Let's cross our fingers, shall we?
So my name's Ian Gregory.
And David asked us to talk about the work that we have done.
I'm more going to talk about work that I'm just starting.
But I think it fits in with the theme of the session quite well.
What I'm going to talk about is work that we have either piloted
or just starting to do under an ERC grant that I got,
entitled Spatial Humanities, Texts, GIS, and Places.
But before I start talking about that in too much detail,
I want to say a little bit about where the idea for this came from,
because I'm actually a geographer by training.
And a geographer that got into this game really threw an interest
in quantitative analysis,
quantitative geography, statistical analysis of quantitative patterns,
that sort of thing that may seem a long way from the humanities.
But another thing about certainly being in a British geography department
through the 90s in particular was, although in theory geography
is a very interdisciplinary discipline that covers everything
from the Earth sciences through the social sciences to the humanities,
it does a remarkably good job of fragmenting into little cliques
that slag each other off from an ignorant and safe distance
and just achieve very little other than running other people's work down.
And that left me with a real scepticism for that sort of approach,
and also a belief, I think, that if GIS is anything,
it's an integrating technology at a technical level
that allows data that's very disparate to be brought together.
And beyond that, it should be able to be a technology
that's able to integrate different disciplinary approaches as well.
And I'm very suspicious of attempts to compartmentalise
little bits of it away from other bits.
It's something that should be seen as a whole.
So in the spirit of that, I started very much working on large quantitative databases,
GIS databases of 19th and 20th century British historical statistics
in something called the Great Britain Historical GIS.
The diagram to show up, to map and the graph up here,
are an attempt to summarise some work that came out of that,
quite a lot of work that went into producing them.
But what this is concerned with is, in the 19th century,
the Victorians realised they had a major problem.
Lots of people were flooding into cities.
Those cities were becoming extremely unhealthy,
and they were starting to get very high mortality rates.
And those mortality rates were particularly pronounced amongst the young.
Babies before the first birthday infants would have mortality rates up to about 200 in a thousand.
In other words, one baby in five dying before its first birthday.
And that would carry on up until about the age of five.
Because of that, the Victorians started quantifying the number of deaths within districts
and creating vast amounts of statistics.
And what came out of that was a public health movement,
which through the 1870s and the 1880s,
increasingly tried to crack down on things like poor sanitation in cities,
it tried to improve provision of midwives,
tried to take a range of actions that would try to drive down into mortality in urban areas.
And not long after these public health acts were introduced,
infant mortality did indeed start coming down,
and has continued to do so throughout the 20th century.
So this orthodoxy has become established that infant mortality decline
was brought about by public health intervention through the 1870s and 1880s.
What the map on the left tries to show,
it's based on some GIS work looking at which areas improved the most
and which areas improved the least over the period from the 1850s,
when we first have data, to the 1900s.
And what it shows is in actual fact,
the areas that had the biggest reductions in infant mortality,
the ones shaded in green, were almost all rural,
and they were almost all in the south and east of England.
The areas that had the lowest improvements in the mortality rate
were these kind of peripheral areas,
through the north of England and down through Wales and into Cornwall.
Also, if you follow it through temporally,
the declines that were occurring particularly in the rural south
and east started long before the public health movement kicked in.
So what that tells us, what the GIS has allowed us to do,
cutting a long story short,
is that the traditional explanation of infant mortality decline
starting because of the public health movement cannot be correct.
If it was correct, you'd get the biggest improvements occurring in urban areas
and then not start until the 1870s, 1880s.
That's not what happens.
So what that shows you is that by using GIS,
what we're able to do is position the data much better to say
what happened, where it happened, and when it happened,
and in that way, challenge the orthodoxy that's out there.
What it's not able to do, at least not in this form,
is say what actually happened.
It's not able to develop its own explanation.
And that's frequently thrown at GIS as a criticism of what's wrong with GIS,
but in actual fact, it's not to do with what's wrong with GIS.
