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Environmental information for military planning
Applied Ergonomics 44 (2013) 595e602
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Applied Ergonomics journal homepage: www.elsevier.com/locate/apergo
Environmental information for military planning Victoria Doherty*, Darryl Croft, Ashley Knight QinetiQ, Cody Technology Park, Ively Road, Farnborough GU14 0LX, UK
a r t i c l e i n f o
a b s t r a c t
Article history: Received 19 April 2011 Accepted 29 November 2012
A study was conducted to consider the implications of presenting Environmental Information (EI; information on current environmental features including weather, topography and visibility maps) for military planning to the growing audience of non-technical users; to provide guidance for ensuring usability and for development of a suitable EI interface, and to produce an EI concept interface mock-up to demonstrate initial design ideas. Knowledge was elicited from current EI users and providers regarding anticipated use of EI by non-specialists. This was combined with human factors and cognition expertise to produce guidance for data usability and development of an EI interface. A simple mock-up of an EI concept interface was developed. Recommendations for further development were made including application of the guidance derived, identification of a user test-bed and development of business processes. Ó 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Keywords: Environmental Presentation Usability
1. Introduction 1.1. Background Environmental Information (EI) is the collective term for a heterogeneous collection of information and data sources concerning environmental features, character"istics and states. For example, it includes weather, climate, bathymetry, topography, visibility maps and others, many of which may also be termed Geographic Information (GI). Currently EI is a specialised information source, available in its raw form to only a handful of military personnel, predominantly specialist ‘Geo’ staff. Geo staff process the data, combining a large number of un-integrated sources, and present outputs that are tailored to the appropriate context to operational commanders to inform their planning decisions. However, this is changing: far wider user communities are being given access to EI, and decision makers themselves will be expected to interact with more data without modification by Geo staff. The format of data presented to Geo staff is complex, highly context-specific and requires a significant knowledge base before it can be used effectively. It is not suitable for non-specialist users with little time to spare to glean the critical information. Thus, the question that is central to this study emerges - how can EI be constructed and presented in a way that is intelligible and useful to
* Corresponding author. Tel.: þ44 (0) 1252 394147. E-mail addresses: [email protected], (V. Doherty).
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non-specialist users without a constant requirement for assistance from Geo staff? At a broader level, the Human Machine Interface (HMI) has been identified as one of the most important facets of any system architecture (Stanard et al., 2006), and is an important determinant of mental workload, Situation Awareness (SA) and task success for system operators (Milne et al., 2001). Indeed, appropriate data that is well presented has the potential to improve task performance significantly through the optimisation of the useresystem interaction. This is particularly important for EI users who will be accessing a variety of information sources to make time-critical decisions that are key drivers of performance in a complex operational context. 1.2. Aim The aim of the study was to use human factors and cognition expertise, and a user-centred design approach to: consider techniques for presentation of EI; present guidance for ensuring EI data usability; and create a paper-based mock-up of an HMI solution concept. The underpinning drivers for this study were: improving user comprehension and situation awareness for environmental information; and optimising the interaction to enhance usability.
0003-6870/$ e see front matter Ó 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved. http://dx.doi.org/10.1016/j.apergo.2012.11.011
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1.3. Approach A user-centred design approach, illustrated in Fig. 1, was followed (BS EN ISO 13407, 1999, subsequently superseded by BS EN ISO 9241 Part 210, 2010), beginning with stakeholder and user interviews. These are described in Section 2, followed by relevant human factors and cognitive considerations on EI data usability and presentation in Section 3. In addition, paper-based mock-ups of interface solution concepts were developed and used as a basis for discussion at a stakeholder workshop. These are briefly outlined in Section 4. Section 5 presents the conclusions drawn from the study. 2. Knowledge elicitation 2.1. User and stakeholder interviews The user requirements capture activity targeted three themes: Who will the end users be and what expertise/skills will they have (or will they need in the future)? What are the users’ specific task requirements and what functionality/information is vital to permit task completion? How do the users work, what are the steps involved, and where do they need support? Information was gathered using a combination of cognitive walkthroughs (Wharton et al., 1994) and interviews. Interviews were conducted with three groups: those who are likely to be users of the system in the future; current expert users of EI in the military, and information providers. Subject matter experts fulfilling these criteria were identified with the project sponsors. One of the strongest drivers for EI data usability requirements is the extent of disparity between user groups and their loci of interest. The focus of this study was on non-specialist ‘warfighters’ who have an interest in making tactical planning decisions that exploit EI. Including technical information providers as interviewees enabled additional understanding of the current approaches to data collection and representation, available support for users, constraints on future changes, and providers’ interpretations of user requests. The interviews used Goal Directed Task Analysis (GDTA, see Fig. 2; Endsley et al., 2003) a semi-structured interview technique, identifying the user’s goals, tasks and information requirements with respect to EI. This tool results in a rich but structured dataset, well suited to this broad area. An interviewer and a scribe attended each interview. This meant that the interviewer could focus on
Fig. 1. The User-Centred Design Process as described in ISO 13407.
Fig. 2. Structure used in interviews for discussion of goals, decisions and information requirements.
following the visual structure of the GDTA with the user while the scribe took detailed notes cross-referencing the GDTA structure. 2.1.1. Interview protocol Users were asked questions in four sections: user profile; GDTA; user requirements for EI; and current viewing technologies used. Interviews lasted between 1 and 2 h. 2.1.1.1. Section 1: User profile. Users were asked to define their role, experience and the types of EI and associated equipment that they use. 2.1.1.2. Section 2: GDTA. For the GDTA, users were asked to describe their goals with respect to EI and the decisions that they make based on EI, leading to the information that is needed by the EI user. Discussion focussed on specific incidents from which EI related requirements could be extracted. A range of examples, including both normal and exception cases, was identified to provide an overview of the key issues and to permit some degree of generalisation. Where interviewees did or had previously done more than one role, time constraints, frequency and importance of use of EI in the role, and recency and frequency with which the role was conducted were used to guide the focus of the interview. They were also asked to consider the role of a non-specialist in the future concept of EI use and the implications in terms of where goals, tasks and decisions would differ from the current process. The interviewer worked through a diagrammatic GDTA (see Fig. 2) with the user for each identified role and task, expanding it as appropriate to encompass the key facets of their role with regard to EI. Questions included the following: 1. What are the goals for your role? [Broken down into sub-goals and focussed specifically on EI use] 2. For each sub-goal e what decisions do you have to make? 3. For each decision e what information do you need? 4. For each piece of information e a. Where do you get that information from and does it always come from the same source? [which elements of EI are being used?] b. If the information comes from multiple systems or individuals, please detail these and the tempo of information provision c. What are the known problems with integrating information from multiple sources? d. How accurate/reliable/critical is your level of confidence in it: on a scale of 1e7? [Can you trust the information all the time?] e. What format is used to convey uncertainty, if any? f. What format do you currently get the information in (please provide pictoral examples if possible i.e. screen dumps)
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What would the ideal format be? How rapidly does the information change/update? What do you do with the information? Are there any known shortfalls with the information as it is currently provided or displayed? If so, what are they? k. Are there ever any conflicts or contradictions in the information provided? 5. For each decision e how do you implement it? [What happens once the decision is made? Is it input into the system in some way? Are other people involved? Is any data modified? For each question, answers were tied to the listed decisions and GDTA ‘tree’ format. The interviewer sought quick answers to each question with a view to getting broad coverage of the EI use in the user’s role. Where time allowed the interviewer returned to seek fuller information on these points at the end of the interview. The output from this section of the interview therefore comprised primarily of: - Interviewer: GDTA tree; information trust rating 1 (do not trust at all) to 7 (trust completely) for each information source; and brief notes - Scribe: more detailed notes on all aspects, as far as possible with cross-references to GDTA ‘tree’.
