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Topic Maps for repositories
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Abstract
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No abstract was provided for this paper.
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Contents
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Introduction
This paper discusses the potential application of Topic Maps as an interface
to a multi-user document repository; presents some possible implementation
approaches to creating Topic Maps for a repository; and finally demonstrates
some graphical tools for Topic Map navigation and creation.
Previous
Table of Contents
Current repository navigation techniques
Hierarchichal browsing
A common feature of nearly every repository system, is the use of a
hierarchy of nested containers for organising and navigating through content.
Typically the structure of any given sub-tree of a hierarchy is defined by
a single user and used by all other users with interest in the content stored
therein. Users of such a hierarchy are therefore constrained by the structure
imposed by the administrator. For small repositories, or repositories used
by a single person, such an organisation may work well - most users are relieved
of the task of organising the content and need only to learn where to look
for the items of interest 1.
As a corpus increases in size, it gets progressively harder for a user
to learn the structure of the hierarchy unless it matches the way in which
that user mentally organises or works with the content. Of course, not all
systems are rigidly controlled by a single administrator - many systems provide
the freedom for users to create and manage a sub-tree of the hierarchy - but
this simply leads to more confusion - without a pre-arranged classification
system, any coherence in the organisational structure is lost as multiple
organisational criteria are squeezed into a single system.
Searching
Browsing is not the only way to find content in a repository - most
repositories also support searching. Most often this is provided for the benefit
of those who consume the data, rather than for those responsible for creating
and maintaining it - giving users a way to completely bypass the structural
organisation of the data. However, the results of the query can only be as
good as the query itself. An under-specified query will result in an unmanageably
large set of hits, and an over-specified query might miss a piece of relevant
content. Furthermore, a query across repositories of differing types requires
that those repositories define a common set of meta-data with commonly agreed
semantics for a combined search to return meaningful results.
Using Topic Maps for repository navigation
Associative browsing
Figure 1
. Associative browsing with a Topic Map
Topic Maps provide the casual browser of the repository, with a richly
cross-linked structure over the repository content.
Topic occurrences create 'sibling' relationships between repository
objects. A single object may be an occurrence of one or more topics, each
of which may have many other occurrences. When a user finds/browses to a given
repository object, this sibling relation ship enables them to rapidly determine
where there are other objects regarding the same topic as the current one.
Topic associations create 'lateral' relationships between subjects - allowing
a user to see what other concepts covered by the repository are related to
the subject of current interest and to easily browse to them. Associative
browsing allows an interested data consumer to wander across a repository
in a guided manner. A user entering the repository via a query might also
find associative browsing useful in increasing the chance of serendipitous
discovery of relevant information.
Topic Map querying
Figure 2
. Topic Map querying
A Topic Map can be used to provide a useful higher-level abstraction
across one or more repositories. Topic Maps provide a number of useful features
for query-based access to the repository:
- Topics can be used to group together repository objects which relate to a single abstract concept. Each repository object may be defined as an occurrence of the topic. Occurrences may be assigned a role, defining the relationship with the parent topic. These typed relationships mean that a user may first query on a concept and then rapidly narrow the size of the results set by occurrence role.
- Scopes can be used for specifying query domains - enabling a user to easily narrow or broaden the size of the query set.
- Facets can be used to provide indexing outside of the underlying repository. Facets enable indexing of repository contents where the underlying repository itself does not. Facets also enable multiple repositories to be indexed with a common set of meta-data, enabling meaningful cross-repository querying.
Topic cartography
The creation of useful Topic Maps should become a prime concern to the
creators of large corpora. Strategies for the creation of such maps would
be driven by the requirements of the Topic Map user and by the constraints
of the authoring environment. Broadly speaking, 3 types of Topic Map can be
identified:
- 1. System Topic Map
- 2. Semantic Topic Map
- 3. User-Defined Topic Map
The system Topic Map
The System Topic Map is a Topic Map which represents the structure of
the underlying repository. Characteristics of repository objects are directly
mapped to Topic Map constructs - these include such characteristics as the
location of the object and object meta-data. Such a mapping could be made
dynamically by an agent interposed between the topic map engine and the underlying
repository and may be combined with other topic maps on-the-fly by a processing
application.
