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USER ASSESSMENT FOR DEVELOPING OPTIMAL CARTOGRAPHIC REPRESENTATION MODELS WITHIN AN AUSTRALIAN MOBILE LOCATION-BASED SERVICES TRAVEL APPLICATION Wealands, K.1, Cartwright, W. 1, Miller, S. 1 and Benda, P.2 1

School of Mathematical and Geospatial Sciences, RMIT University, Australia 2 Telstra Research Laboratories, Australia Email: [email protected], [email protected], [email protected] and [email protected]

ABSTRACT Mobile Location-Based Services (mLBS) are currently driven by technology-centred development, as opposed to the needs of end users. Where users have been made a focus, the research generally concerns issues of overall system appearance, functionality, information content and interaction methods, with little emphasis on cartographic representations. This paper describes the initial stages of an attempt to fill this void through the application of a UserCentred Design (UCD) methodology for optimising cartographic representations within mLBS. What follows is an account of the two user assessment activities adopted for the research. User Profiling involved defining a target user population via an online questionnaire. Analysis of the data produced a high-level overview of the attributes, behaviours and attitudes of Australian leisure-based travellers. User Task Analysis involved in-depth interviews with a subset of the users, in preparation for a deeper understanding of the population. The themes described in this paper represent an initial and necessary component of UCD, as applied to mLBS. Whilst the focus here is on a specific user group and context of use, it is envisaged that many of the concepts based upon the resulting user models will be relevant to mLBS in general.

1.

INTRODUCTION: MOBILE LOCATION-BASED SERVICES

Cartography continues to evolve, adopting and adapting technological innovations and new mediums. Representing an important paradigm shift, the Internet has been closely linked to the future of cartographic research and development, not least in its capacity for faster delivery and increased distribution of geospatial information, but also the possibilities it offers through multimedia and interactivity [1]. Until recently, research in Internet Cartography has concentrated on theory and applications relating to geospatial information services delivered via stationary, desktop computers and fixed-line Internet connections. A new concept has emerged, however, brought about by the advancement of highly portable devices and the mobile Internet, known as ‘mobile Location-Based Services’ (mLBS), which is defined for this research as: wireless services which use the location of a handheld device to deliver applications exploiting pertinent geospatial information about a user’s surrounding environment, their proximity to other entities in space (eg. people, places), and/or distant entities (eg. future destinations) [2]. MLBS essentially represent a merging of two widespread cartographic media – the desktop Web and the paper map – combining the relative benefits of each. Inevitably, there are also a number of unique infrastructure and contextual constraints posed [2], which have prompted research concentrating largely on the technology involved. In a research sense, technology-centred development (focused on applying new technology and investigating technical issues in its application [3]) can be a major facilitator of innovation, often enabling new tools and concepts that may never have been arrived at by other means. Despite such advances, however, at some point researchers and developers should take a step back, since the “build and they will come” and “one tool fits all” attitudes that characterise technology-driven development cannot guarantee the commercial success of new products [4, p.9,5]; a prime example being the failure of early WAP (Wireless Application Protocol) services [6]. This is often because user needs and expectations are rarely considered as part of technology-driven development – as with most products and services, unless mLBS are considered useful to, and therefore adopted by, their target markets, they will not be successful. Research in the area of mLBS has recently turned to the idea of ensuring usefulness in products, encompassing the two complementary concepts of utility and usability. Much activity in this respect comes from the field of Human-Computer

Interaction (HCI), where a number of projects have sought to define user needs for location-aware services [7], whilst others have employed techniques for ensuring systems that meet users’ goals and are easy to use [8,9]. This research has, however, been mainly concerned with issues of overall system appearance, functionality, information content and methods of interaction, with little or no emphasis on the appropriateness of the component cartographic representations [10]. Taking a different approach, cartographic researchers have been working to specifically develop representations for mLBS that will support users’ geospatial tasks. Particular attention has been paid to map design [11,12], with some treatment of non-map geospatial information presentation [13]. Whilst undeniably revealing, the results of these studies have been constrained by a general lack of user involvement (akin to technology-centred development), and thus their usefulness cannot be assured [2]. The research program underlying this paper aims to build on the current cartographic research relating to mLBS by following a methodology more in line with that of the HCI researchers, namely User-Centred Design (UCD). The overall purpose of the research is to investigate, via UCD, optimal techniques for representing, presenting and interacting with geospatial information in dynamic mobile environments, so as to ensure the cartographic usefulness of mLBS for a group of end users.

