Topic Maps and Entity Authority Records: an Effective Cyber Infrastructure for Digital Humanities

The implicit connections and cross-references between and
within texts, which occur in all print collections, can be made
explicit in a collection of electronic texts. Correctly encoded
and exposed they create a framework to support resource
discovery and navigation by following links between topics. This
framework provides opportunities to visualise dense points
of interconnection and, deployed across otherwise separate
collections, can reveal unforeseen networks and associations.
Thus approached, the creation and online delivery of digital
texts moves from a digital library model with its goal as the
provision of access, to a digital humanities model directed
towards the innovative use of information technologies to
derive new knowledge from our cultural inheritance.
Using this approach the New Zealand Electronic Text Centre
(NZETC) has developed a delivery system for its collection of
over 2500 New Zealand and Pacic Island texts using TEI XML,
the ISO Topic Map technology1 and innovative entity authority
management. Like a simple back-of-book index but on a much
grander scale, a topic map aggregates information to provide
binding points from which everything that is known about a
given subject can be reached. The ontology which structures
the relationships between dierent types of topics is based on
the CIDOC Conceptual Reference Model2 and can therefore
accommodate a wide range of types. To date the NZETC
Topic Map has included only those topics and relationships
which are simple, veriable and object based. Topics currently
represent authors and publishers, texts and images, as well as
people and places mentioned or depicted in those texts and
images. This has proved successful in presenting the collection
as a resource for research, but work is now underway to
expand the structured mark-up embedded in texts to encode
scholarly thinking about a set of resources. Topic-based
navigable linkages between texts will include ‘allusions’ and
‘infl uence’ (both of one text upon another and of an abstract
idea upon a corpus, text, or fragment of text).3
Importantly, the topic map extends beyond the NZETC
collection to incorporate relevant external resources which
expose structured metadata about entities in their collection
(see Figure 1). Cross-collection linkages are particularly valuable where
they reveal interdisciplinary connections which can provide
fertile ground for analysis. For example the National Library
of New Zealand hosts a full text archive of the Transactions
and Proceedings of the Royal Society containing New Zealand
science writing 1868-1961. By linking people topics in the
NZETC collection to articles authored in the Royal Society
collection it is possible to discern an interesting overlap
between the 19th century community of New Zealand Pakeha
artists and early colonial geologists and botanists.
In order to achieve this interlinking, between collections, and
across institutional and disciplinary boundaries, every topic
must be uniquely and correctly identied. In a large, full text
collection the same name may refer to multiple entities,4 while
a single entity may be known by many names.5 When working
across collections it is necessary to be able to condently
identify an individual in a variety of contexts. Authority control
is consequently of the utmost importance in preventing
confusion and chaos.
The library world has of course long worked with authority
control systems, but the model underlying most such systems
is inadequate for a digital world. Often the identier for an
entity is neither persistent nor unique, and a single name or
form of a name is unnecessarily privileged (indeed, stands in as
the entity itself). In order to accommodate our goals for the
site, the NZETC created the Entity Authority Tool Set (EATS),6
an authority control system that provides unique, persistent,
sharable7 identiers for any sort of entity. The system has two
particular benets in regards to the needs of digital humanities
researchers for what the ACLS described as a robust cyber
infrastructure.8
Firstly, EATS enables automatic processing of names within
textual material. When dealing with a large collection, resource
constraints typically do not permit manual processing --
for example, marking up every name with a pointer to the
correct record in the authority list, or simply recognising
text strings as names to begin with. To make this process at
least semi-automated, EATS stores names broken down (as
much as possible) into component parts. By keeping track of
language and script information associated with the names,
the system is able to use multiple sets of rules to know how
to properly glue these parts together into valid name forms.
So, for example, William Herbert Ellery Gilbert might be
referred to in a text by “William Gilbert”, “W. H. E. Gilbert”,
“Gilbert, Wm.”, or a number of other forms; all of these can be
automatically recognised due to the language and script rules
associated with the system. Similarly Chiang Kai-shek, being a
Chinese name, should be presented with the family name fi rst,
and, when written in Chinese script, without a space between
the name parts (蒋介石).
Figure 1: A mention of Samuel Marsden in a given text
is linked to a topic page for Marsden which in turn
provides links to other texts which mention him, external
resources about him and to the full text of works that he
has authored both in the NZETC collection and in other
online collections entirely separate from the NZETC.
