A Disciplined Approach to Temporal Evolution and Versioning Support in JSON Data Stores

Abstract

The JSON Schema language lacks explicit support for defining time-varying schemas of JSON documents. Moreover, existing JSON NoSQL databases (e.g., MongoDB, CouchDB) do not provide any support for managing temporal data. Hence, administrators of JSON NoSQL databases have to use ad hoc techniques in order to specify JSON schema for time-varying instances. In this chapter, the authors propose a disciplined approach, named Temporal JSON Schema (τJSchema), for the temporal management of JSON documents. τJSchema allows creating a temporal JSON schema from (1) a conventional JSON schema, (2) a set of temporal logical characteristics, for specifying which components of a JSON document can vary over time, and (3) a set of temporal physical characteristics, for specifying how the time-varying aspects are represented in the document. By using such characteristics to describe temporal aspects of JSON data, τJSchema guarantees logical and physical data independence and provides a low-impact solution since it requires neither updates to existing JSON documents nor extensions to related JSON technologies.

JUpdate: A JSON Update Language

“…Since several JSON-based emerging advanced applications (e.g., e-government and e-health applications) require bookkeeping of the history of data changes and, therefore, need to manage the evolution over time of JSON data, it will be interesting to extend JUpdate to also support updating of temporal JSON data. For this purpose, we intend in our future work to propose a temporal extension of JUpdate, named τJUpdate (Temporal JUpdate), to equip our temporal JSON-based NoSQL framework τJSchema (Temporal JSON Schema) [7,54].…”

“…However, by studying the state-of-the-art of JSON data management (e.g., [2][3][4][5][6][7][8][9][10][11][12]), we have not found a recommended, consensual, and/or standard language for updating (native) JSON data (such as SQL for relational data, XQuery Update Facility for XML data, or SPARQL 1.1 Update for RDF data). Several JSON query languages have been proposed, such as Jaql [13], JSONiq [14], JPQ [15], SQL++ [16,17], JNL [18], JSON-λ [19], JSONata, GROQ, and JMESPath, which all lack modification statements making up a JSON update language.…”

$\tau\text{JOWL}$: A Systematic Approach to Build and Evolve a Temporal OWL 2 Ontology Based on Temporal JSON Big Data

“…Notice that extant JSON data are stored and managed in JOWL as in our previous temporal JSON JSchema framework [34,35] . Moreover, the OWL 2 ontologies are stored and managed in JOWL as in our previous temporal ontology OWL framework [36,37] .…”

Modeling and Transformation from Temporal Object Relational Database into Mongodb: Rules

“…The work in [13] described a migration process from Object relational database to Nosql document database end provided a review of different proposed approach. An overview of Nosql to evaluate the scalability and efficiency in storage of data in oriented document database case study in order to show the representational format and querying management process of Mongodb [14]. The work in [15]introduced a disciplined approach called Jschema(Temporal Json Schema) for the temporal management Json documents by creating a temporal json documents from conventional document that can vary over time, the generated document uses such features of temporal management data.…”