2.

RESEARCH METHODOLOGY

2.1 User-Centred Design UCD is an approach employed in systems design, having been developed under the premise that in order to ensure the usefulness and commercial success of a system, all design activities should position the end user as their focus so that the final product is easy to use and ultimately meets their needs [5,14,15]. Essentially, a UCD approach addresses the questions: ‘How do I understand the user?’ and ‘How do I ensure this understanding is reflected in my system?’ [16, p.93]. The principles and techniques of UCD originated from the early works of researchers Gould and Lewis [5] and Norman and Draper [17], culminating in three enduring principles: (1) early focus on understanding users and their tasks; (2) empirical measurement of product usage by representative users; and (3) an iterative cycle of design, test, and measure. These ideas have since been elaborated and embodied within an international standard, ISO 13407, which provides guidance by way of describing the rationale, planning, principles and activities of UCD practice. The standard discusses four main activities of UCD that are carried out iteratively until the defined objectives have been met [18]: 1) Understand and specify the context of use incorporating user characteristics, user goals/tasks and the environment of use, in order to support user requirements specification and provide a basis for later evaluation activities. Methods include survey, observation, focus groups, interviews and diaries. 2) Specify the user requirements using the previously defined context of use (in particular user tasks), in order to evolve measurable criteria against which the usefulness of the product will be evaluated, and to define user-centred design goals and constraints. Methods include scenarios, user models, domain models, and task models.. 3) Produce design solutions based on the established design goals, guidelines and constraints and incorporating HCI knowledge (relating to visual design, interaction design, usability, etc.). An iterative process of design to support evaluation at different stages of the system development lifecycle. Methods include storyboarding and prototyping. 4) Evaluate designs against requirements throughout development, employing prototypes and applying the taskbased criteria developed previously. Important for determining the degree to which user objectives have been met and obtaining feedback relating to design refinements. Methods include usability inspections and usability testing. The ideals of UCD are grounded in a number of disciplines, most notably cognitive psychology, experimental psychology and ethnography [15]. It aligns closely with the social sciences – concerned with the study of peoples’ beliefs, behaviours, interactions and institutions [19] – which is particularly noticeable in the correlation between specific UCD techniques and social research data collection methods, both quantitative and qualitative [2]. The UCDdriven plan for the research incorporates four key activities, closely aligned with those described above – User Profiling, User Task Analysis, Design and Evaluation. Each of these has been introduced and discussed elsewhere, with respect to its position within UCD, dependencies and relationship to specific qualitative and quantitative social research methods [2,10]. The remainder of this paper further elaborates on the two pre-design phases, User Profiling and User Task Analysis, which together constitute an overall user assessment, based largely on qualitative techniques.

2.2 User Group An early consideration for the research was the design of a cartographic mLBS interface which would be suitable for every user. With the endpoint of the study potentially relevant to all user types, it was considered impossible for a project of this scale to incorporate user-input from the ‘entire population’, not least due to the fact that such a group remains ill-defined. Supplementing this was the knowledge that for any research based on a UCD methodology and importantly, for good design to result, the focus of all research activities on particular users or user groups is considered

to be of certain benefit. To therefore restrict the target user population it was necessary to concentrate on a particular application area. The final selection of ‘leisure-based domestic travel’ was based on consultations with Webraska (the industry partner for the research) regarding their market directions, along with a review of the application areas at the focus of existing research and commercial implementations [10]. A broad and flexible delineation of end user characteristics was then undertaken to facilitate the sourcing of a user group (Table 1). Ethnicity Age group Travel habits

     

Other

 

Australian residents 25-40 years old As a leisure-based activity To distant, often unfamiliar locations On a regular basis (e.g. annually) Predominantly overland (i.e. not by air) Technologically capable Generally time poor

Table 1. Potential end user characteristics.