It's what's to do with the original source that this GIS work is being based on.
What this source does is it quantifies as close as we'll ever know
to the number of births and infant deaths that took place over a 60-year period.
And it locates them in time and in space.
So from one point of view, it's an extremely good source.
But from another point of view,
those infants dying or surviving through that period
have been highly abstracted from the conditions in which they were born, lived and died.
Therefore, we're really not able to develop an explanation from this kind of source.
But it's not a problem with the GIS.
If we were to come at this from a social science point of view,
what we'd want to do is to develop what we...
to bring in a range of what are wrongly called explanatory variables
on a range of issues which would show us
what was actually related to infant mortality decline.
The big problem with that is simply that there are nothing like...
Well, there's a number of problems with it,
but one of the big ones being that there simply aren't data
on all the other factors that might be involved.
Things like breastfeeding, access to safe cow's milk,
sewage schemes, availability of midwives,
working conditions for women in agriculture, etc., etc., etc.
You're simply not going to get quantitative data on that.
So this idea of social science approaches to explain this is a bit of a non-starter.
So if we are going to try and explain it,
we're going to have to go in a very different way.
And that's really where this project kicks in,
because the source that is going to explain this sort of thing
has to be based in texts,
because texts, after all, are where most human knowledge is located.
The problem is, traditionally, texts haven't really been used in GIS.
So the first big part of this project
is really to explore how we can adapt texts
for both use in GIS,
both in terms of turning a text into a GIS,
and then, more importantly,
how can we go about doing automated analysis of them?
The way we go about doing it, in some ways, it's actually not very difficult.
You can use corpus linguistics approaches to, first of all,
identify simply words within a text that are place names.
This is actually from some 1650s news books published in London.
The map on the left shows all of the place names
that we could find within these news books.
There's about 800,000 words of this, so it requires automated techniques.
The map on the right is what we call the density-smooth version of that,
which just makes the pattern a bit easier to understand.
So you can see there's a very clear pattern
of where London-based news books were interested in.
It's particularly England and Wales.
It's also, to a certain extent, the area around Paris
and up into the low countries as well.
Geographies of absence are quite interesting in this.
The fact that they're not particularly interested in Ireland,
Iberia and various other places is also quite interesting.
However, we're not just interested in where a text is talking about.
We're also interested in what it's saying about places.
And again, corpus linguistics techniques can help us out here
by using what's called collocation techniques.
So what words are occurring near to place names?
This is a map of place names where words associated with war
occur near them in the text.
And you can see there's quite a pronounced and quite a different pattern to it.
There's a very strong cluster going on in the northeast of Scotland.
There's another cluster on the port of Brest.
And there's a kind of spread-outy kind of cluster stretching across
from London into the channel ports kind of area
and down to Paris from there.
Another map just showing the distribution of words about money,
which in this case is, again, a different pattern.
Again, it starts in Scotland but runs all the way down the east coast
to Britain through Newcastle and Scarborough to London.
And you've also got a strong cluster on Paris,
another one around Amsterdam kind of area,
and a strong cluster on Tunis.
And that in turn starts to pose some questions.
And this is where this approach becomes,
I think, much more powerful potentially
than the traditional statistical-based approaches.
Because what you can do with this is start to actually drill down
into the original text and then find out
what they were saying about the places.
So actually answer the question,
why are these patterns as they are?
So let's start with the example of Tunis,
which has never been famous as a financial center.
Explore what's going on with that.
What you actually find from this is it's actually a tagging error
that's caused by the word account.
The Turks are being called for account for the wrongs
they've done done to the Christians.
And account is a tagging error.
If you're going to start doing these sorts of automated things
with large amounts of text, you're going to get these problems.
But the GIS, the fact you're mapping it,
throws up that this is an oddity and something
that you want to explore in more detail
and allows you to do it.
Similarly, Scarborough might also seem like an odd place
to be associated with a financial center.
