Safa Brahmia

Internet of Green Things (IoGT) is a technology that allows exchanging information between people and healthy farm things. It provides information like soil moisture, temperature, humidity, and nutrient level via the use of appropriate sensors. IoGT sensor data represent entities which are evolving over time, and several (smart) farming application...

A data lake stores heterogeneous big data, in their native format, without any predefined schema, while providing supports for querying and analyzing such big data. Metadata are necessary for describing the big data stored in the data lake, and metadata management and querying are among the most important functionalities of a data lake management s...

The current release of MongoDB Atlas supports scheduled triggers that are based on periodic events only (e.g., to generate a weekly report, to send an automated monthly email newsletter). However, although non-periodic events, also called single events, are needed in many cases of today's applications (e.g., to schedule an increase of the salaries...

Time-varying JSON data are being used and exchanged in various today’s application frameworks like IoT platforms, Web services, cloud computing, online social networks, and mobile systems. However, in the state-of-the-art of JSON data management, there is neither a consensual nor a standard language for updating (i.e., inserting, modifying, and del...

TempoJCM (Temporal JSON Conceptual Model) is a graphical model for conceptual modeling of temporal JSON data. Like the other conceptual data models, TempoJCM allows only to model the current structure of the real world, i.e., the current entities of this world, with their current properties and their current relationships, and the current temporal...

τJOWL (Temporal OWL 2 from Temporal JSON) is a framework we proposed to allow users of Big Data projects to automatically create, with the closed world assumption (CWA), a temporal OWL 2 ontology from time-varying JSON-based Big Data. Such an ontology, providing the semantics to the data, facilitates complex tasks like Big Data querying, analytics...

JSONPath is a language for locations in a standard JSON document, like the XPath language for XML documents. Its definition is based on the specification of the standard JSON format. Moreover, many JSON query languages, like JSONiq, have been inspired from JSONPath. However, JSONPath allows to navigate only in the current version of a JSON document...

Time-varying JSON data are being used and exchanged in various today’s application frameworks like IoT platforms, Web services, cloud computing, online social networks, and mobile systems. However, in the state-of-the-art of JSON data management, there is neither a consensual nor a standard language for updating (i.e., inserting, modifying, and del...

e-Health IoT sensor data represent entities which are evolving over time, and several healthcare applications require keeping a full history of such data. Moreover, e-Health IoT data can be considered as Big Data and the JSON format is being considered as the best data format to represent Big Data and to facilitate their management, storage and exc...

Although JSON documents are being used in several emerging applications (e.g., Big Data applications, IoT, mobile computing, smart cities, and online social networks), there is no consensual or standard language for updating JSON documents (i.e., creating, deleting or changing such documents, where changing means inserting, deleting, replacing, cop...

Schema versioning of JSON-based Big Data is driven either explicitly by schema changes or implicitly by updates. In the τJSchema framework, we have previously investigated implicit JSON Schema versioning, by dealing with implicit schema changes driven by updates of JSON-based conventional Big Data. Since τJSchema supports not only conventional but...

τJSchema is a framework for managing time-varying JSON-based Big Data, in temporal JSON NoSQL databases, through the use of a temporal JSON schema. This latter ties together a conventional JSON schema and its corresponding temporal logical and temporal physical characteristics set. In our previous work, we have proposed low-level operations for cha...

In previous work, we have proposed the use of a framework, named τJSchema (temporal JSON schema), for the definition and validation of temporal JSON documents that conform to a temporal JSON schema. A τJSchema schema is composed of a conventional (i.e., non-temporal) JSON schema, annotated with a set of temporal logical and temporal physical charac...

Today, although there is an increasing interest in temporal JSON instance documents, since they allow tracking data changes, recovering past data versions, and executing temporal queries, there is no support (data model, modelling language, method, or tool) for conceptual modelling of temporal JSON data. Moreover, even though there are some graphic...

Currently, JSON and JSON Schema languages are being widely used by NoSQL database designers, administrators and application developers. However, there is neither a standard JSON update language (like the XQuery Update Facility language in the XML world), nor a standard JSON Schema change language (like the SQL-DDL language in the relational setting...

τJSchema is a framework for managing time-varying JSON-based big data, in temporal JSON NoSQL databases, through the use of a temporal JSON schema. This latter ties together a conventional JSON schema and its corresponding temporal logical and temporal physical characteristics set. In our previous work, we have proposed low-level operations for cha...

In JSON-based NoSQL data stores, Big Data instance documents and their JSON schemas must evolve over time to reflect changes in the real world. When a JSON instance document, valid with respect to a JSON schema, is updated giving rise to a new document no longer valid with respect to the schema, the update is usually rejected also resulting in user...

Several modern applications (e.g., Internet of Things, online social networks), which exploit big data, require a complete history of all changes performed on these data and their schemas (or structures). However, although schema versioning has long been advocated to be the best solution for this issue, currently there are no available technical su...

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 inst...

τJSchema is a framework for the management of temporal documents stored in JSON format in a NoSQL database, similar to the τXSchema framework proposed for XML. In this work, we extend τJSchema to temporal schema versioning support. The proposed approach provides a systematic solution to the challenging task of evolving a JSON schema while maintaini...

Although NoSQL databases are claimed to be schemaless, several NoSQL database vendors have chosen JSON as agile data representation format and provide a JSON-based API or query facility to simplify the life of application developers. Whereas many applications require the management of temporal data, the JSON Schema language lacks explicit support f...