Describing the “things”: the RDF terms used (part 2)

In the previous post, I described some of the considerations in choosing RDF vocabularies to use for the LOCAH archival metadata. In the tables below, I’ve tried to summarise the properties used to “describe” an instance of each of the classes in our model, i.e. for a particular thing URI, in our dataset, one might expect to find triples with that URI as subject and these property URIs as predicates, and when our data is served as linked data, and a thing URI is dereferenced the “bounded description” provided will include those triples (and others) – though some may be optional, so not necessarily present for all instances (and some may not be present at all until we add some more data…!)

This is really more of a “reference document” than a blog post, but I provide it in part as documentation of the data creation/transformation process, and in part as a guide for potential users of the actual data. Having said that, the data is liable (even likely) to change so consumers should always refer to the actual data for an up-to-date picture of the terms used. I’ve tried to highlight (dark grey background) below terms which I consider to be particularly “at risk” and liable to be removed/replaced, mostly terms from the “locah” vocabulary.

Most of this data is generated from the transformation of the EAD XML documents; a small proportion is added separately. Again, I’ve tried to indicate that in the tables below (light grey background).

Finding Aid

Type rdf:type Class URI locah:FindingAid
foaf:Document
bibo:Document
Label rdfs:label plain literal
Preferred Label skos:prefLabel plain literal
Title dcterms:title plain literal
Identifier dcterms:identifier plain literal
Description dcterms:description plain literal
Conforms to dcterms:conformsTo Standard URI standard:isadg
Publisher dcterms:publisher Repository (Agent) URI
Encoded As locah:encodedAs EAD URI
Topic foaf:topic Archival Resource URI
Subject dcterms:subject Archival Resource URI
Has Part dcterms:hasPart Biographical History URI

The following should probably be an owl:sameAs relationship (or we should just cite the Hub URI?)

See also rdfs:seeAlso Hub Page URI e.g.
http://archiveshub.ac.uk/data/
gb15sirernesthenryshackleton

EAD

Type rdf:type Class URI locah:EAD
foaf:Document
bibo:Document
Label rdfs:label plain literal
Preferred Label skos:prefLabel plain literal
Title dcterms:title plain literal
Identifier dcterms:identifier plain literal
Description dcterms:description plain literal
Date Created dcterms:created plain literal
Conforms to dcterms:conformsTo Standard URI dbpedia:
Encoded_Archival_Description

standard:ead2002
Encoding Of locah:encodingOf Finding Aid URI

The Hub does not currently provide a URI for the EAD document, but it is planned to do so, at which point we should add an owl:sameAs relationship (or just cite the Hub URI?)

Repository (Agent)

Type rdf:type Class URI locah:Repository
foaf:Agent
dcterms:Agent
Label rdfs:label plain literal
Name foaf:name plain literal
Identifier dcterms:identifier plain literal
Country Code locah:
countryCode
plain literal
Maintenance Agency Code locah:
maintenance
AgencyCode
plain literal
Is Publisher Of locah:isPublisherOf Finding Aid URI
Provides Access To locah:
providesAccessTo
Archival Resource URI
Administers locah:administers Place URI
See also rdfs:seeAlso Archon Page URI e.g.
http://www.nationalarchives.gov.uk/
archon/searches/
locresult_details.asp?LR=15

Repository (Place)

Type rdf:type Class URI wg84_pos:
SpatialThing
Label rdfs:label plain literal
Title dcterms:title plain literal
Is Administered By locah:
isAdministeredBy
Repository URI
See also rdfs:seeAlso Archon Page URI e.g.
http://www.nationalarchives.gov.uk/
archon/searches/
locresult_details.asp?LR=15

The following data is not generated from the EAD documents, but added in from a separate source:

Postal Code gn:postalCode plain literal
Located In gn:locatedIn Postcode Unit URI e.g.
http://data.ordnancesurvey.co.uk/id/postcodeunit/CB21ER
Within ossr:within Postcode Unit URI e.g.
http://data.ordnancesurvey.co.uk/id/postcodeunit/CB21ER
Postcode postcode:postcode Postcode Unit URI e.g.
http://data.ordnancesurvey.co.uk/id/postcodeunit/CB21ER

Archival Resource

Type rdf:type Class URI locah:ArchivalResource
Label rdfs:label plain literal
Preferred Label skos:prefLabel plain literal
Title dcterms:title plain literal
Level locah:level Level URI
Page foaf:page Finding Aid URI
Access Provided By locah:
accessProvidedBy
Repository (Agent) URI
Identifier dcterms:identifier plain literal
Date dcterms:date plain literal
Date Created or Accumulated locah:
dateCreated
AccumulatedString
plain literal

The following properties were introduced to distinguish different date cases (date range v single date).

Date Created or Accumulated locah:
dateCreated
Accumulated
typed literal
Date Created or Accumulated (Start) locah:
dateCreated
AccumulatedStart
typed literal
Date Created or Accumulated (End) locah:
dateCreated
AccumulatedEnd
typed literal
Produced In event:produced_in Creation Event URI
Extent (String) locah:extent plain literal
Extent dcterms:extent Extent URI
Language dcterms:language Language URI e.g.
http://lexvo.org/id/iso639-3/eng
Is Represented By locah:
isRepresentedBy
Document URI or Aggregation URI
Origination locah:origination Agent URI
Has Biographical History locah:
hasBiographicalHistory
Bioghist URI
Associated With locah:
asssociatedWith
Concept URI
Has Part dcterms:hasPart Archival Resource URI
Aggregates ore:aggregates Archival Resource URI
Is Part Of dcterms:isPartOf Archival Resource URI
Is Aggregated By ore:isAggregatedBy Archival Resource URI
Members locah:members (RDF Collection)
See also rdfs:seeAlso Hub Page URI e.g.
http://archiveshub.ac.uk/data/
gb15sirernesthenryshackleton-
gb15sirernesthenryshackleton-
imperialtrans-antarcticexpedition

For all of the following, the object is simply a copy of the XML element content from the EAD document as an XML Literal. This is a rather “dumb” and probably not terribly useful “translation” from the EAD; in a future iteration of the transform, we hope to extract further useful triples from this part of the EAD data, and we will probably remove some of these triples.

Custodial History locah:
custodialHistory
XML literal
Acquisitions locah:acquisitions XML literal
Scope and Content locah:
scopecontent
XML literal
Appraisal locah:appraisal XML literal
Accruals locah:accruals XML literal
Access Restrictions locah:
accessRestrictions
XML literal
Use Restrictions locah:
useRestrictions
XML literal
Physical or Technical Requirements locah:
physicalTechnical
Requirements
XML literal
Other Finding Aids locah:
otherFindingAids
XML literal
Location Of Originals locah:
locationOfOriginals
XML literal
Alternate Forms Available locah:
alternateForms
Available
XML literal
Related Material locah:
relatedMaterial
XML literal
Bibliography locah:bibliography XML literal
Note locah:note XML literal
Processing locah:processing XML literal

Level

Type rdf:type Class URI locah:Level
skos:Concept
Label rdfs:label plain literal
Preferred Label skos:prefLabel plain literal
Comment rdfs:comment plain literal
Note skos:note plain literal
Definition skos:definition plain literal
Description dcterms:description plain literal

Language

Type rdf:type Class URI lvont:Language

Creation (Event)

Type rdf:type Class URI locah:Creation
lode:Event
event:Event
Label rdfs:label plain literal
Preferred Label skos:prefLabel plain literal
Product event:product Archival Resource URI
Involved lode:involved Archival Resource URI
Time event:time Temporal Entity URI
At Time lode:atTime Temporal Entity URI

Time Interval

Type rdf:type Class URI time:Interval
time:TemporalEntity
Label rdfs:label plain literal
Preferred Label skos:prefLabel plain literal
Timeline timeline:timeline Timeline URI timeline:universaltimeline
Start timeline:start typed literal
Interval Starts time:intervalStarts Time Interval URI e.g.
http://reference.data.gov.uk/id/
year/1874
End timeline:end typed literal
Interval Ends time:intervalEnds Time Interval URI e.g.
http://reference.data.gov.uk/id/
year/1874
Contains crm:
P86i_contains
Time Interval URI e.g.
http://reference.data.gov.uk/id/
year/1874
At timeline:at typed literal
Interval During time:intervalDuring Time Interval URI e.g.
http://reference.data.gov.uk/id/
year/1874
Falls Within crm:
P86_falls_within
Time Interval URI e.g.
http://reference.data.gov.uk/id/
year/1874

Extent

Type rdf:type Class URI locah:Extent
Label rdfs:label plain literal

In the EAD XML doc, extent is expressed simply as a literal. Where possible we’ve tried to parse out a “unit of measurement” and a quantity, reflected in RDF as a triple where the predicate reflects the unit and the object the quantity, as a typed literal, to try to make comparisons easier. I need to catch up with what current “best practice” is for representing quantities/units of measurement so this may well change. Also, currently, “units” include things like “file”, “paper” and “envelope”, which may not be terribly useful.

Archival Box locah:archbox typed literal (xsd:decimal)
Metre (Linear) locah:metre typed literal (xsd:decimal)
Cubic Metre locah:cubicmetre typed literal (xsd:decimal)
Folder locah:folder typed literal (xsd:decimal)
Envelope locah:envelope typed literal (xsd:decimal)
Volume locah:volume typed literal (xsd:decimal)
File locah:file typed literal (xsd:decimal)
Item locah:archbox typed literal (xsd:decimal)
Page locah:page typed literal (xsd:decimal)
Paper locah:paper typed literal (xsd:decimal)

Origination (Agent)

Type rdf:type Class URI foaf:Agent
dcterms:Agent
Label rdfs:label plain literal
Name foaf:name plain literal
Page foaf:page Biographical History URI
Is Origination Of locah:
isOriginationOf
Archival Resource URI

For links to other agents (external or internal):

Same As owl:sameAs Agent URI
Is Like umbel:isLike Agent URI

Biographical History

Type rdf:type Class URI locah:
BiographicalHistory
bibo:DocumentPart
bibo:Document
foaf:Document
Label rdfs:label plain literal
Preferred Label skos:prefLabel plain literal
Title dcterms:title plain literal
Body locah:body XML literal, plain literal
Topic foaf:topic Agent URI
Subject dcterms:subject Agent URI
Is Biographical History For locah:
isBiographicalHistoryFor
Archival Resource URI
Is Part Of dcterms:isPartOf Finding Aid URI

Concept Scheme

Type rdf:type Class URI skos:ConceptScheme
Label rdfs:label plain literal

Concept (ControlAccess – Subject)

Type rdf:type Class URI skos:Concept
Label rdfs:label plain literal
In Scheme skos:inScheme Concept Scheme URI

For links to other concepts (internal or external). Not generated from the EAD documents, but added in via separate process.

Exact Match skos:exactMatch Concept URI
Close Match skos:closeMatch Concept URI

The following properties represent the structure that is captured for controlaccess elements using the Hub EAD profile.

Name locah:name plain literal
Dates locah:dates plain literal
Location locah:location plain literal
Other locah:other plain literal

Concept (ControlAccess – Persname)

Type rdf:type Class URI skos:Concept
Label rdfs:label plain literal
Focus foaf:focus Person URI
In Scheme skos:inScheme Concept Scheme URI

For links to other concepts (internal or external). Not generated from the EAD documents, but added in via separate process.

Exact Match skos:exactMatch Concept URI
Close Match skos:closeMatch Concept URI

The following properties represent the structure that is captured for controlaccess elements using the Hub EAD profile. Currently, there are properties associated with both the concept and the person who is the foaf:focus of the concept. I’m not sure this is necessary/useful, and we may remove some of these triples.

