about today. The first of all is kind of definition. What is Pelagios? Perhaps just as importantly,
what isn't Pelagios? Secondly, we want to give an outline of the methods of how to become part of
the Pelagios community, cloud, family, whoever you want to talk about it. And thirdly, we'll discuss
some initial outcomes, some of the kind of easy gains, some of the interesting visualizations.
Can we talk because we're going to have to swap across? Yeah, okay, we'll do that. Okay,
does that sound okay? Right, so the third thing we want to do is to outline some initial outcomes,
and those outcomes are both some initial quick wins, some nice visualizations, but also inevitably
some problems that have been raised too. But in the light of yesterday's plenary session,
the opening talk, I think there are also three issues, broader issues that our presentation
will touch upon that I would encourage you all to think about. The first of all is that we think
Pelagios is part of a broader ecosystem, in the sense of an infrastructure, but an infrastructure
that's not top-down imposed, but rather an infrastructure that is part of a group that's
bringing together an infrastructure from the bottom up, so a sense of authority diffused through a
model. So I think that's the first thing that's a broader issue possibly to think about. Secondly,
I'm really following on from that, we want to highlight process. So of course, we'll come up
with hopefully some interesting outcomes and visualizations for you to wonder at, but also
throughout the whole project we've been very interested in documenting what we've been doing,
and that documentation is up on the blog, we'll also be producing a cookbook, and so the second
aspect of process, the process of going through the project I think is also very important.
And that leads into the third thing that Pelagios I think is a case study. Now, Pelagios is about
the ancient world, about places in the ancient world, but it needn't be about places. Pelagios
can be more than just about places, and needn't just be about the ancient world. So hopefully
there are lessons also that can be thought about in more generic fashion, not just specifically
related to places in the ancient world. And the speaker also talked about metaphor,
and Leif has a great metaphor to I think introduce what Pelagios is all about.
Well, the metaphor I think that Elton is referring to is this rather beautiful image here of a
treasure chest, which we used for a previous talk called Linked Open Data in the Humanities,
an open and shut case. I think you'll see what we've done there. However, there's a more important
metaphor I think there, which is about treasure chests, which is that we commonly think about
treasure chests, that the hard thing is getting into them. But actually the really hard problem
about treasure chests is finding them in the first place, as any pirate will be able to tell you.
So that's really what Pelagios' focus is on, is about discovering the treasure,
so that we can actually start to do some interesting things with it.
So first up, Pelagios is about connecting ancient world resources that are online.
So those resources can be text. In my day job I do ancient Greek literature, so I'm interested in
texts. So there are lots of projects that deal with texts in the ancient world that reference
place on the web, but they're also inscriptional resources, so not just texts we get through a
manuscript edition, but inscriptions, more material culture, and also museum objects,
archaeological sites, archaeological finds. Pelagios is about drawing together these kind of
siloed information data sets, bringing them together. So as a user or as a digital humanist,
you can go from one source to another source. However, there's a few things that Pelagios
is not about, and those things are worth flagging up. So one of the things that we're ultimately
trying to find a way around is what's sometimes referred to as the one ring to rule them all
problem. How do we get around the fact that everybody agrees that we need a standard,
then everybody agrees that the standard that we use is their standard? That's effectively
the social issue that we get around. So what Pelagios is not about is data aggregation in
terms of saying to people, why don't you take all your stuff and put it in my big pot.
Pelagios is also not about federated search in the sense of saying, why doesn't everybody implement
my API, and then we can do search across that so we can do it in that way. It's not about
standardization of data representation of saying, right, this is the format in which you need to
expose all of your information, and it's also not about schema alignment or interoperability on a
metadata level in terms of saying, this is how you should structure all your data. This is the world
as you must describe it. So if we're not here to do anything useful, what are we here to do?
Well, the way we perceive the role of Pelagios is about connectivity of different heterogeneous
resources through common references rather than through a common schema. And what does that mean
exactly? Well, hopefully, here's an example that will give you some idea of what it is that we're
trying to do and what it is that we're not trying to do. So for a moment, I want you all to imagine
that you are computers trying to parse information that you haven't come across before. Okay, so I
want you to hopefully to raise your hand at the moment that you think you see a sentence here
where you can start to figure out what it's saying. Okay, that's the first sentence. No hands.
