How many times have you asked yourself, "Can I say 'Cryptomonads are a group of photosynthetic/algal cells,' or must I make note of that one genus that isn't photosynthetic and makes it hard to say what exactly they are?" Well, you're not alone. In scientific publication and in science communication, one of the great challenges is streamlining the message at the expense of at least SOME of the data. But lending a hat-tip to ALL the data makes for unwieldy sentences—exemptions, exceptions and uncertain language add up to difficult reading. Not all the data can be represented, but how do you incorporate it into a coherent message? How do you decide what to emphasize and what to omit? How much qualifying is 'too much'? While some choices may be more subjective than others, this session will address best practices for assembling summaries that are the most accurate representation of the data.
Questions:
- How do you generalize without misrepresenting the data?
- How does one organize the transformation of raw image data (eg. micrographs) to a summary diagram?
- What sorts of details are permissible to omit?
- How does the target audience shape which details stay and go?