Even with an initial definition of the end users, it can be difficult to identify and gain access to representative users when designing new and innovative products [15]. A solution was found following consultation with one of Webraska’s business partners who expressed interest in the potential research products and saw benefit in the data that would arise from the study. The company subsequently offered access to a large number of people in their evaluator database, consisting of users who had self-opted to participate in product testing after visiting one of the businesses’ product Web sites. Whilst there was no guarantee that the evaluators within this database would fulfil the criteria in Table 1, they were deemed to be an appropriate ‘population’ from which representative samples could be sourced. Specific desirable characteristics that the database members fulfilled included:    

3.

Australian residents; unrestricted in terms of age; members of the general public; and users of online directories (i.e. technologically capable).

METHODS: USER ASSESSMENT

With reference to geovisualization in general, Fairbairn et al. [20] identify that individual users tend to react differently to alternative representations of the same geospatial data, depending on their preferences, experiences and abilities. In preparation for the design of cartographic representations for a leisure-based travel mLBS, a user assessment was planned, the purpose of which was to outline the range of user characteristics and requirements present within the target user population (in both general and specific terms) and thus define a global style and approach to the design model development. Comprising the first stage of the assessment, User Profiling was undertaken to describe the users’ geospatial knowledge, skills, experience, training, attributes, travel habits and preferences. Taking the resulting user profile as a starting point, a User Task Analysis was then initiated to obtain an understanding of the users’ travel goals, approaches to relevant tasks, geospatial information needs and problems with current methods during their travels.

3.1 Sampling Considerations For the two user assessment activities, refined user samples were required. The concept of sampling maintains that the responses and characteristics of a ‘representative’ sample should accurately reflect those of the target user population [21]. There are numerous methods of sampling, divided into two categories. Probability sampling uses random processes to produce unbiased samples that truly represent the population. This set of techniques – including simple random, systematic, stratified and cluster sampling – enables the application of powerful statistical analyses on the data and provides for generalisation of results to an entire target user population. Conversely, non-probability or purposeful sampling does not incorporate principles of random selection and therefore cannot make use of inferential statistics from probability theory (i.e. there can be no generalisation of results, nor can levels of precision be calculated). Purposeful techniques include: extreme case, intensity, maximum variation, homogeneous, typical case, critical case, snowball, criterion, theoretical, stratified, opportunistic, convenience and quota sampling [19,21-23]. Taking into consideration the non-random nature of the user group (i.e. each member having used one or more of a suite of online products – including a mapping/directions service) as well as the qualitative purpose of the planned user assessment, purposeful sampling was deemed the most suitable strategy. Criterion sampling was considered particularly relevant, whereby cases that meet some pre-determined criterion of importance are studied. Often employed in

exploratory and qualitative research to gain a deeper understanding of specific cases that are likely to be especially information-rich, this form of sampling is particularly useful in research such as this since the data yielded will be able to influence subsequent data collection techniques [19,22,23]. Criterion sampling was applicable to both phases of the user assessment, with the procedures used described below as part of the respective data collection processes.

