Consistency Evaluation of RDF Data: How Data and Updates are Relevant

Maillot, Pierre; Raimbault, Thomas; Genest, David; Loiseau, Sylvain

doi:10.1109/sitis.2014.39

Cited by 8 publications

(6 citation statements)

References 11 publications

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“…In future works, we plan to apply our measure to di erent problems such as data integration [6] or document clustering as in [12]. Finally, we will work on formalizing the codi cation of the code tables to be included as metadata describing the di erent datasets.…”

Section: Discussionmentioning

confidence: 99%

Measuring structural similarity between RDF graphs

Maillot¹,

Bobed²

2018

Proceedings of the 33rd Annual ACM Symposium on Applied Computing

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In the latest years, there has been a huge e ort to deploy large amounts of data, making it available in the form of RDF data thanks, among others, to the Linked Data initiative. In this context, using shared ontologies has been crucial to gain interoperability, and to be able to integrate and exploit third party datasets. However, using the same ontology does not su ce to successfully query or integrate external data within your own dataset: the actual usage of the vocabulary (e.g., which concepts have instances, which properties are actually populated and how, etc.) is crucial for these tasks. Being able to compare di erent RDF graphs at the actual usage level would indeed help in such situations. Unfortunately, the complexity of graph comparison is an obstacle to the scalability of many approaches. In this article, we present our structural similarity measure, designed to compare structural similarity of low-level data between two di erent RDF graphs according to the pa erns they share. To obtain such pa erns, we leverage a data mining method (KRIMP) which allows to extract the most descriptive pa erns appearing in a transactional database. We adapt this method to the particularities of RDF data, proposing two di erent conversions for an RDF graph. Once we have the descriptive pa erns, we evaluate how much two graphs can compress each other to give a numerical measure depending on the common data structures they share. We have carried out several experiments to show its ability to capture the structural di erences of actual vocabulary usage.

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Section: Discussionmentioning

confidence: 99%

Measuring structural similarity between RDF graphs

Maillot¹,

Bobed²

2018

Proceedings of the 33rd Annual ACM Symposium on Applied Computing

Self Cite

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“…Updating data in a graph database or triple store can easily introduce semantic inconsistencies or eliminate links between resources of the graph, which leads to the separation of entire parts of the whole (subgraphs) [30]. This contrasts with relational databases, where referential integrity, primary keys and other constraints can be used to efficiently enforce a database schema and thus maintain the consistency of the data model.…”

Section: Enforcement Of Ontological Consistencymentioning

confidence: 99%

An Evaluation of Graph Databases and Object-Graph Mappers in CIDOC CRM-Compliant Digital Archives

Costa

Freitas

Silva

2022

J. Comput. Cult. Herit.

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The Portuguese General Directorate for Book, Archives and Libraries (DGLAB) has selected CIDOC CRM as base for its next-generation digital archive management software. Given the ontology foundations of the CRM, a graph database or a triple store were seen as the best candidates to represent a CRM-based data model for the new software. We thus decided to compare several of these databases, based on their maturity, features, performance in standard tasks and, most importantly, the Object-Graph Mappers (OGM) available to interact with each database in an Object-Oriented way. Our conclusions are drawn not only from a systematic review of related works but from an experimental scenario. For our experiment, we designed a simple CRM-compliant graph designed to test the ability of each OGM/database combination to tackle the so-called “Diamond-problem” in Object-Oriented Programming (OOP), to ensure that property instances follow domain and range constraints. Our results show that 1. ontological consistency enforcement in graph databases and triplestores is much harder to achieve than in a relational database, making them more suited to an analytical rather than a transactional role, 2. Object-Graph Mappers are still rather immature solutions and 3. neomodel, an OGM for the Neo4j graph database, is the most mature solution in the study as it satisfies all requirements, although it is also the least performing.

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“…Several recent updating works focus on consistent graph databases. The approach in Maillot et al (2014) differs from ours, by proposing a semantic measure based on the difference between original and updated RDF sub-graph. Both Chabin et al (2019b) and Goasdoué et al (2013) consider RDF updating methods, but the former goes deeper in the study of null values.…”

Section: Related Workmentioning

confidence: 99%

Graph rewriting rules for RDF database evolution: optimizing side-effect processing

Chabin¹,

Eichler

Ferrari³

et al. 2021

IJWIS

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Purpose Graph rewriting concerns the technique of transforming a graph; it is thus natural to conceive its application in the evolution of graph databases. This paper aims to propose a two-step framework where rewriting rules formalize instance or schema changes, ensuring graph’s consistency with respect to constraints, and updates are managed by ensuring rule applicability through the generation of side effects: new updates which guarantee that rule application conditions hold. Design/methodology/approach This paper proposes Schema Evolution Through UPdates, optimized version (SetUpOPT), a theoretical and applied framework for the management of resource description framework (RDF)/S database evolution on the basis of graph rewriting rules. The framework is an improvement of SetUp which avoids the computation of superfluous side effects and proposes, via SetUpoptND, a flexible and extensible package of solutions to deal with non-determinism. Findings This paper shows graph rewriting into a practical and useful application which ensures consistent evolution of RDF databases. It introduces an optimised approach for dealing with side effects and a flexible and customizable way of dealing with non-determinism. Experimental evaluation of SetUpoptND demonstrates the importance of the proposed optimisations as they significantly reduce side-effect generation and limit data degradation. Originality/value SetUp originality lies in the use of graph rewriting techniques under the closed world assumption to set an updating system which preserves database consistency. Efficiency is ensured by avoiding the generation of superfluous side effects. Flexibility is guaranteed by offering different solutions for non-determinism and allowing the integration of customized choice functions.

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Consistency Evaluation of RDF Data: How Data and Updates are Relevant

Cited by 8 publications

References 11 publications

Measuring structural similarity between RDF graphs

Measuring structural similarity between RDF graphs

An Evaluation of Graph Databases and Object-Graph Mappers in CIDOC CRM-Compliant Digital Archives

Graph rewriting rules for RDF database evolution: optimizing side-effect processing

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