Category Archives: historic gazetteer

Linked Data for places – any advice?

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We’d really benefit from advice about what Linked Data namespaces to use to describe places and the relationships between them. We want to re-use as much of others’ work as possible, and use vocabularies which are likely to be well and widely understood.

Here’s a sample of a “vanilla” rendering of a record for a place-name in Cheshire as extracted from the English Place Name Survey – see this as a rough sketch.

<RDF>
<chalice:Place rdf:about=”/place/cheshire/prestbury/bosley/bosley”>
<rdfs:isDefinedBy>/doc/cheshire/prestbury/bosley/bosley
</rdfs:isDefinedBy>
<rdfs:label>Bosley</rdfs:label>
<chalice:parish rdf:resource=”/place/cheshire/prestbury/bosley”/>
<chalice:parent rdf:resource=”/place/cheshire/prestbury/bosley”/>
<chalice:parishname>Bosley</chalice:parishname>
<chalice:level>primary-sub-township</chalice:level>
<georss:point>53.1862392425537 -2.12721741199493</georss:point>
<owl:sameAs rdf:resource=”http://data.ordnancesurvey.co.uk/doc/50kGazetteer/28360″/>
</chalice:Place>
</rdf:RDF>

GeoNames

We could re-use as much as we can of the geonames ontology. It defines a gn:Feature to indicate that a thing is a place, and gn:parentFeature to indicate that one place contains another.

Ordnance Survey

Ordnance Survey publish some geographic ontologies: there are some within data.ordnancesurvey.co.uk, and there’s some older work including a vocabulary for mereological (i.e. containment) relations includes isPartOf and hasPart. But the status of this vocabulary is unclear – is its use still advised?

The Administrative Geography ontology defines a ‘parish‘ relation – this is the inverse of how we’re currently using ‘parish’. (i.e. Prestbury contains Bosley) (And our concepts of historic parish and sub-parish are terrifically vague…)

For place-names found in the 1:50K gazetteer the OS use the NamedPlace class – but it feels odd to be re-using a vocabulary explicitly designed for the 50K gazetteer.

Or…

Are there other wide-spread Linked Data vocabularies for places and their names which we could be re-using? Are there other ways in which we could improve the modelling? Comments and pointers to others’ work would be greatly appreciated.

Chalice at WhereCamp

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I was lucky enough to get to WhereCamp UK last Friday/Saturday, mainly because Jo couldn’t make it. I’ve never been to one of these unconferences before but was impressed by the friendly, anything-goes atmosphere, and emboldened to give an impromtu talk about CHALICE. I explained the project setup, its goals and some of the issues encountered, at least as I see them –

  • the URI minting question
  • the appropriateness (or lack of it) of only having points to represent regions instead of polygons
  • the scope for extending the nascent historical gazetteer we’re building and connecting it to others
  • how the results might be useful for future projects.

I was particularly looking for feedback on the last two points: ideas on how best to grow the historical gazetteer and who has good data or sources that should be included if and when we get funding for a wider project to carry on from CHALICE’s beginnings; and secondly, ideas about good use cases to show why it’s a good idea to do that.

We had a good discussion, with a supportive and interested audience. I didn’t manage to make very good notes, alas. Here’s a flavour of the discussion areas:

  • dealing with variant spellings in old texts – someone pointed out that the sound of a name tends to be preserved even though the spelling evolves, and maybe that can be exploited;
  • using crowd-sourcing to correct errors from the automatic processes, plus to gather further info on variant names;
  • copyright and IPR, and the fact that being out of print copyright doesn’t mean there won’t be issue around digital copyright in the scanned page images;
  • whether or not it would be possible – in a later project – to do useful things with the field names from EPNS;
  • the idea of parsing out the etymological references from EPNS, to build a database of derivations and sources;
  • using the gazetteer to link back to the scanned EPNS pages, to assist an online search application.

Plenty of use cases were suggested, and here are some that I remember, plus ideas about related projects that it might be good to tie up with:

  • a good gazetteer would aid research into the location of places that no longer exist, eg from Domesday period – if you can locate historical placenames mentioned in the same text you can start narrowing down the likely area for the mystery places;
  • the library world is likely to be very interested in good historical gazetteers, a case mentioned being the Alexandria Library project sponsored by the Library of Congress amongst others;
  • there are overlaps and ideas to share with similar historical placename projects like Pleiades, Hestia and GAP (Google Ancient Places).

I mentioned that, being based in Edinburgh, we’re particularly keen to include Scottish historical placenames. There are quite a few sources and people who have been working for ages in this area – that’s probably one of the next things to take forward, to see if we can tie up with some of the existing experts for mutual benefit.

