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I'm here to tell you

2
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why I don't tell the truth about castles.

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You might think it's my job.

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After all, we expect professionals

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to speak with authority
and give us clear-cut solutions,

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and that makes us very, very nervous

7
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because there's so much
we simply don't know about history.

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And as a result,

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a lot of things have become established
in our collective memory as the truth

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simply because someone said it once,

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it sounded convincing,

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and nobody since has stood up to say,

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"Well, we don't know exactly
what it was like,

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but it wasn't like that."

15
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Take Greek temples.

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Everyone knows they're made
of beautiful shining white marble.

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We've seen them that way for centuries,
from postcards to museums,

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and that establishes certain
seeing habits in our heads,

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where we've seen them this way so much
that anything different just looks wrong.

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And yet today we know for a fact

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that they were painted
in bright garish colors;

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we're just a little unclear
on some of the details.

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I've colored this one in myself
in about five minutes of research,

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so it's likely to be wrong
in all the relevant places,

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and it's still more correct
than the white one.

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So why do we continue
to show them in white?

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Well, there's two reasons for that:

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One is that we as humans like certainty.

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And so we would prefer
to be absolutely certain

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even if it's the absolute certainty
that we are absolutely wrong

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(Laughter)

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than to say, "Well,

33
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maybe it could have been approximately,

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I think, something like …"

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And then there's the fact

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that when we're trying to establish
a new truth in people's heads,

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we want it to be
the correct truth this time.

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But even if we're not
entirely clear on all the details,

39
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that doesn't mean
we can't make a statement.

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If you ask me right now what time it is,

41
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I can't tell you,

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but I don't have to shrug my shoulders
and just say, "I have no idea."

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I know this event is on
from 12:00 till 6:00,

44
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so that eliminates
half the clock right there.

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We've had our first coffee break,
we've not had the second,

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so it's between 2:00 and 5:00.

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I know there were people ahead of me,
and I'm not being told I'm out of time,

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so it must be around 4:30.

49
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Is that correct?

50
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I don't know.

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It might not be the truth,
but I don't have to tell you the truth.

52
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I just have to know
how correct I'm likely to be

53
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because how correct I am
can be very, very important.

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Me telling you it's about 4:30
is pretty useless

55
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if you want to know
whether you can still catch your bus;

56
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and in that case,
we might have to ask more people,

57
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we might have to fill it in
with more clues and so on;

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and that's science.

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We ask a question,

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and then we fill in the unknown
and get more and more precise.

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So the scientific method
is pretty well-established:

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You ask a question
about the world around you,

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you research what
you already know about it,

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you design an experiment
to test what you don't know about it,

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you gather the data, you analyze them,
and you reach a conclusion;

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and that conclusion could be,
"I need more data."

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Then you go back,
design another experiment,

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run it again, gather more data,

69
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and you get more data
and more data and more data,

70
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and suddenly you're buried in data,

71
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and you're dealing with big data,

72
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where scientists now have this problem

73
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that there's so many data

74
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they can never read them all
in one lifetime.

75
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They have to find new ways
to deal with that.

76
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And then there's me.

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This is me.

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You can tell I'm not
the kind of scientist with a lab coat,

79
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and my data problem is slightly different.

80
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Basically I'm dealing
with one student's lab report

81
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that they dropped on the floor,

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lost half the pages
and then shuffled the rest,

83
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and there's probably a coffee stain
on the relevant bit.

84
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So what I've got is I've got
half a broken castle,

85
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slightly burned,

86
00:04:23,066 --> 00:04:26,968
I've got a legal contract from 1388
that was written by a guy

87
00:04:26,968 --> 00:04:30,872
who managed to spell the name "Arnold"
four different ways in three pages,

88
00:04:31,672 --> 00:04:33,387
I've got some rocks from the village

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that may or may not have
belonged to this castle,

90
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I have got a map
that was done by a guy

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for whom this was a 10-minute squiggle
in an eighth-year campaign,

92
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a painting that was drawn

93
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about 300 years
after the castle burnt down,

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and a book that was probably propaganda.

95
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And of course I could go
look in the archives,

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I can get another archaeological
excavation going, and so on,

97
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but at some point, there's simply
no way to gather more data.

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And then you expect me to take that

99
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and mash it all up
into the truth about castles?

