Tenzing and the importance of tool development for research efficiency

The way science is done is changing. While some tools are facilitating this change, others lag behind. The resulting mismatch between tools and researchers’ workflows can be inefficient and delay the progress of research. As an example, information about the people associated with a published journal article was traditionally handled manually and unsystematically. However, as large-scale collaboration, sometimes referred to as “team science”, is now common, a more structured and easy-to-automate approach to managing meta-data is required. In the present paper, we describe how the latest version of tenzing (Holcombe et al., 2020) helps researchers collect and structure contributor information efficiently and without frustration. Using tenzing as an example, we discuss the importance of efficient tools to reforming science and our experience with tool development as researchers.