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Matching and Rewriting Rules in Object-Oriented Databases

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A9SUWMLJ3" target="_blank" >RIV/00216208:11320/25:9SUWMLJ3 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203625463&doi=10.3390%2fmath12172677&partnerID=40&md5=b03f2355cadad16fa1b6e8799c111c90" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203625463&doi=10.3390%2fmath12172677&partnerID=40&md5=b03f2355cadad16fa1b6e8799c111c90</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/math12172677" target="_blank" >10.3390/math12172677</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Matching and Rewriting Rules in Object-Oriented Databases

  • Original language description

    Graph query languages such as Cypher are widely adopted to match and retrieve data in a graph representation, due to their ability to retrieve and transform information. Even though the most natural way to match and transform information is through rewriting rules, those are scarcely or partially adopted in graph query languages. Their inability to do so has a major impact on the subsequent way the information is structured, as it might then appear more natural to provide major constraints over the data representation to fix the way the information should be represented. On the other hand, recent works are starting to move towards the opposite direction, as the provision of a truly general semistructured model (GSM) allows to both represent all the available data formats (Network-Based, Relational, and Semistructured) as well as support a holistic query language expressing all major queries in such languages. In this paper, we show that the usage of GSM enables the definition of a general rewriting mechanism which can be expressed in current graph query languages only at the cost of adhering the query to the specificity of the underlying data representation. We formalise the proposed query language in terms declarative graph rewriting mechanisms described as a set of production rules (Formula presented.) while both providing restriction to the characterisation of L, and extending it to support structural graph nesting operations, useful to aggregate similar information around an entry-point of interest. We further achieve our declarative requirements by determining the order in which the data should be rewritten and multiple rules should be applied while ensuring the application of such updates on the GSM database is persisted in subsequent rewriting calls. We discuss how GSM, by fully supporting index-based data representation, allows for a better physical model implementation leveraging the benefits of columnar database storage. Preliminary benchmarks show the scalability of this proposed implementation in comparison with state-of-the-art implementations. © 2024 by the authors.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Mathematics

  • ISSN

    2227-7390

  • e-ISSN

  • Volume of the periodical

    12

  • Issue of the periodical within the volume

    17

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    62

  • Pages from-to

    1-62

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85203625463