The document discusses the challenges and approaches related to querying heterogeneous datasets on the linked data web, focusing on the expressivity-usability trade-off in query mechanisms. It categorizes challenges such as query expressivity, usability, and entity reconciliation, while highlighting various approaches including information retrieval and natural language processing. The trends identified include semantic best-effort query models, user interaction mechanisms, and the integration of external knowledge sources for enhanced querying capabilities.

1. Digital Enterprise Research Institute www.deri.ie
Querying Heterogeneous Datasets on
the Linked Data Web:
Challenges, Approaches, and Trends
André Freitas, Edward Curry, João G. Oliveira,
Seán O’Riain
© Copyright 2009 Digital Enterprise Research Institute. All rights reserved.

2. IEEE Internet Computing
Digital Enterprise Research Institute www.deri.ie
A. Freitas, E. Curry, J. G.
Oliveira, and S. O’Riain,
“Querying Heterogeneous
Datasets on the Linked
Data Web: Challenges,
Approaches, and
Trends,”e  IEEE Internet
Computing, vol. 16, no. 1,
pp. 24-33, 2012.
http://doi.ieeecomputersociety.org/10.1109/MIC.2011.141
http://andrefreitas.org

3. Digital Enterprise Research Institute www.deri.ie
Motivation

4. Querying Data over the Web
Digital Enterprise Research Institute www.deri.ie
 We can see (a) natural language query over two search engines;
(b) corresponding SPARQL representation; and (c) semantic gap
between the user’s information needs and data representation.

5. Expressivity-Usability Trade-Off
Digital Enterprise Research Institute www.deri.ie
 Expressivity–usability trade-off for querying over structured data.
 Blue dots indicate an ideal query mechanism for linked data must
provide both high expressivity and high usability

6. Digital Enterprise Research Institute www.deri.ie
Challenges

7. Challenges
Digital Enterprise Research Institute www.deri.ie
 Analysis focuses on investigation of existing
approaches under the perspective of the
usability-expressivity trade-off.
 This focus guides the categorization and
analysis of existing challenges, approaches
and trends.

8. Challenge Dimensions
Digital Enterprise Research Institute www.deri.ie
 Query Expressivity
 Ability to query datasets by referencing elements
in data model structure, as well as to operate
over the data (aggregate results, express
conditional statements, etc.)
 Usability
 Easy-to-operate, intuitive, and task-efficient
query interface
 Vocabulary-level Semantic Matching
 Ability to semantically match user query terms to
dataset vocabulary-level terms

9. Challenge Dimensions
Digital Enterprise Research Institute www.deri.ie
 Entity Reconciliation
 Matches entities expressed in the query to
semantically equivalent dataset entities
 Semantic Tractability
 Ability to answer queries not supported by
explicit dataset statements
– For example, “Is Natalie Portman an Actress?” can be
supported by the statement “Natalie Portman starred
Star Wars,” instead of an explicit statement “Natalie
Portman occupation Actress,” which might not be
present in dataset

10. Digital Enterprise Research Institute www.deri.ie
Approaches

11. Approaches
Digital Enterprise Research Institute www.deri.ie
 Information Retrieval approaches
 Entity-centric search
 Structure search
 Natural Language approaches
 Question Answering
 Semantic best-effort natural language interfaces

12. Entity-Centric Search
Digital Enterprise Research Institute www.deri.ie
e.g. Sindice

13. Structure Search
Digital Enterprise Research Institute www.deri.ie
e.g. Semplore

14. Question Answering
Digital Enterprise Research Institute www.deri.ie
e.g. FreyA

15. Semantic Best-Effort/NL
Digital Enterprise Research Institute www.deri.ie
e.g. Treo

16. Comparative Analysis (Approaches)
Digital Enterprise Research Institute www.deri.ie

17. Addressing the Challenges
Digital Enterprise Research Institute www.deri.ie
 The functionality analysis of existing
approaches provides insights on how the
major challenges should be addressed.
 This set of strategic functionalities define
the set of trends.

18. Linked Data Web
Digital Enterprise Research Institute www.deri.ie

19. Digital Enterprise Research Institute www.deri.ie
Trends

20. Trends
Digital Enterprise Research Institute www.deri.ie
 Complementary Search and Query Services
 User Interaction and Feedback Mechanisms
 Semantic Best-Effort Query Model
 Natural Language Processing Techniques
 Distributional Semantic Model
 External Knowledge Sources for Semantic
Enrichment
 Integrated Entity Reconciliation Techniques

21. IEEE Internet Computing
Digital Enterprise Research Institute www.deri.ie
A. Freitas, E. Curry, J. G.
Oliveira, and S. O’Riain,
“Querying Heterogeneous
Datasets on the Linked
Data Web: Challenges,
Approaches, and
Trends,”e  IEEE Internet
Computing, vol. 16, no. 1,
pp. 24-33, 2012.
http://doi.ieeecomputersociety.org/10.1109/MIC.2011.141
http://andrefreitas.org

22. Further Reading
Digital Enterprise Research Institute www.deri.ie
 A. Freitas, E. Curry, J. G. Oliveira, and S. O’Riain, A Distributional
Structured Semantic Space for Querying RDF Graph Data, International
Journal of Semantic Computing, vol. 5, no. 4, pp. 433-462, 201
 S. O’Riain, E. Curry, and A. Harth, XBRL and Open Data for Global Financial
Ecosystems: A Linked Data Approach, International Journal of Accounting
Information Systems, vol. 13, no. 2, pp. 141-162, 2012.
 A. Freitas, E. Curry, and S. O'Riain, p A Distributional Approach for
Terminology-Level Semantic Search on the Linked Data Web, in 27th ACM
Symposium On Applied Computing (SAC 2012), 2012.
 A. Freitas, J. G. Oliveira, S. O'Riain, and E. Curry,WA Multidimensional
Semantic Space for Data Model Independent Queries over RDF Data, in
Fifth IEEE International Conference on Semantic Computing (ICSC 2011)
 A. Freitas, T. Knap, S. O’Riain, and E. Curry, W3P: Building an OPM based
provenance model for the Web, Future Generation Computer Systems, vol.
27, no. 6, pp. 766-774, Jun. 2011.