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ITER will produce large volumes of data that need to be visualized and analyzed. This paper describes the development of a graphical data visualization and exploration tool, MINT (Make Informative and Nice Trends), for plant engineers, operators and physicists. It describes the early development phase from requirements capture to first release covering the mistakes, lessons learnt and future steps. The requirements were collected by interviewing the various stakeholders. The initial neglect of the architecture and user-friendliness turned out to be key points when developing such a tool for a project with a long lifetime like ITER. Modular architecture and clear definition of generic interfaces (abstraction layer) is crucial for such a long lifetime project and makes it ready for future adaptations to new plotting, processing and GUI libraries. The MINT application is based upon the development of an independent plotting library, which acts as a wrapper to the underlying graphical library. This allows scientists and engineers to develop their own specific tools, which are immune to changes of graphical library. The development based on Python uses Qt5 as the visual backend., Proceedings of the 18th International Conference on Accelerator and Large Experimental Physics Control Systems, ICALEPCS2021, Shanghai, China

Disruptive events still pose a serious problem for the protection of in-vessel components of large size tokamak devices, representing therefore a key aspect to be considered for the design of next step fusion devices such as ITER and DEMO. If an efficient mitigation is strongly required to avoid damage and preserve the structural integrity of the machine, efficient avoidance schemes are needed to possibly bring the plasma back to a safe operating condition. In this framework, disruption prediction plays a key role and in the last few years a substantial effort has been devoted to developing more sophisticated prediction systems and improving their performance both in terms of success rate and warning time. Many of the presently developed disruption predictors mainly rely on MHD markers related to still rotating modes and, especially, to locked modes, which are basically the final precursor of most of the disruptions. Nevertheless, in many cases the detection warning time is still unsatisfactory with respect to avoidance requirements, and a significant step forward needs to be taken. This work deals with the development of "plasma profile based indicators" for disruption prediction and avoidance in JET, where parameterized peaking factors have been implemented for electron temperature, density and plasma radiation profiles. The basic interplay of the time evolution of different profiles will be described in relation to the phenomenology characterizing specific disruption types together with the relevant time scales. Furthermore, a statistical analysis aiming to describe differences and boundaries between the safe and the disruptive space as well as among specific types of disruptions will be presented, discussing the implications in terms of disruption prediction and avoidance. This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014-2018 under grant agreement No 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission and the ITER Organization.