iStarJSON : a lightweight data-format for i* models

JSON is one of the most widely used data-interchange format. There is a large number of tools open for modelling with i*. However, none of them provides supporting for JSON. In this paper we propose iStarJSON language, a JSON-based proposal for interchanging i* models. We also, present an open source software that transforms XML-based format models to JSON models that expose a set of web services for mining iStarJSON models.Peer ReviewedPostprint (author's final draft

Your {JSON} is not my {JSON} : a case for more fine-grained content negotiation

Information resources can be expressed in different representations along many dimensions such as format, language, and time. Through content negotiation, http clients and servers can agree on which representation is most appropriate for a given piece of data. For instance, interactive clients typically indicate they prefer HTML, whereas automated clients would ask for JSON or RDF. However, labels such as “JSON” and “RDF” are insufficient to negotiate between the rich variety of possibilities offered by today’s languages and data models. This position paper argues that, despite widespread misuse, content negotiation remains the way forward. However, we need to extend it with more granular options in order to serve different current and future Web clients sustainably

Implementing Transitive Credit with JSON-LD

Science and engineering research increasingly relies on activities that facilitate research but are not currently rewarded or recognized, such as: data sharing; developing common data resources, software and methodologies; and annotating data and publications. To promote and advance these activities, we must develop mechanisms for assigning credit, facilitate the appropriate attribution of research outcomes, devise incentives for activities that facilitate research, and allocate funds to maximize return on investment. In this article, we focus on addressing the issue of assigning credit for both direct and indirect contributions, specifically by using JSON-LD to implement a prototype transitive credit system.Comment: accepted by WSSSPE2 - http://wssspe.researchcomputing.org.uk/wssspe2

A Graphical Conceptual Model for Conventional and Time-varying JSON Data

Abstract 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 graphical editors to build JSON Schemata (like JSON Schema Editor of Altova), they do not provide any built-in support for modelling temporal aspects of JSON data. Therefore, designers of JSON-based NoSQL data stores are proceeding in an ad hoc manner when they have to model some temporal requirements. To fill this theoretical and practical gap, we propose in this paper a graphical conceptual model for time-varying JSON data, named Temporal JSON Conceptual Model (TempoJCM). To this purpose, first we define a graphical conceptual model for conventional (i.e., non temporal) JSON data, called JSON Conceptual Model (JCM), and then we extend it to support modelling of temporal aspects of JSON data. TempoJCM facilitates conceptual modelling of both conventional and temporal JSON data, in a graphical and user-friendly manner. An editor supporting TempoJCM is planned to become the user interface for temporal JSON schema design in the τJSchema framework

JSON-LD 1.0 : a JSON-based serialization for linked data

JSON es una serialización útil de datos y formato de mensajería. Esta especificación define JSON-LD, un formato basado en JSON para serializar datos enlazados. La sintaxis está diseñada para integrarse fácilmente en los sistemas implementados que ya usan JSON, y proporciona una ruta de actualización sin problemas de JSON a JSON-LD. Está destinado principalmente a ser una manera de utilizar los datos enlazados en entornos de programación basados ​​en la Web, para crear servicios Web interoperables, y para almacenar datos enlazados en los motores de almacenamiento basadas en JSON.W3

Temporal JSON

JavaScript Object Notation (JSON) is a format for representing data. In this thesis we show how to capture the history of changes to a JSON document. Capturing the history is important in many applications, where not only the current version of a document is required, but all the previous versions. Conceptually the history can be thought of as a sequence of non-temporal JSON documents, one for each instant of time. Each document in the sequence is called a snapshot. Since changes to a document are few and infrequent, the sequence of snapshots largely duplicates a document across many time instants, so the snapshot model is (wildly) inefficient in terms of space needed to represent the history and time taken to navigate within it. A more efficient representation can be achieved by “gluing the snapshots together to form a temporal model. Data that remains unchanged across snapshots is represented only once in a temporal model. But we show that the temporal model is not a JSON document, and it is important to represent a history as JSON to ensure compatibility with web services and scripting languages that use JSON. So we describe a representational model that captures the information in a temporal model. We implement the representational model in Python and extensively experiment with the model. Our experiments show that the model is efficient