Surname locah:surname plain literal
Forename locah:forename plain literal
Dates locah:dates plain literal
Title locah:title plain literal
Epithet locah:epithet plain literal
Other locah:other plain literal

Person (ControlAccess – Persname)

Type rdf:type Class URI foaf:Person
foaf:Agent
dcterms:Agent
crm:
E21_Person
Label rdfs:label plain literal
Name foaf:name plain literal
Family Name foaf:familyName plain literal
Given Name foaf:givenName plain literal
Dates locah:dates plain literal
Title locah:title plain literal
Epithet locah:epithet plain literal
Other locah:other plain literal

For links to other persons (internal or external). Not generated from the EAD documents, but added in via separate process.

Same As owl:sameAs Person URI
Is Like umbel:isLike Person URI

Concept (ControlAccess – Famname)

Type rdf:type Class URI skos:Concept
Label rdfs:label plain literal
Focus foaf:focus Family URI
In Scheme skos:inScheme Concept Scheme URI

For links to other concepts (internal or external). Not generated from the EAD documents, but added in via separate process.

Exact Match skos:exactMatch Concept URI
Close Match skos:closeMatch Concept URI

The following properties represent the structure that is captured for controlaccess elements using the Hub EAD profile. Currently, there are properties associated with both the concept and the family that is the foaf:focus of the concept. I’m not sure this is necessary/useful, and we may remove some of these triples.

Name locah:name plain literal
Dates locah:dates plain literal
Location locah:location plain literal
Other locah:other plain literal

Family (ControlAccess – Famname)

Type rdf:type Class URI locah:Family
foaf:Group
foaf:Agent
dcterms:Agent
Label rdfs:label plain literal
Name foaf:name plain literal
Dates locah:dates plain literal
Location locah:location plain literal
Other locah:other plain literal

For links to other families (internal or external). Not generated from the EAD documents, but added in via separate process.

Same As owl:sameAs Family URI
Is Like umbel:isLike Family URI

Concept (ControlAccess – Corpname)

Type rdf:type Class URI skos:Concept
Label rdfs:label plain literal
Focus foaf:focus Family URI
In Scheme skos:inScheme Concept Scheme URI

For links to other concepts (internal or external). Not generated from the EAD documents, but added in via separate process.

Exact Match skos:exactMatch Concept URI
Close Match skos:closeMatch Concept URI

The following properties represent the structure that is captured for controlaccess elements using the Hub EAD profile. Currently, there are properties associated with both the concept and the organisation that is the foaf:focus of the concept. I’m not sure this is necessary/useful, and we may remove some of these triples.

Name locah:name plain literal
Dates locah:dates plain literal
Location locah:location plain literal
Other locah:other plain literal

Organisation (ControlAccess – Corpname)

Type rdf:type Class URI foaf:Organization
foaf:Agent
dcterms:Agent
Label rdfs:label plain literal
Name foaf:name plain literal
Dates locah:dates plain literal
Location locah:location plain literal
Other locah:other plain literal

For links to other organisations (internal or external). Not generated from the EAD documents, but added in via separate process.

Same As owl:sameAs Organisation URI
Is Like umbel:isLike Organisation URI

Concept (ControlAccess – Geogname)

Type rdf:type Class URI skos:Concept
Label rdfs:label plain literal
Focus foaf:focus Place URI
In Scheme skos:inScheme Concept Scheme URI

For links to other concepts (internal or external). Not generated from the EAD documents, but added in via separate process.

Exact Match skos:exactMatch Concept URI
Close Match skos:closeMatch Concept URI

The following properties represent the structure that is captured for controlaccess elements using the Hub EAD profile. Currently, there are properties associated with both the concept and the place that is the foaf:focus of the concept. I’m not sure this is necessary/useful, and we may remove some of these triples.

Name locah:name plain literal
Dates locah:dates plain literal
Location locah:location plain literal
Other locah:other plain literal

Place (ControlAccess – Geogname)

Type rdf:type Class URI wg84_pos:
SpatialThing
Label rdfs:label plain literal
Name locah:name plain literal
Location locah:location plain literal
Other locah:other plain literal

For links to other places (internal or external). Not generated from the EAD documents, but added in via separate process.

Same As owl:sameAs Place URI
Is Like umbel:isLike Place URI

Concept (ControlAccess – GenreForm)

Type rdf:type Class URI locah:GenreForm
skos:Concept
Label rdfs:label plain literal
In Scheme skos:inScheme Concept Scheme URI

For links to other concepts (internal or external). Not generated from the EAD documents, but added in via separate process.

Exact Match skos:exactMatch Concept URI
Close Match skos:closeMatch Concept URI

Concept (ControlAccess – Function)

Type rdf:type Class URI skos:Concept
Label rdfs:label plain literal
In Scheme skos:inScheme Concept Scheme URI

For links to other concepts (internal or external). Not generated from the EAD documents, but added in via separate process.

Exact Match skos:exactMatch Concept URI
Close Match skos:closeMatch Concept URI

Book/Document (ControlAccess – Title)

Type rdf:type Class URI foaf:Document
bibo:Document
Label rdfs:label plain literal
Title dcterms:title plain literal

Birth (Event)

Type rdf:type Class URI bio:Birth
bio:IndividualEvent
bio:Event
lode:Event
event:Event
crm:E67_Birth
Label rdfs:label plain literal
Preferred Label skos:prefLabel plain literal
Date bio:date typed literal
Date dcterms:date typed literal
Time event:time Temporal Entity URI
At Time lode:atTime Temporal Entity URI
Has Time-Span crm:
P4_has_time-span
Time Interval URI
Agent bio:agent Person URI
Principal bio:principal Person URI
Agent event:agent Person URI
Involved Agent lode:involvedAgent Person URI
Brought Into Life crm:
P98_brought_into_life
Person URI

Death (Event)

Type rdf:type Class URI bio:Death
bio:IndividualEvent
bio:Event
lode:Event
event:Event
crm:E69_Death
Label rdfs:label plain literal
Preferred Label skos:prefLabel plain literal
Date bio:date typed literal
Date dcterms:date typed literal
Time event:time Temporal Entity URI
At Time lode:atTime Temporal Entity URI
Has Time-Span crm:
P4_has_time-span
Time Interval URI
Agent bio:agent Person URI
Principal bio:principal Person URI
Agent event:agent Person URI
Involved Agent lode:involvedAgent Person URI
Was Death Of crm:
P100_was_death_of
Person URI

Floruit (Event)

Type rdf:type Class URI locah:Floruit
bio:IndividualEvent
bio:Event
lode:Event
event:Event
Label rdfs:label plain literal
Preferred Label skos:prefLabel plain literal
Date bio:date typed literal
Date dcterms:date typed literal
Time event:time Temporal Entity URI
At Time lode:atTime Temporal Entity URI
Agent bio:agent Person URI
Principal bio:principal Person URI
Agent event:agent Person URI
Involved Agent lode:involvedAgent Person URI
Was Death Of crm:
P100_was_death_of
Person URI

Object

Type rdf:type Class URI foaf:Document
bibo:Document
Is Aggregated By ore:isAggregatedBy Object Group URI

Object Group

Type rdf:type Class URI ore:Aggregation
dcmitype:Collection
bibo:Collection
Aggregates ore:aggregates Object URI

Describing the “things”: the RDF terms used (part 1)

In previous posts, I described:

  • the model of the “world” on which we’re basing the Archives Hub RDF data: the types of “thing” being described, and (some of) the relationships between them (1, 2, 3); and
  • the patterns for URIs to be assigned to the individual “things”

In this post and the next one, I’ll outline the RDF vocabularies we’re using to describe those “things”. This post covers some of the considerations in choosing the vocabularies and some of the “patterns” we’ve used in deploying them; the next lists the properties and classes you can expect to find in the LOCAH data.

Using existing RDF vocabularies

As far as possible, we’ve tried to make use of existing, deployed RDF vocabularies. These include:

Those distinctions between which vocabulary “describes” what are somewhat rough, particularly taking into account that the “directionality” of properties in RDF is somewhat arbitrary: a triple using the dcterms:creator property to link a created work to an agent is as much “about” the agent as it is “about” the thing created.

However, where we’ve seen a need to express a notion that is not well addressed by an existing vocabulary, we have defined the additional classes and properties required and provided URIs for them as a small “local” LOCAH RDF vocabulary. At this point in time, I consider most of these terms something of a “work in progress”, and likely to be revised (or even dropped completely) before the end of the project. But I suspect some will remain – which, given the bounded timescale of the project, leaves questions about the longer term management of such vocabularies.

Discovering Appropriate Vocabularies

Most of my knowledge of existing RDF vocabularies has come from lurking on good old-fashioned mailing lists, particularly the W3C Semantic Web Interest Group list and the Linked Open Data list. I don’t read every posting by any means, and the signal-to-noise ratio can be variable, but for me they remain an excellent source of information with a knowledgeable and active contributing community (and the archives are a great repository.)

In similar territory, Semantic Stackoverflow provides a “question-and-answer”-style service, though it tends to have a fairly technical focus.

Another useful source is to look at actual linked data datasets, particularly those which are in a similar “domain” to the one you’re working in and cover similar resource types, and check out what vocabularies they are using (and how they are using them). In the library/bibliographic domain in particular, there has been a fairly steady stream of linked data datasets appearing over the last couple of years, so there’s quite a bit to go on, rather less so for the archives case. For a few pointers, see e.g. this review post by Ed Summers (itself already nearly a year old).

There are some services which aim to provide disclosure/discovery services based on aggregations of information about vocabularies and their constituent terms, sometimes called “metadata registries” or “metadata schema registries”. I’ve had mixed experiences of using these services: in some cases the content is not current; in others the coverage is intentionally tailored to the requirements of a particular community, so the challenge becomes one of finding a registry whose coverage matches the task at hand. One service (with quite general coverage) which I have occasionally found useful is Schemapedia, a project by Ian Davis of Talis; it provides “vocabulary”-level descriptions, rather than descriptions of individual “terms” but it includes some examples of actual terms: see, e.g. the entry for the Biographical Vocabulary.

There are a number of services which provide search functions across aggregations of data gathered from the linked data Web/Semantic Web. Sindice crawls and aggregates a huge range of RDF data and provides a “Google”-like search across that aggregation. (I’ve also found navigating such an aggregation helpful in thinking about various aspects of linked data: the sig.ma browser highlights the consequences of merging data from multiple sources, and related issues of provenance, attribution and trust, for example).

Finally, at the risk of stating the obvious, plain old Web search engines can still be a useful entry point.

Having said all this, I admit that the discovery of RDF vocabularies is still something of a challenge, and I continue to come across useful things I’d missed. And having found something potentially useful often raises further questions: Is the vocabulary stable or still being developed? Is it described following “modern” good practice for RDF vocabularies? Is it being managed/curated? By an individual/institution/community? Does it have the support of a community of users? Particularly if the intention is for a dataset to have some longevity, these may be significant considerations.

Patterns for using RDF Vocabularies

While discovering RDF vocabularies capable of expressing the information you want to represent is a first step, it often raises issues of exactly how those vocabularies might best be deployed, or of choosing between several possible alternative solutions.

Leigh Dodds and Ian Davis of Talis have authored a booklet Linked Data Patterns which tries to address some of these challenges, by gathering together some common “patterns” of use, based on existing practice by linked data implementers – though perhaps inevitably at this stage, some aspects of that practice are something of a “moving target” as new challenges are identified and practice evolves to address them. (See, for example, a recent debate on the Linked Open Data mailing list covering the question of expectations for what the object of an rdfs:seeAlso triple might/should dereference to.)

I continue to find the reflections of linked data practitioners an excellent source, particularly those working in domains close to those I’m interested in. I regularly find myself referring to the series of posts by Jeni Tennison on creating linked data. In this context, the fifth post on “Finishing Touches” is particularly relevant, and in large part prompts my next couple of points.