3.2 Data Collection User Profiling: As the first step in understanding and specifying the context of use and specifying the user requirements for the proposed mLBS, User Profiling was aimed at defining the features of the target user population in terms of their psychological (e.g. attitude, motivation), knowledge and experience (e.g. task experiences, geospatial skills and abilities), goal and task (e.g. frequency of travel, task structure) and physical characteristics (e.g. demographics, vision problems). User Profiling is typically performed via social survey [15]. Of the possibilities for conducting a social survey – most notably interviews with parties knowledgeable about the target users or questionnaires distributed to actual users – the questionnaire was the instrument chosen to measure user attribute-, behaviour- and opinion-type data. This was in part due to the relative ease of data collection, based on time constraints and logistics, but also the view that it would prove to be a more reliable and accurate method of data collection than would in-depth interviews with experts [15]. Additionally, since the user group was only vaguely defined, sourcing expert interviewees sufficiently familiar with the target user population was not deemed feasible. Although traditionally a quantitative approach to research, questionnaires can be considered as either quantitative, qualitative or both. The use of closed questions (i.e. with predetermined response categories) enables the collection of data that can be quantified, whilst the use of open-ended questions (prompting descriptive, opinion-based responses) allows for qualitative analysis of the results [23]. While both question styles were used, the questionnaire was not a standardised instrument and thus any quantitative analysis of the results could not be considered reliable. A draft questionnaire was developed incorporating five distinct sections designed to elicit the specific types of information required: General Information – demographics and experiences with location-based information (attribute data); Travel Habits – recent holiday-based travel activities (behaviour data); Travel Information – use of geospatial information whilst travelling on holidays (behaviour data); Location-Based Travel Needs – geospatial information needs / preferences whilst travelling on holidays (attitude data); and Mobile Phone and Computer Skills – current use of mobile phones and computers (attribute, behaviour and attitude data). The questionnaire was then extensively pilot tested and revised to correct any problems encountered by test respondents. The final delivery mechanism selected for the questionnaire was online. The criterion sampling of potential participants was applied in a slightly abstract form, since the ultimate aim was to identify the characteristics of potential users of a leisure-based travel mLBS, yet the available user group was arguably too generic to be considered the ‘target user population’. Its application was thus:  

The questionnaire was sent to all users in the database who (a) had an email address; (b) matched the age criteria (25-40 years of age); and (c) had registered within the last 2 years (increasing the likelihood that their email addresses would be valid). Those users who completed the questionnaire would be considered to have demonstrated an interest in the research, and thus would be considered especially ‘information-rich’. They would subsequently constitute the main User Profiling ‘sample’, as well as embodying the ‘target user population’ for the research.

A ‘Call for Participation’ email containing a link to the questionnaire Web site was then forwarded to the appropriate users, who were given between two weeks and one month to respond. Each time a participant completed and submitted the questionnaire, a text file containing their responses was compiled. The number of ‘successful’ mail outs was 196, which was considered sufficient to yield a reasonable number of responses – assuming a conservative response rate of ten percent [15] – and to constitute a valid sample size, considering the depth of information being gathered [23]. In all, 67 participants responded, totalling almost 35% of those it was considered to have successfully reached. When all participant data had been collected, it was aggregated and analysed (the results of the analysis are shown below).

User Task Analysis: The aim of the User Task Analysis was to augment the user profile by producing a deep understanding of users’ current goals and associated tasks, the personal, social and cultural characteristics they bring to their tasks, the influence of any previous knowledge and experience on their thoughts and actions, the influence of the physical environment, and the qualities that they value most [24]. Traditionally, User Task Analysis is a process of describing and evaluating the finegrained and precisely defined tasks and actions currently performed (or required) by users to achieve specific goals

