research-article

Discovery querying in linked open data

Authors:

Stefan Hagedorn,

Kai-Uwe SattlerAuthors Info & Claims

EDBT '13: Proceedings of the Joint EDBT/ICDT 2013 Workshops

Pages 38 - 44

https://doi.org/10.1145/2457317.2457324

Published: 18 March 2013 Publication History

Abstract

The problem of the inability of machines to interpret and process information published on web pages caused the development of a web of data, next to the web of documents. The idea is known as the Semantic Web, where links between information are established in a way that machines can understand and interpret. With its development, new applications were introduced to query and process this linked data. Additionally the open data initiative was launched with the goal to publish governmental, scientific, and cultural data freely accessible on the web. Often, this open data is offered in a semi-structured form, like CSV files, but can also be transformed into linked data format. With this linked open data, programs can be created that efficiently process queries and find information.

This work is supposed to integrate the support for discovery queries into an existing LOD cache engine. The goal is to develop a new approach that processes SPARQL queries and augments the result with discovered information from different (online) sources. Thus, the approach can help users to explore new information and knowledge more easily. Users should not worry about what particular data is stored locally and which identifiers are used. To do so, we plan to extend the rewriting process during logical optimization of SPARQL queries.

References

[1]

G. Akrivas, M. Wallace, G. Andreou, G. Stamou, and S. Kollias. Context-sensitive semantic query expansion. In ICAIS, pages 109--114. IEEE Comput. Soc, 2002.

Digital Library

[2]

H. Blau, N. Immerman, and D. Jensen. A Visual Query Language for Relational Knowledge Discovery TITLE2:. Technical report, Amherst, MA, USA, 2001.

Digital Library

[3]

A. Bozzon, M. Brambilla, S. Ceri, and P. Fraternali. Liquid Query: Multi-Domain Exploratory Search on the Web. In Interfaces, WWW '10, pages 161--170. ACM Press, 2010.

Digital Library

[4]

K. Braunschweig, J. Eberius, M. Thiele, and W. Lehner. The State of Open Data - Limits of Current Open Data Platforms. In Web Science Track at WWW'12, Lyon, France, 2012.

[5]

H. Cao, D. H. Hu, D. Shen, D. Jiang, J.-T. Sun, E. Chen, and Q. Yang. Context-aware query classification. ACM SIGIR, 106(3):3, 2009.

Digital Library

[6]

N. Cercone, J. Han, Y. Huang, and Y. Fu. Intelligent Query Answering by Knowledge Discovery Techniques. TKDE, 8(3):373--390, June 1996.

Digital Library

[7]

J. Eberius, M. Thiele, K. Braunschweig, and W. Lehner. DrillBeyond: enabling business analysts to explore the web of open data. Proc. VLDB Endow., 5(12):1978--1981, Aug. 2012.

Digital Library

[8]

B. Fitzpatrick. Distributed caching with memcached. Linux Journal, 2004(124):5, Aug. 2004.

Digital Library

[9]

S. Gao, H. Fu, and K. Anyanwu. An agglomerative query model for discovery in linked data: semantics and approach. In WebDB, WebDB '10, pages 2:1--2:6, New York, NY, USA, 2010. ACM.

Digital Library

[10]

Google. Introducing the Knowledge Graph: things, not strings. http://insidesearch.blogspot.de/2012/05/introducing-knowledge-graph-things-not.html {Online. Last accessed: January 6th, 2013}, 2012.

[11]

A. Halevy, M. Franklin, and D. Maier. Principles of dataspace systems. In SIGMOD, PODS '06, pages 1--9, New York, NY, USA, 2006. ACM.

Digital Library

[12]

A. Harth, K. Hose, M. Karnstedt, A. Polleres, K.-U. Sattler, and J. Umbrich. Data summaries for on-demand queries over linked data. In WWW '10, page 411, New York, USA, Apr. 2010. ACM Press.

Digital Library

[13]

O. Hartig, C. Bizer, and J.-c. Freytag. Executing SPARQL Queries over the Web of Linked Data. The Semantic WebISWC 2009, 5823(9-10):293--309, 2009.