Labelling

One of the principles I’ve tried to adhere to, following the guidance by Jeni is that each resource we expose should have a human-readable label, provided using the rdfs:label property, and as far as possible that label should function as a useful “stand-alone” name for the thing.

In some cases this is a straightforward matter of using some text content node in the EAD XML document as an RDF literal. In other cases, a single element in the EAD document is mapped to a number of distinct resources in our model. In these cases, the transformation process typically prefixes or suffixes the source text to generate labels for the various different things. Perhaps unsurprisingly, this sometimes leads to some slightly “artificial” or “stilted” results, so it’s something we may need to refine.

Also, and perhaps more problematically, as I’ve noted in a previous post, the practice of archival description has traditionally relied heavily on a “multi-level description” approach which results in the presentation of resource descriptions “in the context of” the descriptions of other related resources. So it is common to find individual items within a collection labelled simply as something like “Letter”, on the basis that the reader of the finding aid will glean further information from the fact that the description of the item is presented within a context provided by a list of other “sibling” items, all “children” of a “parent” aggregation of some form. Currently our mapping generates the rdfs:label of an item using only the label (EAD unititle element) of that item in the EAD document, with the result that we may indeed end up with many individual resources labelled “Letter” (though of course the description will also include other properties derived from other EAD data and links to “parent” resources). An alternative might be to try to generate a label by “qualifying” the item unittitle, say, by prefixing it with the label of a “parent” resource – though I suspect in practice this would generate some somewhat unwieldy results.

Where the source data makes it seem reasonable to express it, I’ve also indicated the use of a “preferred label”, using the skos:prefLabel property. I’m conscious here of the need to be careful: the SKOS specification includes a number of “integrity conditions”, rules which data using the SKOS vocabulary should follow. Amongst them is the requirement that

A resource has no more than one value of skos:prefLabel per language tag.

The important thing to remember is that this is intended to apply in an “open world” context, not simply as a condition scoped to a particular “document”. The EAD to RDF transform process is performed on a document-by-document basis. Within the Hub dataset, it is quite common that for a single resource, labels for that resource are generated from the content of multiple EAD documents. While in theory naming within the set of EAD documents should be consistent, in practice, the use of variants of names is widespread in our data – the names of archival repositories is one example. Generating an skos:prefLabel triple for each variant would result in a conflict with the integrity condition once the data was merged in the triple store.

Bearing in mind that the “open world” extends beyond the boundaries of our own dataset, the same considerations apply in the case where we are exposing URIs for resources for which other parties already expose descriptions, including an skos:prefLabel triple, and we can’t guarantee that the names in our data correspond to those provided by that source.

Inferencing

Another issue to consider is that referred to by Leigh and Ian in their “Materialize Inferences” pattern, and by Jeni Tennison in her discussion of “Derivable Data”. One of the strengths of using the RDF model is that it is supported by a formal semantics, a framework for reasoning with data, i.e. given some set of data, it is often possible to apply some formalised set of rules to infer or derive additional triples. However, it should not be assumed that all consumers of the data will have access to the tools which support such reasoning, so it may be more appropriate for a data provider like LOCAH to explicitly include at least some of those “derivable” triples in the data we provide.

For a simple example of what I mean, the Friend of a Friend (FOAF) vocabulary provides a property called foaf:name (“A name for some thing.”). As part of their description of that property, the FOAF vocabulary owners provide the triple:

foaf:name rdfs:subPropertyOf rdfs:label .

The RDFS property rdfs:subPropertyOf is one of those properties which is associated with a set of rules. What those rules say is that, for any two properties linked by an rdfs:subPropertyOf relation, two resources related by the first property are also related by the second. So each time I find a triple using foaf:name as a predicate, I can infer (deduce, derive) a second triple using the rdfs:label predicate, e.g. if I find

<http://example.org/id/person/p123> foaf:name “Ernest Henry Shackleton” .

then I can conclude

<http://example.org/id/person/p123> rdfs:label “Ernest Henry Shackleton” .

However, to reach that conclusion, my application needs (a) knowledge of the general rdfs:subPropertyOf inference rule, and (b) knowledge that foaf:name is a subproperty of rdfs:label – and (c) the processing capability to apply that rule!

By providing – “materializing” – both those triples in our source data, we relieve the consuming application of that responsibility – though that benefit comes at the cost of increasing the size of the descriptions we provide.

This tactic can be particularly useful, I think, for properties which are subproperties of “generic” vocabularies like the RDF Schema vocabulary or the Dublin Core vocabularies. Sometimes generic linked data tools have some “built-in knowledge” of, and/or specific behaviour associated with, some of these vocabularies (e.g. to obtain literal names/labels/titles for display to human readers). It may be perfectly reasonable to use a triple with some more specialised subproperty in our data to indicate some specific relationship, but where appropriate it is also helpful to “materialize” the triple using the more generic property as well, so that an application looking for RDF Schema or DC properties can easily access that data.

Extending that slightly, Jeni suggests a “rule of thumb” that “if the result of the reasoning involves a resource from another vocabulary, then we should include it”.

The subproperty case is just one example: the inference of resource type based on rdfs:range and rdfs:domain is another case in point. In the LOCAH data, we’ve tried to provide fairly “generous” type data (e.g. including “super-classes”) where possible – again, on the grounds that such information is a commonly used “hook” in user queries (“Select resources of type T where [some other criteria]”).

The “cost” of this approach is that the dataset and the individual “bounded descriptions” served are larger – so there is a “trade-off” here which we may want to monitor and reconsider once we see how the data is being used.

Events

As I mentioned earlier, we extended our very initial draft model to include a notion of “event”. Currently, the application of this approach in our data is quite limited: it is applied to the “creation”/”origination” of the archival resources, and to the birth, death and “periods of activity” (floruit) of individuals. What we do is similar to the approach sketched by Ben O’Steen in his processing of the British Library’s British National Bibliography data – though with a little more complexity as we make use of event ontologies which model time periods as resources, rather than as literals.

This is probably best illustrated by means of an example. Given a person with birth date of 1901 and death date of 1985, we generate an RDF graph like the following:

RDF Graph of Life Events Data

RDF Graph of Life Events Data

(The image links through to a larger version)

The time interval nodes at the right-hand side are reference.data.gov.uk URIs for years, like http://reference.data.gov.uk/id/year/1901

What I haven’t illustrated on that diagram is that I’ve also included some data using the CIDOC CRM ontology – actually using the Erlangen CRM vocabulary. I’m feeling my way a bit with this, so it is somewhat partial/experimental at the moment, but I hope to refine/extend it in the future.

The point I wanted to highlight is that we’ve made use of multiple “overlapping” vocabularies here – again on the grounds that it may be useful to provide that flexibility to consumers of the data querying using a specific vocabulary. As above, this is a “trade-off” which we may want to monitor and reconsider in the future.

Summary

I’ve tried to cover here some of the issues around our choices of RDF vocabularies and how we’ve deployed them. The next post will summarise the actual terms used.

Two changes to the model and some definitions

Over the last few weeks we’ve been testing our initial cut at an EAD-to-RDF transform against a range of data that extends beyond EAD documents prepared using the Hub data entry template to documents created using other tools – and varying somewhat in terms of the markup conventions used.

In the course of that, I’ve been pondering some of the choices we made in the model I described here and here, and we decided to make a couple of changes (one very minor and the second still relatively so, I think):

  • Archival Resource: We’ve changed the name of the class we were calling “Unit of Description” to “Archival Resource”. I think “Unit of Description” was problematic for two reasons. First, it was ambiguous, because it could be interpreted either as the unit (of archival material) being described (which is what was intended) or as a unit/part of the archival description (which is not what was intended). Second, I adopted it from the ISAD(G) standard, where the context is one in which the archival resources are considered to be the primary things being described. I’m less sure the label works in the “linked data” context where we’re providing statements, and sets of statements (descriptions), “about” not just the archival materials, but many other things. In this context, everything that is described (people, concepts, places, etc) might be seen, in some sense, a “unit of description”, and so using that label for one subset of them seems inappropriate. That left us with finding a suitable alternative, a generic term that covers archival material in general, at any level of description (fonds, collection, item etc), and “archival resource” seemed like a reasonable fit.
  • Origination as Concept: When I first sketched out the model, I raised some questions, including (as “question 3” in that post) whether it was useful/necessary to model the origination of the archival resource as a pair of concept and agent, following the pattern used for the <controlaccess> terms. Having experimented with that approach, we’ve decided it introduces unnecessary complexity and we’ve fallen back on treating <origination> as a simple relation between archival resource and agent. The use of concept and agent is retained for the <controlaccess> case, where names are typically drawn from an “authority file”, as it allows us to maintain the distinction between a conceptualisation of the agent (as reflected by the authority record/entry) and the agent itself (a distinction which is also made in the model underpinning datasets such as VIAF, which we will be making links to).

The revised model is summarised in the following diagram (an amended version of Figure 3 from the earlier post):

Amended data model for EAD

Amended data model for EAD

i.e. an Archival Resource and a Biographical History are now related directly to an Agent.

Below is a draft list of human-readable definitions for the classes in the model. Some are simply references to classes provided by existing vocabularies like Dublin Core, FOAF, event vocabularies:

Finding Aid
A document describing an archival resource.
Subclass of: bibo:Document, foaf:Document
EAD
A document conforming to the Encoded Archival Description standard.
Subclass of: bibo:Document, foaf:Document
Biographical History
A narrative or chronology that places the archival materials in context by providing information about their creator(s). A finding aid may contain several such narratives or chronologies pertaining to different archival materials and their creators.
Subclass of: bibo:DocumentPart, (bibo:Document), foaf:Document
Repository
An institution or agency responsible for providing access to archival materials.
Subclass of: foaf:Organization, (foaf:Agent), dcterms:Agent
Place
= wgs84_pos:SpatialThing
Postcode Unit
= ospc:PostcodeUnit
Archival Resource
Recorded information in any form or medium, created or received and maintained, by an organization or person(s) in the transaction of business or the conduct of affairs, and maintained for its long-term research value. An archival resource may be an individual item, such as a letter or photograph, or (more commonly) some aggregation of such items managed and described as a unit.
Level
An indicator of the part of an archival collection constituted by an archival resource, whether it is the whole collection or a sub-section of it.
Subclass of: skos:Concept
Language
= lvont:Language
Extent
The size of an archival resource.
Subclass of: dcterms:SizeOrDuration
Temporal Entity
= time:TemporalEntity
Creation
An event that resulted in the creation or accumulation of an archival resource.
Subclass of: event:Event, lode:Event
Concept
= skos:Concept
Concept Scheme
= skos:ConceptScheme
Agent
= foaf:Agent, dcterms:Agent
Person
= foaf:Person, (foaf:Agent), dcterms:Agent
Family
A group of people affiliated by consanguinity, affinity, or co-residence.
Subclass of: foaf:Group, (foaf:Agent), dcterms:Agent
Organisation
= foaf:Organization, (foaf:Agent), dcterms:Agent
Genre or Form
A category of archival material, defined either by style or technique of intellectual content, order of information or object function, or physical characteristics.
Subclass of: skos:Concept
Function
A sphere of activity or process.
Subclass of: skos:Concept
Birth
= bio:Birth, (bio:IndividualEvent), (bio:Event),
(event:Event), (lode:Event)
Death
= bio:Death, (bio:IndividualEvent), (bio:Event),
(event:Event), (lode:Event)
Object
= foaf:Document, bibo:Document
Book
= bibo:Book, (bibo:Document), (foaf:Document)

Assessing Linked Data

For me, the journey from an understanding of modelling data, and creating our own models for the Hub and Copac, to being able to understand the processes and decisions involved in creating XML RDF has been challenging. It has raised one question that often applies when dealing with something quite technical: how much should a manager (in my case an archivist managing an online archive service) be expected to understand the ‘technical’ aspects of something?  This is a question I have spoken about and written about before; mainly in terms of what archivists (or other information professionals) in the digital age need to know in order to understand the implications of choices around things like data structure and software systems.  In the case of Linked Data, I am still not sure how much I need to know about the detail of Linked Data, the RDF model, the use of RDF XML, the benefits of other output fomats, the application of stylesheets, etc. I have been thinking about how hard it is to create Linked Data – I have had a few enquiries from colleagues who are interested in doing the same sort of thing already and I want to be able to offer useful advice.

