JSON Schema Inference Approaches

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10418922" target="_blank" >RIV/00216208:11320/20:10418922 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1007/978-3-030-65847-2_16" target="_blank" >https://doi.org/10.1007/978-3-030-65847-2_16</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-65847-2_16" target="_blank" >10.1007/978-3-030-65847-2_16</a>

Result language

angličtina

Original language name

JSON Schema Inference Approaches

Original language description

Since the traditional relational database systems are not capable of following the contemporary requirements on Big Data processing, a family of NoSQL databases emerged. It is not an exception for such systems not to require an explicit schema for the data they store. Nevertheless, application developers must maintain at least the so-called implicit schema. In certain situations, however, the presence of an explicit schema is still necessary, and so it makes sense to propose methods capable of schema inference just from the structure of the available data. In the context of document NoSQL databases, namely those assuming the JSON data format, we focus on several representatives of the existing inference approaches and provide their thorough comparison. Although they are often based on similar principles, their features, support for the detection of references, union types, or required and optional properties differ greatly. We believe that without adequately tackling their disadvantages we identified, uniform schema inference and modeling of the multi-model data simply cannot be pursued straightforwardly.

Czech name

—

Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

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

Project

<a href="/en/project/GA20-22276S" target="_blank" >GA20-22276S: Unified Management of Multi-Model Data</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2020

Confidentiality

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

Article name in the collection

Advances in Conceptual Modeling

ISBN

978-3-030-65846-5

ISSN

0302-9743

e-ISSN

—

Number of pages

11

Pages from-to

173-183

Publisher name

Springer International Publishing

Place of publication

Austria

Event location

Vienna, Austria

Event date

Nov 3, 2020

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000604160100016