澳门六合彩

Low-cost tools, including open source hardware, are changing how research is done and by whom. With broadened participation, factors such as the amount, type, and frequency at which data is being collected are changing. This shift can pose challenges to interpreting the quality鈥攁nd ultimately credibility鈥攐f low-cost tools and their data. 

The concept of 鈥渇itness for use鈥� can be defined as 鈥渢he degree to which a dataset is suitable for a particular application or purpose, encompassing factors such as data quality, scale, interoperability, cost, and data format鈥� (Holdren, 2015). The traditional way to assess data quality includes validity, completeness, consistency, and accuracy among others.  In the context of low-cost tools, we aim to outline challenges and potential solutions related to data quality and fitness for use by analyzing thetools themselves, as well as their digital environment, their regulatory context, and social context. Building a deeper understanding of how intentionally adopting a fitness for use perspective will facilitate not only greater uptake of low-cost tools but potentially more equitable access to science.