One thing that occurs to me is that it is reasonable to acknowledge that Linked Data does involves programming skills, and therefore it is not so dissimilar from structuring and outputting your data through a traditional relational database, for example, where you would expect that specialist skills are needed. But in either case there is the the same need for a manager to understand what the system offers and be able to offer the best service to researchers. I think what is important from the point of view of the manager is to be involved with the decision-making process and understand the implications of Linked Data; you need to know what you are saying about your own data. I am not sure that this requires a thorough knowledge of RDF and certainly I only have a rudimentary knowledge of stylesheets (and no knowledge of programming).

Service managers or administrators are not expected to understand systems from an in-depth technical point of view. But in fact, I think that one of the advantages of RDF model is that it is easier to get a sense of what is going on in terms of data processing than typically occurs with a database management system. After about six months of learning about Linked Data and RDF (I estimate that this translates into about one month of fairly intense learning), I can look at the stylesheet that we have for the Archives Hub, to transform the EAD data into RDF XML, and I can look at an RDF document representing the entities that we are describing, and I have a reasonably good overall sense of what it all means, which helps me with my main role: to understand the outputs and the potential benefits of Linked Data. For Locah, we’ve used XSLT, but there is no requirement for this, and maybe one of the challenges of outputting Linked Data is that there are a number of options in terms of translating your RDF model into an output.

There is no doubt that choices made now about how we model the data will have implications for what users can do with it, and some choices may limit future potential more than others. For example, which ‘things’ do we choose to represent? Should we have a conceptualisation of a person as an entity represented in the description, and to link this to a conceptualisation of the person? Which information should we provide as URIs and which as literals? I’m only gradually coming to understand the implications of these decisions, as we start to explore the potential of the data. Of course, this is always true, whatever data, structures and systems we are working with. This brings me to another point that I think is probably particularly relevant for Locah: we are doing this work at a time when we are very much early adopters. Whilst the classic Linked Data diagram may give the impression that the world has embraced Linked Data, the reality is that it is still very much at a hand-crafted level: we have not had tools available to us to aid us in this work, and in the case of EAD, there has been very little activity up till now. It is therefore difficult to judge how feasible it might be to output RDF in the future, as it is likely that more tools will be developed, and there will be greater awareness and skills built up around the whole Semantic Web. However, I wonder if we are currently still at that difficult point where we need to build the momentum of the Linked Data movement, but it is still very unfamiliar and poorly understood by many data providers?

Many Linked Data evangelists claim that Linked Data is ‘easy’. I’m not sure that it is necessarily easy, and I don’t think that it’s very helpful to say that it is easy. Easy compared to what? Easy for whom? It’s easy if you know how, if you have the requisite skills and experience, but we need to persuade people who don’t yet know how that it is worth doing, and provide a realistic assessment of the skills that are required. I suppose the question of how easy it is does rest in large part on the data you are working with as well. Archival finding aids are quite challenging. As Mark Matienzo, archivist at Yale University, states in his presentation on Linked Data and Archival Description: “Archival description is inherently multi-level and relational” and “EAD is both too flexible and too unforgiving” to be Linked Data friendly…and database-friendly for that matter. Also, ISAD(G) recommends the non-repetition of information and archival description generally contains implicit information. I suppose Linked Data might help provide the opportunity and impetus to move towards a more Web-friendly way of describing archives, if it does become more widely used.

At present, I can’t help thinking that if archive repositories and libraries would like to output their data as Linked Data, many of them will struggle, and I would have thought it might be similar for other types of data providers. I do think that expertise is required, and time needs to be invested in understanding some key aspects of Linked Data. On the other hand, this is the case whenever you are looking at creating effective means to output structured (but often inconsistent) data. However, I think that it makes good sense for the Archives Hub and Copac to do this work, as it is on behalf of our contributors, so it effectively will allow these repositories and libraries to output Linked Data.  In other words, it may be that for Linked Data to really take hold, it will benefit from this kind of aggregated set-up, where skills and resources can be pooled. At present, I’m inclined to think that it is worth the investment of time and resources by our Locah team because it is benefitting a large number of data providers. I think it will be important for us to convey to our contributors, and indeed to other archivists and librarians, what we are doing and why, what the implications are and what the benefits may be. I have already had contact with two people, one representing another aggregation of content, interested in benefitting from our work. This is really important, because it potentially makes the investment more worthwhile.

We are in a fortunate position with the Locah project because we are part of a JISC-funded innovations project, with a team of people with a variety of skills, and we have support from Talis, who have significant experience of Linked Data.  If we can work on behalf of our community, then I feel that the time invested may be worthwhile. For the second half of our year-long project we will want to explore the benefits more thoroughly – we will be looking at the crucial issues of creating links to other data, which is really Linked Data’s key selling point, and we will be developing a prototype to show some potential benefits for researchers.

(With thanks to Pete and Ade for their contributions to this blog post).

Identifying the “things”: URI Patterns for the Hub Linked Data

In my previous couple of posts, I outlined the model of the “world” on which we’re basing the RDF data we’re generating from the Archives Hub‘s EAD XML documents.

At the heart of the Linked Data approach is the principle that all the “things” we want to “say anything about” should be named using a URI, and that those URIs should use the http URI scheme, so that they can be easily “looked up” or “dereferenced” using Web technologies in order to obtain some information provided by the URI owner about the thing. So, having specified the types or classes of thing we want to refer to and describe, the next step is to decide on the structure of the http URIs that we’ll use to name the “instances” of those classes – the individual “things” – archival resources, repositories, concepts, persons, places, and so on. In this post, I’ll try to describe the patterns we’re using, and outline how we construct individual URIs using those patterns from the EAD input data. As I hope will become clearer, the nature of the input data conditions the form of the patterns we’ve chosen. This has turned into a rather long post (again!) but I hope the detail is useful – I think it’s important for us to try to document our processes and some of the issues we’ve grappled with as well as to present the conclusions.

In some (most) cases, these will be newly created URIs, under a domain that we (well, MIMAS and the Archives Hub service) own. For these URIs, the project is responsible for choosing the URIs and putting in place the mechanisms to ensure that their dereferencing results in the provision of some “useful information”. In other cases, we will simply be citing existing URIs, defined by other agencies who (hopefully!) provide for their dereferencing.

The UK Cabinet Office has recently published some general guidelines on URI patterns for government Linked Data, Designing URI Sets for the UK Public Sector, and within the JISC programme strand under which LOCAH is funded, projects are encouraged to follow the recommendations of those guidelines. Following these guidelines, the general URI pattern recommended to identify “things” is:

http://{domain}/id/{concept}/{reference}

where:

  • concept is a name for a class (resource type), like “person”
  • reference is a name for an individual instance of that class or type

Our RDF data is being generated, at least in the first instance, by processing EAD XML documents, so we want to construct our URIs for our “things” from content within those XML documents. And we want to do so in a way that, as far as possible, ensures that each of those URIs is an unambiguous name/referrer, i.e. it identifies a single “thing”, and we don’t end up with a single URI being used for what are in fact two different things. On the other hand, we can live with the case where we end up with multiple URIs, all of which identify a single thing, because information can be added at a later stage to indicate that they are synonyms.

The other point to note is that the initial transformation step is being performed on a “document-by-document basis”, i.e. taking a single EAD document as input and outputting RDF/XML. So for any given resource, the information we generate – including the URI of the resource – is based only on the content of that document (and any generally applicable information we can embed in the transform itself). There may be other data “about” that “thing” in another EAD document but we don’t have access to it at the time of transformation.

Also, it’s desirable that we construct our URIs in such a way that if we need to re-run the transform, we generate the same URIs from the same input data (unless we explicitly decide to change the patterns for some reason).

Finally, although the patterns below often make use of human-readable strings from the EAD document content, I haven’t treated human-readability as a major consideration. Having said that, I’ve tended to make use of (slightly normalised forms of) human-readable strings where possible, rather than, say, creating opaque “hashes”.

As with other aspects of the work, at this stage, this is a first cut at tackling the issue, and we may revise our approaches based on the experience of applying them over the dataset. Having gone through and constructed patterns for the various resource types, looking back over them now, I think I can see a small number of distinct methods that we’ve used:

  1. Identifiers: For some of these “things”, the EAD documents contain some sort of formally assigned identification code or number, which unambiguously – at least within the scope of the Hub collection – identifies that instance within the set of resources of that type (i.e. it serves as a “reference” in the terms of the Designing URI Sets… document). This is the case, for example, with the languages of the materials, using the did/langmaterial/language/@langcode attribute value. A variant of this is the case where such an identifier can be constructed from a combination of multiple pieces of content. Repositories, for example, can be identified by the pair of country code (ead/eadheader/eadid/@countrycode) and maintenance agency code (ead/eadheader/eadid/@mainagencycode). For these cases a combination of the name of the resource type and that identification code provides the basis for the “reference” part of the URI.
  2. “Authority-Controlled” Names: For many of the “things”, however, the EAD documents do not contain such a code; rather, they refer to things only by name. In some cases, the form of the name is drawn from an “authority file” – indicated in the EAD document – and the name includes sufficient information (e.g. birth/death dates, titles etc for a person) to make the resulting string an unambiguous referrer within the set of names from that source. For these cases, a combination of a name for the authority file and the name provides the basis for the “reference”. However, this does depend on the creator of the EAD document having accurately transcribed the “authoritative” form of the name, at least sufficiently to maintain unambiguity of reference.
  3. “Rule-Based” Names: In other cases, the “thing” is named, not using a name from a controlled list, but rather a name constructed according to some codified set of rules, where the rules used are indicated in the EAD document. The intent behind such rules is to try to ensure consistency of form and unambiguity of reference. The National Council of Archives’ Rules for the Construction of Personal, Place and Corporate Names (one of the rule sets recommended to Hub data creators) states “A personal name is constructed by combining mandatory and optional components of the name so that the person concerned can be identified with certainty and distinguished from others bearing similar names. An individual should have only one authorised form of name and each name should apply to only one individual.”Typically, as for the “authority file” case, this is achieved through the inclusion of dates, titles etc for persons. For these cases, a combination of a name for the rules and the name itself should provide the basis for the “reference”. However, in practice, the picture with the Hub data is somewhat more complex. First, in some cases where it is claimed that rules are followed, the content itself indicates that this is not the case. For example, the NCA Rules mandate that a personal name should include “the year in which a person was born or died, the span of years of his/her lifetime or the approximate period covered by his/her activities”, even if those dates are estimated. But there are cases in the data marked up as following the NCA Rules which do not meet this requirement – e.g. personal names providing only surname and forename with no dates – , which I suspect may result in ambiguous references. Second, even where the rule is followed and the mandatory components are present, the distributed nature of Hub data creation means that I suspect there is still some possibility that a single personal name may be used in two different sources to refer to what in fact are two different people (Consider e.g. the case of two data providers using the name “Smith, John, fl 1920-1950”).
  4. “Locally-Scoped” Names: In other cases, the form of the name is neither authority-controlled nor rule-based, but nevertheless there is some expectation that the form of the name used is sufficient to make it an unambiguous referrer within some context. This is the case, for example, with the content of the did/origination element. The difficulty, however, is in establishing reliably what that context is. What is that “local scope”? We’ve tentatively taken the approach that such names have been constructed in such a way as at least to be unambiguous within the collection of submissions to the Hub by a single repository. So by combining the repository identifier and the name, hopefully, we can arrive at a “reference” which avoids ambiguity. Again, it may turn out that this assumption is unreliable, and results in ambiguous references, so we may need to revisit this approach.
  5. “Identifier Inheritance”: (I’m sure there must be a formal term for this but I’m not sure what it is!) In these cases the EAD document does not provide an unambiguous name for the “thing” itself; however the “thing” has a simple relationship with some other “thing” for which identification fits into one of the other categories. Where the relationship is one-to-one, a URI can be constructed by adopting the pattern for that other “thing” and substituting the name of the resource type. An example of this is the case of the “biographical history” associated with a “unit of description”. The unit of description has an identifier (based on a pattern described below) and since – in data constructed using the Hub template – each unit has at most one biographical history, replacing the “unit” resource type name with a “bioghist” resource type name gives us a suitable URI path, e.g. for a unit of description for which the URI path contains “/unit/gb15abc”, the URI for the biographical history would contain “/bioghist/gb15abc”.A variant of this is the case where the relationship is many-to-one, rather than one-to-one. Here the approach needs to be extended to include e.g. a sequence number to distinguish the multiple “things”. This is the approach taken for the Unit of Description, where a “child” (“part”) unit of description uses the URI of the “parent” (“whole”) unit suffixed with a sequence number, e.g. for a unit of description for which the URI path contains “/unit/gb15abc”, the URIs for the “child” units would contain “/unit/gb15abc-1”, “/unit/gb15abc-2” and so on. In theory, this should not be necessary as the unitid for a unit should be unique within an EAD document, but in practice we’ve found that this is not the case in the actual data. (In this case, the identifier would be “reproducable” only if any new units are inserted at the end of a sequence rather than in the middle).
  6. So, with the caveat above that this is all somewhat tentative at this stage, I summarise below the approaches taken to generating URIs for instances of each of the classes in the Hub model. Note that sometimes, an instance of the same class is generated in different “contexts” within the EAD document, and in these cases different rules for URI construction may be applied in those different contexts, depending on the information available within the EAD document.