Second sentence. No hands. Third sentence. A few hands here and up here. Okay, four sentence. Okay,
hopefully, most of you, mostly English speakers in the room. So why is this interesting? Well,
the reason it's interesting is you were able to figure out potentially what that third sentence
was because you understood the tokens and the vocabulary that was involved there. In fact, the
second sentence, despite the fact that there's no grammatical consistency to that, but that's not
using English grammar. Now, the second sentence does use English grammar, but it uses a vocabulary
which you're not familiar with. So rather bizarrely, you knew what that was saying without knowing
what it was saying. And that's important because the third sentence, and I think it's the third
sentence that we're dealing with with Pelagios, enables you to figure out that this is probably
salient to your interests, despite the fact that you couldn't perform an analysis on that. Okay,
that sentence might have said the sentence isn't easy to read, or it might have said isn't the
sentence easy to read. You don't know what that sentence actually says, but you can figure out
that it might be something that you're interested in. The second sentence, in contrast, you could
parse if you only knew that it was interesting to you in the first place. Okay, so our interest here
is about enabling you to find salience to find things which you might be worthwhile to exploring,
but it's not giving you a system whereby you can then perform digital analyses on that
instantly and immediately. So how do we do that? Well, we need to find a common vocabulary, and in
our case, we're looking at the concept of place. And the common vocabulary that we use is the
Pleiades gazetteer of places in the ancient world. And for each of those places, it gives us a global
identifier, a URI, a uniform resource identifier that is specific to that place. And by using that
global identifier and by associating our stuff there, we know that when I talk about Athens,
and Elton talks about Athens, that we may or may not be talking about Athens, well, in our case,
not Athens, Georgia, because Athens, Georgia, of course, is not in the Pleiades gazetteer,
but then in fact, we're talking about Athens Attica. So that means that depending on what your
resources are, whether they're texts or images or maps, effectively anything that refers to the
concept of a place, we can annotate those places. So here we've got some text, here we've got Athens
and Sparta, and we associate with the specific places on the web a given URI. So we say that
this place on the web appears to be a reference to this conceptual place in the world. And what
that enables us to do is take two separate graphs of information, or perhaps Nexus would be a good
way to put this. So Pleiades provides a whole bunch of related information between different
places, but also because they're places in the world, then we can look at the associations between
them in terms of distance, for example, or their latitude or longitude on the surface of the Earth.
In contrast, ancient world resources themselves may also have connections between them in the form
of hyperlinks or cross-references, but they can also be islands. So over here, we can see that
the ancient world resources are divided into two sections. Because Pelagios creates a graph
between these two different data sets, a larger graph, we can actually find ways to navigate
between them. Okay, so I'm going to hand over to Elton to tell you a little bit about what that's
enabling us to do. Thanks. First of all, we should mention partners who have come on board. So not
only our own institutions, J.P. University and the University of Southampton, but also we should
mention Raina Simon, who is the other co-ironist project from the Austrian Institute of Technology,
and then a whole bunch of, and if any of you are a classicist in the room, you'll recognise some
of these resources, Arachne, Claros, Fastie, Nomisma, Perseus, and then some others come
aboard to the British Museum, Inscriptions of Israel-Palestine. So these are now the
Pelagios community. If you're a member of this group, you've annotated your data,
as Leif has been describing, and now as a member, you can then start doing some interesting things.
First of all, we have the Pelagios API, and there are, I think, three quick wins here.
First of all, there's context, so that as a member of our community, you can make your data richer
because you'll be able to find other stuff related to what your data set is all about.
So the example here is Delos. It's an island in the Aegean, and if your data set references Delos,
you can then immediately find out with your Pelagios API that there are these other data sets,
Klaus, Perseus, Google Ancient Places, all also talk about Delos, and the bottom visualisation
there under the title Neighbourhood gives you a sense of the places mentioned most often in
relationship to Delos, Rome, Athens, Greece, Hellas, and the Peloponnese. So that's one thing,
it can make your data more valuable because you can go and find other stuff that can give you a
context for your data. But secondly, and this goes back to the opening metaphor that Leif introduced,
it also allows your data to be more discoverable so that other people can find your stuff. And this,
I think, is especially crucial for us as judicial humanists thinking of issues of sustainability.
