IIMS 96 contents
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Principles of link composition for hypermedia titles

John Robertson and John Leaney
University of Technology, Sydney
As our ability to generate, store and transmit computer based data increases, our capacity to effectively organise (structure), retrieve and utilise this information becomes more problematic. New and better methods must be developed to structure this vast information base. The authors present a formal reference model for hypermedia authoring which may be used as a basis to address the concerns expressed. This model is premised upon concept maps being logically equivalent to the associative link system. This work provides a method which may be used to guide the hypermedia author's structuring process.


Hypermedia (sometimes referred to as interactive multimedia) is the merging of multimedia technology with hypertext information structuring principles. Hypermedia provides the reader with non-sequential access to an information base containing text, images, sound and video (Martin 90, Slatin 91). This is accomplished through the provision of a network of links which bind associated (or related) chunks of information together. The reader then uses these links to browse through the information space, travelling between related concepts.

Enormous efforts has been placed on the development of new technologies to physically manage the collection, storage and dissemination of electronic based data. These advances now allow vast libraries of information to be electronically stored and indexed. Workstations exist which allow easy access to computerised information, and international networks of interacting users are commonplace (Flanagan 95, Whole Earth Catalog 95, EFF 95). While there are still many purely technical problems to solve, there appears to be no essential barriers in bringing information to large numbers of users in a presentable way, allowing them to manipulate it, and allowing them to make contributions to the overall collection (Reynolds 89).

The migration of information from a paper based medium to a computer based delivery system requires the restructuring of the information. The understanding and management of this process has made little progress since the inception of the hypermedia concept in 1945.

If "the value of information lies in how it is organised"(Berk 91) is true, then new and better methods must be developed to structure this vast information base if it is to be of any value to people. Further, in order for such systems to be economically viable it is necessary to find more cost effective techniques for authoring the network of associative links.

In particular, what are the construction rules for the "hyper" portion of hypermedia? Rules of composition must be developed to guide associative link creation during hypermedia title production. Reviews of many recently published multimedia titles have shown their hypermedia link systems to be shallow, and/or incomplete and on occasion inaccurate (Bernstein 90). Link construction principles, metric systems and measurement methodologies are required to analyse the accuracy and effectiveness of the associative link system within a multimedia titles.

This paper will look at the issues associated with the structuring and retrieval of hypermedia information, specifically, the development of associative links systems which are the heart of hypermedia titles. Can we develop "rules of composition" to guide the hypermedia author's structuring process?

The authors herein present the research being done, namely the development of a formal reference model for hypermedia authoring. The paper postulates that concept maps are logically equivalent to the associative link system contained within hypermedia systems. The use of the concept model formalism provides the potential for rigorously measuring important quality attributes of a link system.

The hypermedia authoring process and current research

The authoring process

over the years the authors have been asked quite regularly "what is hypermedia?". Although there are numerous and sometimes conflicting models/definitions for hypermedia there is general agreement that the central tenant of any hypermedia system is the connecting of related concepts within the information space using links (Nielsen 90, Smith 88). The hypermedia system's reader browses an information space, traversing nodes or chunks of data that are structurally, semantically or pragmatically related.

The author must work with two forms of structure, the logical structure of the information, and the physical structure of the storage/presentation system. The physical structure is tightly bound to the hardware and software system which is used to deliver the information. Issues such as layout, typography, user input devices, screen size and colour capability are just a few of the considerations an author must take into consideration when designing a hypermedia system. The logical structure is driven by the information contained within the hypermedia database, the purpose of the system and the nature of the user community.

Shneiderman, Kreitzberg and Berk stated the "Golden Rules of Hypertext" (Shneiderman 91) to be

  1. To improve information accessibility
  2. To enhance useability
  3. To increase the reader's satisfaction (Glushko, 89)
All three goals are affected by the appropriateness, completeness, and accuracy of the link system developed by the author. "Success or failure of a hypertext product is dependent on how well the developer deploys links." (Davidson 89)

The process of authoring this associative graph is currently very problematic. We lack the models, methodology and tools to assure proper informational design and development of hypermedia titles. "without such design guidelines and tools the ever growing network of interlinked applications is becoming increasingly spaghetti like and hard to maintain" (Bieber 95). Specifically what rules or principles of design should be followed in order to create an effective link system?

The authoring process consists of creating "meaningful" nodes, anchors and links (Garzotto 91). Links are organised into structures.


