Enhanced metrics for temporal dimensions toward assessing Linked Data: A case study of Wikidata
The development of Linked Open Data (LOD) has transformed the web into a decentralized extensive database. With this dataflow, ensuring quality level became very quickly a crucial issue. Many approaches were proposed using metrics and dimensions inherited from traditional relational databases to ass...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-09-01
|
| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157821001257 |
| _version_ | 1818498583450615808 |
|---|---|
| author | Mohamed Amine Ferradji Fouzia Benchikha |
| author_facet | Mohamed Amine Ferradji Fouzia Benchikha |
| author_sort | Mohamed Amine Ferradji |
| collection | DOAJ |
| description | The development of Linked Open Data (LOD) has transformed the web into a decentralized extensive database. With this dataflow, ensuring quality level became very quickly a crucial issue. Many approaches were proposed using metrics and dimensions inherited from traditional relational databases to assess LOD quality. However, classic metrics used to measure dimensions like Currency, Volatility and Timeliness are unreliable knowing they use exclusively temporal metadata. We believe that assessing data “freshness” could emphasize their validity, considering the assumption that current data is tightly correlated with its credibility. In this paper, we propose an upgraded version for time-related metrics to make them more efficient and more suitable for assessing linked data. Using Wikidata as study case and Wikipedia as reference to “current” data, we implement our approach and compare it to the most relevant approach to find out the crucial part played by a reliable Currency and Volatility to determine data up-to-dateness. |
| first_indexed | 2024-12-10T20:17:35Z |
| format | Article |
| id | doaj.art-70429b864c49483a8b7a6192a36b3497 |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-12-10T20:17:35Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-70429b864c49483a8b7a6192a36b34972022-12-22T01:35:09ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782022-09-0134849834992Enhanced metrics for temporal dimensions toward assessing Linked Data: A case study of WikidataMohamed Amine Ferradji0Fouzia Benchikha1Corresponding author.; Faculty of New Technologies of Information and Communication, LIRE Laboratory, University Constantine 2, AlgeriaFaculty of New Technologies of Information and Communication, LIRE Laboratory, University Constantine 2, AlgeriaThe development of Linked Open Data (LOD) has transformed the web into a decentralized extensive database. With this dataflow, ensuring quality level became very quickly a crucial issue. Many approaches were proposed using metrics and dimensions inherited from traditional relational databases to assess LOD quality. However, classic metrics used to measure dimensions like Currency, Volatility and Timeliness are unreliable knowing they use exclusively temporal metadata. We believe that assessing data “freshness” could emphasize their validity, considering the assumption that current data is tightly correlated with its credibility. In this paper, we propose an upgraded version for time-related metrics to make them more efficient and more suitable for assessing linked data. Using Wikidata as study case and Wikipedia as reference to “current” data, we implement our approach and compare it to the most relevant approach to find out the crucial part played by a reliable Currency and Volatility to determine data up-to-dateness.http://www.sciencedirect.com/science/article/pii/S1319157821001257Data qualityWikidataCurrencyVolatilityTimelinessLinked data |
| spellingShingle | Mohamed Amine Ferradji Fouzia Benchikha Enhanced metrics for temporal dimensions toward assessing Linked Data: A case study of Wikidata Journal of King Saud University: Computer and Information Sciences Data quality Wikidata Currency Volatility Timeliness Linked data |
| title | Enhanced metrics for temporal dimensions toward assessing Linked Data: A case study of Wikidata |
| title_full | Enhanced metrics for temporal dimensions toward assessing Linked Data: A case study of Wikidata |
| title_fullStr | Enhanced metrics for temporal dimensions toward assessing Linked Data: A case study of Wikidata |
| title_full_unstemmed | Enhanced metrics for temporal dimensions toward assessing Linked Data: A case study of Wikidata |
| title_short | Enhanced metrics for temporal dimensions toward assessing Linked Data: A case study of Wikidata |
| title_sort | enhanced metrics for temporal dimensions toward assessing linked data a case study of wikidata |
| topic | Data quality Wikidata Currency Volatility Timeliness Linked data |
| url | http://www.sciencedirect.com/science/article/pii/S1319157821001257 |
| work_keys_str_mv | AT mohamedamineferradji enhancedmetricsfortemporaldimensionstowardassessinglinkeddataacasestudyofwikidata AT fouziabenchikha enhancedmetricsfortemporaldimensionstowardassessinglinkeddataacasestudyofwikidata |