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How not to collect data: organizing data for long-term use and re-use
Speaker
Stephanie Hampton
Washington State University
Stephanie Hampton is a Professor in the School of the Environment and Director of the Center for Environmental Research, Education and Outreach at Washington State University. Hampton’s research ranges from basic investigations in aquatic science using statistical analysis of large databases to broader applications of empirical evidence in environmental issues. Prior to joining WSU, she was Deputy Director of the National Center for Ecological Analysis and Synthesis (NCEAS) at the University of California - Santa Barbara. Hampton is active in exploring methods by which the scientific community can more broadly engage in data sharing, data-intensive research, and open science; she leads efforts to improve computational literacy, the culture of scientific collaboration, and accessibility of robust cyberinfrastructure in the environmental sciences. For more, follow her on Twitter @se_hampton
Most scientists have experienced the disappointment of opening an old data file and not fully understanding the contents. During data collection, we frequently optimize ease and efficiency of data entry, producing files that are not well formatted or described for longer term uses, perhaps assuming in the moment that the details of our experiments and observations would be impossible to forget. We can make the best of our sometimes embarrassing data management errors by using them as ‘teachable moments’, opening our dusty file drawers to explore the most common errors, and some quick fixes to improve day-to-day approaches to data. Read more
Most scientists have experienced the disappointment of opening an old data file and not fully understanding the contents. During data collection, we frequently optimize ease and efficiency of data entry, producing files that are not well formatted or described for longer term uses, perhaps assuming in the moment that the details of our experiments and observations would be impossible to forget. We can make the best of our sometimes embarrassing data management errors by using them as ‘teachable moments’, opening our dusty file drawers to explore the most common errors, and some quick fixes to improve day-to-day approaches to data.
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