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Number of steps in datathief8/16/2023 ![]() Vitousek et al., 2018a, Bodensteiner et al., 2021). Finally, qualitative comparative reviews of a research question provide synthesis of a topic and data, but do not present analyses of data (e.g. Second, meta-analyses estimate the overall strength of evidence for a particular hypothesized effect by examining associations within many independent studies that have each addressed the hypothesis (e.g. effect of the environment on physiology and phenotype Noble et al., 2018a Gunderson and Stillman, 2015 Iglesias-Carrasco et al., 2020 Wu and Seebacher, 2020). First, analyses of comparative trait data (hereafter ‘trait-based analyses’) examine specific traits collected at a species or population level, typically aimed at questions of macro-ecological or -evolutionary interest (e.g. physiological scaling relationships Francis et al., 2018 White et al., 2019). ![]() Many decisions in database curation depend on the form of comparative research being undertaken ( Fig. 1). However, careful consideration of the challenges and trade-offs can lead to a useful and effective database with enduring benefits to the research field ( Whitlock, 2011 White et al., 2013). Compiling these data into a database can be an arduous process with many pitfalls. Comparative studies typically rely on high-quality data sourced from many independent empirical studies ( Davidson et al., 2011 Muñoz and Price, 2019). As such, they can provide major advances in biology, particularly in the fields of physiology and biomechanics. These approaches may address common mechanistic processes, reveal constraints on traits, highlight trade-offs in resource allocation and functional design, and generate new hypotheses (e.g. We argue that curating databases that are broader than one research question can provide a large return on investment, and that research fields could increase efficiency if community curation of databases was established.Ĭomparative studies have long been inspired by scientific questions seeking patterns or insights that cannot be answered with a single species ( Schmidt-Nielsen, 1972 Schmidt-Nielsen, 1975 Somero, 2000 Seebacher et al., 2015 Geange et al., 2021). Finally, we assert that the curation of single-question databases has several disadvantages: it limits the possibility of using databases for multiple purposes and decreases efficiency due to independent researchers repeatedly sifting through large volumes of raw information. We highlight how one's approach to these tasks often depends on the goal of the study and the nature of the data. We focus on four major tips: (1) carefully strategizing the literature search (2) structuring databases for multiple use (3) establishing version control within (and beyond) your study and (4) the importance of making databases accessible. This Commentary provides an introduction to building databases for comparative analyses and highlights challenges and solutions that the authors of this Commentary have faced in their own experiences. ![]() Unlike many scientific endeavors, building a database is a process that many researchers undertake infrequently and in which we are not formally trained. Whether conducting a species-level trait-based analysis or a formal meta-analysis of study effect sizes, comparative approaches share a common reliance on reliable, carefully curated databases. As the pace of science accelerates, there is ever-increasing access to diverse types of data and open access databases that are enabling and inspiring new research. Comparative analyses have a long history of macro-ecological and -evolutionary approaches to understand structure, function, mechanism and constraint.
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