## 1 Introduction  
The scientific community must confront large volumes of increasingly complex data, making difficult their analysis. This need has promoted an increasing development of scientific visualisation techniques based on the use of the visual channel [1, 2, 3, 4]. However, a large number of visual stimuli can saturate the sense of sight [5]. For this reason, rendering multisensory information can be of great help when exploring the data. In this article, we suggest a new technique to facilitate the use of other sensory channels, in particular the haptic sense, to help in the analysis of complex data. Our technique can be used either alone or to reinforce or supplement the visual information. Using haptic data visualisation (HDV) to show complex data through haptic stimulus allows the users to perceive different data characteristics through the sense of touch [6, 7]. Devices can be used to present haptic information, and the user can get qualitative or quantitative knowledge about the presented data in several areas of application. For example, in [PERSON] et al. [8], authors use haptic information for the analysis of dense and complex filiform structures in the neurobiology context or, in [PERSON] et al. [9], they use it for education. The haptic modality is not only useful for users who are blind or partially sighted, but it can also be used to increase the number of presented variables or to duplicate some variables to reinforce their presentation [10]. Some authors propose using haptic signals, called haptic icons, to represent non-haptic related abstract concepts [11]. However, using the tactile channel in a non-natural way may present different problems. A major approach to understanding human sensory organs is through psychophysical experiments. Psychophysical parameters also define the time and intensity that perceptual memory will remember [12; 13; 14]. Average users' ability to discriminate the different haptic icons highly depends on users' limited short-term memory [15]. This is one of the major reasons that explain why haptics is not frequently used for rendering quantitative or qualitative abstract data. We propose a new method named haptic tuning fork to increase the discriminability of haptic icons. The idea is to add a reference signal to the haptic icon to help users discriminate the different haptic icons, similarly as the musical tuning fork works. The use of a reference signal could reduce or even eliminate the need for short-term memory. The range of renderable signals highly depends on the haptic device. To maximise the users' ability to discriminate different signals, they must be carefully selected. Haptic device limitations, such as the device degrees of freedom, working space or latency, must be considered. Additionally, perception principles, such as the Weber-Fechner law [16], also play a relevant role. In this paper, we propose a methodology to select and order a proper set of haptic stimuli. Following the analogy with music, we call a haptic scale to a set of ordered haptic icons. Haptic icons are commonly created varying the signal frequency, amplitude, or shape. Previous studies have determined that frequency is the parameter that is best distinguished, followed by shape. Therefore, we validate the haptic scales creating frequency-based haptic icons sets. Furthermore, we have used the shape to increase the number of discriminable signals. As mentioned above, this methodology is device-dependent, and it has to be applied to define haptic icons for any new haptic hardware used in the system. We applied our methodology to an impedance kinesthetic device (Novint Falcon [17]), and we validated it, together with the haptic tuning fork, in our experiments that study, using a haptic device, to what extent subjects can discriminate between different rendered haptic icons.