## 1 Introduction  
The key importance of mechanical factors on the physiological functions and processes that take place in the bone tissue, in both healthy and pathological conditions, is widely accepted [1; 2; 3]. Therefore, in recent decades, important efforts have been made in the mechanical characterisation of bone tissue [4; 5] (at different scales), and the mathematical modelling of its mechanical and mechanobiological behaviour [6; 7; 8]. On the one hand, the properties of the bone tissue are affected by a high number of factors, such as its morphological complexity and porosity, anisotropic orientation of trabeculae and osteons or its inherent hierarchical structure. A large number of studies characterise the structural and mechanical behaviour of the bone tissue by means of micromechanical [9; 10], nano-mechanical [11] and macroscopic approaches [12], to cite a few. They all show the heterogeneity of this tissue at all scales and the difficulty of relating experimental measurements to real tissue properties. For example, [PERSON] et al. [11] show, with atomic force microscopy experiments and computational simulations, that the nanomechanical properties and shape of cortical bone are directly related to their macroscopic mechanical behaviour, being this structure-property relation a key factor in some non-physiological behaviour of the bone tissue. Therefore, processes such as bone damage, bone remodelling and bone-related diseases (e.g., osteoporosis and fracture healing) could be better understood by relating microscale material heterogeneity to its macroscopic structural performance. One of the techniques that allows to obtain microscopic parameters in inhomogeneous, anisotropic and non-linear materials is digital image correlation (DIC). It is particularly suitable for biological tissues and has been successfully used for measuring the strain field in bone tissue [13; 14; 15]. It consists of comparing the positions of different points of reference within a deformable loaded region that is photographed at different times. These points of reference are usually painted in the sample using a spray to create a speckles pattern. Using this method, the strain field of a region of interest within a specimen may be provided with microscopic resolution. The advantage of this method over others, such as nanoindentation [10; 11], is that the whole strain field is recorded easily for different loading conditions. This technique, however, generate large amounts of data in comparison with traditional methods. On the other hand, there is a vast literature related to modelling bone tissue in many different scenarios and at several scales. The models may be classified--according to the observation scale--as macroscopic and microscopic. At the macroscopic scale, several issues have been addressed in the last few decades, such as modelling/remodelling [16; 17; 18; 19; 20; 21; 22; 23], poroelasticity [24; 25], bone healing [26; 27; 28] or bone tissue engineering [29; 30; 31; 32] among many others. Moreover, the driven mechanical stimulus [33; 34; 35; 27; 36] and the microstructural distribution of mechanical variables have also been studied [37; 38; 39; 40]. The multiscale analysis is a technique initially applied in the framework of the mechanics of heterogeneous materials. Specifically, multiscale techniques have been used in the analysis of fluid circulation within a porous medium [41], plasticity [42; 43], thermoelasticity or composite adhesives [44; 45], to cite a few (refer to [46] for a review of multiscale analysis in different applications). On the other hand, multiscale analysis has progressively developed great potential for the combined macro-and-micro analysis of biological tissues due to their hierarchical, multiphase and heterogeneous nature [47], such as tissue engineering processes [30; 31; 48]. Camcellous bone has been one the first candidates to be analysed through a multiscale approach [49; 50; 51].