2.1.1.3. Section 3: user requirements for EI. The third section of the interview sought additional contextual information regarding use of EI. Questions included: 1. What elements of EI do you need and which do you use? If more than one element is detailed, please prioritise the importance of each. 2. How accessible are the elements that you require? a. How easy is it to access information (i.e. is the information cluttered or does it have an associated time delay?) b. How easy is it to assimilate information? c. How easy is it to input/change information? 3. What information do you need access to at the same time? a. Which pieces of information do you have to integrate together? b. How easy is it to integrate the information? 4. How could using EI be made easier for you? a. For each, how would these changes help? b. Are there any known drawbacks or problems with the current systems and current visualisations? (What would you like to have that you currently don’t have?) c. Is there anything that you have but don’t need?
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the outputs of the cognitive walkthroughs and interviews, when brought together, provided a substantial understanding of the user and stakeholder requirements. 2.2. Analysis The interviews and cognitive walkthroughs therefore provided a rich data source. The data gathered were used to identify requirements for EI dissemination, differences between user groups and important task components, the decision-making associated with different tasks, and the situation awareness requirements necessary to make effective decisions. Attention was focussed on those tasks that users anticipated to be of high frequency and high importance for the future warfighter. Output from the interviews was collated and organised into appropriate themes across all users. Data from the different user groups was compiled to develop an understanding of current goals, tasks and decisions and the anticipated warfighter role and the business process currently used. Anticipated changes to the allocation of tasks to specialists and warfighters were summarised. Issues associated with each difference in goal and in task allocation were identified as well as known issues with the current business process. An abundance of information sources was identified, so the available information sources were categorised and grouped according to their relevance to user tasks. User preferences regarding viewing technologies were analysed to. Visual examples of the current data presentation were used to build a fuller picture of the existing situation. Factors regarding the data usability were extracted. A list of key decisions across all users was identified and a functional system requirements list developed based on this, including both information and interface requirements. Functional system requirements included items such as; “need to know priority of information types” [information] and “the system should be able to combine the data available, even when in different formats” [interface]. Although categorised as interface requirements, many rely on accurate details of data collection and other aspects of metadata to be available in a consistent and usable manner and as such are closely intertwined with data requirements. These relationships were highlighted as part of the analysis. The Cognitive Walkthrough output was also analysed to enrich understanding of the tasks and, in particular, potential conflicts in requirements between users. Once data collation and analysis was complete, implications for designing usability into EI for the future warfighter were considered (see Section 3). 2.3. Summary of findings
2.1.1.4. Section 4: current viewing technology. Users were asked about current viewing technology. The main output from this section was a list of current technologies used and the user’s preferences regarding them. 2.1.2. Cognitive walkthroughs Cognitive walkthroughs were also conducted using two relevant case studies. These involved Human Factors (HF) experts simulating users of the system, and ‘walking through’ the interface to perform frequent, typical tasks, as well as rare critical ones (such as error recovery). The sequential nature of walkthroughs can often reveal problems that higher-level metrics such as heuristic analysis might miss. Given the scope of the EI interface, further investigations were recommended to include potential adverse effects of fatigue on system use by simulating a ‘working day’ of a system user. Thus
The goals of a non-specialist when exploiting EI were summarised as, “identifying the impact of EI related variables on operational decisions, as one input to the overall decision-making process”. The tasks identified as relevant to non-EI specialists were combinations of mapping and analysis. Their main components were terrain analysis and comparison against military force presence and characteristics. Examples included: identification of blue/red (friendly/enemy) available avenues of approach; visibility from way points and positioning of lookouts; key high ground and points of defence; and trafficability (or ‘goings’ analyses) for each of the available vehicle types.
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2.3.1. Business processes Fundamental base data products for EI adhere to different representation standards, specific to source providers or type. Geo staff use these products to develop mission-specific analysed mapping and recommendations. Their output informs operational command ‘customers’ and is typically accompanied by a verbal brief. The process is illustrated in a simplified form in Fig. 3. The goals of the ‘warfighter’ are therefore to assimilate the bespoke EI products, developed by Geo staff for a specific mission with other information in support of their strategic and tactical planning. The unfolding future systems and processes will provide nonspecialists with access to data earlier in the process, allowing them to perform simple analyses themselves that would previously have been conducted by Geo staff. This may result in a number of issues. Greater effort will be required from the warfighter to exploit EI as they will have to process the data themselves. This may well be in conflict with the priorities/pressures of their job role. Non-specialists may not understand how sources relate to one another, which sources are required for a task or how display constraints should be set. Non-specialist users may find it difficult to remain aware of changing information or time constraints. Enhanced data usability and presentation are therefore both critical to retaining a system that allows warfighters to incorporate EI into their planning decisions. 2.3.2. Contextual variations and information sources The wide range of information sources that interviewees referred to were compiled into a combined taxonomy, shown in Fig. 4. The variety of uses and data sources shows that users will need support to maintain awareness of the relevant and available information sources and their comparative priority. The next section describes how cognitive and HF principles we applied to EI for the warfighter and some resulting requirements for generating and presenting data in a useable manner. 3. Designing usability into EI The heterogeneity of the user group led to the conclusion that guidance for creating usable data would have greater long term use than an attempt to design a single interface. The visualisation problem was examined from a cognitive perspective to identify how novel techniques could be used to improve the presentation of complex imagery to non-expert users. Recommendations were made regarding the design approach, information management critical to EI and potentially geographic information displays, including: recency of information; uncertainty presentation; displacement and scale; colour; clutter; situational awareness (SA) and workload. 3.1. Information conflicts It was anticipated that the loss of verbal briefing would make it more important that the data are able to stand on their own: to be unambiguous. Careful technological design can play a part in
Specialist Users Raw environmental data
analysis
Non-specialist Users Environmental Information
analysis
Decision
Fig. 3. Flow of environmental information and decision making.
