Abundance is easier to measure than importance, probably this is why we protect rare rather than important species. However, helping important species may indirectly benefit a lot of other species, including the rare ones, while protecting the rare is typically a local benefit. We need to improve the conceptual and methodological background of studying the importance of species. Importance roughly means large secondary effects after removal or extinction, realized mainly by direct and indirect chain effects spreading out from the focal population. We need to quantify these relationships, instead of reciting the conventional wisdom of holistic science „everything is connected to everything else” (what is basically true). This is why one way to assess the importance of species might be the quantification of their position in complex interaction networks. Network analysis, if the methods are carefully chosen, helps a lot in quantifying the topological characteristics of species, interactions and whole systems, and most importantly, clarifies how to link species to ecosystems. I present a number of techniques how to measure positional importance (e.g. centrality), imported mostly from social network analysis. These include local, mesoscale and global network indices. I discuss their relationships and biological relevance. I also present possible extensions for multispecies models. Finally, I will discuss the possibilities for testing the results. The quantitative and predictive description of important species (e.g. keystones) is of extreme importance for both better understanding ecosystem functioning and setting better priorities in conservation.