The author creates nodes by parsing the originating text, images, sound or video clips into nodes. A node is a "chunk of information that deals with a single theme."(Robertson 92). It should express a complete idea. It should not be dependent upon any external information for understanding, in other words a person should be able to read the node and understand its meaning regardless of how the reader navigated to the node. This is critical because in a hypermedia system, a reader can typically enter a node from many different external points. The author can make no assumption on what the reader has read prior to entry to the node and additionally can make no assumption about where the reader is to go when leaving the node.

Anchors and links

Anchors and links are objects which bind together concepts expressed within an information space. By performing some action on an anchor point in the media the user traverses a link to some other related concept in the hypermedia database (another anchor point).

There are three basic classes of links: structural, associative (Frisse 88) and application specific. The structural links bind nodes together replicating the structure of the original media. These type of links are sometimes referred to as an objective link (Kahn 89). They represent the explicit structure of the original material.

Associative links bind nodes together based on semantic or pragmatic relationships. They are added to the title during the authoring process as the author perceives associations between ideas represent in nodes. These links are sometimes called subjective links because they are based upon the subjective understanding of the information by the author (Kahn 89).

The third class of link is the application specific link. Although this type of link can also be structural or associative, there are times when an application specific link is not one of these. For example, the author may be engaged in the development of a hypermedia title for instructional purposes. He/she may wish to create a link between a set of nodes that originally came from different references. Therefore these nodes are not originally structurally related. In addition, the content of the nodes to be linked are not semantically or pragmatically similar. The link may be used as a means of transitioning between two different concepts within a lesson plan. Since the nodes are not semantically related, this link does not qualify as an associative link but rather as a link developed to implement an instructional path through the information space. This type of link is application specific. If this hypermedia database was to he used for another purpose, this link would not necessarily exist.

Another example would be a link between two WWW nodes; one dealing with the mating habits of the Tasmanian Devil and anvil sales in Arkansas, USA. They might be linked together because the web author was listing his hobby interests. The link does not reflect either a structural similarity because the origination of the information comes from disparate sources, and it would be extremely difficult to discern an associative relationship between these two concepts. The motivation for linking originates from the user needs, an application requirement.

There are a number of hypermedia models that identified other link types. These typically are application specific type links (Parunak 91, Trigg 83, Bornstein 90, Furuta 90, Lange 90). The study of discourse grammar deals with the definition of kinds of relationships and types of links that can exist between nodes (Beekinan 74, Beekman 81, Grimes 75, Longacre 76, Longacre 80, Mann 87).


Sets of links create structures. There are four types of structures: linear, matrix, hierarchical and graph. Well designed hypermedia systems use a creative mixture of these four organisational structures (Rauscher 92).


The linear structure is commonly used for two purposes: structural and application specific. The syntactic linear structure is used to represent the sequential nature of the included information's original format. It is generally desirable to retain the sequential organisation of the paper based original documents. Therefore chapter 1 will be linked to chapter 2, enabling the reader of the online version of the information to traverse through the information in the same order available in the paper version.

The second use of linear structures is the trail (Bush 45) or Guide Path or Guided Tour (Trigg 88). These provide a selected sequential passage through the hypermedia title's link structure. These trails are application specific, commonly used for educational purposes. The author creates an explicit path through the information space in order to convey concepts in a sequential manner.

Some hypermedia presentation systems impose linearity on the information base; the author has no choice. HyperCard is one such system. Nodes (or cards) are ordered in a linear stack.


The matrix structure can be used to organise information that originated as relational databases, tables, spreadsheets, game boards, maintenance manuals and street plans (Brochmann 89). It is a powerful structure for organising information that is regular in structure. A node is created for each cell, or location within the original structure. Matrix links connect each node to it's immediate neighbours. The reader of the hypermedia system is able to browse the table through these links providing a quick way find information.

Many common problems lend themselves to a grid structure (Rauscher 92). Matrix structures can also be developed for application specific purposes. Commercial multimedia kiosks and educational systems commonly utilise this structure.


The hierarchical structure can be used for structural (syntactic), semantic, pragmatic and application specific purposes.

Structural links can be hierarchical in nature as when they are used to bind entries within a book's table of content or index to the chunks of data these entries refer to. Chapters can be connected to sections within the chapter through the use of structural links.

Hierarchical links can be used to establish semantic or pragmatic relationships between two bits of information in disparate references. For example, hierarchical links can be used to link from anchor points within a map of Australia in an atlas to individual maps of the states and territories. Links can be developed connecting each state map to encyclopedic entries for cities and regions within their geographical boundaries.

Hierarchical links can be used for application specific purposes also. Once again, application specific hierarchical links can be generated by the hypermedia author or instructional designer for instructional purposes.

