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Measuring Quality of Evolution in Diachronic Web Vocabularies Using Inferred Optimal Change Models
| Content Provider | Semantic Scholar |
|---|---|
| Author | Meroño-Peñuela, Albert Guéret, Christophe Schlobach, Stefan |
| Copyright Year | 2015 |
| Abstract | The Semantic Web uses various commonly agreed vocabularies to enable data from various sources to be effectively integrated and exchanged among applications. In this design, a critical point is the arbitrariness in which these vocabularies can change in subsequent versions. New vocabulary versions reflect changes in the domain, meet new user requirements, and address pitfalls. However, these new versions have an impact in the workflow of publishers of Linked Open Data (LOD), who need to sync their datasets with the new vocabulary releases to avoid ramifications. Predictability of changes in diachronic Web vocabularies is thus highly desired. How predictable are these vocabulary changes in practice? In a longer term, how can we measure the quality of evolving Web vocabularies, and discern between those that "evolve conveniently", and those that change on an arbitrary, even harmful, basis? In this paper, we propose a metric to automatically measure the quality of the evolution of Web vocabularies, based on the performance of inferred optimal change models from past vocabulary versions using well understood evolution predictors. We apply this metric to 139 vocabulary chains from various Semantic Web sources, finding that 39.80% of them evolve in a highly predictable manner. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.semantic-web-journal.net/system/files/swj1244.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
