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Table 6 Comparison of proposed automated approach to other existing framework. The ’Novelty’ of each framework in this table are not comprehensive and only include relevant content to enable comparison

From: Automated approach for quality assessment of RDF resources

 

SWIQA (2011)

Sieve (2012)

RDFUnit (2014)

Luzzu (2016)

Our approach (2022)

Purpose

Proposal of a framework for information quality assessment of Semantic Web data

Proposal of a Linked Data Quality Assessment and Data Fusion module employed by the Linked Data Integration Framework (LDIF)

Proposal of a framework based on the data quality integrity constraints (represented in SPARQL patterns)

Proposal of a semantic framework based on Dataset Quality Ontology (daQ)

Proposal of an automated approach to assess the foundational characteristics as the starting point for linked data quality assessment

Scope of metrics

Mixed (5)

Mixed (3)

Mixed (17)

Mixed (25)

Only foundational (6)

Example metric

Legal Value Range Rules

Completeness

TYPRO-DEP: A resource of a specific type should have a certain property.

Basic Provenance and Extended Provenance

Non-resolvable URIs

Example or explanation

’The property foo:population must only contain values greater than zero. ’

“In the use case described in this paper, the task required retrieving 3 attributes (areaTotal, foundingDate, populationTotal) for all 5565 objects (Brazilian municipalities).”

’a dbo:Person should have a dbo:birthDate’

’if a dataset, usually of type void:Dataset or dcat:Dataset, has the most basic provenance information; that is information related to the creator or publisher, using the dc:creator or dc:publisher properties. ’

’1) Check if an RDF resource is resolvable (Boolean), or 2) check if URIs in that RDF resource are resolvable, and measure the proportion of non-resolvable URIs to all unique URIs. ’

Link

Not found

https://github.com/wbsg/sieve

https://github.com/AKSW/RDFUnit

https://github.com/Luzzu/Framework

https://github.com/sxzhang1201/assess-rdf-resource

Tooling last update

Not found

2014

2022

2021

2022

Novelty

The first linked data quality framework

Connection with Linked Data Integration Framework (LDIF)

Use of SPARQL pattern

Add semantic layer and quality metadata to assessment framework

Focus on foundational aspects