Batch Mode Ontology Instance Updates with Automated Inconsistency Management in the τJOWL Ecosystem

Abstract

τJOWL (Temporal OWL2 from Temporal JSON) is an ecosystem designed to automatically create a time-referenced OWL2 ontology from a JSON data file containing time-referenced Big Data. This ontology acts as a “schema” to manage time-referenced JSON Big Data instances. In our previous research, we explored the effects of time-referenced JSON data updates, which are interactively and incrementally executed by the τJOWL database administrator (DBA), at both instance and schema levels. In this work, we enrich our proposal by addressing time-referenced JSON data updates executed in batch mode. This situation arises when the τJOWL DBA wants to incorporate a new time-referenced JSON file into the τJOWL DB, such as one prepared offline or imported from an external source. Such a data file needs to be integrated with the current ontology instance to create a new version. Additionally, certain instance updates may render them inconsistent with their ontology schema. Therefore, our proposed solution is to automatically create and apply changes to the ontology schema to maintain global consistency. Our new method for handling ontology instance updates within the τJOWL ecosystem, enhances flexibility in knowledge management and ontology evolution. It also supports time-referenced versioning of both big data instances and ontology schema, ensuring the τJOWL DB remains consistent in a transparent way.