LODQuMa: A Free-ontology process for Linked (Open) Data quality management
For many years, data quality is among the most commonly discussed issue in Linked Open Data (LOD) due to the huge volume of integrated datasets that are usually heterogeneous. Several ontology-based approaches dealing with quality problems have been proposed. However, when datasets lack a well-defin...
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| Format: | Article |
| Language: | English |
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Springer
2022-09-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157821001348 |
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| author | Samah Salem Fouzia Benchikha |
| author_facet | Samah Salem Fouzia Benchikha |
| author_sort | Samah Salem |
| collection | DOAJ |
| description | For many years, data quality is among the most commonly discussed issue in Linked Open Data (LOD) due to the huge volume of integrated datasets that are usually heterogeneous. Several ontology-based approaches dealing with quality problems have been proposed. However, when datasets lack a well-defined schema, these approaches become ineffective because of the lack of metadata. Moreover, the detection of quality problems based on an analysis between RDF (Resource Description Framework) triples without requiring ontology statistical and semantical information is not addressed. Keeping in mind that ontologies are not always available and they may be incomplete or misused. In this paper, a novel free-ontology process called LODQuMa is proposed to assess and improve the quality of LOD. It is mainly based on profiling statistics, synonym relationships between predicates, QVCs (Quality Verification Cases), and SPARQL (SPARQL Protocol and RDF Query Language) query templates. Experiments on the DBpedia dataset demonstrate that the proposed process is effective for increasing the intrinsic quality dimensions, resulting in correct and compact datasets. |
| format | Article |
| id | doaj-art-acb08d7f6f4a40fbb4a42b3a91e215d2 |
| institution | Kabale University |
| issn | 1319-1578 |
| language | English |
| publishDate | 2022-09-01 |
| publisher | Springer |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj-art-acb08d7f6f4a40fbb4a42b3a91e215d22025-08-20T03:52:02ZengSpringerJournal of King Saud University: Computer and Information Sciences1319-15782022-09-013485552556310.1016/j.jksuci.2021.06.001LODQuMa: A Free-ontology process for Linked (Open) Data quality managementSamah Salem0Fouzia Benchikha1Corresponding author.; LIRE Laboratory, Abdelhamid Mehri - Constantine 2 University, Constantine, AlgeriaLIRE Laboratory, Abdelhamid Mehri - Constantine 2 University, Constantine, AlgeriaFor many years, data quality is among the most commonly discussed issue in Linked Open Data (LOD) due to the huge volume of integrated datasets that are usually heterogeneous. Several ontology-based approaches dealing with quality problems have been proposed. However, when datasets lack a well-defined schema, these approaches become ineffective because of the lack of metadata. Moreover, the detection of quality problems based on an analysis between RDF (Resource Description Framework) triples without requiring ontology statistical and semantical information is not addressed. Keeping in mind that ontologies are not always available and they may be incomplete or misused. In this paper, a novel free-ontology process called LODQuMa is proposed to assess and improve the quality of LOD. It is mainly based on profiling statistics, synonym relationships between predicates, QVCs (Quality Verification Cases), and SPARQL (SPARQL Protocol and RDF Query Language) query templates. Experiments on the DBpedia dataset demonstrate that the proposed process is effective for increasing the intrinsic quality dimensions, resulting in correct and compact datasets.http://www.sciencedirect.com/science/article/pii/S1319157821001348Linked Open DataQuality assessmentQuality improvementSynonym predicatesProfiling statisticsDBpedia |
| spellingShingle | Samah Salem Fouzia Benchikha LODQuMa: A Free-ontology process for Linked (Open) Data quality management Journal of King Saud University: Computer and Information Sciences Linked Open Data Quality assessment Quality improvement Synonym predicates Profiling statistics DBpedia |
| title | LODQuMa: A Free-ontology process for Linked (Open) Data quality management |
| title_full | LODQuMa: A Free-ontology process for Linked (Open) Data quality management |
| title_fullStr | LODQuMa: A Free-ontology process for Linked (Open) Data quality management |
| title_full_unstemmed | LODQuMa: A Free-ontology process for Linked (Open) Data quality management |
| title_short | LODQuMa: A Free-ontology process for Linked (Open) Data quality management |
| title_sort | lodquma a free ontology process for linked open data quality management |
| topic | Linked Open Data Quality assessment Quality improvement Synonym predicates Profiling statistics DBpedia |
| url | http://www.sciencedirect.com/science/article/pii/S1319157821001348 |
| work_keys_str_mv | AT samahsalem lodqumaafreeontologyprocessforlinkedopendataqualitymanagement AT fouziabenchikha lodqumaafreeontologyprocessforlinkedopendataqualitymanagement |