How accurate does geographic information (GI) need to be, when compared to the real world, to gain user trust? To better understand the user experience, do we need to consider data structures, formats and user manuals as types of user interface? What caused KML to become a de facto standard, overtaking GML, which is seemingly well engineered? These questions concern the usability of GI. While the GIS industry is starting to be aware of the importance of usability in software and hardware product development, so, too, are some providers of GI. There is, however a lack of research and methodologies designed for understanding usability of information itself rather than the interface or system through which it is presented. This is both a huge oversight and opportunity, when considering that information can sometimes cost 95% of the total project value, or that in many products the information itself is critical to the user’s experience – for example, in personal navigation devices (PND). The level of usability of GI combined with system usability can also impact on productivity as significant time and resources may be spent on their management. In some situations it can even have safety critical implication – as in the case of a satnav user who followed directions on to a rail track minutes before a train crashed into her car (BBC®, 2008). This paper is based on a report from a workshop that was organised by Ordnance Survey to discuss the usability of GI. It was a first opportunity for researchers from diverse backgrounds, including cartography, GI science, human factors, ergonomics and human-computer interaction to come together and discuss this important issue. The outcomes of the workshop, though preliminary, are relevant to any user of GI – and the issues identified might change the way people in the industry think about and evaluate GI products alongside applications.

1. Usable geographic information – what does it mean to users?
Jenny Harding, Ordnance Survey®, Sarah Sharples, University of Nottingham, Muki
Haklay, UCL®, Gary Burnett, University of Nottingham, Yasamin Dadashi, Network Rail,
David Forrest, University of Glasgow®, Martin Maguire, Loughborough University,
Christopher J. Parker, Loughborough University, Liz Ratcliffe, Ordnance Survey
Abstract
How accurate does geographic information (GI) need to be, when compared to the real world, to gain user
trust? To better understand the user experience, do we need to consider data structures, formats and user
manuals as types of user interface? What caused KML to become a de facto standard, overtaking GML, which
is seemingly well engineered?
These questions concern the usability of GI. While the GIS industry is starting to be aware of the importance
of usability in software and hardware product development, so, too, are some providers of GI. There is,
however a lack of research and methodologies designed for understanding usability of information itself
rather than the interface or system through which it is presented. This is both a huge oversight and
opportunity, when considering that information can sometimes cost 95% of the total project value, or that in
many products the information itself is critical to the user’s experience – for example, in personal navigation
devices (PND). The level of usability of GI combined with system usability can also impact on productivity as
significant time and resources may be spent on their management. In some situations it can even have
safety critical implication – as in the case of a satnav user who followed directions on to a rail track minutes
before a train crashed into her car (BBC®, 2008).
This paper is based on a report from a workshop that was organised by Ordnance Survey to discuss the
usability of GI. It was a first opportunity for researchers from diverse backgrounds, including cartography, GI
science, human factors, ergonomics and human-computer interaction to come together and discuss this
important issue. The outcomes of the workshop, though preliminary, are relevant to any user of GI – and the
issues identified might change the way people in the industry think about and evaluate GI products alongside
applications.
Introduction
Usability of GI is very much part of ‘Realising the value of place’, as difficulties with using information
sources will be weighed by users against value. This is not straightforward, however, as the user experience
is partly dependent on how the data or information is accessed – a function of other factors, including
hardware and application interfaces. For many users, the usability of the information itself is something to
which they may pay little attention. It’s a dynamic situation, too, with existing data products being used in
ever-diverse applications and new products developing to meet existing and emerging needs.
As defined by international standard (ISO 9241-11), ‘usability’ refers to the ‘extent to which a product can be
used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified
context of use’.
While much current research and established methodologies in the field of product usability focus on tangible
products, such as devices, and on computer interfaces, there is comparatively little focus on usability of
information and data products such as digital GI.
This paper considers the increasing diversity in contexts of use for GI, and highlights some key challenges
and requirements for evaluating usability of GI. It is based on outcomes from a workshop organised by
Ordnance Survey (March 2009) to discuss challenges for investigating usability of GI. Bringing together
researchers from diverse backgrounds, including cartography, GI science, human factors, ergonomics and
human-computer interaction, the workshop aimed to address the question of whether and how usability of
information can be evaluated, and is it possible to decouple information from the interface used to access it?
