Seismology focuses on the study of earthquakes and associated phenomena to characterize seismic sources and Earth structure, which both are of immediate relevance to society. This article is composed of two independent commentaries about the state of ICON principles (Goldman et al., 2021) in seismology and reflects the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (Section 1) integration of multiscale and multidisciplinary observations; (Section 2) high-performance computing and open-source algorithms. In the past century, seismology has benefited from two co-existing technological advancements - the emergence of new, more capable sensory systems and affordable and distributed computing infrastructure. Integrating multiple observations is a crucial strategy to improve the understanding of earthquake hazards. However, current efforts in making big datasets available and manageable lack coherence, which makes it challenging to implement initiatives that span different communities. Building on ongoing advancements in computing, machine learning algorithms have been revolutionizing the way of seismic data processing and interpretation. A community-driven approach to code management offers open and networked opportunities for young scholars to learn and contribute to a more sustainable approach to seismology. Investing in new sensors, high-performance computing, and open-source algorithms following ICON principles will enable new discoveries across the Earth sciences.