Sustainability, if you want your project to survive, you want people to find your project and to use it.
That leads into the third thing, reuse. In many ways, sustainability is reuse. People find your
resource, people use your resource, it's going to get sustained. So that's really, Pelagios is
enabling these three contexts, I think. So just to give you some examples, here's one project
partner open context. This is a resource overseen by Eric Kanzer, University of Berkeley, and it's
about people who are working on archaeological digs, providing their data free, open, and Eric
puts it up on his website, has a nice interface. And now on the left-hand side there, you see
that in association with these coins that are found in Byzantium, modern-late Istanbul, there
are all these other resources from the Pelagios community that reference Byzantium. So as a user
or as somebody who's interested in coins, you can then get a fuller context for that kind of
information. This is another kind of alternative example. This is kind of related to Normisma,
which is kind of run by Sebastian Heath as a kind of technical director, and along with
Nick Rabinowitz, they kind of played around with the concept Pelagios and come up with this really
neat tool, what I think is neat, so that if you've got your browser, you pass your browser over a
particular place name, in this case it's Pompeii, and it gives you a pop-up box that tells you what's
at the end of that link. So rather than having to click on a series of links, you can simply pass
your browser over the underlined word and you get a sense of what's at the end of it, if it's worth
chasing up the link, for example. And this is all in JavaScript, which means you can be embedded in
any website. So if you have those URIs in your website, you can embed that straight away and get
all those links. One thing we've also been doing, so that's what partners have been doing, have been
able to do because they've joined Pelagios, we've also, as part of the whole project itself, have
been playing around with the concept of widgets as well, so that we've been developing a few widgets
that can sit on partners websites, you'll simply have a Pelagios icon, so as a user you see the
Pelagios icon, you click on the icon, that opens up and gives you the potential lists of places,
a list of resources you might want to then chase up to find out more context,
more information about a particular place. So as well as those which are all now functioning and
available, there are also some functioning and available but much more experimental approaches
that we're exploring as well. So one of those, coming back to that graph network that I should
have showed you on earlier on, is an interface that enables you to explore that graph in two
different directions. So on the left we can explore the relationships between places through the data,
so we can say, for example, these three labels in this graph are for three different places,
let's say that they're Athens and Rome and Byzantium, and we can say, okay, well, which
data resources do we have? They refer to all of those places because they're the places that I'm
interested in. Or we can look at it the other way around and say with all these different data sets
which ones seem to be most similar here, so based on the places that they're referring to. So on the
right hand side all these little bubbles refer to Pelagios data sets and by clicking on them we can,
the thickness of the line can show how many place references they have in common. So again we can
find similarity of resources as well. Another experimental interface we've been playing with
at the moment are heat maps of annotations, so which places in the ancient world seem to be
getting the most interest in terms of references to them by Pelagios partners. As you'll see though
here, the sharp-eyed amongst you will notice that there is a sort of grid formation here,
that is not to sense variation to be clear. That is because some of the coordinates for these,
originally when the Pleiades was first digitized many of its coordinates were derived from the
grid squares of the Barrington Atlas and that's what you're seeing there. However over time many
of the coordinates are, and the continuously coordinates are being introduced through the
Damacy project, the digital atlas of the Roman medieval civilization, and over time that will
improve. But again one of the things that we need to work with with these heat maps is ways of
removing those, if you like, kind of arbitrary coordinates. However it's crucial to point out
Pelagios does not require spatial coordinates to work, it requires the basic principles of URIs.