Though preliminary, these outcomes are relevant to users and producers of GI – and the issues identified
might change the way people in the industry think about and evaluate GI products alongside applications.

2. GI products – a special case for evaluating usability?
Demands for GI
In recent years the GI marketplace has seen rapid development, expanding and diversifying from use of
paper mapping products through use of digital mapping data files to current use of spatial information
databases and web-based applications. Developments in technologies alongside global forces for change
have led to changes in the customer base and demands for GI products. Issues such as increasing pressures
on national infrastructures, resources and the environment on the one hand, and accessible technologies
(such as GPS and the Internet) on the other, have all influenced demand for types of data and ways in which
customers wish to access and use data.
GI has become more a part of the mainstream information economy, with levels of information easily
accessible to all for both viewing and contributing information to, for example, through web-based map sites
such as Windows Live® Local and Google® Maps. Ongoing trends in GI include extending data models from
2 dimensions to 3 (incorporating height), 4 (including the temporal dimension) and beyond to include ‘virtual
worlds’. These offer enhanced ability to detect and represent changes associated with events, processes and
flows.
At the same time, developments towards the automated generation of GI products from core databases
means that it is ever more important to focus on usability of data content as well as on the ‘products’ and
services built around that content.
The user experience
The total user experience of products and services is very important to GI providers. An important part of
this is the usability of geographic data and information products themselves. However, the user’s experience
of how usable these products are is often dependent not only on the data or information itself but also on
how it is accessed – a function of other factors, including hardware and application interfaces.
In the case of printed map products, the hardware (printed material), interface (the way the information is
presented) and content are, generally, designed together and the user experiences these components as a
whole. With digital products, however, the hardware, application interface and data or information (often
from multiple sources) are each separate products, usually from different suppliers, and put together in the
user’s context of use. Each of these components contributes to the overall user experience.
Because of this, the correct source of a usability issue is not always immediately apparent. For instance, user
needs and product usability research to date within Ordnance Survey have drawn on a number of techniques,
including task focused interviews with users, expert review and user diaries. While each approach produced
useful results, further analysis is sometimes required to separate out data issues from interface or
application issues.
How then can we best evaluate the usability of data or information as distinct from application and systems
interfaces? We suggest that tackling this question benefits from an interdisciplinary approach and
complements other initiatives focusing on GI usability within the GI science community. These include the
ICA’s Commission on Use and User Issues, an international group for sharing and developing knowledge on
this area in GI science. A current initiative is to develop a research reference book focusing on methods
available and how they may be applied. On a related note with a focus on GIS, Muki Haklay (UCL) is
developing an introductory book on HCI and GIS, details of which are at http://hciandgis.wetpaint.com/
Evaluating usability in an environment of increasingly diverse technology, uses and
user populations
User requirements and evaluation challenges
Current human factors research is addressing a number of challenges associated with novel interactive
technologies. User-system interaction is taking place in an increasingly diverse user population (with ranges
of age, experience and background) with increasing system functionality, integration of multiple applications
on single devices (as seen with the iPhone® apps, for example), increasing data complexity, database size
and integration of information, smaller, more portable or mobile devices and systems being used in more
diverse environments and tasks. Increased collaborative working, with shared interactions and remote

3. working add further dimensions to user-system interaction. It is necessary to understand the relationship
between these human factors challenges and the design and specification of underlying data in the context of
GI usability.
Human factors methods for user requirements specification and evaluation are routinely applied to interfaces,
but are less easily transferred to data. Users are inevitably much more aware of the interface itself than the
underlying systems. Indeed, it can be the role of the interface designer to ‘protect’ the user from underlying
complexity of a system. This is often seen in mobile device design, for example, where a user may be
unaware when they are interacting with an application or menu that is located on or managed by their device
and when they are interacting with an application provided by a service provider. The view of the user is
therefore influenced by the way in which the data is presented to them, rather than the qualities of the data
itself.
Therefore there is a need for interface independent methods of specifying user requirements and evaluating
GI. However, we need to acknowledge that data will be viewed or used via a mediating device of some sort.
Challenges for user requirements specification include:
What technology will the user be employing to view and interact with data (screen size, processing
capability etc).