100
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You want a reconstruction
that's so realistic

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it feels like you're really there,

102
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like every little pebble
in the courtyard is just right.

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There's a reason that a lot
of sites and museums

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don't use the word "reconstruction";

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instead, you find a picture,

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and next to it, it has the disclaimer
"Artist's impression."

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And that doesn't mean
they didn't do any research;

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it just means they didn't document
what they researched.

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We don't know who they talked to,
which books they read,

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which conclusions they drew,

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and which other theories they discarded.

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Now, imagine for a moment

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that we would treat a text the same way.

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You go into the museum.

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There's a plaque, and it says,
"Author's impression."

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The author thinks there might
have been a castle here.

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You wouldn't take that very seriously.

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So why do we treat text
so differently from models?

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It's because we've come to a consensus
on what makes a scientific text,

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and it's quite simply this.

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When you're writing
a scientific document,

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you put in footnotes,

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you cite works by previous scholars,

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you show your argumentation -

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you simply give your document provenance -

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because showing you a picture of the truth

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isn't going to help you
without me explaining why it's true.

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The truth is, all of these
are correct at the same time.

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That's the truth,
but it's not a very helpful truth,

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because without context,
data are not information.

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So I'll give you a little context.

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So for a little context,

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this first clock shows
the time in Luxembourg,

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and the second one
has the time in Tokyo,

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the third one is one
of those annoying clocks

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everyone had in their kitchens
about 10 years ago

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that actually run counterclockwise,

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and the fourth one is not a clock,
it's a barometer -

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you just wouldn't know that
by looking at it.

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So in historic research,

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when we deal with images,
we know what to do:

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We give those provenance
through metadata and paradata.

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Metadata you've probably heard.

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Metadata are data about the data.

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You can see those when
you're browsing your computer,

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and you can see who made a file,
when it was made,

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when it was last opened, and so on.

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Paradata are slightly more complex.

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Paradata are data
that give context for the data,

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so like how they were gathered,
how they were processed,

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which decisions were made
about them, and so on.

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The metadata for this image

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would be that it was taken by me
on the first of June, 2017

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on a Sony compact camera.

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The paradata are that it was
picture 111 in a series of 128

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and I took it on my first
research trip to this castle.

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And I love to show this picture

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because this picture has everything in it
that is wrong with models.

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You walk up the stairs in this castle,
you come to the attic,

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and there's a big glass box
with this model sitting in it.

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And what I love about it

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is that there are no data
attached to it whatsoever.

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You don't have a scale bar.

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You don't have a date
it was made or who made it.

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You don't have a date
it's supposed to represent.

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There's nothing even to say

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that it's supposed to be this castle
that you're standing in.

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And if you're talking
about decision-making processes

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in the reconstruction,

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if you take a closer look
at that center tower there,

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it becomes very, very obvious

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the size of that tower was not based
on an archeological excavation

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or because there was
a foundation there or something.

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No, that's the size
of the toilet paper roll they had.

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(Laughter)

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And so this model makes me happy

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because it's everything
I'm trying to avoid.

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And I'm not the only person
trying to avoid this kind of thing.

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A lot of intelligent people
are working and avoiding this.

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There are some hugely
complex systems these days

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that go into great detail on data,

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metadata, paradata,
how they all relate, and so forth;

183
00:09:02,775 --> 00:09:05,954
and my favorite one
takes about six months to learn.

184
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Now that's bad enough for me
as a researcher,

185
00:09:08,724 --> 00:09:10,790
but imagine that you,
as a museum visitor,

186
00:09:10,790 --> 00:09:12,839
have to go on a six-month
training course

187
00:09:12,839 --> 00:09:14,852
to understand what you're seeing.

188
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So, instead, I have a system
that's just good enough for me.

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I simply take my model,

190
00:09:21,686 --> 00:09:26,792
and I tell you which parts are true
and which ones are not.

191
00:09:26,792 --> 00:09:28,893
So probably true is the easiest.

192
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That's the category of things
that I think are true

193
00:09:31,826 --> 00:09:33,858
because they're still there,

194
00:09:33,858 --> 00:09:36,567
so that could be things
like the castle ruins.

195
00:09:37,757 --> 00:09:39,696
Next, pretty close to true,

196
00:09:40,981 --> 00:09:42,696
we have a lot of evidence for those.