mitigating for this loss, for example by providing outputs that are standardised and have full metadata. Interviewees pointed out that information conflicts are frequent. Interviewees said expertise is required to understand why a conflict has occurred and to identify the source that is most likely to give an accurate representation. This is important as, for example, if two information sources portray an entity in different locations, they may be interpreted as showing two separate entities rather than as being conflicting information due to, for example, issues of displacement or scale. It was recommended that if users are to get the most from EI, the following need to be standard practice: capture metadata regarding scale at which data is captured; use the metadata to constrain presentation to the appropriate scale; alert the user to differences in scale between images; and produce products in a standardised format. It may also be necessary to add automated alerts to potential conflicts, warning users to seek specialist assistance from Geo staff. 3.2. Uncertainty Where information can be identified as ‘uncertain’, appropriate representations can be developed. For example, the warfighter should be intuitively aware if different information sources are more or less reliable due to how recently they were updated, but without the information supplied becoming overwhelming. Such factors can be built into accurate metadata that would permit automated interrogation and adjustment to the display of the data element depending on a number of factors relating to its certainty. Those data sources that are ‘certain’ should be clearly distinguishable from those that are ‘uncertain’ and should be coded accordingly. This is important to allow the user to interpret and draw appropriate conclusions from the data presented. QinetiQ has produced a guide to presentation of location, temporal and identity uncertainty (Christie et al., 2007). It includes advice on use on how and when to use different types of symbology, three of which are illustrated in Fig. 5. Each of the designs illustrated has strengths and weaknesses and is suited to one or more contexts of use; these are discussed in the presentation guide. It is important, however, to avoid over-use and reliance on colour as that is the distinguishing feature for so many other EI data. Moreover, the metadata will only be usable if it is coded in a consistent format and language. Hazard matrices are another very effective solution for representing uncertainty of multiple variables in a manner than can be assessed quickly and then investigated in more detail as required. Automated programmes could be designed to assist quick production. 3.3. Information management A common problem with EI is having too much information on the display (clutter), resulting in errors and frustration. The clutterrelated solutions that were discussed included: Allow user to compare images using an overlay (but do not separate the data) Allow user to group information into categories and to manipulate the display according to these (like layers) Highlight symbology conflicts to the user and allow them to manipulate codes used Provide a prioritisation function, based on subject matter expert knowledge, capable of determining how much
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Fig. 4. Consolidated categorisation of EI.
information is currently being displayed and temporarily ‘hiding’ the low priority information. The hidden information would be accessible quickly and easily. Introduction of a prioritisation function would require the coding to enable interpretation of data priority. It is highly likely that priority of data elements will vary according to the task at hand. As such, it will be necessary to work with subject matter experts to explore how relative priority can be determined and what metadata elements can be used to inform the priority model. Currently information is presented as layers, each layer forming a map overlay containing a different category of information, battlespace geometry for example. In the majority of cases the data itself is also stored as separate layers (rather than individual data items), minimising the potential for interaction and automation. The interviewees felt that layered presentation helps to decrease the clutter on the screen and makes clear what data is available. However, storing and processing of data in discrete category layers means that data presentation is also presented without context and precludes the opportunity for integrated presentation. Therefore, all inference of any interactivity or confliction between data sources is left to the operator. There is great potential for error here, particularly when data sources provide updates at different time intervals.
Layering can be beneficial as it allows the presentation of large amounts of complex data but to ensure layering is effective on complex data presentations, excellent structuring is required. Environmental information is intrinsically complex due to the need to convey vast amounts of data in a way that is easily understandable and interpretable. One such example is weather data in which a vast amount of information such as frontal systems, pressure systems and wind speed and direction are presented using symbology to enable the data to be presented in a compact manner. Furthermore, these data sources may be subject to uncertainty and require regularly updating, adding to the complexity of the data. Unfamiliarity with weather information, symbology and weather models would make interpretation extremely difficult for the nonspecialist user. Therefore, whilst the use of layering and symbology to create a more sparse information display may be beneficial for expert users, non-specialist users may require more detail to be presented to them to aid understanding. The sources of data required to complete a task may be very different, for instance, a task may require information on the location of cloud layers as well as information on the positioning of artillery. Consideration will need to be given to the best way to combine and present such disparate information sources in a way that is understandable. These underlying data issues can make the presentation of environmental information extremely complex. It is therefore necessary to work with subject matter experts to explore the complexities of the information that needs presenting and how structuring can support this. Categorisation of information in layers is consistent with the human tendency to chunk related information and will help users to understand what is available and, if layered appropriately, how the information sources relate to one another. If data are processed as one integrated set, the layering presentation has potential to become much more powerful: enhancing coherence and flexibility. As such, it was recommended that where possible, information should be presented as separable layers (each showing one category of information elements), as it is currently, but with the underlying data integrated and processed together. Further work is required to determine the optimal layering structure and how far non-technical users should be able to tailor the structure. 3.4. Colour
Fig. 5. Three types of uncertainty representation discussed in Christie et al. (2007).
Colour is often the only source of information that is used to distinguish one environmental entity or region from another.
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Effective use of colour increases operator performance, although it provides most benefit combined with another discriminator (e.g. shape) to add redundancy to a display (Ministry of Defence, 2008). However, there are two critical issues that challenge reliance on colour: many military situations exist where limited colour information is available, for instance, due to ambient lighting, glare or technological capability available; and when images are overlaid (stated as a requirement for EI interpretation) colour information is very likely to be lost or confused. A number of potential solutions were discussed. It is imperative that data is coded in such a way that it can be identified meaningfully so that it can be represented in an appropriate way for the purpose at hand. In presentation, a recommendation could be made to the environmental information providers to standardise the use of colour palettes and to review and minimise the reliance on colour coding for distinguishing one environmental region or feature from another. When overlaying one environmental product on top of another, the problem of one colour obscuring another could also be addressed by employing a dynamic overlay (see Section 4.2). Algorithms for identification and notification of colour conflicts were discussed with caution as the user could potentially be faced with many hundreds of colour conflicts being highlighted to him or her when two products are overlaid e an unmanageable and unhelpful situation. Data fusion was not considered due to the timescales of the study. In sum, a number of potential solutions were available to address the issues associated with colour use. Code data thoroughly to enable fit for purpose representation Minimise reliance on colour coding to distinguish one environmental region from another; where possible, use colour as a redundant code Use colour only to highlight very important aspects or support certain functionality Standardisation of colour palettes and/or allow the user to manipulate colour coding in their display Within reason, allow the system to alert to colour conflicts or hidden data Dynamic overlays
