Technical Setup Prototype Mark I (1)

The technical setup for the first prototype of the live data sonification tool has been sketched on a whiteboard in the DataShaka office. All green text refers to technical data work required for me to do on the DataShaka side (such as gathering and sending out internal metrics, etc.); all black text represents the work that needs to be done for the development of the sonification application itself. All red underlined text represents elements that still need to be implemented. All red written text are future amendments, stretch goals or possibilities for Prototype II.

The data sonification tool itself will be a webapp, reading and storing the data stream with d3.js and creating live sound synthesis through JavaScript. Interface and design of the app will be done in HTML and CSS. The data stream will come through the live data visualisation platform DataDog, which is currently used at the DataShaka office to show all metrics on an screen inside the office space. As DataDog provides an accessible API, it is logical to make use of this platform as various internal metrics are already gathered at this place. Ultimately however, it is planned as a stretch goal that all data will stream without the usage of any third party software. A tempting possibility for this is to make use DataShaka's intelligent storage platform DISQ (Dynamic Intelligent Storage and Query) and pull the data from its API. This would however require a few pieces of work on this storage platform, as DISQ does not yet record these metrics. Also, additional features would have to be included to the DISQ API. This will have to be challenged and aligned with DataShaka's all other priorities, which is reason for this goal to only be defined as a stretch goal.

The first step will be to create a webapp that can produce the required sounds and possibly already represents fake data sets. This way, evaluating the sound design and interactivity is possible at an early stage and not necessarily depended on back end issues, such as the connection of DataDog's API and its data stream to the webapp.