However, in this case, it actually turns out to be genuine.
What was going on is there was a war between England and Holland
and they were landing what they called rich prize ships at Scarborough.
So it is actually associated with money.
And similarly, the big cluster in the northeast of Scotland
associated with war, well, there was a rebellion going on there.
And we're able to drill into the text
and find out what they're saying about these places.
And if we wanted to, then actually refer back
to the original parts in the text where these concordances,
as they're called, were taken from.
So actually, what we're able to do here
is move into what Franco Moretti terms distant reading, which
both allows us to stand back from the text and abstract them,
but also to then use this as a tool to explore
where we should be reading in more detail and allow us to do that.
I'll skip over that.
We're also going to apply that in more detail
to a study of literature in the Lake District, which
were piloted quite extensively, just exploring originally
two quite short texts to see the kind of things we can do.
So we're exploring Thomas Gray's tour in 1769
and contrasting it with Samuel Taylor Coleridge's
tour in 1802.
We can do things like the density smooth maps
to show what places they're most interested in.
In Gray's case, it's the area around Keswick.
Up here in Coleridge's case, it's
Scarfell in the area around that.
We can compare and contrast these
by doing overlay operations.
These areas are areas just talked about by Coleridge.
The areas in dark green are just talked about gray.
And the in-between kind of light greens and yellows
are talked about by both of them.
The interesting thing about this map
is it kind of summarizes it.
Although they're both Lake District writers,
they really didn't overlap very much.
So there's two very different things going on
in the two different texts.
We can also map their emotional response to the landscape.
How positive or negative were they
about the places they were talking about?
And this gives a slightly different pattern
to the overall pattern of place names,
because what we see with Gray is he's particularly
interested in the area in Borodale
in the southern part of Derwent water,
but also responds very strongly to Ullswater,
whereas Coleridge very much centered on Scarfell,
but also lights in Newlands Valley quite a lot.
So again, we're able to abstract and talk about these things
from a distance.
We're also, as I said, able to integrate
other sources of data.
So we have the locations of all the places they mentioned.
And by overlaying that with a terrain model,
we're able to actually explore the heights
that they're both visiting and talking about.
The blue bars on this are places that Gray was
actually visiting, and the red bars are places
he's talking about from a distance.
And the pattern is really quite striking.
He spends most of his time below 1,000 feet.
And he talks about, without visiting,
places that are either near to him
or that the high peak's in the Lake District.
And he almost completely ignores the areas in between.
Whereas Coleridge, on the other hand,
is much more across the height land.
He went up Scarfell, the highest mountain
in the Lake District.
So there's quite a lot of high heights in there.
But people tend to really stress that part of his tour.
Gray spends much more of his time though
talking about lower parts of the Lake District as well.
We can also integrate other types of information,
particularly polygon-based sources
to look at things like the population densities
of where they were talking about too.
And that's, there's nothing particularly surprising
about what we find there.
Gray spent a lot of the time in the more urban parts
where Coleridge consciously avoided them.
But at least we can start to quantify and demonstrate that.
We're also interested in comparing historical representations
to the landscape with more modern representations.
What this slide attempts to do,
although it looks slightly like someone spilt something on it,
what it tries to do is map all of the photos
of the Lake District that are geotagged in Flickr,
a Web 2.0 site.
And it's, so really what it's showing
is where are people interested in
within the Lake District today.
And there's some really quite interesting patterns.
Again, the geography of absence is very interesting.
Large parts of the national park,
what's now the national park, which is enclosed in green,
actually have no photographs of them in them at all,
which was really surprising.
But what you find is people tend to photograph places
either in the urban centers like Keswick, Kendall,
Ambleside, Windermere, places like that,
or they go very much follow along the natural roads
and so on.
So this line across here, if you know it,
is hard not past and rhinos past,
two very narrow little windy roads
that go up into the mountains.
These are the kind of areas
that seem to be drawing people in.
