The objects considered here are graphs encountered in practice in various domains: computer science, social sciences, health care, etc. The knowledge of these objects ask for several key questions which are addressed in this course: how to measure them in their real-world context in order to obtain a faithful view of their structure, which is not biased by the measurement tool? what are the essential structural properties of these graphs and what is their impact on phenomenon occuring on them (diffusion, epidemics)? how to take into account the dynamics of their topology? how to generate, for simulations, synthetic graphs having similar properties? and at last, how to efficiently extract information from these objects given their huge size?