- The body of the talk is where you're going to spend most
of your time during the talk.
That's the main course.
That's what people are coming to see your talk for.
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- You are making an argument about your data.
You're telling your story.
You're showing your logical flow,
how you got the data,
the implications from that data and where you're going next.
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- Depending on how much time you have for your talk
and how complicated your experiments are,
it is important to pick very wisely
what you want to talk about.
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- You don't want to try to speed through all of your data
in a 10 minute talk.
The 30 to 45 minute talk,
I'll probably spend a lot more time
really making decisions about the order
that I'm presenting the data.
If I'm using a complicated technique,
I'm really able to spend the time to break down
that technique for my audience.
- One can structure their talk differently
to get different messages across.
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If I'm presenting at a conference to a group of individuals
who are within my area of expertise
I might get into a lot of detail and depth.
But say when I was presenting my job talk,
I was trying to give an overview of the work that I've done
rather than go too far in depth in
on any particular topic itself.
- What is the information that my audience is going to need
to understand the relevance and the significance
of the work that I am doing?
- The main purpose of giving a talk
is to convey that information.
And there are two primary means of doing that.
You know, what you say, and what you show on your slides.
And those two really need to be in service of each other.
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- Think about an illustrated book.
There are the words that amplify the story,
and then there often are pictures.
Some information in the talk is just better shown,
like a dataset or like a certain bullet points
to really make clear what the main topic of your talk is.
- For each individual slide, what you want is a main point.
And that main point needs to relate to the core message.
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Other data, which may have been relevant in my paper,
but may not necessarily be required
to understand my core message, that can go away.
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First, I like to talk about the experimental setup.
What are the methods that I used for the experiment
that I'm about to show you?
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- We took the coral mucus that was collected.
We took the bacteria inside of that mucus.
We took our fingerprinting technique,
and we came up with a representative value.
This way we can compare and contrast
the different communities in the different corals.
- The audience is then primed and ready
to receive and interpret the data
that I'm about to show them.
Then I show them the data,
and I try to do that in a very clear and accessible way.
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- On the axis, you'll notice
they aren't your typical X and Y axis.
Instead, these are variation axis.
This means that the farther apart two points are,
the more different the bacterial communities are,
and the closer they are, the more similar they are.
- And then I talk about, okay,
what did I learn from this data?
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- Healthy corals are all alike,
but every sick coral is sick in its own way.
- Finally, I like to end by talking about
what are the future directions.
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If you do that for each supporting piece of data,
it really does allow your audience
to follow along your research story,
to follow along what experiments you did and why
and how that led you to the next experiment.
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- Just as much as we need to think about,
"Am I making it too complicated?"
There also needs to be thinking about,
"Am I taking too much out?
"Am I simplifying it so much
that actually the exciting science part
is really kind of no longer present?"
- And give your audience credit
that they will be able to understand the data
that you're going to present,
even if it is a general audience,
as long as you don't over complicate the figures,
over complicate the explanation,
you try to distill your message in a succinct and clear way.
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