we have all the data we need? The lack of awareness on the completeness state of a knowledge graph (KG) may result in bias or even falsity for any decisions made based on the KG. Given a KG, one may be wondering how its completeness may vary across different topics. In this paper, we present ProWD, a framework and tool for profiling the completeness of Wikidata, a central KG on the (Semantic) Web that is open and free to use. ProWD measures the degree of completeness based on the Class-Facet-Attribute (CFA) profiles. A class denotes a collection of entities, which can be of multiple facets, allowing attribute completeness to be analyzed and compared, e.g., how does the completeness of the attribute "educated at" and "date of birth" compare between male, German computer scientists, and female, Indonesian computer scientists? ProWD generates summaries and visualizations for such analysis, giving insights into the KG completeness. ProWD is available online at~\urlhttp://prowd.id.

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Digital Library

Cited By

Zhang YXiao G(2024)How to Implement a Knowledge Graph Completeness Assessment with the Guidance of User RequirementsJournal of Systems Engineering and Electronics10.23919/JSEE.2024.00004635:3(679-688)Online publication date: Jun-2024
https://doi.org/10.23919/JSEE.2024.000046
Zhang YXiao G(2024)Classification of Knowledge Graph Completeness Measurement TechniquesJournal of Systems Engineering and Electronics10.23919/JSEE.2023.00015035:1(154-162)Online publication date: Feb-2024
https://doi.org/10.23919/JSEE.2023.000150
Hamel OFareh M(2024)Deep sequence to sequence semantic embedding with attention for entity linking in context of incomplete linked dataEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108689134(108689)Online publication date: Aug-2024
https://doi.org/10.1016/j.engappai.2024.108689
Show More Cited By

Index Terms

Wikidata Completeness Profiling Using ProWD
1. Information systems
  1. Information systems applications
    1. Collaborative and social computing systems and tools
      1. Wikis
    2. Decision support systems
      1. Data analytics
  2. World Wide Web
    1. Web data description languages
      1. Semantic web description languages
        Resource Description Framework (RDF)

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Completeness and soundness guarantees for conjunctive SPARQL queries over RDF data sources with completeness statements¹

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Completeness Management for RDF Data Sources

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Published In

cover image ACM Conferences

K-CAP '19: Proceedings of the 10th International Conference on Knowledge Capture

September 2019

281 pages

ISBN:9781450370080

DOI:10.1145/3360901

General Chairs:
Mayank Kejriwal
University of Southern California Information Sciences Institute, USA
,
Pedro Szekely
University of Southern California Information Sciences Institute, USA
,
Program Chair:
Raphaël Troncy
EURECOM, France

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGAI: ACM Special Interest Group on Artificial Intelligence

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 September 2019

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Funding Sources

Universitas Indonesia
Free University of Bozen-Bolzano

Conference

K-CAP '19

Sponsor:

SIGAI

K-CAP '19: Knowledge Capture Conference

November 19 - 21, 2019

CA, Marina Del Rey, USA

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Overall Acceptance Rate 55 of 198 submissions, 28%

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Cited By

Zhang YXiao G(2024)How to Implement a Knowledge Graph Completeness Assessment with the Guidance of User RequirementsJournal of Systems Engineering and Electronics10.23919/JSEE.2024.00004635:3(679-688)Online publication date: Jun-2024
https://doi.org/10.23919/JSEE.2024.000046
Zhang YXiao G(2024)Classification of Knowledge Graph Completeness Measurement TechniquesJournal of Systems Engineering and Electronics10.23919/JSEE.2023.00015035:1(154-162)Online publication date: Feb-2024
https://doi.org/10.23919/JSEE.2023.000150
Hamel OFareh M(2024)Deep sequence to sequence semantic embedding with attention for entity linking in context of incomplete linked dataEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108689134(108689)Online publication date: Aug-2024
https://doi.org/10.1016/j.engappai.2024.108689
Chen HPieptea LDing J(2022)Construction and Evaluation of a High-Quality Corpus for Legal Intelligence Using Semiautomated ApproachesIEEE Transactions on Reliability10.1109/TR.2022.315612671:2(657-673)Online publication date: Jun-2022
https://doi.org/10.1109/TR.2022.3156126
Abián DMeroño-Peñuela ASimperl E(2022)An Analysis of Content Gaps Versus User Needs in the Wikidata Knowledge GraphThe Semantic Web – ISWC 202210.1007/978-3-031-19433-7_21(354-374)Online publication date: 16-Oct-2022
https://doi.org/10.1007/978-3-031-19433-7_21
Arnaout HRazniewski SWeikum GPan J(2021)Negative Knowledge for Open-world WikidataCompanion Proceedings of the Web Conference 202110.1145/3442442.3452339(544-551)Online publication date: 19-Apr-2021
https://dl.acm.org/doi/10.1145/3442442.3452339

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