Abstract Field data collection is a foundation of ecological research, but it can be challenging and error‐prone. Researchers planning and undertaking fieldwork for the first time are especially vulnerable to logistical issues that can be avoided with more guidance. We offer guidelines to enhance the accuracy and efficiency of field data collection. Our guidance takes the prospective field ecologist through five steps: (1) identifying which variables should be recorded (focusing on your scientific question, but considering opportunities for additional data collection); (2) designing the data structure (understanding data structure, assigning useful IDs and avoiding confusing characters); (3) preparing a data collection protocol (building in redundancy, choosing a data collection technology, clean data recording and taking additional notes); (4) undertaking a pilot test (including data collection and digitising, communicating with the team); (5) following the protocol (assigning a decision‐maker, noting any changes, following routines and backing up data). This article is motivated by our own trial‐and‐error experiences and those of our colleagues and students, and a desire to help future researchers to avoid them. Our intention is to streamline the planning and field stages of data collection to avoid common pitfalls, thereby saving money, time and resources and supporting the whole data life cycle. Field data collection occurs across disciplines looking to understand the natural world, and each field excursion poses its own unique challenges. However, these guidelines can be useful as a starter for researchers to support open, reproducible, efficient and effective field data collection.
Jones et al. (Thu,) studied this question.