[15,25]. Considering the ill-defined and open-ended nature of users’ goals in tourism environments [26] however, a ‘goal-driven’ approach was deemed more appropriate here, aiming to determine user needs for the purpose of providing decision-making support, rather than defining a step-by-step process for users to follow in pursuit of a goal [27,28]. The data collection techniques available for User Task Analysis are largely qualitative, generally requiring face-to-face contact with users. Three primary techniques were investigated, within which a number of methods were available: observation – e.g. verbal protocols, talking immediately after the task, role playing and staged scenarios, cued recall [16,15,29-31]; interviewing without observation – e.g. process analysis, ethnographic interview, artefact walkthrough, critical incident technique [23,24,30,32], and focus groups [24]. The final selection required a balance between the level of detail required, the resources available, the suitability of the technique to the study and what was possible. One-onone critical incident interviews were ultimately chosen (a variation on the traditional critical incident technique [33]), which focused the data collection on users’ specific holidays as ‘critical incidents’. The major benefit of this detailed and rapid data collection technique was that by concentrating on specific tasks and behaviours in the absence of observation, generalisations and opinions could be avoided. A draft interview instrument (again non-standardised) was developed incorporating questions carefully designed to elicit specific types of information about a user’s recent holiday: experience and behaviour – what the user does or has done (behaviours, experiences, actions, activities); opinion and values – what the user thinks about some issue or experience, i.e. their cognitive and interpretive processes (goals, intentions, desires, expectations); feeling – the user’s responses to their experiences and thoughts (emotions); knowledge – what the user knows (facts); sensory – what the user has seen, heard, touched, tasted and smelled (stimuli experienced); and background/demographic – how the user categorises themself (characteristics). In addition to the questions, two ‘artefact’ presentations were prepared to assist with users’ recall of geospatial information sources they may have used during their holidays. The first of these contained images and text of pre-trip planning materials, whilst the second related to on-trip materials. The interview and artefacts were then pilot tested and revised to (a) ensure they were understandable to test users and operated effectively, (b) provide interviewer experience and (c) test the operation of the videorecording equipment. Purposeful criterion sampling was again employed to obtain a subset of users, with a set of criteria initially determined to isolate participants who would provide a deeper understanding of geospatially-related leisure-based travel goals and tasks. These criteria were based on the target users’ responses to the user profiling questionnaire:    

willing to participate further in the research; Victorian – more likely to attend face-to-face interviews held in Melbourne; over the age of 25; more than 25% of holidays taken within the last two years were to new destinations – unfamiliar travel behaviours were considered to be more informative than those during familiar travel; and  had provided detailed comments for any/all of the open-ended questions, thus considered willing to share experiences and opinions. A final sample size of eight was selected, constituting almost 12% of the total user population and 18% of the users remaining, once the above criteria were applied. Such a sample size was deemed acceptable on the basis that: (a) sufficient individuals would remain for participation during the remaining phases of the research; (b) the selection of particularly information-rich participants and a highly detailed analysis of the data would maximise its validity, meaningfulness and insights generated [23]; (c) the available resources (e.g. time, personnel, facilities) would be optimised; and (d) the qualitative purpose of the research did not warrant generalisation to a larger population, thus statistical reliability was irrelevant. The sample was randomly selected, however a mix of pertinent characteristics was sought – gender, age group, holiday frequency, holiday distance, holiday duration, mode of transportation and mLBS interest. During each interview (lasting between one and two hours), numerous techniques were employed to build a rapport with the participant. Probes, illustrative examples, presupposition, prefatory statements and interested listening served to assign importance to the information being provided, thus encouraging users to increase the richness and depth of their responses [22-24,32]. Notes were taken by both the interviewer and an assistant/observer during each interview, to supplement the later analysis.

3.3 Validity and rigour The tendency thus far toward qualitative methods of data collection and analysis warranted a qualitative approach to ensuring validity and reliability (hereon referred to as rigour). Whilst rigour is concerned with consistency in the development of themes which are considered unique to the group under study, validity deals with the accuracy and credibility of the findings. No efforts were made (nor was it intended) to assure the statistical reliability and validity of the questionnaire and interview as measurement instruments, however, for this stage of the research the validity and rigour of the data were maximised in a number of ways, using the recommendations of researchers in the field of

qualitative research [21,22,34]. In particular, a great deal of care was taken during the development of the questionnaire and interview, including careful question construction and wording to ensure clarity and avoid issues such as ‘response bias’ [34]. Additionally, Creswell [35] defines a number of strategies for performing accuracy checking on the outcomes of a qualitative study, six of which were employed (or upcoming) for the user assessment: 1) Triangulation – the use of disparate data sources, different investigators, multiple interpretation theories or multiple methods in order to build a justification for identified themes. 2) Member checking – allowing the participants involved to assess the accuracy of the findings. 3) Rich, thick description – conveying findings using sufficient detail to express the experiences shared. 4) Clarification of researcher bias – statement through ‘self-reflection’ of the bias brought to the study in order to create an open and honest narrative. 5) Presentation of negative / discrepant information – inclusion of findings that do not agree with the identified themes, thus adding to the study’s credibility. 6) Peer debriefing – a review of the study findings by peers to ask questions and validate conclusions drawn.

