Ontology-based data access – Beyond relational sources

Botoeva, Elena; Calvanese, Diego; Cogrel, Benjamin; Corman, Julien; Xiao, Guohui

doi:10.3233/ia-190023

Cited by 10 publications

(8 citation statements)

References 14 publications

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“…SPARQL Generate [42]), or (b) a direct-mapping strategy is hard-coded in the software (e.g. TARQL 7 , CSV2RDF 8 , Any23 9 ). In the rst case -a framework based on mapping languages -data engineers benet from a declarative language that can express mappings towards dierent data sources, allowing better transparency and maintainability of the data transformation pipeline.…”

Section: Knowledge Graph Constructionmentioning

confidence: 99%

“…Although the OBDA paradigm has been also applied over document-based databases [9,45] and CSV les [15], most of the existing approaches focus on providing access to relational database and optimising algorithms for translating SPARQL queries into SQL queries (refer to Xiao et al [64] for a complete overview). The rst algorithm was essentially based on backward chaining [12], but the query produced were extremely large for execution by DBMSs.…”

Section: Toit Acm Transactions On Internet Technologymentioning

confidence: 99%

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Knowledge Graph Construction with a Façade : A Unified Method to Access Heterogeneous Data Sources on the Web

Asprino

Daga

Gangemi

et al. 2023

ACM Trans. Internet Technol.

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Data integration is the dominant use case for RDF Knowledge Graphs. However, Web resources come in formats with weak semantics (for example CSV and JSON), or formats specific to a given application (for example BibTex, HTML, and Markdown). To solve this problem, Knowledge Graph Construction (KGC) is gaining momentum due to its focus on supporting users in transforming data into RDF. However, using existing KGC frameworks result in complex data processing pipelines, which mix structural and semantic mappings, whose development and maintenance constitute a significant bottleneck for KG engineers. Such frameworks force users to rely on different tools, sometimes based on heterogeneous languages, for inspecting sources, designing mappings, and generating triples, thus making the process unnecessarily complicated. We argue that it is possible and desirable to equip KG engineers with the ability of interacting with Web data formats by relying on their expertise in RDF and the well-established SPARQL query language [2]. In this article, we study a unified method for data access to heterogeneous data sources with Facade-X, a meta-model implemented in a new data integration system called SPARQL Anything. We demonstrate that our approach is theoretically sound, since it allows a single meta-model, based on RDF, to represent data from (a) any file format expressible in BNF syntax, as well as (b) any relational database. We compare our method to state-of-the-art approaches in terms of usability (cognitive complexity of the mappings) and general performance. Finally, we discuss the benefits and challenges of this novel approach by engaging with the reference user community.

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Section: Knowledge Graph Constructionmentioning

confidence: 99%

Section: Toit Acm Transactions On Internet Technologymentioning

confidence: 99%

Knowledge Graph Construction with a Façade : A Unified Method to Access Heterogeneous Data Sources on the Web

Asprino

Daga

Gangemi

et al. 2023

ACM Trans. Internet Technol.

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“…QANDA, on the other hand, doesn't use the ontological relationships like QUASE in order to verify responses. Ontology-based information retrieval system [1] Ontoseek is developed [2]. During the retrieval process, it looks for content rather than string.…”

Section: Related Workmentioning

confidence: 99%

“…A discipline known as ontology-based information extraction is one in which the extraction process is directed by an ontology [1]. The extraction of information is a multi-step process that includes which was before the text into a machine-readable form and establishing heuristics to find the relevant information to also be extracted [2].…”

Section: Introductionmentioning

confidence: 99%

An efficient ontology model with query execution for accurate document content extraction

Eswaraiah¹,

Syed²

2023

IJEECS

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<span lang="EN-US">The technique of extracting important documents from massive data collections is known as information retrieval (IR). The dataset provider coupled with the increasing demand for high-quality retrieval results, has resulted in traditional information retrieval approaches being increasingly insufficient to meet the challenge of providing high-quality search results. Research has concentrated on information retrieval and interactive query formation through ontologies in order to overcome these challenges, with a specific emphasis on enhancing the functionality between information and search queries in order to bring the outcome sets closer to the research requirements of users. In the context of document retrieval technologies, it is a process that assists researchers in extracting documents from data collections. It is discussed in this research how to use ontology-based information retrieval approaches and techniques, taking into account the issues of ontology modelling, processing, and the transformation of ontological knowledge into database search queries. In this research work, an efficient optimized ontology model with query execution for content extraction from documents (OOM-QE-CE) is proposed. The existing ontology-to-database transformation and mapping methodologies are also thoroughly examined in terms of data and semantic loss, structural mapping and domain knowledge applicability.</span>

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“…Our work focuses on this second approach that allows data access, integration, quality checking, and governance through an ontology and its application in the semantic web world. Ontology-based access data (OBDA) [1] is one of the paradigms used to implement the second approach, a powerful solution for high-level data access, [2] it allows users to create high-level queries that OBDA automatically converts into low-level queries suited for the used database (DB) engines [3]. One of the most known implementations of OBDA was Ontop, a project introduced by the Free University of Bozen-Bolzano released under the Apache license.…”

Section: Introductionmentioning

confidence: 99%

Bridging the gap between the semantic web and big data: answering SPARQL queries over NoSQL databases

Massari

Mhammedi²,

Gherabi³

2022

IJECE

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Nowadays, the database field has gotten much more diverse, and as a result, a variety of non-relational (NoSQL) databases have been created, including JSON-document databases and key-value stores, as well as extensible markup language (XML) and graph databases. Due to the emergence of a new generation of data services, some of the problems associated with big data have been resolved. In addition, in the haste to address the challenges of big data, NoSQL abandoned several core databases features that make them extremely efficient and functional, for instance the global view, which enables users to access data regardless of how it is logically structured or physically stored in its sources. In this article, we propose a method that allows us to query non-relational databases based on the ontology-based access data (OBDA) framework by delegating SPARQL protocol and resource description framework (RDF) query language (SPARQL) queries from ontology to the NoSQL database. We applied the method on a popular database called Couchbase and we discussed the result obtained.

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Ontology-based data access – Beyond relational sources

Cited by 10 publications

References 14 publications

Knowledge Graph Construction with a Façade : A Unified Method to Access Heterogeneous Data Sources on the Web

Knowledge Graph Construction with a Façade : A Unified Method to Access Heterogeneous Data Sources on the Web

An efficient ontology model with query execution for accurate document content extraction

Bridging the gap between the semantic web and big data: answering SPARQL queries over NoSQL databases

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