    We haven’t yet finalised the domain name we’ll be using, so for the purposes of the following, {root} represents the domain and the first part of the path. Italicised text is used for the URI patterns (or parts of them); bold text is used for XPath(-ish!) representations of the source of data within the EAD XML document.

    Finding Aid

    Pattern(s)

    {root}/id/findingaid/{eadid}

    eadid
    normalised form of ead/eadheader/eadid

    Example:

    {root}/id/findingaid/gb15sirernesthenryshackleton

    EAD document

    Pattern(s)

    {root}/id/EAD/{eadid}

    eadid
    normalised form of ead/eadheader/eadid

    Example(s)

    {root}/id/ead/gb15sirernesthenryshackleton

    Repository (Agent)

    Pattern(s)

    {root}/id/repository/{repositoryid}

    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode

    Example(s)

    {root}/id/repository/gb15

    Repository (Place)

    Pattern(s)

    {root}/id/place/{repositoryid}

    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode

    Example(s)

    {root}/id/place/gb15

    Unit of Description

    Pattern(s)

    {root}/id/unit/{unitid}

    unitid
    normalised form of archdesc/did/unitid and position within archdesc/dsc/c tree

    Note: In principle, it should be possible to use c/unitid content rather than position in tree, but in practice, there are cases where unitid content is not unique within the EAD document.

    Example(s)

    {root}/id/unit/gb15sirernesthenryshackleton

    {root}/id/unit/gb15sirernesthenryshackleton-1

    Level

    Pattern(s)

    {root}/id/level/{level-name}

    level-name
    archdesc/@level or archdesc/@otherlevel or c{n}/@level or c{n}/@otherlevel

    Example(s)

    {root}/id/level/fonds

    Language

    Pattern(s)

    http://lexvo.org/id/iso639-3/{langcode}

    Note: use existing lexvo.org URIs for languages.

    langcode
    did/langmaterial/language/@langcode

    Example(s)

    http://lexvo.org/id/iso639-3/eng

    Creation (Event)

    Pattern(s)

    {root}/id/creation/{unitid}

    unitid
    normalised form of archdesc/did/unitid and position within archdesc/dsc/c tree

    Example(s)

    {root}/id/creation/gb15sirernesthenryshackleton

    Creation (Time)

    Pattern(s)

    {root}/id/creationtime/{unitid}

    unitid
    normalised form of archdesc/did/unitid and position within archdesc/dsc/c tree

    Example(s)

    {root}/id/creationtime/gb15sirernesthenryshackleton

    Extent

    Pattern(s)

    {root}/id/extent/{unitid}

    unitid
    normalised form of archdesc/did/unitid and position within archdesc/dsc/c tree

    Example(s)

    {root}/id/extent/gb15sirernesthenryshackleton

    Biographical History

    Pattern(s)

    {root}/id/bioghist/{unitid}

    unitid
    normalised form of archdesc/did/unitid and position within archdesc/dsc/c tree

    Example(s)

    {root}/id/bioghist/gb15sirernesthenryshackleton

    Concept (Origination)

    Pattern(s)

    {root}/id/concept/agent/{repositoryid}/{origination-name}

    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode

    Example(s)

    {root}/id/concept/agent/gb15/sirernesthenryshackleton

    Agent (Origination)

    Pattern(s)

    {root}/id/agent/{repositoryid}/{origination-name}

    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode

    Example(s)

    {root}/id/agent/gb15/sirernesthenryshackleton

    Concept (ControlAccess – Subject)

    Pattern(s)

    {root}/id/concept/{source}/{subject-name}

    {root}/id/concept/{repositoryid}/{subject-name}

    source
    controlaccess/subject/@source
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    subject-name
    normalised form of controlaccess/subject

    Example(s)

    {root}/id/concept/lcsh/antiquities

    Concept (ControlAccess – Persname)

    Pattern(s)

    {root}/id/concept/person/{source}/{person-name}

    {root}/id/concept/person/{rules}/{person-name}

    {root}/id/concept/person/{repositoryid}/{person-name}

    source
    controlaccess/persname/@source
    rules
    controlaccess/persname/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    person-name
    normalised form of controlaccess/persname/

    Example(s)

    {root}/id/concept/person/nra/shackletonernesthenry1874-1922sirknightexplorer

    {root}/id/concept/person/ncarules/holdenwendyfl1990cartoonist

    {root}/id/concept/person/gb1832/berlinisaiah1909-1997sirknighthistorian

    Person (ControlAccess – Persname)

    Pattern(s)

    {root}/id/person/{source}/{person-name}

    {root}/id/person/{rules}/{person-name}

    {root}/id/person/{repositoryid}/{person-name}

    source
    controlaccess/persname/@source
    rules
    controlaccess/persname/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    person-name
    normalised form of controlaccess/persname/

    Example(s)

    {root}/id/person/nra/shackletonernesthenry1874-1922sirknightexplorer

    {root}/id/person/ncarules/holdenwendyfl1990cartoonist

    {root}/id/person/gb1832/berlinisaiah1909-1997sirknighthistorian

    Concept (ControlAccess – Famname)

    Pattern(s)

    {root}/id/concept/family/{source}/{family-name}

    {root}/id/concept/family/{rules}/{family-name}

    {root}/id/concept/family/{repositoryid}/{family-name}

    source
    controlaccess/famname/@source
    rules
    controlaccess/famname/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    family-name
    normalised form of controlaccess/famname/

    Example(s)

    {root}/id/concept/family/nra/dundasviscountsmelvilledunira

    {root}/id/concept/family/ncarules/boucicault

    Family (ControlAccess – Famname)

    Pattern(s)

    {root}/id/family/{source}/{family-name}

    {root}/id/family/{rules}/{family-name}

    {root}/id/family/{repositoryid}/{family-name}

    source
    controlaccess/famname/@source
    rules
    controlaccess/famname/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    family-name
    normalised form of controlaccess/famname/

    Example(s)

    {root}/id/family/nra/dundasviscountsmelvilledunira

    {root}/id/family/ncarules/boucicault

    Concept (ControlAccess – Corpname)

    Pattern(s)

    {root}/id/concept/organisation/{source}/{org-name}

    {root}/id/concept/organisation/{rules}/{org-name}

    {root}/id/concept/organisation/{repositoryid}/{org-name}

    source
    controlaccess/corpname/@source
    rules
    controlaccess/corpname/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    org-name
    normalised form of controlaccess/corpname/

    Example(s)

    {root}/id/concept/organisation/nra/britishbroadcastingcorporation

    {root}/id/concept/organisation/aacr2/dailymail%28london%2Cengland%29

    {root}/id/concept/organisation/gb1578/vizards%2Csolicitors%2Cmonmouth

    Organisation (ControlAccess – Corpname)

    Pattern(s)

    {root}/id/organisation/{source}/{org-name}

    {root}/id/organisation/{rules}/{org-name}

    {root}/id/organisation/{repositoryid}/{org-name}

    source
    controlaccess/corpname/@source
    rules
    controlaccess/corpname/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    org-name
    normalised form of controlaccess/corpname/

    Example(s)

    {root}/id/organisation/nra/britishbroadcastingcorporation

    {root}/id/organisation/aacr2/dailymail%28london%2Cengland%29

    {root}/id/organisation/gb1578/vizards%2Csolicitors%2Cmonmouth

    Concept (ControlAccess – Geogname)

    Pattern(s)

    {root}/id/concept/place/{source}/{place-name}

    {root}/id/concept/place/{rules}/{place-name}

    {root}/id/concept/place/{repositoryid}/{place-name}

    source
    controlaccess/geogname/@source
    rules
    controlaccess/geogname/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    place-name
    normalised form of controlaccess/geogname/

    Example(s)

    {root}/id/concept/place/lcsh/mcmurdosound%28antarctica%29

    {root}/id/concept/place/ncarules/canada

    {root}/id/concept/place/gb982/meirionethshire%28wales%29

    Place (ControlAccess – Geogname)

    Pattern(s)

    {root}/id/place/{source}/{place-name}

    {root}/id/place/{rules}/{place-name}

    {root}/id/place/{repositoryid}/{place-name}

    source
    controlaccess/geogname/@source
    rules
    controlaccess/geogname/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    place-name
    normalised form of controlaccess/geogname/

    Example(s)

    {root}/id/place/lcsh/mcmurdosound%28antarctica%29

    {root}/id/place/ncarules/canada

    {root}/id/place/gb982/meirionethshire%28wales%29

    Concept (ControlAccess – GenreForm)

    Pattern(s)

    {root}/id/concept/{source}/{genreform-name}

    {root}/id/concept/{rules}/{genreform-name}

    {root}/id/concept/{repositoryid}/{genreform-name}

    source
    controlaccess/genreform/@source
    rules
    controlaccess/genreform/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    genreform-name
    normalised form of controlaccess/genreform

    Example(s)

    {root}/id/concept/aat/buildingplans

    Concept (ControlAccess – Function)

    Pattern(s)

    {root}/id/concept/{source}/{function-name}

    {root}/id/concept/{rules}/{function-name}

    {root}/id/concept/{repositoryid}/{function-name}

    source
    controlaccess/function/@source
    rules
    controlaccess/function/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    function-name
    normalised form of controlaccess/function

    Example(s)

    {root}/id/concept/agift/miningregulations

    Book

    Pattern(s)

    {root}/id/document/{title}

    source
    controlaccess/title/@source
    rules
    controlaccess/title/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    title
    normalised form of controlaccess/title

    Example(s)

    {root}/id/document/aacr2/thecastlediaries1974-761980

    Birth (Event)

    Pattern(s)

    {root}/id/birth/{source}/{person-name}

    {root}/id/birth/{rules}/{person-name}

    {root}/id/birth/{repositoryid}/{person-name}

    source
    controlaccess/persname/@source
    rules
    controlaccess/persname/@rules
    repositoryid
    normalised form of concatentation of ead/eadheader/eadid/@countrycode and ead/eadheader/eadid/@mainagencycode
    person-name
    normalised form of controlaccess/persname/

    Example(s)

    {root}/id/birth/nra/shackletonernesthenry1874-1922sirknightexplorer

    {root}/id/birth/ncarules/allenjim1926-1999playwright

    {root}/id/birth/gb1832/berlinisaiah1909-1997sirknighthistorian

    Object

    Pattern(s)

    {object-uri}

    object-uri
    dao/@href or daogrp/daoloc/@href

    Example(s)

    http://library.kent.ac.uk/library/special/html/specoll/jack.gif

    Object Group

    Pattern(s)

    {root}/id/group/{unitid}-{groupno}

    unitid
    normalised form of archdesc/did/unitid and position within archdesc/dsc/c tree
    groupno
    position within daogrp sequence for archdesc or c{n}

    Example(s)

    {root}/id/group/gb0254ms274-1

    Time Interval (Year, Month, Day)

    i.e. specific intervals of time.