What level of experience or knowledge does the user have (How well does the user understand the
interface? How well does the user understand the data, its implications and capabilities?)
How can the user be supported in articulating novel needs or design ideas?
In addition, many traditional evaluation methods focus on interaction with the interface rather than data. For
example, observation will provide information about a user’s key presses, mouse clicks or eye movements,
but methods that address the cognitive aspects of decision making and processing, such as verbal protocol or
critical decision techniques, are needed if we wish to understand how the data is used or understood. There
is also a need for us to be able to predict the requirements and user response to future systems, using
formative evaluation, rather than relying on summative techniques. This may require the combination of
qualitative and quantitative data evaluation techniques, and embedding such evaluation within product
development teams in organisations. We know that data is increasing in volume and complexity, so the need
to clearly identify data requirements for specific tasks and contexts is critical if systems are going to be
efficient, both from a processing (time taken to retrieve required information) and user (e.g. number of
menus or options being navigated) perspective. The issue of trust is also pivotal: if data is perceived as being
unreliable then users will not use it to its maximum potential; we need to understand how the interface and
data itself influences the perception of data reliability and the resultant behaviour of the user.
Usability issues and the link to user diversity
To understand user requirements that were highlighted in the previous section, it can be valuable to identify
‘types’ of users. From the point of view of usability of GI, users may be grouped into broad types: system
administrator, developer, expert or ‘power’ user, domain expert and general user. Each has a different role,
level of expertise and frequency of use with respect to GI, which together influence their experience of GI
usability. Taking each of these in turn, key characteristics and example usability issues may be summarised
as follows:
System administrator: Largely concerned with importing and managing GI, providing access to information
for a wide range of users and applications. The usability of, for example, change only update will suit some
system administrators and not others, depending on how they manage their data holdings. Understanding
their daily needs can explain the take up of change only update data provision
Developer: Uses GI within an application and is concerned with fitness for purpose, data structure,
performance and so on. Developers are not always aware that around 95% of GIS investment is in the data.
Though many different GI formats have been developed over the years, those that are in most use tend to
be formats that are easy to learn rather than those that were engineered with the intention of optimising
them for use. For example we can see that despite its limitations, the ESRI® shapefile format is successful
and effective as a de facto format, and more so than OGC® agreed file formats.
Power user: Familiar with GIS operations and integrates GI for specific tasks, though may not be so familiar
with semantics of the datasets used. The user may confuse data content and the visualisation/interface,
often not seeing the difference between the two. Metadata is very important for finding and using the right

4. data, yet, because of the complexity of metadata formats, many (most?) datasets are not well annotated.
This suggests an underlying problem for the management and annotation of GI datasets.
Specialist domain user: Has specialist knowledge in their own domain, but is not a specialist in GIS or
cartography. GIS and GI datasets are used as a tool for their own task-related purposes. For these users
both the data and the software are black boxes, but they are capable of evaluating the data in light of their
domain knowledge.
General user: GI is used as part of another task, such as navigation to a location. The user tends to regard
the information as factual and up to date. For example, there are instances of in car navigation system users
following system directions without using their own judgment.
Given the above, the following key points and questions need to be considered in terms of user diversity
when investigating usability of GI:
Which users/personas do we need to understand for the particular product?
How are existing products and formats used, by whom and for what purposes? Research can be
formulated around case study analyses.
What has changed and why over the history of digital GI use, when comparing producer selected
formats to user selected formats?
Think of data formats, user manuals and metadata as part of the user interface.
Examples of usability priorities in relation to contrasting user contexts
Outlined below are three studies that illustrate some of the ways in which user context is key to
understanding what usability means to the user.
Spatial information on hand-held computers for railway track workers
Applied human factors research identified spatial information and local knowledge as the most important
items of information for railway track workers (Dadashi et al 2008, 2009). Advances in mobile computing and
LBS (location-based services) offer great potential for providing easy-to-use and accessible spatial
information to workers on the trackside. While the lack of access to relevant information causes difficulty,
presentation of spatial information on hand-held devices needs to address a number of challenges in order to
be effective in the task context, where safety is of paramount importance. These include: the scaling issue -
how much of the real world can you present on a hand-held computer screen? What information is a priority
to present and how? What does the user need to interact with and how? Is it best to present people with
information that they are used to or that which would be better for the task?