3.5. Situation awareness Careful consideration needs to be given to the concept of operator SA when developing an interface that will permit the display of, and interaction with, EI. In order to achieve this, a definition of SA is required. By far the most globally accepted definition of SA is the one proposed by Endsley: “The perception of the elements in the environment within a volume of time and space, the comprehension of their meaning and the projection of their status in the near future” (Endsley, 1988). Bearing in mind the vast amount of EI that will potentially be available to the warfighter, users will need to remain situationally aware of what is not currently being displayed. This issue might relate to layers of information that are currently switched off, or might pertain to important information updates or products that have only recently become available to the operator. For this reason, it was suggested that a combination of ‘dynamic icons’, video
windows and text boxes be employed, particularly for contexts where data updates may not all be made at once. 3.6. Mental workload Conflicting demands were identified as an issue in the interviews. This makes it particularly important that the mental demand placed on users by EI interpretation is appropriate. Task demands should be regulated so that they do not overload operators, or interfere with their decision-making ability. Ensuring that workload is not too low has become increasingly important in recent years, as increasing amounts of automation are designed into systems (Becker et al., 1991, cited in Rubio et al., 2004, p. 62). Moreover, extraneous workload is likely to be higher for non-specialists meaning that they will require greater support than Geo staff users. 3.7. Analysis techniques Differences between available EI processing systems were highlighted in the interviews. Users are likely to require support in identifying the implications of dealing with different software. One example raised was that of measurement, which is frequently used but unsuitable for urban environments in which sheers (rather than slopes) must be manually entered into the system. Given the time constraints on non-specialists, it is likely that the new business processes will result in increased use of standardised products and a decrease in tailoring context-specific visualisations. Therefore effort should be applied into ensuring that standards are developed that satisfy requirements in multiple contexts. It is likely that, to account for differences between specialist domains, a number of tailored standards may be required and users given the functionality to select the most appropriate for their task. 3.8. Allocation of category ranges Many tailored EI visualisations use colour to distinguish between regions of differing characteristics, for instance vegetation or soil type, ocean depth or ‘go/no go’ areas for a particular vehicle. Fig. 6 shows one product in which weather predictions have been portrayed using different colours for each of a number of temperature ranges. Interviewees stated that the allocation of category ranges requires understanding of both data integrity and the intended application. Non-specialists are likely to require support in defining the points of difference (category boundaries) when deriving these images and may not have the required expertise to define ranges appropriately in all circumstances. To achieve a usable dataset, assistance was recommended for derivation of category boundaries including expert verification and, in the longer term, context-based guides. 3.9. Summary Achieving usable data for this user group is a demanding remit. The user group is a large and heterogeneous subgroup of the military population; they will use overlapping but differing data sources to perform varied tasks. Use of metadata is likely to be central to progress, but will require attention to maintaining appropriate and consistent formatting, modelling, language and content so that it can be recorded and interpreted by multiple interface systems. Attention also needs to be paid to the underlying data issues such as the complexity of fusing large amounts of different types of data in a way that is understandable to the non-specialist user. The study focused on those issues that were identified as common across user groups to address aspects pertinent to EI data usability and inform a concept interface design, described in Section 4.
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2/Swipe (two layers available but presented one at a time, with a user control to move the boundary between the two, allowing a swipe effect moving the boundary of one layer of the other) Directly controlled by user Facilitates comparison of particular image areas Resolves colour conflicts 3/Flicker (presentation alternates between two layers, permitting the operator to see features on both. The timing of such flickering would be critical however if the visualisation were to be effective. Flickering between more than two products was not considered as part of the study) Facilitates comparison of overall images Likely to highlight differences between image sources Resolves clutter and colour conflicts: allows co-located information to be compared 4/Transparency (top overlay can be made to look semitransparent) Fig. 6. Weather map, discriminating regions of predicted temperature range differences by colour (provided by the Met Office, 2007).
4. Interface design The concept interface design drew together output from the knowledge elicitation activities and guidance on designing-in EI usability. A concept HMI was developed and discussed with users in a feedback workshop. A brief overview of the interface design work is included for completeness. 4.1. Concept interface design To demonstrate the design ideas and recommendations to the end users, we produced a mock-up of a potential EI interface for nonspecialist users. An existing information management interface was modified in accordance with the UCD approach (User-Centred Design e BS EN ISO 13407, 1999) and recommendations. The interface was chosen for its flexibility to be configured by the operator to meet their information needs, thereby maximising task performance. This technology can be scaled to offer information management solutions for system operators within any dynamic operating environment. This is relevant to GI systems that are likely to vary in size due to the large number of potential users and applications. The HMI provided an information management interface with dynamic icons that display element status without requiring a large area of the screen to be dedicated to that element. One of the main challenges was to reduce the complexity of overlaid images.
Facilitates comparison of image consistency and interaction of information Colour and location conflicts may still occur 5. Conclusions The military warfighter perspective provides useful guidance on the development of GI systems and a unique viewpoint on the problem area. Vast amounts of complex and varied information are required in challenging contexts and for multiple roles. A focus on EI may promote useful ideas and discussion on the scope and application of GI, as well as the importance of UCD in the future developments of GI systems. Building usability into data creation is critical to success. This includes metadata such as time, date, source, location, and scale; flexibility in symbology and colour of display; building in the ability to analyse and coordinate data ‘in the box’; tailoring detail in data coding so that information can be presented to users in a way that is relevant to their expertise and goals. Consideration must also be given to the underlying information issues. It will be important to consider the nature, complexity and quantity of information sources to enable a structure for how data is coded. Consideration will also have to be given to the mental model of the user and whether they have sufficient background knowledge to interpret the information. Consideration of both the points described on data presentation and any underlying data/ information issues will help to ensure that the resulting nonspecialist interaction with EI is improved.
4.2. Reducing complexity of overlaid images Acknowledgements Four dynamic overlays were discussed with stakeholders. These enable the user to alternate between products or layers. 1/Overlay functionality Aim for user control and ability to tailor display as appropriate to each task and context Optimal solution will be dependent on both user preference, context and task Fusion not considered due to anticipated timelines: likely to be of added benefit in future but is currently a very complex process
The authors would like to thank the UK Ministry of Defence who funded this work. References BS EN ISO 13407 1999. Human-centred design processes for interactive systems. BS EN ISO 9241 Part 210, 2010. Human centred design for interactive systems. Christie, M.J., Helman, S., Croft, D.G., Shaw, G.J. 2007. The impact of uncertainty symbology on decision making within NEC. Technical Report. QinetiQ/06/02483. Defence Standard 00-250 (2008) Defence Standard: Human Factors for Designers of Systems.
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Endsley, M.R., 1988. Situation awareness global assessment technique (SAGAT). In: Paper Presented at the National Aerospace and Electronic Conference (NAECON), Dayton, OH. Endsley, M.R., Bolté, B., Jones, D.G., 2003. Designing for Situation Awareness; an Approach to User-centred Design. Taylor & Francis, London. Milne, T.J., Macklin, C.M., Croft, D.G., 2001. The development of a large screen display demonstrator. A technical customer report for ARP 26F22eDERA/CHS/MID/TR010107/1.0. Ministry of Defence, 2008. Defence Standard 00-250 Issue 1 Human Factors for Designers of Systems Part 3: Technical Guidance.
Rubio, S., Díaz, E., Martín, J., Puente, J.M., 2004. Evaluation of subjective mental workload: a comparison of SWAT, NASA-TLX, and workload profile methods. Applied Psychology 53 (1), 61e86. Stanard, T., Wampler, J., Kendall, C., Osga. G., 2006. Hci Design Patterns for C2: A Vision for a DoD Design Reference Library. Report Produced by Wright Patterson AFB for the US Department of Defense. Document Number AFRL-WS 06-0107. Wharton, C., Rieman, J., Lewis, C., Polson, P., 1994. The cognitive walkthrough method: a practitioner’s guide. In: Nielsen, J., Mack, R.L. (Eds.), Usability Inspection Methods. John Wiley & Sons, New York, pp. 105e140.
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Applied Ergonomics journal homepage: www.elsevier.com/locate/apergo
Environmental information for military planning Victoria Doherty*, Darryl Croft, Ashley Knight QinetiQ, Cody Technology Park, Ively Road, Farnborough GU14 0LX, UK
a r t i c l e i n f o
a b s t r a c t
Article history: Received 19 April 2011 Accepted 29 November 2012
A study was conducted to consider the implications of presenting Environmental Information (EI; information on current environmental features including weather, topography and visibility maps) for military planning to the growing audience of non-technical users; to provide guidance for ensuring usability and for development of a suitable EI interface, and to produce an EI concept interface mock-up to demonstrate initial design ideas. Knowledge was elicited from current EI users and providers regarding anticipated use of EI by non-specialists. This was combined with human factors and cognition expertise to produce guidance for data usability and development of an EI interface. A simple mock-up of an EI concept interface was developed. Recommendations for further development were made including application of the guidance derived, identification of a user test-bed and development of business processes. Ó 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.
Keywords: Environmental Presentation Usability
1. Introduction 1.1. Background Environmental Information (EI) is the collective term for a heterogeneous collection of information and data sources concerning environmental features, character"istics and states. For example, it includes weather, climate, bathymetry, topography, visibility maps and others, many of which may also be termed Geographic Information (GI). Currently EI is a specialised information source, available in its raw form to only a handful of military personnel, predominantly specialist ‘Geo’ staff. Geo staff process the data, combining a large number of un-integrated sources, and present outputs that are tailored to the appropriate context to operational commanders to inform their planning decisions. However, this is changing: far wider user communities are being given access to EI, and decision makers themselves will be expected to interact with more data without modification by Geo staff. The format of data presented to Geo staff is complex, highly context-specific and requires a significant knowledge base before it can be used effectively. It is not suitable for non-specialist users with little time to spare to glean the critical information. Thus, the question that is central to this study emerges - how can EI be constructed and presented in a way that is intelligible and useful to
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non-specialist users without a constant requirement for assistance from Geo staff? At a broader level, the Human Machine Interface (HMI) has been identified as one of the most important facets of any system architecture (Stanard et al., 2006), and is an important determinant of mental workload, Situation Awareness (SA) and task success for system operators (Milne et al., 2001). Indeed, appropriate data that is well presented has the potential to improve task performance significantly through the optimisation of the useresystem interaction. This is particularly important for EI users who will be accessing a variety of information sources to make time-critical decisions that are key drivers of performance in a complex operational context. 1.2. Aim The aim of the study was to use human factors and cognition expertise, and a user-centred design approach to: consider techniques for presentation of EI; present guidance for ensuring EI data usability; and create a paper-based mock-up of an HMI solution concept. The underpinning drivers for this study were: improving user comprehension and situation awareness for environmental information; and optimising the interaction to enhance usability.
0003-6870/$ e see front matter Ó 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved. http://dx.doi.org/10.1016/j.apergo.2012.11.011
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1.3. Approach A user-centred design approach, illustrated in Fig. 1, was followed (BS EN ISO 13407, 1999, subsequently superseded by BS EN ISO 9241 Part 210, 2010), beginning with stakeholder and user interviews. These are described in Section 2, followed by relevant human factors and cognitive considerations on EI data usability and presentation in Section 3. In addition, paper-based mock-ups of interface solution concepts were developed and used as a basis for discussion at a stakeholder workshop. These are briefly outlined in Section 4. Section 5 presents the conclusions drawn from the study. 2. Knowledge elicitation 2.1. User and stakeholder interviews The user requirements capture activity targeted three themes: Who will the end users be and what expertise/skills will they have (or will they need in the future)? What are the users’ specific task requirements and what functionality/information is vital to permit task completion? How do the users work, what are the steps involved, and where do they need support? Information was gathered using a combination of cognitive walkthroughs (Wharton et al., 1994) and interviews. Interviews were conducted with three groups: those who are likely to be users of the system in the future; current expert users of EI in the military, and information providers. Subject matter experts fulfilling these criteria were identified with the project sponsors. One of the strongest drivers for EI data usability requirements is the extent of disparity between user groups and their loci of interest. The focus of this study was on non-specialist ‘warfighters’ who have an interest in making tactical planning decisions that exploit EI. Including technical information providers as interviewees enabled additional understanding of the current approaches to data collection and representation, available support for users, constraints on future changes, and providers’ interpretations of user requests. The interviews used Goal Directed Task Analysis (GDTA, see Fig. 2; Endsley et al., 2003) a semi-structured interview technique, identifying the user’s goals, tasks and information requirements with respect to EI. This tool results in a rich but structured dataset, well suited to this broad area. An interviewer and a scribe attended each interview. This meant that the interviewer could focus on
Fig. 1. The User-Centred Design Process as described in ISO 13407.
Fig. 2. Structure used in interviews for discussion of goals, decisions and information requirements.
following the visual structure of the GDTA with the user while the scribe took detailed notes cross-referencing the GDTA structure. 2.1.1. Interview protocol Users were asked questions in four sections: user profile; GDTA; user requirements for EI; and current viewing technologies used. Interviews lasted between 1 and 2 h. 2.1.1.1. Section 1: User profile. Users were asked to define their role, experience and the types of EI and associated equipment that they use. 2.1.1.2. Section 2: GDTA. For the GDTA, users were asked to describe their goals with respect to EI and the decisions that they make based on EI, leading to the information that is needed by the EI user. Discussion focussed on specific incidents from which EI related requirements could be extracted. A range of examples, including both normal and exception cases, was identified to provide an overview of the key issues and to permit some degree of generalisation. Where interviewees did or had previously done more than one role, time constraints, frequency and importance of use of EI in the role, and recency and frequency with which the role was conducted were used to guide the focus of the interview. They were also asked to consider the role of a non-specialist in the future concept of EI use and the implications in terms of where goals, tasks and decisions would differ from the current process. The interviewer worked through a diagrammatic GDTA (see Fig. 2) with the user for each identified role and task, expanding it as appropriate to encompass the key facets of their role with regard to EI. Questions included the following: 1. What are the goals for your role? [Broken down into sub-goals and focussed specifically on EI use] 2. For each sub-goal e what decisions do you have to make? 3. For each decision e what information do you need? 4. For each piece of information e a. Where do you get that information from and does it always come from the same source? [which elements of EI are being used?] b. If the information comes from multiple systems or individuals, please detail these and the tempo of information provision c. What are the known problems with integrating information from multiple sources? d. How accurate/reliable/critical is your level of confidence in it: on a scale of 1e7? [Can you trust the information all the time?] e. What format is used to convey uncertainty, if any? f. What format do you currently get the information in (please provide pictoral examples if possible i.e. screen dumps)
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What would the ideal format be? How rapidly does the information change/update? What do you do with the information? Are there any known shortfalls with the information as it is currently provided or displayed? If so, what are they? k. Are there ever any conflicts or contradictions in the information provided? 5. For each decision e how do you implement it? [What happens once the decision is made? Is it input into the system in some way? Are other people involved? Is any data modified? For each question, answers were tied to the listed decisions and GDTA ‘tree’ format. The interviewer sought quick answers to each question with a view to getting broad coverage of the EI use in the user’s role. Where time allowed the interviewer returned to seek fuller information on these points at the end of the interview. The output from this section of the interview therefore comprised primarily of: - Interviewer: GDTA tree; information trust rating 1 (do not trust at all) to 7 (trust completely) for each information source; and brief notes - Scribe: more detailed notes on all aspects, as far as possible with cross-references to GDTA ‘tree’.