Figure 3
. The system Topic Map
A key use of a System Topic map would be in creating a bridge between
the repository and the Topic Map environments. It may be easier for someone
used to navigating through the repository directly to get used to a Topic
Map view of a repository if there are 'landmarks' which map directly to the
underlying structure. Where time and effort has been spent in creating a hierarchical
organisation of data in a repository, the System Topic Map provides a portable
means for capturing the result of that effort. Many organisations have already
made the choice to store portable data (XML, SGML etc.) but a move to a new
repository can lose all of the effort and knowledge encapsulated in the organisation
and repository-level meta data associated with the content.
A further use for a System Topic Map is in combining multiple repositories
of the same type into a single 'virtual' repository which can be browsed seamlessly.
A single topic map application could communicate with and merge the output
of multiple system topic map engines.
The semantic Topic Map
The Semantic Topic Map is generated by automatically extracting meaning
from the content of the repository and representing the connections made by
analysis of that meaning as a Topic Map. Whereas in a System Topic Map the
topics represent repository objects; in a Semantic Topic Map the topics represent
concepts described by one or more repository objects.
Content analysis may be simply driven by such characteristics as document
structure, meta-data or contained hyper-links. Typically a well-marked up,
well cross-linked corpus will generate a good Semantic Topic Map. A more complex
approach, might make use of linguistic analysis to extract meaning from the
textual content of documents.
Figure 4
. Semantic Topic Map generation
While it is possible that some semantic analysis could be done 'on-the-fly',
the processing overhead of some of the more advanced forms of analysis might
make Semantic Topic Map generation and asynchronous process. The rules used
for the semantic analysis are, in themselves, an important form of knowledge
as they encode the way in which the relationships between repository objects
are inferred from their content by users of the repository. Some semantic
information may be encoded as associations between topics or as topic-occurrence
relationships. Other semantic information may be extracted which applies to
just a single repository object and this information may be represented using
a facet.
When used to generate an index for a corpus, a semantic Topic Map provides
indexing features above and beyond those of a standard static index. Scopes
provide a means of quickly creating domain-specific indices - combining multiple
domain-specific indices on demand would enables each user of the same corpus
to create their own personalised index of that corpus. Facets provide easily
searchable meta-data. Associations provide rich, typed cross-linking between
conceptual areas.
The user-defined Topic Map
The User-Defined Topic Map provides an individual with a means of creating
their own perspective on a set of data. User perspectives may be:
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| Organisational | The perspective maps the repository
to enhance location/retrieval of data. |
| Knowledge-driven | The perspective adds value
to the data by asserting associations between repository objects based on
some deeper understanding of the concepts represented by those objects. |
| Task-driven | The data is organised according
to the user's work processes. |
User-defined Topic Maps have potential application in 3 areas:
- Individual Workspaces
- Shared Workspaces
- Knowledge Management
Individual workspaces
Using a Topic Map to create an individual workspace gives the user a
means of better managing access to frequently used documents and to organise
data in multiple ways. Topic Maps can be used to create logical paths from
an abstract concept to a specific document in a way which more closely matches
the way the user thinks. Tools are needed to make the construction, maintenance
and navigation of such Topic Maps as easy as possible and to integrate as
tightly as possible with the day-to-day tools and processes. Topic Maps allow
a user to relate single data instances to multiple subject areas - such as
a standard text referenced from multiple projects. Topic Maps also give the
application the freedom to link to resources in other tools (such as email,
PIM systems and remote documents) - enabling the user to pull information
from many disparate sources into a single coherent set for their use.
Tools are already available that aid in this form of personal organisation.
Topic Maps may be used as an interchange format between such products and/or
platforms - for example moving my mind map from my PC to my Palm and back
or creating a 'mobile' workspace on an Internet-accessible site that can travel
with me.
Shared workspaces
Shared workspaces enable users to share knowledge by communicating to
each other the associations and relationships between data instances. Multiple
Topic Maps may be combined with relatively little effort, to quickly generate
a composite view of the same data set. Topic Maps created by individual users
can thus be shared across an organisation, enabling many other users to gain
the insights and benefit from the knowledge encoded in the Topic Map. As with
any Topic Map application, data instances may be in a repository or located
elsewhere within or outside the organisation - as long as it can be addressed
in some way.
When user share their workspaces, Topic Map merging rules and applying
additional scoping using added themes can be used to ensure that the perspective
of different people are combined only to the degree desired by the end-user.