Digital Library

[14]

R. Jones, B. Rey, O. Madani, and W. Greiner. Generating query substitutions. In WWW '06, page 387, New York, USA, May 2006. ACM Press.

Digital Library

[15]

A. Kadlag, A. V. Wanjari, J. Freire, and J. R. Haritsa. Supporting Exploratory Queries in Databases. In DASFAA, pages 594--605, 2004.

[16]

T. B. Lee. Linked Data - Design Issues. http://www.w3.org/DesignIssues/LinkedData.html {Online. Last accessed: January 17th, 2013}, 2009.

[17]

G. Marchionini. Exploratory search. Communications of the ACM, 49(4):41, Apr. 2006.

Digital Library

[18]

J. Umbrich, M. Karnstedt, J. X. Parreira, A. Polleres, and M. Hauswirth. Linked Data and Live Querying for Enabling Support Platforms for Web Dataspaces. In DESWEB, Washington DC, USA, Apr. 2012.

Digital Library

Cited By

Sohn MJeong SKim JLee H(2015)Augmented context-based recommendation service framework using knowledge over the Linked Open Data cloudPervasive and Mobile Computing10.1016/j.pmcj.2015.07.00924:C(166-178)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1016/j.pmcj.2015.07.009
Im SSohn MJeong SLee H(2014)Keyword-Based SPARQL Query Generation System to Improve Semantic Tractability on LOD CloudProceedings of the 2014 Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing10.1109/IMIS.2014.95(102-109)Online publication date: 2-Jul-2014
https://dl.acm.org/doi/10.1109/IMIS.2014.95

Index Terms

Discovery querying in linked open data
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
  2. Information retrieval
    1. Information retrieval query processing
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

Recommendations

Query Processing in a Mediator Based Framework for Linked Data Integration

In this paper, the authors present a three-level mediator based framework for linked data integration. In the approach, the mediated schema is represented by a domain ontology, which provides a conceptual representation of the application. Each relevant ...
An Investigative Study on the Quality Aspects of Linked Open Data
CCIOT '18: Proceedings of the 2018 International Conference on Cloud Computing and Internet of Things

Linked Open Data refers to a set of best practices that empowers enterprises to publish and interlink their data using existing ontologies on the Semantic Web. The focus of linked open data is to move from document-based Web to a Web of interlinked data,...
Querying data provenance
SIGMOD '10: Proceedings of the 2010 ACM SIGMOD International Conference on Management of data

Many advanced data management operations (e.g., incremental maintenance, trust assessment, debugging schema mappings, keyword search over databases, or query answering in probabilistic databases), involve computations that look at how a tuple was ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

EDBT '13: Proceedings of the Joint EDBT/ICDT 2013 Workshops

March 2013

423 pages

ISBN:9781450315999

DOI:10.1145/2457317

General Chair:
Giovanna Guerrini
Università di Genova, Italy

Copyright © 2013 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 ACM 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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 March 2013

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

EDBT/ICDT '13

EDBT/ICDT '13: Joint 2013 EDBT/ICDT Conferences

March 18 - 22, 2013

Genoa, Italy

Acceptance Rates

EDBT '13 Paper Acceptance Rate 7 of 10 submissions, 70%;

Overall Acceptance Rate 7 of 10 submissions, 70%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
287
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)0

Reflects downloads up to 20 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Sohn MJeong SKim JLee H(2015)Augmented context-based recommendation service framework using knowledge over the Linked Open Data cloudPervasive and Mobile Computing10.1016/j.pmcj.2015.07.00924:C(166-178)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1016/j.pmcj.2015.07.009
Im SSohn MJeong SLee H(2014)Keyword-Based SPARQL Query Generation System to Improve Semantic Tractability on LOD CloudProceedings of the 2014 Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing10.1109/IMIS.2014.95(102-109)Online publication date: 2-Jul-2014
https://dl.acm.org/doi/10.1109/IMIS.2014.95

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents