The paper proposes a unified approach to mapping and clustering of bibliometric networks, aiming to integrate the VOS mapping technique with a weighted and parameterized variant of modularity-based clustering. The authors demonstrate that these two techniques can be derived from the same underlying principle, enhancing transparency and consistency in the analysis. They illustrate their approach by creating a combined mapping and clustering of frequently cited publications in the field of information science from 1999 to 2008. The results provide a detailed overview of the field's structure, distinguishing between the information seeking and retrieval (ISR) subfield and the informetrics subfield. The proposed method is particularly useful for generating multiple maps at different levels of detail, facilitating the use of bibliometric mapping in science policy contexts.The paper proposes a unified approach to mapping and clustering of bibliometric networks, aiming to integrate the VOS mapping technique with a weighted and parameterized variant of modularity-based clustering. The authors demonstrate that these two techniques can be derived from the same underlying principle, enhancing transparency and consistency in the analysis. They illustrate their approach by creating a combined mapping and clustering of frequently cited publications in the field of information science from 1999 to 2008. The results provide a detailed overview of the field's structure, distinguishing between the information seeking and retrieval (ISR) subfield and the informetrics subfield. The proposed method is particularly useful for generating multiple maps at different levels of detail, facilitating the use of bibliometric mapping in science policy contexts.