4.

PRELIMINARY ANALYSIS AND DISCUSSION

The role of the user assessment within the UCD lifecycle is to establish and describe the characteristics of the target user population, their goals and tasks and the context of use which will drive decision-making during subsequent design and evaluation phases. At the time of writing, the User Profiling analysis was complete, with the User Task Analysis modelling yet to begin. Here we present a discussion of the key findings from the User Profiling, followed by the modelling procedure planned for the User Task Analysis.

4.1 User Profiling: Key Findings Having taken a largely qualitative approach to the User Profiling data collection, it was important to continue this into the associated analysis. During initial data aggregation, particular effort was made to produce a qualitative narrative of the results. This yielded an emergent and comprehensive picture of the target user population from which high-level themes and trends could be evolved. During in-depth analysis of the narrative, each aspect of the target user population was considered in terms of its relevance to the profiling activity, the implications it posed to the design models and requirements for further investigations. Rather than summarising separate user profiles for each significant category of users, the decision was made to formulate the final user profile as a ‘range’ of characteristics, based on the need to consider the users as individuals with very personal goals and requirements. The final user profile shown in Table 2 is categorised according to user characteristics, context of use and user preferences, each of which will come into play during use and learning of the final product [24]. Characteristics (Range)

Design Model Implications

Male or female

Different approaches/abilities with navigation, spatial tasks

Aged 25+

Physical attributes degraded with age (e.g. eyesight, memory)

Australian residents

Tailored to the Australian domestic travel environment

User Characteristics

None to limited relevant vision problems

Context of Use

 

Issues with fine detail and/or small screens Colour blindness

Moderate to frequent domestic travellers

Familiarity with the service will increase with each holiday and should be accommodated

Visitors of familiar or unfamiliar destinations

Different geospatial needs depending on level of familiarity with destination

Holiday durations range from short- to medium- to long-term

Different geospatial needs depending on duration of holiday

Travel by car or air to destinations

Different geospatial needs depending on mode of transport

Demonstrate movement around destination

 

Navigation and related geospatial tasks need to be supported at the destination Different geospatial needs depending on mode of transport

Undertake widely varying activities

Provide consistent support for geospatial tasks

Regularly rely on map-based products for navigation

Carefully consider the purpose and use of maps, ensuring quality

Table 2. The user profile and related implications for the cartographic design models. Characteristics (Range)

Design Model Implications

Context of Use (cont.) Actively seek tourism information before and during travels

Incorporate the most common types and sources of information

Have some reliance on less tangible information sources

Support different methods of storing and accessing intangible geospatial information

Experience a variety of wayfinding and decision-making problems

Consider common difficulties and attempt to overcome, where possible

Have high familiarity with the desktop/laptop computer environment

Assume general proficiency with computer-type interaction tools (e.g. keyboard/pad, colour screen, mouse) and multimedia (e.g. hyperlinks, sounds, graphics, video, animation)

Have high familiarity with the use of mobile phones for voice and non-voice uses

 

Assume general proficiency with mobile phone interaction methods (e.g. keypad, predictive text, joystick/scroll key, stylus) and multimedia (e.g. voice, sound, images, vibration) Account for potential unfamiliarity with SmartPhones

Not formally trained and experienced with geospatial information and representations

Support different levels of geospatial information knowledge

Comfortable with familiar, general-purpose map representations (e.g. street directory)

Consider the incorporation of familiar representations (or aspects of) to satisfy currently accepted/preferred techniques