Knowledge management
Topic Maps can be used to encode ontologies prepared by one or more
subject matter experts. Such a map may be used simply to transfer an ontology
from one tool to another, or as a 'publishing medium' for an ontology. A topic
map engine combined with other analysis tools (such as linguistic analysis
tools) could be used to automatically annotate documents according to a given
ontology and record the resulting annotation as a Topic Map. Again, Topic
Map merging rules could be used to generate composite or comparative views
of the same data set using different ontologies or analysis methods.
Topic Map GUIs
Topic Maps may be statically published (as a subject index, for example)
or more dynamically displayed to the user. For the types of 'workspace' applications
described above, an intuitive GUI is a key requirement for success. Topic
Maps enable users to create large quantities of meta-data and highly interconnected
sets of data. The challenge for a GUI is to present this graph and the associated
meta-data in a readily interpretable manner.
Data visualisation techniques are gradually entering the mainstream.
As graphics hardware prices continue to fall and new software becomes available,
building a compelling Topic Map GUI is becoming easier.
Topic Map GUI approaches
Topic Maps are essentially interconnected graphs with (potentially)
many dimensions of meta-data. There are a number of approaches to the visualisation
of such data already in the commercial domain:
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| Hyperlinked-Trees | A graph can be interpreted
as a hierarchical tree relationship with additional hyper-links between nodes.
Topic Maps support this type of visualisation due to the hierarchical relationship
between topics, associations and types and also the containment nature of
the relationship between topics and occurrences and associations and association
roles. Standard GUI tools are capable of displaying this kind of tree. For example STEP's on-line topic maps (http://www.topicmaps.com ). Distorted tree visualisations such as InXight's Hyperbolic Tree Browser (http://www.inxight.com/demos/ht/index.html) enable a larger proportion of the hierarchy to be displayed in the same amount of screen real-estate as the traditional tree browser. |
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| Graphs | Graph visualisation displays the Topic
Map as a set of interconnected nodes. A static graph visualisation simply
displays the nodes with their interconnections. Dynamic graph visualisations
limit the scope of vision of the user to the node of interest and all nodes
within a certain distance. As the user shifts focus from node to node, the
display of the graph changes interactively. This form of visualisation enables
all of the connections in the Topic Map to be more equally displayed, rather
than making a dominant hierarchical relationship and at the same time avoids
overwhelming the user with the quantity of information contained in the Topic
Map. Mind mapping tools such as the Brain from Natrificial (http://www.thebrain.com) use this form of display quite effectively. |
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| Landscapes | An interesting data visualisation
technique is to display interconnected information as a landscape, assigning
coordinates to topics according to their interconnections and height to coordinates
according to the degree of relevance or the degree of convergence of multiple
topics. This is the approach used by Cartia's ThemeScape product (http://www.cartia.com)
to create the NewsMaps web-site (http://www.newsmaps.com) - not
a Topic Map application, but the potential is there. |
| Worlds | The data model of Topic Maps seems to
lend itself well to the construction of three-dimensional spaces. Topics may
be assigned coordinates in 3D space according to specific characteristics.
A static 3D world enables the user to 'fly-through' the Topic Map; to learn
the 'lie of the land'; to meet other user's browsing through the same map
or even to bookmark frequently visited locations. A dynamic 3D world would
respond to the user's movements, bringing 'most relevant' topics nearer and
moving others further away as the user's focus changes. Three-dimensional
worlds are already implemented as glorified chat-rooms (http://www.activeworlds.com),
perhaps Topic Maps provide a framework for putting these worlds to serious
use. |
Conclusion
While the current focus for Topic Navigation Maps is on the creation
of static publication indexes, there is significant scope for the use of the
Topic Navigation Map standard in 'indexing' more dynamic data and to provide
an organisational construct on top of one or more repositories.
Topic Map meta-data and facets provide a means of creating a common
index across multiple repositories, allowing searching and browsing applications
to treat many disparate repositories as a single virtual repository. Topic
Map merging and scoping rules facilitate the sharing of individual Topic Maps,
allowing users to benefit from the knowledge of others.
To move forward in the use of Topic Maps for these kinds of applications,
development of compelling visualisation techniques is a must. Fortunately
the tools to build these visualisations are becoming readily available and
standard home and business hardware is already capable of advanced visual
display which would have been prohibitively expensive only three or four years
ago.