Biomedical Research and Integrated Biobanking: An Innovative Paradigm for Heterogeneous Data Management by Massimiliano Izzo

Author:Massimiliano Izzo
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

3.2 Why JSON?

Fig. 3.1An example of a JSON data object. The three fundamental types are shown: strings (in blue), numbers (orange), booleans (green) and null (grey). Other types—such as date, timestamps, and emails are represented as formatted stings. Notice that array are allowed to contain heterogeneous values

JSON is a text format for the serialisation of structured and semi-structured data. It is derived from JavaScript object literals, hence the name. In practice, it is a minimal and portable textual subset of JavaScript [1]. It has gained a huge popularity as the preferred data exchange format on the web, given the ubiquitous nature of JavaScript language, present and extensively employed in all the major web browsers.1 JSON provides a paradigm to store data and metadata in an organised yet flexible and easy-to access way. I find surprising that so far there have been no academic effort to use it as a format to store heterogeneous scientific metadata. An example of JSON is provided in Fig. 3.1. A JSON object is enclosed within curly brackets. The object is composed by a set of properties expressed as key—value pairs. Any recognised Unicode string is a valid key. JSON support four primitive values—string, number, boolean and null—and two structured subtypes: objects and arrays. It is therefore possible to nest objects within other object, building up a hierarchical structure. Arrays are ordered lists of objects or primitive types and are enclosed within square brackets. There exist various comparisons between JSON and XML available on the internet, so I am not going to repeat most of the arguments that have already been raised by more expert developers. I limit myself to two key considerations relevant to my design goals:JSON is an object-oriented model. Even though its syntax has been extrapolated from JavaScript its textual nature makes it language-independent. It does not required data binding libraries to be parsed in C-like languages like C++, Java and C#. In Python, another language widely used by the scientific community, support is provided by the standard libraries. In MATLAB there are various options available, the most popular being JSONlab.

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