Less comfortable with other navigational maps

Avoidance of undesirable map characteristics

Variability in need to orient maps in the direction of travel

Support individual preferences for map orientation

Have no to some difficulty determining compass directions Have no to few difficulties remembering a previous route

Support individual preferences/needs for directional awareness

 

Consider different methods of navigational support for familiar vs. unfamiliar destinations Account for individual navigational needs

Rarely become lost

Consider minimal user positioning, upon request

Can relatively easily provide and follow landmark-based routes and follow directions/distances

Support individual preferences for route formats, ensuring adequate landmark information

Holidays variously include or don’t include the travel to/from/between destination(s)

Provide support for the different holiday behaviours

Variably open to a range of navigational information access methods/representations

Avoid less accepted methods/representations and capitalise on those most preferred

User Preferences

Require detailed local information at destinations

 

Ensure sufficient local detail to cater for user needs Establish tolerances/techniques to ensure data accuracy and timeliness

Would use a leisure-based travel mLBS

The research motivation is vindicated

Have varying reasons for use, non-use or dependent use of a leisure-based travel mLBS



Mainly interested in using a leisure-based travel mLBS in ‘ontrip’ situations, with some ‘pre-trip’ requirements

Provide sufficient ‘on-trip’ support

          

Ensure convenience and efficiency, to enhance the holiday experience and justify the service’s use Maximise physical portability Ensure flexibility in the service and its platform so that nonholiday uses are possible Integrate disparate information for a seamless user experience Ensure the currency and accuracy of the information provided, to an appropriate threshold Utilise the benefits of traditional information access methods Focus on the provision of decision-support Provide an accessible and appropriate cost model, reflecting the value of the service Maximise information relevance for the individual user Maximise service reliability (access and information) Provide information at a range of detail, to cater for varying holiday and destination types Ensure overall usability of the service

Table 2 (cont.). The user profile and related implications for the cartographic design models.

The category for ‘user characteristics’ comprised the demographics of the target user population, as well as their visionrelated physical attributes. The gender demographic was found to be of particular importance for the design, considering the widely accepted differences between males and females in their approaches to, and abilities with,

navigation and other spatial tasks [36,37]. Vision was also a major factor, with a range of colour, detail and age-related design issues to be considered. The ‘context of use’ category was by far the most extensive, incorporating travel habits and behaviours, use of geospatial information whilst travelling, issues related to wayfinding and decision-making and general experience with both mobile technology and geospatial information. Particularly important to the design were: (a) the range of holiday types undertaken by participants (based on duration, activities, transport modes, familiarity with the destination, etc.) requiring the design to support vastly differing geospatial information goals, tasks, needs and preferences; and (b) the participants’ self-definition of their own abilities and experience with geospatial information, which emphasised the wide range of individual differences to be supported. The final category, ‘user preferences’, concerned user desires for geospatial information (including access) whilst travelling, and opinions about a proposed leisure-based travel mLBS. Of most interest to the design was the identification of two distinct holiday behaviours: (1) where the travel to/from/between the destination(s) is as much a part of the holiday as the destination itself; and (2) where the holiday is focussed solely on the destination(s). Also of note was the users’ reliance on map-based representations during their holidays, despite a desire for non-map navigational instructions. The user profile was completed prior to the commencement of the User Task Analysis data collection, thus enabling the interview questions to incorporate existing user knowledge and to address any requirements for further investigation.

4.2 User Task Analysis: Modelling Procedure The anticipated endpoint of the User Task Analysis is a model which can be used as input for the design activities. Whilst there are numerous ways to conduct user task analysis modelling, again the intention is to take a goal-driven approach, with the basic aims of such being to uncover and convey: (a) the information directly related to achieving a goal; (b) the sub-goals that must be realised in order to meet the goal; (c) information that can be used to test the validity and reliability of the goal-related information; (d) information which may restrict possible goal solutions; (e) variation in information requiring the setting of other goals; and (f) related information that may influence decisionmaking [28]. The first step involves goal identification, which is not always simple, with goals having a broader scope and coarser granularity than tasks [25,27]. Once an initial set of user goals is obtained, however, associated requirements and additional goals can be defined and elaborated by a process of refinement and abstraction. Finally, the goals and requirements can be verified and validated with respect to one another, in conjunction with scenarios and personas generated from the data [27]. Of the available goal-driven modelling techniques, a combination of the AWARE [25] and goal/information diagram [28] techniques was selected for the research – Figure 1 describes the process.