    Pattern(s)

    http://reference.data.gov.uk/id/year/{yyyy}

    http://reference.data.gov.uk/id/month/{yyyy}-{mm}

    http://reference.data.gov.uk/id/day/{yyyy}-{mm}-{dd}

    Note: use existing reference.data.gov.uk URIs for intervals.

    langcode
    did/langmaterial/language/@langcode

    Example(s)

    http://reference.data.gov.uk/id/year/1921

    http://reference.data.gov.uk/id/month/1921-06

    http://reference.data.gov.uk/id/day/1921-06-03

Some more “things”: some extensions to the Hub model

Having had a little more time to experiment with the Archives Hub EAD data, and to think about what sort of operations on the RDF data we might wish to perform or enable others to perform, I’ve introduced a few small extensions to the model I described a couple a few weeks ago.

Extents

At our last project meeting, we talked about some of the possibilities for visualisations of the data. One of the ideas (suggested by Jane) is to explore representing relative sizes of collections, perhaps on a map, so that, for example, a researcher could provide a geographic location and a subject area and get a visual representation of the relative sizes of collections within that area.

The EAD XML format provides an element called <extent> for “information about the quantity of the materials being described or an expression of the physical space they occupy”. Although the EAD Tag Library provides guidelines to try to encourage some uniformity of the content, the data in the Hub EAD documents is quite variable. Examples of the content in the samples I’ve looked at include:

  • 6.5 linear metres
  • 2.04 metres
  • 0.48m
  • 190 archive boxes
  • 13 boxes
  • One sheet of paper
  • 13 lever arch files, 48 sound tape reels, 490 audio cassette tapes (1 filing cabinet)

In the initial model, this was just treated in RDF as a single triple with subject the URI of the unit of description (an archival collection or some part of it) and this string a literal object. I’m suggesting changing this to treat the “extent” as a resource with its own URI, rather than simply as a literal. Doing that enables us – for at least some of these cases – to make explicit that it is a value measured in some “unit” (linear metres, archival boxes), to “normalise” the way those units are represented (so e.g. “linear metres”, “metres” and “m” can be mapped to a single form in the RDF data), and possibly to make comparisons, albeit approximate ones, between extents measured in different units (for example, “archival boxes” and “linear metres”).

So we end up with patterns in the RDF graph like:

unit:123 dcterms:extent extent:123 .

extent:123 ex:metres “2.04”^^xsd:decimal .

Having said that, I recognise that the nature of the input data is such that such techniques are usefully applicable only to a subset of the data; I’m not sure there’s a great deal we can do with “composite” strings like the last one in the list above, other than present them to a human reader.

Events and Times

One of the other ideas for presenting data we’ve chewed around is that of some sort of “timeline” view. It’s something I’ve been quite keen to explore – though I’m conscious that the much of the most useful information is, in the EAD documents, in the form only of prose in the “biographical/administrative histories” provided for the originators of the archives.

As a first tentative step in this direction, I’ve introduced a notion of “event” into the model, where, in the first instance:

  • the Creation of a unit of description is modelled as an event taking place during a period of time
  • (where birth/death dates are provided in the input) the Birth and Death of a person are modelled as events taking place during a period of time

It’s possible to generate this just from simple processing of the input data. It may be possible to go further and generate a richer range of “events” through the use of some flavour of intelligent text analysis/”entity extraction” tools on the biographical/administrative history text, but that’s something for us to consider in the future.

Postcodes

Finally – and as I noted in the previous post this is something which goes beyond the content of the EAD documents themselves – prompted mainly by the recent announcement by John Goodwin that the Ordnance Survey had extended their linked data dataset to include “post code units”, I’ve added in a notion of “Postcode Unit” so that we can make links to resources from that dataset (and also to the UK Postcodes dataset).

So the revised model looks something like the figure below:

Diagram showing data model for EAD data

Figure 1

So, I’m hoping that – bug fixes aside – I can stop tinkering with this for a while 🙂 and that we can work with this version of the model, and test out what is possible and where any “pain points” are, and then think about where further changes might be useful.

Modelling Copac data

With the Archives Hub data well under way, it was time to start looking at the Copac data.  The first decision to be made was which version of Copac data to use – consolidated or unconsolidated.  As part of the process of adding records to Copac they are de-duplicated, allowing different institutions’ records for the same item to be presented as one record, instead of several.  For more info on Copac de-duplication, see this blog post.

So our first question was: deal with the individual records from each library, or with the consolidated records created for Copac?  This made us think about the nature of what we were describing. The unconsolidated records (generally!) relate to the actual, physical ‘thing’ – what in FRBR would be the ‘item’.

The consolidated records are closer to (but by no means a perfect example of) the FRBR manifestation.  That is to say, they are describing different physical instances of the same theoretical work; in linked data terms, they are ‘same as’.  They aren’t perfect manifestation level records, as there may be other records on Copac for the same manifestation which haven’t been consolidated due to cataloguing differences.  At Copac, we err on the side of caution, and would rather have this happen, than have records which aren’t the same consolidated into the same record.

So we could do our mapping and our transformations at unconsolidated level, and then use ‘same as’ to link together the descriptions that would later be consolidated in Copac.  But as we’re accepting Copac’s judgement that they are describing the same set of items, why not save ourselves that trouble, and work from the consolidated description?  We can then hang the individual bibliographic records off this central unit of description.

This means that all of the information provided by the different libraries is related to the same unit of description.  The bibliographic records that go together to make up a consolidated Copac record may not contain all of the same information, but they won’t contain any contradictory information.  Thus two records which are the same in all details except date of publication (say 1983 in one, 1984 in the other) will not consolidate, but records which are the same in all details except that one contains a subject where the other does not, will consolidate.

In fact, subjects are one of the things (along with notes) that don’t affect consolidation at all.  We will combine all of the subjects that come in individual descriptions, so that a consolidated record might end up with the subjects:

Management

Management — theory

Management (theoretical)

Business & management

We will leave these in the linked data description for the same reason they are left in the Copac description – while such similar terms may seem superfluous, they actually increase discoverability, by providing multiple access points.  They will link into the central ‘unit of description’, rather than the individual bibliographic records.

Once we’d decided on this central unit of description (name TBD, but likely to be ‘Copac record’ or something boringly similar), other aspects of the description started to fall into place.  Some of these were straightforward – publication date, for instance, is fairly obviously a literal – while others took more thought and discussion.

Among the more complicated issues was that of creator.  We are working with MODS data, which has come from MARC data, and MARC allows you to have only one ‘creator’.  This creator sits in the 100s as the main access point, and all other contributors (including co-authors!) are relegated to the 700s, where they become what we have decided to call ‘other person associated with this unit of description’.  Not very snappy, but hopefully fairly accurate.  In theory, the role that this person has in the creation of the item should be reflected in a MARC indicator, but in practise this is not often included in descriptions.  Where it is indicated that a person (or a corporate body) is an editor, contributor, translator, illustrator etc, we can build these into the modelling; where not, they will have to be satisfied with the vague title of ‘associated person’.

This will work for most situations, but it does still leave room for error.  Where a person is named in the 700s with no indicator of role, it is possible that they are a person who was associated with one particular item, rather than the manifestation – a former owner or bookseller, for example.  While we do want to present this information, which works as another access point, and may be of interest to users, we have the problem that this information should really be associated with the item, not our quasi-manifestation.  This information only concerns one specific physical item, as described in one of the individual bibliographic records. Should it really have a link to our central unit of description?  If not, where do we link it to?  Our entries for individual bib records describe only the records themselves, not a physical real-world item.  It’s an interesting point, and one we’ll be dicussing more as the project goes on.

We’re continuing to work with Copac data, and will discuss other issues here as they arise.

The “things” in EAD: a first cut at a model

As mentioned by Jane in a couple of previous posts, she, Bethan and I met up in Manchester in August to share our thoughts about how to model the Archives Hub EAD data in a form that can be represented in RDF.

RDF in a nutshell

For the purposes of this discussion, the main point to bear in mind is that the “grammatical principle” underpinning RDF is one of making simple three-part statements, each of which makes an assertion of a relationship (of some particular type) between two things. So for example, in RDF I can “say” things like:

Document 123 has-title “Arthur and George”

or

Document 123 is-authored-by Person P
Person P has-name “Julian Barnes”

When considering how to represent EAD data in RDF, then, the first step is to try to take a step back from the “nitty-gritty” of the EAD XML markup, and think about the three part statements we might construct to represent the “information content” of that document. We need to think in terms, not of XML documents and elements and attributes and nesting/containment, but rather of what an EAD document is “saying” about “things in the world” (perhaps more accurately, in the “world” as conceptualised by the creator of the archival finding aid, shaped by archival description practices in general) and what sort of questions we want to answer about those “things”. What are the “things” – and here I use the term in a general sense to include concepts and abstractions as well as material objects – that an EAD document provides information about? What are the relationships between these things? What else does an EAD document say about those things?

Note: The discussion here does not cover the “document”/”description” side of the “Linked Data” picture i.e. for each “thing”, we’ll be providing a “description” of that “thing” in the form of a “document”. Metadata describing that “document” will be important in providing information about provenance and currency, for example, but that is not discussed here.

EAD as used by the Archives Hub

The EAD XML format was designed to cope with the “encoding” of a wide range of archival finding aids, including those constructed according to the (slightly different) cataloguing practices and traditions of different communities.

Further, many features of the EAD format are optional: one can construct a valid EAD document using only a fairly minimal level of markup, or one can use more detailed markup to represent more information.

This flexibility can be something of a “double-edged sword”: on the one hand, it enables data creators to accommodate a wide range of data, and it provides choice in the level of detail of markup (and human resources in creating that markup!) to be applied; on the other hand, it can make working with EAD data quite complex for a consumer, particularly when processing data from a range of sources which perhaps use a range of different conventions and features of the language.

In part to address this sort of issue (as well as to make things simpler for data providers by insulating them from the detail of EAD markup), the Archives Hub provides a forms-based EAD editor, based primarily on the information categories enumerated by the ISAD(G) archival description standard, which generates EAD documents following a consistent set of markup conventions. (I sometimes think of this as a “profile” of EAD, a narrower set of constraints than that imposed by the EAD DTD/schema itself, but I’m not sure that sort of terminology is in widespread use in this context.)