A set of experiments, which attempted to answer these questions, were designed and conducted. Results
identified the importance of the types of information to be accessible (including trust in that information), the
intuitiveness of the interaction, the structure of information as being as important as the amount of
information, the match between the information and the workers’ tasks (Dadashi et al, 2008; Dadashi et al,
2009).
Differences in public and professional needs for information from climate change satellite data
The European climate change project, EuroClim (www.euroclim.net), aimed to provide a climate change
modelling and monitoring portal for public users (including educators, teachers, science writers) and
professional users (including scientists, policymakers, NGOs). Information accessed from the portal ranges
from indicators (such as rainfall, temperature, snow cover measures) through ‘processed indicators’ (that is
with some analysis, such as mean temperature) to ‘products’ (such as maps of growing season length or
effects of snow change on skiing).
Evaluation of the information provided on the portal identified potential usability issues for improvement. For
professional users these included resolution of the data, frequency of update, inconsistency with other
datasets and the need for more flexible georeferencing. The importance of specific metadata was highlighted
in order to understand the background to the data. For the public users, terminology and definitions used
were not necessarily meaningful. This user group requires more support and explanation to help their
understanding of information and data provided, as there is perhaps more of a tendency to believe
information as seen without questioning it. While these users are less concerned about the details of the
data, this may lead to misunderstanding. Climate-change data also needs to be ‘brought to life’ in some way

5. that they can control and interact with if policymakers and the public are to appreciate it and for it to feed
usefully into policymaking.
Volunteered or user-generated GI – usability benefits and issues
Volunteered geographic information (VGI) may be defined as ‘The act of creating geographic information by
largely untrained volunteers’ (Goodchild 2007). It has also been called ‘crowdsourcing’, or peer-produced GI.
A number of easily accessible technologies facilitate collection and access to user generated content,
including mapping websites, availability of base mapping online, GPS capture devices (including phones with
GPS receivers) and content sites such as Flickr® and YouTube®. An example output is OpenStreetMap™:
free mapping produced in WIKI style using open source software and user-generated content. The data
structure is simple, and suitable interfaces are available for each type of user. This simplicity makes the
dataset attractive to many users.
Map mash-ups may be seen as key vehicles for VGI and are a concept whereby people can share information
(for example, experiences, photos) by way of associating their own information to a shared map base. An
example of how VGI can impact our lives includes providing map-based information in areas hit by disaster
(for example, map mash-ups were produced of notices about lost people following Hurricane Katrina)
VGI is an exciting research field as it has vast future potential applications in society and potential to add
value to map information. However, it raises interesting questions such as how can the quality of VGI be
trusted if no one is responsible for it. As yet this is a little researched area. Key research questions include:
Who are the stakeholders in VGI applications, and what are their relationships to each other?
What are the different perspectives on value for VGI users, contributors and developers, and how do
these relate to their choice of map?
What ‘ecological’ differences are present between VGI stakeholders (that is differences due to
external factors which surround the individual), and how does this influence their understanding of
value?
GI usability linked to system usability
Producing base map information for thematic maps
Mapping systems are capable of producing good maps but offer little or no assistance to the user to produce
good cartographic design. While decision makers use digital map data and GIS for their own task-related
purposes and have specialist knowledge of their topic, they may have little knowledge of cartography and
map design, as this is not their primary task. For these users (described as ‘specialist domain users’ earlier in
this paper) the base mapping data may not be of interest in its own right, but forms a necessary contextual
backdrop to the user’s own data.
A key question is, what topographic base information is needed to underpin the user’s data – and this
depends on purpose of use. This is a neglected part of map design, but some topographic information may
be necessary in order to understand the particular user’s specialist information. Certain topographic
information can act as locational referents (or landmarks) while other information may be irrelevant and add
clutter.
Selection of base information depends on several factors, including map topic, scale, purpose of use and user
experience levels, together with the probability of including different types of base information in accordance
with the topic of the map. Previous work has sought to help the user by means of developing a knowledge
base to structure the selection of relevant base mapping information (Forrest, 1999). Data is organised
hierarchically to suit different levels of requirement, depending on purpose and scale. Components are called
from a database based on the user defining a number of parameters. Success relies in part on the data
model of source data incorporating well-structured/classified data.