There were loads of other interesting presentations and talk at WhereCamp… but this post is already too long.

Linking historic places: looking at Victoria County History

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Stuart Dunn mentioned the Victoria County History in his writeup of discussions with the Clergy of the Church of England Database project. Both resources are rich in place-name mentions and historic depth; as part of the Chalice project we’re investigating ways to make such resources more searchable by extracting historic place-names and linking them to our gazetteer.

Here’s a summary of some email conversation between Stuart, Claire Grover, Ross Drew at EDINA and myself while looking at some sample data from VCH.

The idea is to explore the possibilities in how Chalice data could enhance / complement semi-structured information like VCH (or more structured database-like sources such as CCED).

It would be very valuable, I think, to do an analysis of how much effort and preparation of the (target) data is needed to link CHALICE to VCH, and a more structured dataset like CCED. By providing georeferences and toponym links, we’re bringing all that EPNS documentary evidence to VCH, thus enriching it.

It would be very interesting if we were able to show how text-mining techniques could be used to add to the work of EPNS (extracting place references that aren’t listed, and suggesting them to editors along with suggested attestations (source and date).

In the more immediate future; this is about adding links to Chalice place-references to other resources, that would allow us to cross-reference them and search them in interesting ways.

Text mining isn’t absolutely necessary to map the EPNS place names to the VCH text. On the other hand, LTG have all the processing infrastructure to convert formats, tokenise the text etc. so we could put something in place very quickly. It wouldn’t be perfect but it would demonstrate the point. I’ve not seen the CCED data, so don’t know how complex that would be.

Here’s a sample reference to a volume of VCH that may have some overlap with the Shropshire content we have in “born-digital” form from EPNS. There’s the intriguing prospect of adding historic place-name text mining/search in at the digitisation phase, so resources can be linked to other references as soon as they’re published.

Connecting archives with linked geodata – Part I

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This is the first half of the talk I gave at FOSS4G 2010 covering the Chalice project and the Unlock services. Part ii to follow shortly….

My starting talk title, written in a rush, was “Georeferencing archives with Linked Open Geodata” – too many geos; though perhaps they cancel one another out, and just leave *stuff*.

In one sense this talk is just about place-name text mining. Haven’t we seen all this before? Didn’t Schuyler talk about Gutenkarte (extracting place-names from classical texts and exploring them using a map) in like, 2005, at OSGIS before it was FOSS4G? Didn’t Metacarta build a multi-million business on this stuff and succeed in getting bought out by Nokia? Didn’t Yahoo! do good-enough gazetteer search and place-name text mining with Placemaker? Weren’t *you*, Jo, talking about Linked Data models of place-names and relations between them in 2003? If you’re still talking about this, why do you still expect anyone to listen?

What’s different now? One word: recursion. Another word: potentiality. Two more words: more people.

Before i get too distracted, i want to talk about a couple of specific projects that i’m organising.

One of them is called Chalice, which stands for Connecting Historical Authorities with Linked Data, Contexts, and Entities. Chalice is a text-mining project, using a pipeline of Natural Language Processing and data munging techniques to take some semi-structured text and turn the core of it into data that can be linked to other data.

The target is a beautiful production called the English Place Name Survey. This is a definitive-as-possible guide to place-names in England, their origins, the names by which things were known, going back through a thousand years of documentary evidence, reflecting at least 1500 years of the movement of people and things around the geography of England. There are 82 volumes of the English Place Name Survey, which started in 1925, and is still being written (and once its finished, new generations of editors will go back to the beginning, and fill in more missing pieces).

Place-name scholars amaze me. Just by looking at words and thinking about breaking down their meanings, place-name scholars can tell you about drainage patterns, changes in the order of political society, why people were doing what they were doing, where. The evidence contained in place-names helps us cross the gap between the archaeological and the digital.

So we’re text mining EPNS and publishing the core (the place-name, the date of the source from which the name comes, a reference to the source, references to earlier and later names for “the same place”). But why? Partly because the subject matter, the *stuff*, is so very fascinating. Partly to make other, future historic text mining projects much more successful, to get a better yield of data from text, using the one to make more sense of the other. Partly just to make links to other *stuff*.

In newer volumes the “major names”, i.e. the contemporary names (or the last documented name for places that have become forgotten) have neat grid references, point-based, thus they come geocoded. The earliest works have no such helpful metadata. But we have the technology; we can infer it. Place-name text mining, as my collaborators at the Language Technology Group in the School of Informatics in Edinburgh would have it, is a two-phase process. First phase is “geo-tagging”, the extraction of the place-names themselves; using techniques that are either rule-based (“glorified regular expressions”) or machine-learning based (“neural networks” for pattern cognition, like spam filters, that need a decent volume of training data).