So, we made the “pragmatic” decision to work, in the first instance at least, on the basis of this particular set of EAD markup conventions, rather than trying to address the full EAD format, which means we can limit the number of variants we need to deal with. Having said that, even for the case of data created using the Hub editor, an element of variation is present, because although the data entry form generates a common high-level structure, data creators can apply different markup within those high-level structural components. In this first cut at a model, we have focused on analysing those common structural elements, with the intention of extending and refining our approach at a later stage.

In the course of this (or in thinking about it afterwards) we’ve come up with a few questions, which I’ll try to highlight in the course of the discussion below. Any feed back on these points (or indeed on any other aspect of the post!) would be very welcome.

The “world” as seen by EAD

Jane and I had both done some doodling before our meeting, and we started out by walking through our ideas, highlighting both those aspects which seemed pretty clear and uncontroversial, and aspects where we were uncertain or several alternatives seemed possible (and reasonable). Although we were using slightly different terminology, I think we had come up with quite similar notions, and after a bit of discussion, we arrived at a first cut at a “core” model which I’m representing graphically in Figure 1 below. This isn’t intended as a formal UML or E-R diagram, but each box represents a type of “thing” (a class) and each arrow represents a type of relationship between individual things (“instances” of those classes):

Diagram showing draft data model for EAD data (1)

Figure 1

So the “core” types of things identified in this first stage were:

  • Unit of Description: these are the “units” of archival material, a document or set of documents, the actual stuff held in the repository and described by the finding aid. It’s a “generic” class to reflect the archival description principle of “multi-level description”. An archival finding aid typically has a “hierarchical” structure, in which one “unit of description” is (described as logically forming) “part of” another “unit of description”. A finding aid may provide a only a “collection-level” description of a collection which contains many thousands of individual records, without describing those records individually at all; or it may include descriptions of various component groupings and sub-groupings of records; or it may indeed go as far as describing individual records within such groupings. For each Unit of Description, information relevant to that particular unit is provided. EAD and ISAD(G)) allow for the provision of more or less the same set of information whatever the “level” of unit described, though in practice some elements are more commonly used for “aggregate/group” units.
  • Archival Finding Aid: these are the documents created by archival cataloguers to describe the archival materials. Often a single finding aid describes (or has as its topic/subject) several units of description, but it may be the case that a finding aid describes only a single unit – where only a description of the collection as a whole is provided.
  • Repository (Agent): the organisations who curate and provide access to the archival material, and who create and maintain the archival finding aids. (EAD allows for the possibility that two different agencies perform these two roles; the Hub EAD Editor works on the basis that a single agent is responsible for both).
  • Origination (Agent): the entity (individual, organisation or family) “responsible for the creation, accumulation, or assembly of the described materials before their incorporation into an archival repository” (from the description of the EAD <origination> element). Jane analysed the rather complex nature of the ISAD(G) Creator/EAD origination relationship, which encompases notions of both “item creator” and “collector”, in <a href="http://archiveshub.ac.uk/blog/?p=2401"an earlier post on the Archives Hub blog.
  • “Things” which are referenced in the form of names used as “access points” or “index terms” using the EAD <controlaccess> element. The Hub EAD Editor supports the provision of the following as <controlaccess> terms, and recommends the use of a number of thesauri or “authority files” from which they should be drawn: Names of “Subjects” (topics); Personal Names; Family Names; Corporate Names; Place Names; Book Titles; Names of Genres or Forms; Names of Functions. So the corresponding “things named” are: Concepts, Persons, Families, Organisations, Places, Books, Genres or Forms, and Functions. As Jane notes in her recent post the relationship between the Unit of Description and the entity named in the <controlaccess> element is not necessarily a relationship of “about”-ness, but a rather less specific one, which for the moment we’ve labelled as simply “associated with” (though a better label might be preferable!).

(I’ve shown the Origination and Repository as distinct classes in the diagram, rather than as a single Agent class, because, as I hope will become clearer below, it ends up that they participate in a slightly different set of relationships).

We went on to extend and refine this core model to accommodate more of the information from the EAD document.

First, we refined the way the “access points” are represented. I’d discussed this aspect of the model with Leigh Dodds of Talis and he suggested that we consider modelling the physical entities here as concepts, in turn related to physical entities, i.e. that we represent the “conceptualisation” of a person, family, organisation or place captured in a thesaurus entry or authority file record, as distinct from the actual physical entity. So, to take an example which I think Bethan used during our conversation, we can distinguish between a conceptualisation of William Blake as a poet and one of William Blake as an artist, each in turn related to William Blake the person.

Although I don’t plan to discuss the specifics of RDF vocabulary in this post, it’s worth noting that the FOAF RDF vocabulary has recently been extended with the addition of a property, foaf:focus, to represent the relationship between the conceptualisation and the thing conceptualised (person, place etc), to support exactly this convention.

For some of the <controlaccess> named entities – like the topics, genres/forms and functions – there is no “other thing conceptualised” and it is sufficient to model them simply as concepts (or as instances of a subclass); and for the book case, we’ll just treat it as a “book” (and for the moment, at least, sidestep any FRBR-ish issues).

In both cases, the notion that the concept is a member of a specific thesarus/authority file can be captured by introducing the notion (from SKOS) of a “Concept Scheme”.

Question 1: One question raised by this approach is whether, for the cases where there is a distinct entity involved, in transforming an EAD document into RDF, we should:

  1. Coin URIs for, and generate “descriptions” of, both the concept and the person/family/organisation/place conceptualised (with a triple with a foaf:focus predicate relating the two? Or:
  2. Coin a URI for, and generate a “description” of only the concept, and leave the relationship with the person/family/organisation/place conceptualised “out of scope” at the transform stage (though that relationship might be obtained at a later stage by linking the concept to external data)?

My inclination is to do the former, on the grounds that this enables us to capture more of the information present in the EAD document i.e. to capture the information that where a <persname> element is used, this is the name of a conceptualisation of a person, where a <corpname> element is used, this is the name of a conceptualisation of an organisation, and so on.

Question 2: Is it necessary/useful to also model the name itself as a distinct resource? I think we can manage without that, but we may revisit that point in the future.

Second, having made this choice for the <controlaccess> entities, we decided to apply it also to the case of the “origination” agent discussed above, with the “origination” relationship becoming one between a Unit of Description and a conceptualisation of an agent, rather than between a Unit of Description and the agent itself. I admit I’m still not completely sure this is necessary/useful/”the right thing to do”. The use of the <origination> element in the Hub EAD profile is described in the guidelines here. It allows for names to be presented in “the commonly used form of name”, rather than the form specified by an authority record (and indeed a survey of the data reveals a good deal of variation), so it’s a bit more difficult to argue that this corresponds directly to the name of an entry (concept) listed in an “authority file”.

Question 3: Is it necessary/useful to introduce a “conceptualisation” of the agent who “originated” the Unit of Description? For now, we’re working on the basis that it is, but we may revisit that choice.

This extended model is represented graphically in Figure 2:

Diagram showing draft data model for EAD data (2)

Figure 2

A final stage of refinement gave us a few further extensions.

First the EAD Document is introduced as a particular “encoding of” the Finding Aid.

Second, I’ve suggested that we model the Biographical or Administrative History associated with each Unit of Description as a resource in its own right, distinct from the Finding Aid as a whole. I’m not sure this is strictly necessary, and again it’s something that we may revist in the future. But it enables us to provide information about the Biographical History as a distinct resource. One of the reasons this may be useful is that we’ve discussed (albeit somewhat vaguely at this point!) analysing/mining the text of the Biographical History as a source of further information, and having a URI for the Biographical History enables us to be explicit about the source of that data. We can also make the Biographical History the subject of triples to indicate that it is related not just to the Unit of Description but also to the entity who “originated” that unit (or, given the discussion above, to the conceptualisation of that entity). Also, we could associate it with different literal expressions (e.g. the original EAD fragment as XML Literal, but also an XHTML or plain text derivative). It also, of course, makes the Biographical History into a resource that others can refer to in their own assertions in their own data.</p

Third, we introduced the “level” of the Unit of Description as a distinct resource, a concept. This means that each “level” within the (relatively small) set used within the Hub data can each be assigned a distinct URI, and described in their own right, and – again – referenced by others.

Fourth, similarly, the “language” of the Unit of Description is treated as a distinct resource. (The plan here is that we’ll try to simply reference resources within an existing Linked Data dataset, such as lexvo.orga>.)

Fifth, the EAD <dao> and <daogrp< elements are mapped into a relationship between the Unit of Description and an external digital object (or group of objects). I’ve labelled the relationship here as “is represented by” as that is the description provided by the EAD documentation, but I think Jane and Bethan felt that in practice in the Hub data, the relationship might sometimes be rather less specific than that.

For the moment, the other EAD elements corresponding to ISAD(G) elements (i.e. to textboxes in the Hub data entry form) will be treated as properties with XML Literal values (though we could follow the <bioghist> approach and generate individual URI-identified resources if that proves to be useful).

Sixth – and here we stepped slightly beyond the scope of the EAD document itself (so I’ve greyed it out in the diagram below) – we’ve added a notion of the location of the Repository and a relationship between the Repository-as-Agent and that Place. Although details of repository location aren’t included in the Hub EAD documents, Jane and Bethan said they do have that data available, and it should be fairly easy to integrate it.

So we’ve ended up with the model illustrated in Figure 3.

Diagram showing draft data model for EAD data (3)

Figure 3

Question 4: Are we missing any obvious “things” that we need to treat as resources?

Note: In this post, I haven’t gone as far here as to enumerate all the properties that will be used to describe instances of each of those classes, but I’ll provide that in a future post.

Multi-level description, context, “completeness” and “inheritance”

The one remaining question – and perhaps one of the thorniest to address fully – is that arising from one of the fundamental characteristics of the nature of archival description. As noted above, archival description is typically based on a “hierarchical”, “multi-level” approach, in which, within a single finding aid, information is provided about an aggregation of records, and then about component parts of that aggregation, and so on, perhaps down to the level of providing descriptions of individual records, but often stopping short of that.

The ISAD(G) standard presents principles of moving from the general to the specific, and providing information relevant to the particular unit of description (ISAD(G) 2.2):

Provide only such information as is appropriate to the level being described. For example, do not provide detailed file content information if the unit of description is a fonds; do not provide an administrative history for an entire department if the creator of a unit of description is a division or a branch.

And of “non repetition” (ISAD(G) 2.4):

At the highest appropriate level, give information that is common to the component parts. Do not repeat information at a lower level of description that has already been given at a higher level.

In some cases, it may indeed be the case that if some descriptive attribute is not explicitly provided for the unit of description, then the information provided for its “parent” unit in the hierarchy is applicable; however, this is often not the case. The elements of the ISAD(G) Identity Statement Area (or the EAD <did> child elements), for example, are specific to the unit of description and do not apply to its “child” units; and for many other descriptive elements, a simple rule of “direct inheritance” may not be appropriate. For the <controlaccess> elements, for example, a “blunt” inference rule that the named entities “associated with” a unit of description are also “associated with” every “child” unit (and so on “down the tree”) may result in associations that are simply not useful to the consumer of the data.

In a post on the Archives Hub blog, Jane emphasised the value of the “Linked Data” approach in making things mentioned in our data into “first-class citizens”. One consequence of the multi-level approach in archival description practice is a strong sense of the importance of “context”, and that the descriptions of the “lower level” units should be read and interpreted in the context of the higher levels of description (perhaps even that they are in some sense “incomplete” without that “contextual” data). In contrast, the “Linked Data” approach typically involves exposing “bounded descriptions” of individual resources. Now, certainly, yes, those “bounded descriptions” include assertions of relationships with other resources (including the sort of part-whole/member-of/component-of relationships present here), and those links can be followed by consumers to obtain further information on the other resources – however, there is no requirement or expectation that consumers will do so. So, there is arguably a (perhaps unavoidable) element of tension between the strongly “contextual” emphasis of EAD and ISAD(G) and the “bounded descriptions” of “Linked Data”. Rather than seeing that as an insurmountable hurdle, however, I think it provides an area that the project can usefully explore and evaluate.