2.1.1.3. Section 3: user requirements for EI. The third section of the interview sought additional contextual information regarding use of EI. Questions included: 1. What elements of EI do you need and which do you use? If more than one element is detailed, please prioritise the importance of each. 2. How accessible are the elements that you require? a. How easy is it to access information (i.e. is the information cluttered or does it have an associated time delay?) b. How easy is it to assimilate information? c. How easy is it to input/change information? 3. What information do you need access to at the same time? a. Which pieces of information do you have to integrate together? b. How easy is it to integrate the information? 4. How could using EI be made easier for you? a. For each, how would these changes help? b. Are there any known drawbacks or problems with the current systems and current visualisations? (What would you like to have that you currently don’t have?) c. Is there anything that you have but don’t need?
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the outputs of the cognitive walkthroughs and interviews, when brought together, provided a substantial understanding of the user and stakeholder requirements. 2.2. Analysis The interviews and cognitive walkthroughs therefore provided a rich data source. The data gathered were used to identify requirements for EI dissemination, differences between user groups and important task components, the decision-making associated with different tasks, and the situation awareness requirements necessary to make effective decisions. Attention was focussed on those tasks that users anticipated to be of high frequency and high importance for the future warfighter. Output from the interviews was collated and organised into appropriate themes across all users. Data from the different user groups was compiled to develop an understanding of current goals, tasks and decisions and the anticipated warfighter role and the business process currently used. Anticipated changes to the allocation of tasks to specialists and warfighters were summarised. Issues associated with each difference in goal and in task allocation were identified as well as known issues with the current business process. An abundance of information sources was identified, so the available information sources were categorised and grouped according to their relevance to user tasks. User preferences regarding viewing technologies were analysed to. Visual examples of the current data presentation were used to build a fuller picture of the existing situation. Factors regarding the data usability were extracted. A list of key decisions across all users was identified and a functional system requirements list developed based on this, including both information and interface requirements. Functional system requirements included items such as; “need to know priority of information types” [information] and “the system should be able to combine the data available, even when in different formats” [interface]. Although categorised as interface requirements, many rely on accurate details of data collection and other aspects of metadata to be available in a consistent and usable manner and as such are closely intertwined with data requirements. These relationships were highlighted as part of the analysis. The Cognitive Walkthrough output was also analysed to enrich understanding of the tasks and, in particular, potential conflicts in requirements between users. Once data collation and analysis was complete, implications for designing usability into EI for the future warfighter were considered (see Section 3). 2.3. Summary of findings
2.1.1.4. Section 4: current viewing technology. Users were asked about current viewing technology. The main output from this section was a list of current technologies used and the user’s preferences regarding them. 2.1.2. Cognitive walkthroughs Cognitive walkthroughs were also conducted using two relevant case studies. These involved Human Factors (HF) experts simulating users of the system, and ‘walking through’ the interface to perform frequent, typical tasks, as well as rare critical ones (such as error recovery). The sequential nature of walkthroughs can often reveal problems that higher-level metrics such as heuristic analysis might miss. Given the scope of the EI interface, further investigations were recommended to include potential adverse effects of fatigue on system use by simulating a ‘working day’ of a system user. Thus
The goals of a non-specialist when exploiting EI were summarised as, “identifying the impact of EI related variables on operational decisions, as one input to the overall decision-making process”. The tasks identified as relevant to non-EI specialists were combinations of mapping and analysis. Their main components were terrain analysis and comparison against military force presence and characteristics. Examples included: identification of blue/red (friendly/enemy) available avenues of approach; visibility from way points and positioning of lookouts; key high ground and points of defence; and trafficability (or ‘goings’ analyses) for each of the available vehicle types.
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2.3.1. Business processes Fundamental base data products for EI adhere to different representation standards, specific to source providers or type. Geo staff use these products to develop mission-specific analysed mapping and recommendations. Their output informs operational command ‘customers’ and is typically accompanied by a verbal brief. The process is illustrated in a simplified form in Fig. 3. The goals of the ‘warfighter’ are therefore to assimilate the bespoke EI products, developed by Geo staff for a specific mission with other information in support of their strategic and tactical planning. The unfolding future systems and processes will provide nonspecialists with access to data earlier in the process, allowing them to perform simple analyses themselves that would previously have been conducted by Geo staff. This may result in a number of issues. Greater effort will be required from the warfighter to exploit EI as they will have to process the data themselves. This may well be in conflict with the priorities/pressures of their job role. Non-specialists may not understand how sources relate to one another, which sources are required for a task or how display constraints should be set. Non-specialist users may find it difficult to remain aware of changing information or time constraints. Enhanced data usability and presentation are therefore both critical to retaining a system that allows warfighters to incorporate EI into their planning decisions. 2.3.2. Contextual variations and information sources The wide range of information sources that interviewees referred to were compiled into a combined taxonomy, shown in Fig. 4. The variety of uses and data sources shows that users will need support to maintain awareness of the relevant and available information sources and their comparative priority. The next section describes how cognitive and HF principles we applied to EI for the warfighter and some resulting requirements for generating and presenting data in a useable manner. 3. Designing usability into EI The heterogeneity of the user group led to the conclusion that guidance for creating usable data would have greater long term use than an attempt to design a single interface. The visualisation problem was examined from a cognitive perspective to identify how novel techniques could be used to improve the presentation of complex imagery to non-expert users. Recommendations were made regarding the design approach, information management critical to EI and potentially geographic information displays, including: recency of information; uncertainty presentation; displacement and scale; colour; clutter; situational awareness (SA) and workload. 3.1. Information conflicts It was anticipated that the loss of verbal briefing would make it more important that the data are able to stand on their own: to be unambiguous. Careful technological design can play a part in
Specialist Users Raw environmental data
analysis
Non-specialist Users Environmental Information
analysis
Decision
Fig. 3. Flow of environmental information and decision making.
