**5. Conclusions**

A measure of centrality for biplex networks (APABI) based on the APA centrality for spatial networks with data has been designed and implemented following the two-layers approach for PageRank model. The advantage of having a measure of centrality of this type is twofold; on the one hand, we can determine the importance of the nodes of a network when we study various relationships between the nodes. On the other hand, we can work with several data sets associated with the nodes themselves, without any connection or relationship between them.

This measure, initially proposed for two layers of topological relationships and data, can be easily extended to any set of layers and thus add the relationships between the nodes. Its use in the study of social networks can allow us to relate various aspects of the actors, as well as their interactions. These possibilities are shown in the example studied, where the social and professional relationships of a group of people that are part of a sports group are analyzed. The importance of each node (player) is analyzed both from the social and game aspects, respectively. From the proposed centrality we determine the most influential players in the team. It is observed how the most relevant nodes in each of the layers do not have to be the most important when analyzing the related data.

**Author Contributions:** All authors contributed equally to this work: conceptualization, methodology, formal analysis, investigation and writing—original draft preparation.

**Funding:** This research is partially supported by the Spanish Government, Ministerio de Economía y Competividad, gran<sup>t</sup> number TIN2017-84821-P.

**Conflicts of Interest:** The authors declare no conflict of interest.