So as a lot must say, describe Pelagios as something of a family or a collective or a
collaboratory, that's certainly true but it also means you don't have to join Pelagios if you like
to join Pelagios. Anybody can use the approaches that we're developing and in doing so can kind of
link into that cloud of ancient world data. So what we sometimes refer to is the three steps to
heaven, which are relatively straightforward, which is again one of the reasons that we've
grown so rapidly, Pelagios has really only been going for about a year now. So the first thing
is that you need, there are three crucial things, the first is that your data needs to be available
on the web with stable URIs. If you're not interested in sharing your data, if you're not
interested in other people finding it, that's fair enough but Pelagios has nothing to offer you
because Pelagios is about making your stuff discoverable. The second thing is that you need
to map your place references to the Pleiades gazetteer of the ancient world. Now I did say
earlier on that there isn't, we're not about wandering to rule them all and there would be
those who perhaps understandably would say well hang on wait you're cheating now because you are
saying that we need to map this stuff to the Pleiades gazetteer of the ancient world. In fact
you don't necessarily have to map to the Pleiades gazetteer, you could map to any gazetteer.
The beauty of this system is it's much easier to align gazetteers than it is to align say large
scale ontologies. So if you want to map to geonames we have Pleiades plus which maps between
Pleiades and geonames for example. So you could pick your gazetteer but what's crucial is that
you use a URI based gazetteer that you're mapping to. The second point to make out is that that's
actually, that's the hard part. The semantics of this process are a human process, you can use
fully automated mechanisms and many of the projects and partners including Google and
your places and I both work on do use automated methods and that means that sometimes the data
isn't perfect. In other cases you may have a smaller data set and you can do it by hand
but certainly the challenging aspect is doing that and we as a result we're developing a
cookbook of methods to help people with that process, to learn best practices.
And then finally you need to publish places as RDF. Now that's usually again the point where people
freak out a little bit and say wait but you said this was easy. This is easy in the sense that RDF
is a relatively simple format. It's typically the large scale ontologies which make it difficult
to use. We use a very simple ontology called the open annotation ontology and that essentially
simply says this place over here on the web we're annotating with this concept. There's a couple of
additional labels that we add in there but largely speaking it's a fairly straightforward process and
we've managed to go through that in the space of half an hour in terms of showing people the ropes
of how to do that RDF aspect of it. We also use the vocabulary of interlinked data sets as ways
of people maybe able to sub-categorize their annotations in various ways which again
facilitates discoverability. So issues identified so far. Things have moved really quite rapidly
over the course of the past year but of course there are also still areas where we're developing
conventions to make this process again yet easier to work. So some of the issues we're facing
are as far as the technical issues include RDF dumps. So RDF is not a specific format. There are
various ways of exposing your data as RDF and that we again to be to be clear we're not asking you to
embed or change your data any way. The RDF can sit entirely separately but we ask the partners to host
their own RDF and they might do that as a single file. They might do it as thousands of individual
files or they might use something like sparkle pointing to a triple store. So one of the things
we've been working out and developing is a system that can essentially it knows the URL of that
particular triple store or where to find that information and can automatically pass that in.
Another issue is the human readability. It's one thing to have these annotations but we need to
have labels that again facilitate mean that when they're discovered in the wild people understand
what that annotation is referring to. Again we've been developing conventions to help with that
human readability in varying contexts. The third thing is dataset partitions. So in for example
in Google ancient places we have chapters in books and books and collections and so on.
If we just give a giant RDF dump to saying here are all the thousands of annotations that we have
that's not terribly helpful when I'm suddenly thinking great we're almost done.
We're faced with hundreds of annotations so what we encourage people to do is subdivide those and
again we're developing the conventions to figure out what's the right level of granularity
and then versioning. How do we update the data as people how do we make it clear that data has
been updated over time. So just to finish and this is just 10 seconds really. I think this is
also not just an issue for people bringing this stuff together. So for us and our partners
aggregating data it also I think reflects back on the humanist in this and how you conceptualize
the data in the first place. So just one example an uncertain reference that made sense to you
this item was probably made in such and such a place perhaps doesn't make so much sense when
it's combined with five ten a hundred a thousand other datasets. So I think this process has also
got the partners think very carefully about what they mean when they start labeling stuff and I
think that's a very interesting and very useful skill also you know as part of the humanist part
of digital humanities. So PlanGos has been taking an extreme keep it simple approach we should grow
the web of data not build it and to learn more there we've like I've been saying like I said
right at the beginning we've been documenting this process on our blog and we've also been
in the process now in the final month of the project to put together cookbook so that you
can come along and do it yourself basically. Thanks very much.