(If I remember correctly) we made the decision that, for now at least, the only piece of information for which we would implement an explicit “inheritance” from a “higher-level” Unit of Description to a “lower” one (and generate additional RDF triples in the data) would be that of the repository which provides access to the material (i.e. the EAD <repository> element).

Conclusion

As I said above, the model I’ve outlined here is intended as very much a first cut, not the “last word”, and something we’ll most likely revisit and refine further in the future, particularly as we see in practice what it enables us (and others) to do with the data generated, and where we might require some further tweaks to enable us to do more. For now, we feel it provides a basis for our initial work on transforming EAD data into RDF.

The next steps are:

  1. to decide on URI patterns for the URIs we will be generating (i.e. URIs for instances of the classes in the diagram above)
  2. to select terms from existing RDF vocabularies and to define any additional RDF terms required to create “descriptions” of these things based on information from the EAD document
  3. to create a transformation that implements the model (in the first instance, an XSLT transform)

I’ve already done some work on all of these, and I’ll write about them in a separate post here – which hopefully will be rather shorter than this one and will take me rather less time to write!

Creating Linked Data: more reflections from the coal face

This post is to highlight some of the barriers and challenges to the creation of Linked Data.  This is a personal reflection, trying to be honest about the challenges as I have found them and the learning experience, which is inevitably a personal thing depending upon your own background, experience and ways of thinking and working. However, I think it also reflects some of the general challenges as we have come across them.

Vocabulary

It comes as no surprise that I have found the terminology somewhat confusing, and it has sometimes led me astray. Only this week Bethan and I were getting tangled up in a conversation about ‘things’  within the data model. We spent a while talking about how having a ‘Hub conceptualisation’ and a ‘thing-in-its-own-right conceptualisation’ of an entity would allow for more clarity. With ‘thing’, ‘concept’, ‘label’, ‘property’, ‘value’, ‘predicate’, ‘information resources’, ‘non-information resources’ etc. – there is quite a bit of room for misinterpretation in communication. I have looked at definitions, but these can actually sometimes hinder rather than help. I think that an attempt at a definitive glossary for Linked Data would help enormously.

Landscape

For me, it has taken a while to really get into the Linked Data way of thinking. I have actually kept a kind of diary of my thoughts over the last 2-3 months, and when I look back now at my earliest attempts at understanding how to model the data, they certainly show a pretty steep learning curve. I started, for example, by being unsure about whether we were wanting to provide information on the ‘creator’ of the archive or the archive itself and what sort of relationships between ‘things’ to include. I don’t think this is surprising, as the power of RDF is that it can be used to model anything – it doesn’t help you by giving you a limited scope or particular rules to start with (which is, of course, generally a good thing).

Archival descriptions

I listened to a number of audio tutorials, read a number of reports, blogs, etc., and learnt a great deal from these, but I still found the lack of examples within my own particular domain to be a barrier. Talis provide a very excellent tutorial that you can sit and listen to, but the real-world example is for a whiskey distillery. It somehow seems a long way away from an archival description! So, I would definitely say this lack of information for my domain was a barrier. But, of course, for others who want to output their finding aids as Linked Data in the future, we should start to see models developing that they can use, with examples and information to help (Locah, we hope, being one source of help).

Expertise and experience

The Locah team has a variety of expertise and experience, but it is undoubtedly true to say that I would be struggling a great deal more than I have done if we had not had the input of Pete Johnston from Eduserv, who has been very much involved in the EAD modelling. Whilst it is important (and pleasant) to give credit where it’s due,  the real point here is actually that I think a certain level of expertise is important, to model data and output RDF. I have experience as an archivist and understand EAD and metadata, Pete also has experience of working with archival descriptions, and also substantial experience of metadata standards and issues around the Semantic Web and technical interoperability. We also have Bethan Ruddock working with us, who now has 18 months experience of working with EAD descriptions, and is a trained librarian. That is just the core team looking at the archival data modelling.  In addition, the expertise of UKOLN will come into play with other aspects of the project.

I find it hard to see how this sort of work could currently be done by a team with substantially less experience in these sorts of areas. However, it is important to state that we will also be working with Talis, who have a great deal of expertise in Linked Data. They are providing access to their own Triple Store and other benefits that we can take advantage of. Others thinking of outputting Linked Data could look to involve companies like Talis more heavily, thus taking advantage of their expertise and requiring less in-house expertise.

The benefits of data modelling

One of the areas that I spent most time trying to find good tuturials about was data modelling. I may have missed some things that would have been very useful, but as it is I found that there simply wasn’t enough helpful information about how to create a data model. This would have saved me quite a bit of time because I think the data model is so central to what we are doing and provides such an effective way to visualise the entities and relationships between them. I think this was partly a case of examples being too simplistic, and partly a lack of data models that used catalogue data – not necessarily archival finding aids, but at least something similar.

The data

I think that we are going to find challenges around the actual content. There are numerous examples of inconsistencies, such as where the ‘creator’ is ‘Joe Bloggs and others’ rather than just a name, or where the access points do not have rules or a source associated with them. I’ve just found some descriptions where the content for the ‘extent’ should acutally really be in the ‘scope’. Some descriptions have rather unsatisfactory references, some do not include the language field, a few do not even include the creator field. For some fields we will just be outputting literal values, but for others consistency would help a great deal with the creation of RDF, particularly when thinking about the vocabulary (or predicate) that we use to define the relationship between a subject and object.  This is the challenge of creating Linked Data for descriptions that have been created by 200 different institutions over several decades and by 100s of different people. We’ll have to see how it goes!

The issue of access points

Within EAD there are access points, or index terms, associated with the description. These are most commonly subject, name and place. We’ve found that establishing the nature of the relationship between the unit of description and the access point is not easy. It looks like the relationship is going to be something very unspecific, such as ‘associatedWith’. I’m not sure yet whether this has any implications…

Conclusions

For me, after a few weeks away from thinking about Locah and Linked Data, getting back into the whole mindset actually takes about an hour and a nice cup of tea. In other words, the mindset I require to think about Linked Data currently feels separate from my normal working mindset. I think this is because LD requires something different. This in itself makes it quite challenging. It doesn’t fall naturally into what we do in the Hub and how we think about metadata.

However, the very big plus with this different kind of thinking is that really by definition it puts what the user is interested in at the forefront of your thinking. Well, maybe I should qualify that: I believe it puts what the user is interested in at the forefront. This is because we understand that users of archives are usually primarily interested in individuals, families, organisations, subjects and places. What they want is information on Sir Ernest Shackleton, Barbara Castle, Victorian theatre, town planning, a local business, a scientific organisation, the history of Manchester the industry of Sheffield,  or anything else. They don’t tend to know that they want to access a particular archive. Or if they do, it is often due to an assumption that there is ‘an archive’ on the person or organisation that they are researching. Even if there is an archive, there may may be a misplaced assumption that this archive is pretty much all the stuff about that entity. Furthermore, there are going to be many many researchers out there who will not be aware of archives and how to access them.  Linked Data provides a way to link archives into…well, into just about anything else.

Making sense of modelling EAD

Last week Pete Johnston, Bethan Ruddock and I got together and shut ourselves in a room for 5 hours with a whiteboard, flipchart and with our thinking caps on. Pete has already posted some thoughts about architecture and workflows following this meeting. I thought I would share some more informal thoughts of my own – from the perspective of an archivist and someone gradually getting to grips with Linked Data and RDF modelling.

Now that I understand a bit more about RDF, I can see where some of my misunderstandings were leading me astray. Firstly, it took me quite a while to get away from the idea of modelling the EAD record, rather than the actual data. This might seem obvious to those conversant in Linked Data, but I’ve been dealing with records as the unit of information for the last 20 years. With Linked Data you have to get away from this and think about the actual concepts within the data. The record (the EAD description in this case) exists as an entity along with everything else, but it can be misleading to take it as the starting point for data modelling.

I found actually getting a ‘starting point’ a bit difficult. I think this is because everything can be a starting point, and also because I kept going back to thinking of something like <http://archiveshub.ac.uk/search/record.html?id=gb15sirernesthenryshackleton> as the starting point (the record itself). I then moved away from this and started thinking about the archival creator as a central concept. I knew that in RDF this person or organisation would be a subject. I also knew that this subject would need a URI and that we might want to tell people about stuff related to this subject, but I struggled with how we would provide URIs for subjects like this, and also how we would link the creator as subject to things like the index term subjects.

After a quick chat with Pete Johnston I started to understand the real role of URIs within Linked Data. We are probably going to create URIs ourselves for things (concepts) within the Hub. So, we might create a URI for every archival creator, and a URI for every repository, etc. We agreed that we needed to model the data within our world before looking too much at linking to data outside of it.  Whilst I had listened to, and read a good deal of literature on Linked Data, I somehow hadn’t quite got the idea that you might create URIs yourself for your own concepts and that these would be documents in their own right, so then you can link to these URIs within your statements and you can include whatever information you think will be useful within these documents.

For example, we were using Sir Ernest Henry Shackleton as a sample record (the famous Antarctic Explorer). He would have a URI – something like archiveshub.ac.uk/id/person/sirernesthenryshackleton. By providing him with a URI we can then create triples (statements) that include this URI. For example:

archiveshub.ac.uk/id/person/sirernesthenryshackleton ‘created’ http://archiveshub.ac.uk/search/record.html?id=gb15sirernesthenryshackleton.

We can then decide what information we will put in this document that identifies Sir Ernest, so that when researchers look up the URI, they get useful information. We can include links to external locations and we can look at using the ‘sameAs’ relationship to link to other representations of the same person.

Some URIs are fairly straightforward. We will create URIs for archival levels, and then these can in theory be used by others who want to identify levels within the data. For something like language, we will probably use URIs that are already available.

It is useful within data modelling to distinguish the real from the conceptual. So, going back to Sir Ernest, he is a flesh and blood person, and he can also be represented as a concept. If we are thinking about subjects used as index terms within the data, you might have ‘Exploration’ as a subject. We want Sir Ernest, the man described within our description, to be associated with this subject, so we can do this by making him into a concept, and giving that concept a URI. We can then link that to a literal value – his name. In our meeting we discussed one of the advantages of conceptual agents as being that we can distinguish between the person or organisation in its entirety and the person or organisation within this particular context. Archives often only represent a small part of someone’s life or an organisation’s activities, so it is helpful to talk about ‘Sir Ernest Shackleton’ as the explorer and leader of the British National Antarctic Expedition of 1907-1909.

So, we are now starting to move towards a model where we have URIs for a number of key concepts within the Hub. Our intention is to limit the number of concepts that we create URIs for, at least at this stage. We will also simplify some areas with the EAD modelling that we can then open up for investigation later on. For example, it would be good to look at version control and how we might filter changes to Hub descriptions through to the RDF XML, but we think that initially it is a good idea to create Linked Data from our basic model so that we can get feedback and also benefit from the learning process.

The main text heavy field that we are planning to create URIs for at this stage is the Biographical and Administrative History. We haven’t yet explored this thoroughly, but with URIs for archival creators and URIs for administrative and biographical histories, one’s thoughts start to turn to name authorities and EAC-CPF (Encoded Archival Context – Corporate Bodies, Persons and Families – a means to markup information about archival creators in XML). We are not looking at creating EAC descriptions, but it would be good to keep in line with this in whatever ways we can in order to facilitate the subsequent creation of EAC records, or incorporation of our data into EAC records.

We will soon be able to share our current data model, so keep an eye on our blog. We welcome any feedback that the community might have.