The advantage of hierarchical structures are that readers are already familiar with them (Brochmann 89).


The graph structure provides the ultimate in expressive power (Brochmann 89). Unlike linear, matrix, or hierarchical structures the author is not bound by any rules as how the links should be constructed. Graph structures are used almost exclusively for associative linking. The only constraint to the author is the reasonableness of the semantic/ pragmatics of the associative links within the structure (Herrstrom 89).

Authoring research

As the problem of hypermedia authoring gains increased prominence internationally, more research is being initiated to address this problem. Most research focuses on techniques for the programmatic conversion of media into hypermedia. The reason for this is that the cost of the hypermedia authoring process is very high. This cost is primarily human labour costs. To identify ways to have the computer do most of the work and reduce the amount of time that humans were involved seemed immediately appealing. Efforts to "calculate" the conversion focus primarily upon the extraction of structural links. The reason for this is that the structure can often be extracted directly using conventional text models (Bernstein 90). The use of typographic or pattern matching techniques to discover the linear structure of the media is often straightforward and very successful. Hierarchical structures linking table of contents and index entries to their respective portions of media as well as hierarchical links between chapters and sections, sections and subsections can be easily derived. But hypermedia is more than the replication of the original data in electronic form together with the original data's linear and hierarchical structures. Hypermedia is the extension on this model to include associative link structures.

Except when associative links already exist and are explicitly noted, such as cross references in the source material, it is extremely difficult to identify associative relationships through structural cues. Format is not meaning. The development of associations or semantic and pragmatic links requires a method for understanding the meaning of the data.

It is because of the extreme difficulty of content analysis, that most of the research in hypermedia authoring concentrates on the automatic identification of structural linear links during the conversion of existing information into a hypermedia structure. It is felt that the identification of these structural links is a tractable problem and thus provide immediate benefits to commercial authors.

Most attempts at developing associative link systems are hand crafted. This is because of the requirement for understanding the material requires human intellect. There have been attempts to augment this hand crafted method with computer based tools (Robertson 94). It is understood that this assistance can only provide rudimentary help and the suggestions will not always be correct. But, some help is better than none. Some of the more promising and interesting efforts in this direction are (Bernstein 90, Clitherow 89, Lenat 86, Lenat 89, Hayes 89, Yankelovich 85, Conklin 87, Marchionini 88).

Although all these works have made important inroads into the understanding of hypermedia authoring methodologies, they have not resulted in the breakthrough necessary to ameliorate the prohibitive cost constraints facing commercial hypermedia title developers. More work must he conducted to establish more viable authoring techniques. New design methodologies must be developed. We found no strong theories, or all embracing models, to help solve the problems of hypermedia authoring. Nor did we find an adequate design methodology. For this reason we are looking at the use of concept maps as a model for the hypermedia design process.

Concept maps

Concept mapping is a type of structured conceptualisation which can be used by people to develop a conceptual framework of a subject domain. It is a set of techniques used to map a set of ideas and how they are semantically or pragmatically interrelated (Novak 84). Concept mapping is often used as method of evaluation and planning. (Trochim 89).

The resulting diagram is a pictorial representation of the information space, displaying all the ideas as points in a multi-dimensional space and showing how these ideas are related to each other. Distance between points or ideas in the map represent the similarity or dissimilarity between the ideas. Multi dimensional scaling algorithms are use to derive this distance. The statements are then organised into groups using a clustering algorithm.

There are a number of ways to conduct a concept mapping exercise. We have chosen a method developed by William Trochim (Trochim 89). Other approaches have been developed by (Novak 84) and (Rico 83).

Authoring research at UTS

Because of the problems mentioned, we are attempting to develop an alternative methods for the generation of hypermedia graph systems.

The technique developed at UTS is an adaptation and extension on the concept mapping methodology developed by William Trochim (Trochim 89). Our technique is heavily based on Trochim, but for different ends. Our process has four stages.

Stage one

A group of subject matter experts reviews the information to be included in the title, according to specified criteria. During this review the experts or group of experts identify important concepts or ideas which are contained in the data. At the completion of this review each reviewer's list is compiled into a single list.

Stage two

This single list is put onto cards, one item per card. The resulting stack of cards are then redistributed to the participants. The experts are asked to organise the cards into piles by placing the cards dealing with similar ideas into the same pile. This is done individually without consultation with any of the other participants. At the end of this step each domain expert has a set of card stacks, each stack containing cards that have similar statements.

The experts are also given a list of all the statements derived in stage one. Each participant is asked to rank the importance of each statement according to some scale. This is also done individually, without consultation.