197
00:09:42,696 --> 00:09:43,699
So for example,

198
00:09:43,699 --> 00:09:46,621
I was saying foundations,
towers on foundations -

199
00:09:46,621 --> 00:09:49,844
we fill in the gaps
what we have good evidence.

200
00:09:50,254 --> 00:09:53,962
Third stage, extrapolation,
could be true - maybe not.

201
00:09:53,962 --> 00:09:56,583
That's where I'm working
on secondary and tertiary data,

202
00:09:56,583 --> 00:09:58,253
like the maps and images.

203
00:09:58,253 --> 00:10:00,360
And then there's my favorite category -

204
00:10:01,015 --> 00:10:03,495
the stuff that's not really true.

205
00:10:04,900 --> 00:10:07,399
Now, these things I need
to put in my model

206
00:10:07,709 --> 00:10:10,328
because the model would be
missing something without it.

207
00:10:10,328 --> 00:10:13,094
If I didn't put these in,
I would be telling you a lie,

208
00:10:14,014 --> 00:10:16,142
but I have no idea what to really put in.

209
00:10:16,482 --> 00:10:17,816
It's an interesting problem.

210
00:10:17,816 --> 00:10:21,882
So that's things like I know
the great hall had paintings on the walls,

211
00:10:21,882 --> 00:10:24,259
I will never know what exactly
was painted on them,

212
00:10:24,259 --> 00:10:25,829
so I have to make something up,

213
00:10:25,829 --> 00:10:28,628
but if I left them as a blank stone
the way they are now,

214
00:10:28,628 --> 00:10:30,668
that would be making a statement.

215
00:10:31,398 --> 00:10:34,773
And then, of course, I need to attach
my metadata and my paradata,

216
00:10:34,773 --> 00:10:37,738
and tell you why it's in that category.

217
00:10:38,058 --> 00:10:41,174
And finally, I need
to make very, very sure

218
00:10:41,174 --> 00:10:43,531
that you don't only know
why it's in that category

219
00:10:43,531 --> 00:10:45,892
but which part exactly
I'm talking about.

220
00:10:46,492 --> 00:10:49,142
If you remember that clock from earlier,

221
00:10:49,472 --> 00:10:52,769
well, I can tell you for a fact
that it's Friday afternoon.

222
00:10:53,089 --> 00:10:55,788
I can also tell you
with absolute certainty

223
00:10:55,788 --> 00:10:59,842
that sometime in the last two millennia,
we had a castle on this hill.

224
00:11:00,542 --> 00:11:02,537
What I cannot tell you

225
00:11:02,537 --> 00:11:06,119
is whether in that window, in 1548,

226
00:11:06,119 --> 00:11:09,719
we had an archway
and that archway had a stone

227
00:11:09,719 --> 00:11:12,864
and that stone was exactly
312 millimeters wide.

228
00:11:13,234 --> 00:11:15,101
It could have been 317,

229
00:11:15,101 --> 00:11:17,800
but my drawing is going to say
one way or the other.

230
00:11:19,600 --> 00:11:23,669
And that is the really, really
interesting point for future researchers

231
00:11:23,949 --> 00:11:26,531
because if I've told you
I have no idea what was here,

232
00:11:26,531 --> 00:11:29,530
they can use that point to research,
and then they can say,

233
00:11:29,530 --> 00:11:32,540
"Look, we found more data,
and actually you're completely wrong.

234
00:11:32,540 --> 00:11:35,025
It was 483 millimeters."

235
00:11:35,025 --> 00:11:36,569
And I can say, "Hooray!"

236
00:11:36,569 --> 00:11:39,615
because that advances
our state of collective knowledge.

237
00:11:40,025 --> 00:11:42,127
So if I'm doing science properly,

238
00:11:42,127 --> 00:11:44,751
I want people to be able
to prove me wrong.

239
00:11:46,390 --> 00:11:49,887
So that's why I'm not going to tell you
the truth about castles,

240
00:11:51,454 --> 00:11:54,344
and why I make it
very, very clear to you

241
00:11:54,804 --> 00:11:56,336
when I'm just making it up.

242
00:11:56,336 --> 00:11:57,707
(Laughter)

243
00:11:58,487 --> 00:11:59,740
Thank you.

244
00:11:59,740 --> 00:12:02,454
(Applause)