We can compare that back with the literature
and see whether these are the same kind of patterns
that were followed in the past as well.
Again, though, we don't wanna just abstract away
from the text.
We want to use these abstractions
as a way of understanding the text better.
And this system here attempts to help you
with your close reading of the text as well.
So what you've got on this window here is
you can read along, there's two ways into doing this.
You can either read along with one of the texts here,
which you can see has got the place names,
highlighted in it, and by clicking on a place name,
see where that place name is on the map.
And even if you know the Lake District well,
some of these texts are hard to follow.
And if you don't know it at all,
this sort of thing really does contextualize
the information very well.
Or alternatively, what you can do is simply click
on a place that you're interested in on the map.
And from there, it will give you the list
of all the people that have mentioned that place
within their text, and you can then follow it through
to actually find the paragraph that they're talking about.
So it's not just a way of abstracting away from the text,
it's also a way of enhancing and enriching the text
so that you can understand it in a bit more detail.
What we're gonna do longer term though,
so these two packages focus first of all on methodologies
and then on trying to apply them
to Lake District literature.
But eventually I want to bring this back to this map here
to actually bring together sources
like 19th century newspapers,
sources like official reports and parliamentary debates,
to see whether we can then use this sort of technique
in collaboration with the quantitative sources,
to actually see whether we can use these
to explore why infant mortality come down,
to bring it full circle and actually bring the explanation in,
to see what is different about these sorts of areas
shaded green when infant mortality went down a lot,
compared to these sorts of areas shaded red where it didn't.
And actually use text and statistics together
to try and understand these sorts of patterns
based on a range of very different and previously,
the kind of sources that people tend to not use together
to actually bridge that quantitative quality of divide
and get a better handling not just on the what, where and when,
but also on the why infant mortality
and other patterns like this were followed through.
At the same time as part of this project,
we've got a number of activities in terms of developing,
I hope developing the use of GIS,
which we'll publicise at some stage.
So to stick this back to David's original questions
that he put in the abstract for it,
what are the advantages of GIS?
Well, frankly, it provides us in this context
with a completely new way of looking at text,
at least I think it's a completely new way of looking at text.
A number of other people are working in this general area as well.
But what it allows you to do is summarise the broad patterns,
but also then identify where you should be focusing on in more detail.
So it's both descriptive and explanatory.
The limitations, I'm not so sure about the limitations yet
because we haven't done it yet, but I'm sure there will be some.
When it comes to the positivist assumptions,
I don't want to get too much into this now,
but I'm a bit, I'm not sure GIS has any positivist assumptions.
I think people may have assumptions, but GIS is just a technology.
And if you make assumptions on it, that's your decision.
Don't blame the technology for it.
I think a better question would be,
how does GIS allow you to adapt what you want to do
into a humanity-style framework?
And the trick is to actually not allow yourself
to be driven by the technology.
It's to allow for you to drive the technology in ways
that you want to go.
The third question, what lessons have you learned
that would be helpful for other scholars in use of technology?
Well, first of all, it's never as easy as you think.
It always takes longer than you expect.
And it requires an amount of collaboration,
probably more collaboration than you think,
because being both good at the technology,
good at the geography, and good at the humanities discipline
or whatever you're interested in,
takes quite a lot of different skill sets.
And I don't think anybody brings all three of those to the table.
The second one is people using GIS tend to overstress,
I think, the importance of maps.
Actually, the maps are just a vehicle to the understanding.
And you shouldn't get too hung up on both the advantages of them
and also the limitations of them.
And thirdly, and going back to my point about geography as a discipline,
really, this isn't about trying to argue that your way of doing things
is better than anybody else's way of doing things.
Really, this is about doing things well yourself,
and therefore demonstrating that GIS,
or whatever technology you're using,
actually has a lot to offer in terms of conducting applied scholarship
that changes the understanding of various disciplines within the humanities.
I'll leave it at that. Thank you.