Develop salient user personas and scenarios

Define and hierarchically arrange users’ sub-goals (with respect to goals)

Define users’ tasks and information / design requirements for achieving each goal/sub-goal

Define cause-effect relationships (including conflicts) between goals, goals/requirements and requirements

Classify each requirement in terms of its impact on design dimensions

Verification and validation

Refinement and abstraction

Define target users’ travel-related goals and problems

Figure 1. The user task analysis modelling technique.

*

*

*

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The end result of the user assessment will be twofold: (1) the user profile in Table 2 and (2) a model (or hierarchy) of user goals/sub-goals and associated tasks and information requirements, each related to particular aspects of the impending design. Just as important, however, will be a set of representative user personas and scenarios associated with the now-complete picture of the target user population. Whilst the personas will represent archetypal users of a leisure-based travel mLBS, including their behaviour patterns and goals [38], the scenarios will describe typical ‘interactions’ with the final system [39]. Both entities will not only help to keep the design process “focused on the needs and concerns of users” [39, p.45] rather than the technology, they will also provide a basis for the ensuing evaluation activities.

5.

CONCLUSIONS AND FUTURE WORK

This paper has described the initial phases of a research project aimed at improving the usability, and thus commercial success, of mLBS through a user-centred approach to the design of cartographic representation and interaction methods. As far as can be ascertained, it is among the first research of its kind in the field of cartography, particularly regarding the involvement of real users from the outset through to the final product. As the first step in a complete target user assessment, the User Profiling activity collected data relating to the geospatial knowledge, skills, experience, education/training, attributes, habits, preferences and capabilities of a selected user population. The result was a user profile which was fed into the second user assessment activity – a goal-driven User Task Analysis. Whilst currently underway, this phase will ultimately produce a model of the users’ goals, sub-goals, tasks and information requirements, as well as a set of personas and scenarios. The next phase of the research will take the results of the user assessment and use them as input into the production of preliminary design models, incorporating alternative cartographic representations. These will then be evaluated by users through prototyping.

6. [1] [2]

[3]

[4] [5] [6] [7] [8]

[9]

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BIOGRAPHY OF PRESENTING AUTHOR Karen Wealands (nee Urquhart) commenced her PhD candidacy at RMIT University in April 2002, supported by the Australian Research Council under a Commonwealth Government Linkage Scholarship. In 1999 she successfully completed a combined degree, obtaining her Bachelor of Geomatics (with Honours) and Bachelor of Science (Environmental Studies) at the University of Melbourne. During her final year she completed a joint research project involving the development of prototypical interactive, computer-based, multimedia learning modules for teaching Geographic Information Systems to university students, which earned a High Commendation from the Australian Excellence in Surveying Awards. Following this Karen worked for two and a half years as a Management Consultant with PricewaterhouseCoopers Consulting in Melbourne, Australia. Her current research, entitled “Representation models for the delivery of useful, interactive geospatial information services via the mobile Internet”, is being undertaken in the School of Mathematical and Geospatial Sciences at RMIT and involves a close working relationship with the project’s industry partner, Webraska Mobile Technologies. The focus of this research is on the usefulness of geospatial information representations, delivered via small-screen, mobile communication devices, which combines her interest in the everyday use of geospatial data with her project-based industry experience. Karen is a member of the ICA Commission on Maps and the Internet, the Computer-Human Interaction Special Interest Group of Australia, the British Cartographic Society and the Society of Cartographers.