The ability to identify entities within plain text and add
structured, machine-readable mark-up contributes to the
growth of electronic text corpora suitable for the types of
computational analysis oered by projects such as the MONK
environment.9 This is, however, distinct from the problem of
identifying substrings within a text that might be names, but
that are not found within EATS. This problem, though signicant,
does not fall within the main scope of the EATS system.10
Similarly, disambiguating multiple matches for the same name
is generally best left to the determination of a human being:
even date matches are too often problematic.11
Secondly, the system is built around the need to allow for
an entity to carry sometimes confl icting, or merely dierent,
information from multiple sources, and to reference those
sources.12 Having information from multiple sources aids in
the process of disambiguating entities with the same names;
just as important is being able to link out to other relevant
resources. For example, our topic page for William Colenso
links not only to works in the NZETC collection, but also to
works in other collections, where the information on those
other collections is part of the EATS record.
It is, however, barely sucient to link in this way directly from
one project to another. EATS, being a web application, can itself
be exposed to the net and act as a central hub for information
and resources pertaining to the entities within the system.
Since all properties of an entity are made as assertions by
an organisation, EATS allows multiple such organisations to
use and modify records without touching anyone else’s data;
adding data harvesting to the mix allows for centralisation of
information (and, particularly, pointers to further information)
without requiring much organisational centralisation. One benefi t of this approach is handling entities about which
there is substantial dierence of view. With topics derived
from research (such as ideas and events) there are likely
to be dierences of opinion as to both the identifi cation of
entities and the relationships between them. For example
one organisation may see one event where another sees two.
To be able to model this as three entities, with relationships
between them asserted by the organisations, a potentially
confusing situation becomes clear, without any group having
to give up its own view of the world. The EATS system can
achieve this because all information about an entity is in the
form of a property assertion made by a particular authority in
a particular record (see fi gure 2).
The technologies developed and deployed by the NZETC
including EATS are all based on open standards. The tools and
frameworks that have been created are designed to provide
durable resources to meet the needs of the academic and wider
community in that they promote interlinking between digital
collections and projects and are themselves interoperable with
other standards-based programs and applications including
web-based references tools, eResearch virtual spaces and
institutional repositories.
Figure 2: The EATS objects and basic relationships
Only once both cultural heritage institutions and digital
humanities projects adopt suitable entity identiers and
participate in a shared mapping system such as EATS, can there
exist unambiguous discovery of both individual resources and
connections between them. The wider adoption of this type
of entity authority system will contribute substantially to the
creation of the robust cyber infrastructure that will, in the
words of the ACLS “allow digital scholarship to be cumulative,
collaborative, and synergistic.”
Notes
1 For further information see Conal Tuhoy’s \Topic Maps and TEI |
Using Topic Maps as a Tool for Presenting TEI Documents” (2006)
http://hdl.handle.net/10063/160.
2 The CIDOC CRM is an ISO standard (ISO 21127:2006) which
provides denitions and a formal structure for describing the implicit
and explicit concepts and relationships used in cultural heritage
documentation. For more information see http://cidoc.ics.forth.gr/.
3 The initial project work is being undertaken in collaboration with
Dr Brian Opie from Victoria University of Wellington and is centred
around the work and infl uences of William Golder, the author of the
fi rst volume of poetry printed and published in New Zealand.
4 For example, the name Te Heuheu is used in a number of texts to
refer to multiple people who have it as part of their full name.
5 For example the author Iris Guiver Wilkinson wrote under the
pseudonym Robin Hyde.
6 For more analysis of the weakness of current Library standards for
authority control and for more detail information on EATS see Jamie
Norrish’s \EATS: an entity authority tool set” (2007) at http://www.
nzetc.org/downloads/eats.pdf.
7 Being a web-based application the identiers are also dereferencable
(ie resolve a web resource about the entity) and therefore can be
used as a resource by any web project.
8 “Our Cultural Commonwealth: The fi nal report of the American
Council of Learned Societies Commission on Cyberinfrastructure
for the Humanities & Social Sciences” (2006) http://www.acls.org/
cyberinfrastructure/OurCulturalCommonwealth.pdf.
9 Metadata Oer New Knowledge http://www.monkproject.org/.
10 EATS can be provided with name data on which to make various
judgements (such as non-obvious abbreviations like Wm for William),
and it would be trivial to get a list of individual parts of names from
the system, for identication purposes, but there is no code for actually
performing this process.
11 That said, the NZETC has had some success with automated
ltering of duplicate matches into dierent categories, based on name
and date similarity (not equality); publication dates provide a useful
cut-o point for matching.
12 A source may be a primary text or an institution’s authority
record.