Stage three

The stacks and the ranking lists are collected. Through the use of multi-dimensional scaling algorithms the results of stage two are converted into a map (see Figure 1). Each labelled point on the map corresponds to a concept generated in step one. The distance between each point and any other point in the map is a measure of the similarity or dissimilarity of the two concepts.

Figure 1

Figure 1: Map of concepts

Stage four

Clustering algorithms can then be used to group the statements together based on this similarity 1 dissimilarity measurement (see Figure 2). The domain expert group is then called together and asked to reach consensus on the clusters. The group is asked to provide tides for each clustering. Additionally they are asked to organise the clusters into regions. A region is a set of clusters with similar focus.

Figure 2

Figure 2: Clusters of concepts

At this point the information has been organised into a three level hierarchy (see Figure 3).

Figure 3

Figure 3: Hierarchical conceptual structure

This hierarchical index of the information contained within the information space can be integrated into the hypermedia title. By linking from each leaf or statement in the index to occurrences of that concept (as identified by the subject experts in stage one), the reader can utilise the index to reach all important instances of a concept. We refer to the destination point of the links from an hierarchical index entry to the actual media in the title as a content anchor (see Figure 4).

Figure 4

Figure 4: Associative links

Stage five

The final stage of our authoring process is to generate the associative links between the content anchors which are destinations for the same hierarchical index concept. This works because we know that these sets of content anchors are all dealing with the same semantic or pragmatic concepts, based on the experts grouping (see Figure 5).

Figure 5

Figure 5: Hierarchical links

By following the five steps elaborated upon above, an author or set of authors can develop a rich and complete hierarchical and associative link structure over a subject domain or collection of references.

Description of the first experiment

The first (trial) of the method described occurred in the authoring of material for the world wide web. The material was prepared as part of an Australian Government initiative in software engineering education, called SE Web ( software engineering web). This project is to provide industry with anonymous access to information on software engineering.

The authors were commissioned with writing an introductory tutorial for the SE Web project. The tutorial was devised based upon the focus statement, "describe the critical and practical issues in managing and improving software development in industry", using the process described in this paper to obtain the statements and named clusters. The domain experts were a group of six people who together have 23 years of industrial software development experience and 29 years of educational software development experience. One of the domain experts (also one of the authors) wrote up the web pages, which are still under construction.

Observations from the SE web authoring


The experts were asked to put the statements into clusters. No directions were given and we ended up with two sets of eight clusters, one of about 16 clusters, one of about 20 clusters and two of about 30 clusters. This confused the subsequent analysis, both by machine (the multi-dimensional scaling) and by people (the selection and naming of the clusters). However, the machine's first attempt at clustering rapidly, in a period of 1.5 hour, led to consensus on 14 clusters.


The author used the fourteen named clusters and the selection of statements, ordered by importance and "belongedness"[1] to begin writing the web nodes. The material was written (and if the truth be known, is being written) from numerous significant sources in software engineering. During the process of authoring, terms came up which had to be defined. Some major ideas (such as 'design') were left out as a consequence of the focus statement. It was a temptation to create new 'clusters', which would have distorted the purpose of the experiment. This problem was handled by a glossary, which gave simple definitions of any terms which needed elaboration.

Associative links were formed where statements ended belonging to two clusters, but which for syntactic reasons, ended up in one cluster. For example, one statement was "testing requires people", and there are clusters named "testing" and "people". The word "testing" comes first in the statement so it is in the "testing" cluster, with an associative link into the cluster "people". Another way of authoring this tutorial would have been to provide links into material as described in Figure 5, which would provide additional cross reference links.


We have proposed an organisational model for hypermedia which is information oriented. This model is based on concept maps, a graph based tool for displaying the connections in people's minds. A draft method for hypermedia authoring has been developed based on the concept map model. This method offers promise for the effective and (relatively) fast development of associative links. An initial experiment has been performed which suggests that the method has promise.


  1. belongedness is a term which we are still formalising. It represents how strongly the experts considered a statement belonged to a particular cluster. It is being formalised along the ideas of strength of membership of a class (or cluster).


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Authors: John Robertson and John Leaney
School of Electrical Engineering
University of Technology, Sydney

Please cite as: Robertson, J. and Leaney, J. (1996). Principles of link composition for hypermedia titles. In C. McBeath and R. Atkinson (Eds), Proceedings of the Third International Interactive Multimedia Symposium, 362-370. Perth, Western Australia, 21-25 January. Promaco Conventions. http://www.aset.org.au/confs/iims/1996/ry/robertson.html

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