Ontology Mapping and SPARQL Rewriting for Querying Federated RDF Data Sources

Makris, Konstantinos; Gioldasis, Nektarios; Bikakis, Nikos; Christodoulakis, Stavros

doi:10.1007/978-3-642-16949-6_32

Cited by 25 publications

(19 citation statements)

References 8 publications

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“…al. [5] is quite close to our approach. A formal model for RDF triple patterns rewriting is defined.…”

Section: State Of the Artsupporting

confidence: 83%

Incremental SPARQL Query Processing

Torre-Bastida

2013

The Semantic Web: Semantics and Big Data

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Abstract. The number of linked data sources available on the Web is growing at a rapid rate. Moreover, users are showing an interest for any framework that allows them to obtain answers, for a formulated query, accessing heterogeneous data sources without the need of explicitly specifying the sources to answer the query. Our proposal focus on that interest and its goal is to build a system capable of answering to user queries in an incremental way. Each time a different data source is accessed the previous answer is eventually enriched. Brokering across the data sources is enabled by using source mapping relationships. User queries are rewritten using those mappings in order to obtain translations of the original query across data sources. Semantically equivalent translations are first looked for, but semantically approximated ones are generated if equivalence is not achieved. Well defined metrics are considered to estimate the information loss, if any.Keywords: Semantic Web, Linked Open Data Sources, query reformulation, query rewriting, ontology mapping. Problem Statement and Research QuestionThe Linked Open Data (LOD) initiative has made available to the users a large number of data sources from various domains such as education, life sciences, government data, literature, geography and others. Two commonly used approaches for query processing in this context are: 1) to query the different data sources independently, one by one; or 2) to integrate first the data sources into a local centralized warehouse and then to process queries in a centralized way on the warehouse. Both approaches present relevant problems such as the user needed expertise following the first approach and the scalability problems that arise in the second one. In this scenario an alternative approach is appearing, the so called federated approach, in which a query is formulated and its answer is obtained from different sources but with the distinguishing feature that the technical details associated to the distributed query answering process are transparent to the user. The work developed in this thesis is placed in this approach, but our system will have the added feature that the user does not need to have specific knowledge of the language in whichthe different data sources are modeled. We summarize our research question as the following one: How P.

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“…al. [5] is quite close to our approach. A formal model for RDF triple patterns rewriting is defined.…”

Section: State Of the Artsupporting

confidence: 83%

Incremental SPARQL Query Processing

Torre-Bastida

2013

The Semantic Web: Semantics and Big Data

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show abstract

“…Alignments implement a specific alignment format, as specified by the authors. Still, [17] authors do not clearly justify the need of this alignment format. Their approach is further detailed in [18], notably by defining several functions for graph pattern rewriting.…”

Section: Related Workmentioning

confidence: 83%

“…When comparing both methods, [17] has the advantage of relying on Description Logic, and consequently supporting different query types (SELECT, CONSTRUCT, etc.) along with different SPARQL solution modifiers (LIMIT, ORDER BY, etc.).…”

Section: Related Workmentioning

confidence: 99%

“…Correndo et al [19] provide an explanation for SPARQL query rewriting implementation for ontology interoperation by stating that ontology alignments defined on top of the logical layer imply reasoning over a considerable amount of data thus compromising query execution time. Approaches presented in [17] [19] represent successful optimizations of query execution times. Still, their main drawbacks concern addressing the possibility for writing queries using terms from different ontologies, along with offering extended inference capabilities (e.g.…”

Section: Related Workmentioning

confidence: 99%

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FOWLA, A Federated Architecture for Ontologies

Farias¹,

Roxin²,

Nicolle³

2015

Rule Technologies: Foundations, Tools, and Applications

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Abstract. The progress of information and communication technologies has greatly increased the quantity of data to process. Thus, managing data heterogeneity is a problem nowadays. In the 1980s, the concept of a Federated Database Architecture (FDBA) was introduced as a collection of components to unite loosely coupled federation. Semantic web technologies mitigate the data heterogeneity problem, however due to the data structure heterogeneity the integration of several ontologies is still a complex task. For tackling this problem, we propose a loosely coupled federated ontology architecture (FOWLA). Our approach allows the coexistence of various ontologies sharing common data dynamically at query execution through logical rules. We have illustrated the advantages of adopting our approach through several examples and benchmarks. We also compare our approach with other existing initiatives.Keywords: SWRL · Horn-like rules · Federated ontology architecture · OWL · SPARQL · Backward-chaining reasoning · Semantic interoperability IntroductionWith advances of the information and communication technologies the amount of data to process and share has exponentially increased. Consequently, there is a growing demand for information interoperability. Indeed, with the advent of the personal computer in the 1980s, data interoperability first became an issue, then with the advent of the Internet has risen the need for more principled mechanisms for interoperability. When considering enterprise information systems, three layers of interoperability exist. Physical interoperability (first level) concerns the lower levels of the ISO/OSI network hierarchy and has been solved through network protocols such as Ethernet and TCP/IP. The second level concerns syntactic interoperability, namely the form of the messages exchanged in the information system. This issue has been solved through syntactic standards such as the Extensible Markup Language (XML)[6]. Finally, the third level of interoperability addresses the meaning of the exchanged messages and is called semantic interoperability. When implemented, semantic interoperability allows automatic machine-processing of data. These advances are really important in the context of enterprise information integration (EII) [1], building information models [2] and more in general in semantic web. Ontologies defined using

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“…However, vocabulary level heterogeneity must be resolved to process keyword based queries in a federation. SPARQL query rewriting is one approach for resolving vocabulary level heterogeneity [17], [18], [19]. The input query must be written in SPARQL using a specific vocabulary for applying this solution.…”

mentioning

confidence: 99%

Path index based keywords to SPARQL query transformation for semantic data federations

Cooray

Wikramanayake

2016

Int J on Adv. in ICT for Emerging Countries

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Abstract-Semantic web is a highly emerging research domain. Enhancing the ability of keyword query processing on Semantic Web data provides a huge support for familiarizing the usefulness of Semantic Web to the general public. Most of the existing approaches focus on just user keyword matching to RDF graphs and output the connecting elements as results. Semantic Web consists of SPARQL query language which can process queries more accurately and efficiently than general keyword matching. There are only about a couple of approaches available for transforming keyword queries to SPARQL. They basically rely on real time graph traversals? for identifying subgraphs which can connect user keywords. Those approaches are either limited to query processing on a single data store or a set of interlinked data sets. They have not focused on query processing on a federation of independent data sets which belongs to the same domain. This research proposes a Path Index based approach eliminating real time graph traversal for transforming keyword queries to SPARQL. We have introduced an ontology alignment based approach for keyword query transforming on a federation of RDF data stored using multiple heterogeneous vocabularies. Evaluation shows that the proposed approach have the ability to generate SPARQL queries which can provide highly relevant results for user keyword queries. The Path Index based query transformation approach has also achieved high efficiency compared to the existing approach.

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Ontology Mapping and SPARQL Rewriting for Querying Federated RDF Data Sources

Cited by 25 publications

References 8 publications

Incremental SPARQL Query Processing

Incremental SPARQL Query Processing

FOWLA, A Federated Architecture for Ontologies

Path index based keywords to SPARQL query transformation for semantic data federations

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