mitigating for this loss, for example by providing outputs that are standardised and have full metadata. Interviewees pointed out that information conflicts are frequent. Interviewees said expertise is required to understand why a conflict has occurred and to identify the source that is most likely to give an accurate representation. This is important as, for example, if two information sources portray an entity in different locations, they may be interpreted as showing two separate entities rather than as being conflicting information due to, for example, issues of displacement or scale. It was recommended that if users are to get the most from EI, the following need to be standard practice: capture metadata regarding scale at which data is captured; use the metadata to constrain presentation to the appropriate scale; alert the user to differences in scale between images; and produce products in a standardised format. It may also be necessary to add automated alerts to potential conflicts, warning users to seek specialist assistance from Geo staff. 3.2. Uncertainty Where information can be identified as ‘uncertain’, appropriate representations can be developed. For example, the warfighter should be intuitively aware if different information sources are more or less reliable due to how recently they were updated, but without the information supplied becoming overwhelming. Such factors can be built into accurate metadata that would permit automated interrogation and adjustment to the display of the data element depending on a number of factors relating to its certainty. Those data sources that are ‘certain’ should be clearly distinguishable from those that are ‘uncertain’ and should be coded accordingly. This is important to allow the user to interpret and draw appropriate conclusions from the data presented. QinetiQ has produced a guide to presentation of location, temporal and identity uncertainty (Christie et al., 2007). It includes advice on use on how and when to use different types of symbology, three of which are illustrated in Fig. 5. Each of the designs illustrated has strengths and weaknesses and is suited to one or more contexts of use; these are discussed in the presentation guide. It is important, however, to avoid over-use and reliance on colour as that is the distinguishing feature for so many other EI data. Moreover, the metadata will only be usable if it is coded in a consistent format and language. Hazard matrices are another very effective solution for representing uncertainty of multiple variables in a manner than can be assessed quickly and then investigated in more detail as required. Automated programmes could be designed to assist quick production. 3.3. Information management A common problem with EI is having too much information on the display (clutter), resulting in errors and frustration. The clutterrelated solutions that were discussed included: Allow user to compare images using an overlay (but do not separate the data) Allow user to group information into categories and to manipulate the display according to these (like layers) Highlight symbology conflicts to the user and allow them to manipulate codes used Provide a prioritisation function, based on subject matter expert knowledge, capable of determining how much
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Fig. 4. Consolidated categorisation of EI.
information is currently being displayed and temporarily ‘hiding’ the low priority information. The hidden information would be accessible quickly and easily. Introduction of a prioritisation function would require the coding to enable interpretation of data priority. It is highly likely that priority of data elements will vary according to the task at hand. As such, it will be necessary to work with subject matter experts to explore how relative priority can be determined and what metadata elements can be used to inform the priority model. Currently information is presented as layers, each layer forming a map overlay containing a different category of information, battlespace geometry for example. In the majority of cases the data itself is also stored as separate layers (rather than individual data items), minimising the potential for interaction and automation. The interviewees felt that layered presentation helps to decrease the clutter on the screen and makes clear what data is available. However, storing and processing of data in discrete category layers means that data presentation is also presented without context and precludes the opportunity for integrated presentation. Therefore, all inference of any interactivity or confliction between data sources is left to the operator. There is great potential for error here, particularly when data sources provide updates at different time intervals.
Layering can be beneficial as it allows the presentation of large amounts of complex data but to ensure layering is effective on complex data presentations, excellent structuring is required. Environmental information is intrinsically complex due to the need to convey vast amounts of data in a way that is easily understandable and interpretable. One such example is weather data in which a vast amount of information such as frontal systems, pressure systems and wind speed and direction are presented using symbology to enable the data to be presented in a compact manner. Furthermore, these data sources may be subject to uncertainty and require regularly updating, adding to the complexity of the data. Unfamiliarity with weather information, symbology and weather models would make interpretation extremely difficult for the nonspecialist user. Therefore, whilst the use of layering and symbology to create a more sparse information display may be beneficial for expert users, non-specialist users may require more detail to be presented to them to aid understanding. The sources of data required to complete a task may be very different, for instance, a task may require information on the location of cloud layers as well as information on the positioning of artillery. Consideration will need to be given to the best way to combine and present such disparate information sources in a way that is understandable. These underlying data issues can make the presentation of environmental information extremely complex. It is therefore necessary to work with subject matter experts to explore the complexities of the information that needs presenting and how structuring can support this. Categorisation of information in layers is consistent with the human tendency to chunk related information and will help users to understand what is available and, if layered appropriately, how the information sources relate to one another. If data are processed as one integrated set, the layering presentation has potential to become much more powerful: enhancing coherence and flexibility. As such, it was recommended that where possible, information should be presented as separable layers (each showing one category of information elements), as it is currently, but with the underlying data integrated and processed together. Further work is required to determine the optimal layering structure and how far non-technical users should be able to tailor the structure. 3.4. Colour
Fig. 5. Three types of uncertainty representation discussed in Christie et al. (2007).
Colour is often the only source of information that is used to distinguish one environmental entity or region from another.
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Effective use of colour increases operator performance, although it provides most benefit combined with another discriminator (e.g. shape) to add redundancy to a display (Ministry of Defence, 2008). However, there are two critical issues that challenge reliance on colour: many military situations exist where limited colour information is available, for instance, due to ambient lighting, glare or technological capability available; and when images are overlaid (stated as a requirement for EI interpretation) colour information is very likely to be lost or confused. A number of potential solutions were discussed. It is imperative that data is coded in such a way that it can be identified meaningfully so that it can be represented in an appropriate way for the purpose at hand. In presentation, a recommendation could be made to the environmental information providers to standardise the use of colour palettes and to review and minimise the reliance on colour coding for distinguishing one environmental region or feature from another. When overlaying one environmental product on top of another, the problem of one colour obscuring another could also be addressed by employing a dynamic overlay (see Section 4.2). Algorithms for identification and notification of colour conflicts were discussed with caution as the user could potentially be faced with many hundreds of colour conflicts being highlighted to him or her when two products are overlaid e an unmanageable and unhelpful situation. Data fusion was not considered due to the timescales of the study. In sum, a number of potential solutions were available to address the issues associated with colour use. Code data thoroughly to enable fit for purpose representation Minimise reliance on colour coding to distinguish one environmental region from another; where possible, use colour as a redundant code Use colour only to highlight very important aspects or support certain functionality Standardisation of colour palettes and/or allow the user to manipulate colour coding in their display Within reason, allow the system to alert to colour conflicts or hidden data Dynamic overlays
