## 2 Previous Work  
Scientific and industrial fields involve massive data sets. Disciplines such as Big Data focus on automatic processing and extraction of these data sets. However, when the aim is not clearly defined or necessitates knowledge that cannot be entirely formalised, automatic extraction techniques are limited, and it is necessary to involve humans in the process of data exploration and analysis [19]. Visual perception has limitations such as the context effect [20] or crowding, and the inability to recognise objects in clutter [21]. Additionally, when there is a large amount of data, visualising every data point can lead to over-plotting and may visually overwhelm visual users' perceptual and cognitive capacities [5]. There has been mounting interest in non-visual forms of presenting information [10]. Information can be conveyed using the sense of touch which can help visually impaired people or be useful when other modalities are not available [22; 23]. Alternative representations are not only useful to blind or partially sighted users, but they are also useful in situations where the visual domain is impractical or overloaded [1; 24; 25; 26]. Several research fields, such as virtual reality, have leveraged the development of interfaces that provide feedback through different sensory channels. These advances have been applied to the exploration of large data sets using, for example, the haptic and auditory sensory channels. [PERSON] et al. [19] present an overview of the haptic rendering methods used for analysing massive data sets. There are several haptic rendering techniques designed to represent different abstract concepts [10] such as maps [27], graphs [15], diagrams [28; 29], tables [30], networks [31] or icons [32]. In these investigations, the authors use different types of haptic navigation algorithms to understand the shape or structure of the data. In addition, in some of them, they use haptic signals (such as friction or tactile texture) to represent different properties of these structures. Haptic icons are brief tactile, or force stimuli associated with a predefined meaning [11] and they can be used for representing abstract data. Haptic icons can be tactile or kinesthetic stimuli, depending on the haptic device. [PERSON] and [PERSON] [33] describe the haptic icons as a potential tool to improve the interaction in different areas, particularly when there is an overload of the visual system, or it is limited or unavailable. Haptic devices can be used to present information, and consequently, the user gains quantitative, qualitative, or holistic knowledge about the different data [10]. In the case of quantitative data, [PERSON] et al. [15] indicate that the solution using tactile stimuli for each data is rather ineffective and confusing because they need to rely on the users' short-term memory. According to several authors [34; 35] the success of the representation of variables using haptic stimuli is influenced by the high dependence of humans on the short-term memory, which is limited for most subjects. This capability prevents representing a large number of quantitative data using the haptic channel. Therefore, utilising the haptic display is reduced to data requiring low accuracy. The capacity limits of human cognition are not well defined. [PERSON] ([PERSON], 1956) reports that the capacity of working memory is seven chunks of information, plus or minus two, and the short-term memory limit is about seven chunks, but this number also depends on the category of the chunks used (digits, words, or haptic stimuli, for example). To address this limitation, several authors combine the haptic feedback with auditory stimuli, especially for the representation of quantitative information [27; 36; 37; 38]. [PERSON] et al. in [15] adopted a multimodal approach, using haptics for navigation and dedicating the auditory modality for providing quantitative values through synthesised speech and an overview through sonification.