Second phase is “geo-resolution”; given a set of place-names and relations between them, figuring out where they are. The assumption is that places cluster together in space similarly as they do in words, and on the whole that works out better than other assumptions. As far as i can see, the state of the research art in Geographic Information Retrieval is still fairly limited to point-based data, projections onto a Cartesian plane. This is partly about data availability, in the sense of access to data (lots of research projects use geonames data for its global coverage, open license, and linked data connectivity). It’s partly about data availability in the sense of access to thinking. Place-name gazetteers look point-based, because the place-name on a flat map begins at a point on a cartesian plane. (So many place-name gazetteers are derived visually from the location of strings of text on maps; they are for searching maps, not for searching *stuff*)

So next steps seem to involve

  • dissolving the difference between narrative, and data-driven, representations of the same thing
  • inferring things from mereological relations (containment-by, containment-of) rather than sequential or planar relationsOn the former – data are documents, documents are data.

On the latter, this helps explain why i am still talking about this, because it’s still all about access to data. Amazing things, that i barely expected to see so quickly, have happened since i started along this path 8 years ago. We now have a significant amount of UK national mapping data available on properly open terms, enough to do 90% of things. OpenStreetmap is complete enough to base serious commercial activity on; Mapquest is investing itself in supporting and exploiting OSM. Ordnance Survey Open Data combines to add a lot of as yet hardly tapped potential…

Read more, if you like, in Connecting archives with linked geodata – Part II which covers the use of and plans for the Unlock service hosted at the EDINA data centre in Edinburgh.

Visiting the English Place Name Survey

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I was in Nottingham for OSGIS at the Centre for Geospatial Sciences on Tuesday; skipped out between lunch and coffee break to visit the English Place Name Survey in the same leafy campus.

A card file at EPNS

A card file at EPNS

Met with Paul Cavill, who dropped me right in to the heart of the operation – stacks of index cards in shoe boxes. Each major name has a set of annotation cards, describing different related names and their associations and sources – which range from Victorian maps to Anglo-Saxon chronicles.

The editing process takes the card sets and turns them right into print-ready manuscript. The manuscript then has very consistent layout conventions – capitalisation, indentation. This is going to make our work of structure mining a lot easier.

Another bonus I wasn’t expecting was the presence of OSGB grid references for all the major names. The task of making links becomes a snap – I was imagining a lot of iterative guesswork based on clustering and closeness to names in other sources. (There are four Waltons in the UK in geonames, dozens in the EPNS).

On this basis I reckon the entity recognition will be a breeze, LTG will hardly have to stretch their muscles, which means we can ask them to work on grammars and machine learning recognisers for parts of other related archives within the scope of CHALICE.

Pic_0622_026And we would have freedom in the EDINA team’s time to do more – specifically to look at using the National Map Library of Scotland’s map rectifier tools to correlate the gazetteer with detailed line-drawn maps  also created by the late H. D. G. Foxall. Digitisations of these maps live in the Shropshire Records Office. We must talk with them about their plans (the Records Office holds copyright in the scans).

The eye-opener for me was the index of sources, or rather the bibliography. Each placename variant is marked with a few letters identifying the source of the name. So the index itself provides a key to old maps and gazetteers and archival records. To use Ant Beck’s phrase the EPNS looks like a “decoupled synthesis” of placename knowledge in all these sources. If we extract its structure, we are recoupling the synthesis and the sources, and now know where to look next to go text mining and digitising.

Pic_0622_024So we have the Shropshire Hundreds as a great place to start, as this is where the EPNS are working on now and the volumes are “born digital”. Back at CDDA, Paul Ell has some of the very earliest volumes digitised, and if we find a sample from the middle, we can produce grammar rules that we can be pretty confident will extract the right structure from the whole set, when the time comes to digitise and publish the entire 80+ volume, and growing, set.

But now i’m fascinated by the use of the EPNS derived data as a concordance to so many associated archives documenting historic social patterns. Towards the end of our chat Paul Cavill was speculating about reconstructing Anglo-Saxon England by means of text mining and georeferencing archives – we could provide a reference map to help archaeologists understand what they are finding, or even help them focus on where to look for interesting archaeology.

Paul had been visited by the time-travelling Mormons digitising everything a couple of weeks previously, and will hopefully offer an introduction – i would really, really like to meet them.