3.5. Situation awareness Careful consideration needs to be given to the concept of operator SA when developing an interface that will permit the display of, and interaction with, EI. In order to achieve this, a definition of SA is required. By far the most globally accepted definition of SA is the one proposed by Endsley: “The perception of the elements in the environment within a volume of time and space, the comprehension of their meaning and the projection of their status in the near future” (Endsley, 1988). Bearing in mind the vast amount of EI that will potentially be available to the warfighter, users will need to remain situationally aware of what is not currently being displayed. This issue might relate to layers of information that are currently switched off, or might pertain to important information updates or products that have only recently become available to the operator. For this reason, it was suggested that a combination of ‘dynamic icons’, video
windows and text boxes be employed, particularly for contexts where data updates may not all be made at once. 3.6. Mental workload Conflicting demands were identified as an issue in the interviews. This makes it particularly important that the mental demand placed on users by EI interpretation is appropriate. Task demands should be regulated so that they do not overload operators, or interfere with their decision-making ability. Ensuring that workload is not too low has become increasingly important in recent years, as increasing amounts of automation are designed into systems (Becker et al., 1991, cited in Rubio et al., 2004, p. 62). Moreover, extraneous workload is likely to be higher for non-specialists meaning that they will require greater support than Geo staff users. 3.7. Analysis techniques Differences between available EI processing systems were highlighted in the interviews. Users are likely to require support in identifying the implications of dealing with different software. One example raised was that of measurement, which is frequently used but unsuitable for urban environments in which sheers (rather than slopes) must be manually entered into the system. Given the time constraints on non-specialists, it is likely that the new business processes will result in increased use of standardised products and a decrease in tailoring context-specific visualisations. Therefore effort should be applied into ensuring that standards are developed that satisfy requirements in multiple contexts. It is likely that, to account for differences between specialist domains, a number of tailored standards may be required and users given the functionality to select the most appropriate for their task. 3.8. Allocation of category ranges Many tailored EI visualisations use colour to distinguish between regions of differing characteristics, for instance vegetation or soil type, ocean depth or ‘go/no go’ areas for a particular vehicle. Fig. 6 shows one product in which weather predictions have been portrayed using different colours for each of a number of temperature ranges. Interviewees stated that the allocation of category ranges requires understanding of both data integrity and the intended application. Non-specialists are likely to require support in defining the points of difference (category boundaries) when deriving these images and may not have the required expertise to define ranges appropriately in all circumstances. To achieve a usable dataset, assistance was recommended for derivation of category boundaries including expert verification and, in the longer term, context-based guides. 3.9. Summary Achieving usable data for this user group is a demanding remit. The user group is a large and heterogeneous subgroup of the military population; they will use overlapping but differing data sources to perform varied tasks. Use of metadata is likely to be central to progress, but will require attention to maintaining appropriate and consistent formatting, modelling, language and content so that it can be recorded and interpreted by multiple interface systems. Attention also needs to be paid to the underlying data issues such as the complexity of fusing large amounts of different types of data in a way that is understandable to the non-specialist user. The study focused on those issues that were identified as common across user groups to address aspects pertinent to EI data usability and inform a concept interface design, described in Section 4.
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2/Swipe (two layers available but presented one at a time, with a user control to move the boundary between the two, allowing a swipe effect moving the boundary of one layer of the other) Directly controlled by user Facilitates comparison of particular image areas Resolves colour conflicts 3/Flicker (presentation alternates between two layers, permitting the operator to see features on both. The timing of such flickering would be critical however if the visualisation were to be effective. Flickering between more than two products was not considered as part of the study) Facilitates comparison of overall images Likely to highlight differences between image sources Resolves clutter and colour conflicts: allows co-located information to be compared 4/Transparency (top overlay can be made to look semitransparent) Fig. 6. Weather map, discriminating regions of predicted temperature range differences by colour (provided by the Met Office, 2007).
4. Interface design The concept interface design drew together output from the knowledge elicitation activities and guidance on designing-in EI usability. A concept HMI was developed and discussed with users in a feedback workshop. A brief overview of the interface design work is included for completeness. 4.1. Concept interface design To demonstrate the design ideas and recommendations to the end users, we produced a mock-up of a potential EI interface for nonspecialist users. An existing information management interface was modified in accordance with the UCD approach (User-Centred Design e BS EN ISO 13407, 1999) and recommendations. The interface was chosen for its flexibility to be configured by the operator to meet their information needs, thereby maximising task performance. This technology can be scaled to offer information management solutions for system operators within any dynamic operating environment. This is relevant to GI systems that are likely to vary in size due to the large number of potential users and applications. The HMI provided an information management interface with dynamic icons that display element status without requiring a large area of the screen to be dedicated to that element. One of the main challenges was to reduce the complexity of overlaid images.
Facilitates comparison of image consistency and interaction of information Colour and location conflicts may still occur 5. Conclusions The military warfighter perspective provides useful guidance on the development of GI systems and a unique viewpoint on the problem area. Vast amounts of complex and varied information are required in challenging contexts and for multiple roles. A focus on EI may promote useful ideas and discussion on the scope and application of GI, as well as the importance of UCD in the future developments of GI systems. Building usability into data creation is critical to success. This includes metadata such as time, date, source, location, and scale; flexibility in symbology and colour of display; building in the ability to analyse and coordinate data ‘in the box’; tailoring detail in data coding so that information can be presented to users in a way that is relevant to their expertise and goals. Consideration must also be given to the underlying information issues. It will be important to consider the nature, complexity and quantity of information sources to enable a structure for how data is coded. Consideration will also have to be given to the mental model of the user and whether they have sufficient background knowledge to interpret the information. Consideration of both the points described on data presentation and any underlying data/ information issues will help to ensure that the resulting nonspecialist interaction with EI is improved.
4.2. Reducing complexity of overlaid images Acknowledgements Four dynamic overlays were discussed with stakeholders. These enable the user to alternate between products or layers. 1/Overlay functionality Aim for user control and ability to tailor display as appropriate to each task and context Optimal solution will be dependent on both user preference, context and task Fusion not considered due to anticipated timelines: likely to be of added benefit in future but is currently a very complex process
The authors would like to thank the UK Ministry of Defence who funded this work. References BS EN ISO 13407 1999. Human-centred design processes for interactive systems. BS EN ISO 9241 Part 210, 2010. Human centred design for interactive systems. Christie, M.J., Helman, S., Croft, D.G., Shaw, G.J. 2007. The impact of uncertainty symbology on decision making within NEC. Technical Report. QinetiQ/06/02483. Defence Standard 00-250 (2008) Defence Standard: Human Factors for Designers of Systems.
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Endsley, M.R., 1988. Situation awareness global assessment technique (SAGAT). In: Paper Presented at the National Aerospace and Electronic Conference (NAECON), Dayton, OH. Endsley, M.R., Bolté, B., Jones, D.G., 2003. Designing for Situation Awareness; an Approach to User-centred Design. Taylor & Francis, London. Milne, T.J., Macklin, C.M., Croft, D.G., 2001. The development of a large screen display demonstrator. A technical customer report for ARP 26F22eDERA/CHS/MID/TR010107/1.0. Ministry of Defence, 2008. Defence Standard 00-250 Issue 1 Human Factors for Designers of Systems Part 3: Technical Guidance.
Rubio, S., Díaz, E., Martín, J., Puente, J.M., 2004. Evaluation of subjective mental workload: a comparison of SWAT, NASA-TLX, and workload profile methods. Applied Psychology 53 (1), 61e86. Stanard, T., Wampler, J., Kendall, C., Osga. G., 2006. Hci Design Patterns for C2: A Vision for a DoD Design Reference Library. Report Produced by Wright Patterson AFB for the US Department of Defense. Document Number AFRL-WS 06-0107. Wharton, C., Rieman, J., Lewis, C., Polson, P., 1994. The cognitive walkthrough method: a practitioner’s guide. In: Nielsen, J., Mack, R.L. (Eds.), Usability Inspection Methods. John Wiley & Sons, New York, pp. 105e140.