About the Book
The face of academia is changing. It is no longer sufficient to just publish or perish. We are now in an era where Twitter, Github, Figshare, and Alt Metrics are regular parts of the scientific workflow. Here I give high level advice about which tools to use, how to use them, and what to look out for. This book is appropriate for scientists at all levels who want to stay on top of the current technological developments affecting modern scientific careers. The book is based in part on the author's popular guides including guides for
The book is probably most suited to graduate students and postdocs in the sciences, but may be of interest to others who want to adapt their scientific process to use modern tools.
About the author: Jeff Leek is an Associate Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. He is a co-founder and co-director of the Johns Hopkins Data Science Specialization on Coursera that has enrolled over 3 million aspiring data scientists. His research has helped contributed to our understanding of the genomic basis of brain development, blunt force trauma, and cancer. He is blogs at Simply Statistics and can be found on twitter at @jtleek and @simplystats
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Table of Contents
- Introduction
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Paper writing
- Writing - what should I do and why?
- Writing - what tools should I use?
- Writing - further tips and issues
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Publishing
- Publishing - what should I do and why?
- Publishing - what tools should I use?
- Publishing - further tips and issues
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Peer review
- Peer review - what should I do and why?
- Peer review - what tools should I use?
- Peer review - further tips and issues
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Data sharing
- Data sharing - what you I do and why?
- Data sharing - what tools should I use?
- Data sharing - further tips and issues
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Scientific blogging
- Blogging - what should I do and why?
- Blogging - what tools should I use?
- Blogging - further tips and issues
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Scientific code
- Scientific code - what should I do and why?
- Scientific code - what tools should I use?
- Scientific code - further tips and issues
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Social media in science
- Social media - what should I do and why?
- Social media - what tools should I use?
- Social media - further tips and issues
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Teaching in science
- Teaching - what should I do and why?
- Teaching - what tools should I use?
- Teaching - further tips and issues
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Books
- Books - what should I do and why?
- Books - what tools should I use?
- Books - further tips and issues
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Internal scientific communication
- Internal communication - what should I do and why?
- Internal communication - what tools should I use?
- Internal communication - further tips and issues
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Scientific talks
- Scientific talks - what should I do and why?
- Scientific talks - what tools should I use?
- Scientific talks - further tips and issues
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Reading scientific papers
- Reading scientific papers - what should I do and why?
- Reading scientific papers - what tools should I use?
- Reading scientific papers - further tips and tricks
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Credit
- Credit - what should I do and why?
- Credit - what tools should I use?
- Credit - further tips and issues
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Career planning
- Career planning - what should I do and why?
- Career planning - what tools should I use?
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Your online identity
- Your online identity - what should I do and why?
- Your online identity - what tools should you use?
- Your online identity - further tips and tricks
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About the author
- Should you follow my lead?
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About the Author
Jeffrey Leek
Jeff Leek is Associate Professor of Biostatistics and Oncology at Johns Hopkins Bloomberg School of Public Health and co-director of the Johns Hopkins Specialization in Data Science. He writes for the blog Simply Statistics and can be found on Twitter @jtleek, @simplystats.
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Causes Supported
Data Carpentry
Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Our goal is to provide researchers high-quality, domain-specific training covering the full lifecycle of data-driven research.
From astronomy to molecular biology and digital text, our increasing capacity to collect data is changing research. It allows us to ask questions that previously could not have been answered, and it changes the impact that research has on society. Although petabytes of data are now available, most disciplines are struggling to translate this sea of data into knowledge. The missing step between data collection and research progress is a lack of training for scientists in crucial skills for effectively managing and analyzing large amounts of data. Data Carpentry addresses this gap by teaching researchers the fundamental data skills they need to conduct their research. Our goal is to provide researchers high-quality, domain-specific training covering the full lifecycle of data-driven research. We teach hands-on workshops in data organization, management, and analysis to increase data literacy and improve research efficiency and reproducibility.