In testing the approach using Ordnance Survey Strategi® data (at 1:250 000 scale), database issues
included the large number of feature classes. A four-level hierarchical organisation (from layer/theme to sub-
sub-feature class) was created from this to facilitate data selection. The knowledge base mapped this
hierarchy across identified core map topics (for example, topographic, political, communication) and defined
levels of detail. Together these components can be used to generate base maps relevant to topic, level of
detail and scale.

6. The approach is responsive to user requirements and could make mapping software easier to use and help
reduce the production of poor map outputs (as yet expert systems mechanisms are not implemented in GIS).
Creation of a knowledge base does require precise information on how features are classified in a source
database (including rules for how the classification is applied), which often is not sufficiently clear in user
guides. Also it is important to understand how the classification of features in one dataset relates to that in
another (for example, relationship between Meridian™ 2 and Strategi classifications). To make data more
useable, better structures for some features are needed together with better published information about
content. Developments in ontologies, where the meaning of a classification system is made explicit, and
automated generalisation, to assist the structuring and simplification of information, may help in both these
areas.
Digital GI and vehicle applications
Digital GI is among the technologies that will enable new design elements of future vehicles and their
applications. Vehicle applications can be served by digital mapping in a number of ways. As noted by Burnett
(2009) some applications specifically target areas such as safety and efficiency by either providing
information or services relevant to the driving task (e.g. route guidance and navigation, speed warnings,
traffic light assistance), whereas others fundamentally change what we consider to be driving (e.g. forward
obstacle collision avoidance, autonomous driving). It is also important to note that some applications served
by digital maps provide information for comfort, entertainment or productivity reasons (i.e. they are not
related to the driving task), for instance, booking a restaurant.
Key human-centred design issues in this area concern GI reliability, accuracy and content. Such issues
manifest themselves in terms of common human factors topics, such as user attention, workload, situation
awareness, trust/confidence, behavioral adaptation, environmental learning and skills development. For
instance, human factors knowledge indicates that people will often over-trust technology in situations where
objective and subjective reliability are poorly calibrated (Wickens et al., 2004). Such a phenomenon exists
for vehicle navigation systems where drivers do not necessarily understand the limits of the underlying
digital map database and are inclined to follow inappropriate routes (Forbes and Burnett, 2007).
The content of digital maps is of particular importance to the design of vehicle navigation systems. In this
respect, landmarks (e.g. churches, traffic lights, petrol stations) have been shown to be critical to the design
of usable systems (see Burnett, 2000). Nevertheless, difficulties arise in choosing good landmarks for use in
specific contexts. A number of research studies have considered this issue: for instance, Burnett, Smith and
May (2001) compared landmark identification from direct observation of routes by non-locals using video
with landmark identification from mental representations of routes by locals. Key characteristics of good
landmarks for navigation were identified to be: permanence, visibility, usefulness of location and uniqueness.
Methods of obtaining suitable usable landmark information require more research. The two primary
approaches include directly from an existing digital map (limited in fidelity) or through site visits (time
consuming and expensive). An alternative method is to gather information on landmark quality indirectly via
other in-car activities. In this respect, a PhD project at the University of Nottingham is currently exploring
the potential for drivers and passengers to reveal information about landmarks through mass participation in
an ’eye spy‘ type game.
Key research considerations for usability of GI
From the subjects explored in this paper, a wide range of research questions and issues are identified
towards evaluating usability of GI. Key considerations may be summarised as follows:
Interfaces
Interfaces to data need to be evaluated with respect to the user role and context of use. Besides
application interfaces, data formats, user manuals and metadata can all be seen as part of the user
interface with geographic data.
What metadata is needed for professionals and the public? How can we effectively communicate
information about data?
Collaborative system use is increasingly common, with shared interactions and shared data
presenting an added dimension to user-system interaction.
Where does the dataset end (content and so on) and visualisation of data start?

7. GI content, quality, structure, formats
How much and what information (in terms of content, resolution, quality) is needed for task
completion in different user contexts? How do cartographic rules in applications and dataset design
help or conflict with information needs?
How can a user articulate their need for GI content and level of detail (that is how do they explain
their vision – without being constrained by what they know already)?
What are the differences (in characteristics) between user-generated data and professionally
produced data?
Why do ad hoc formats for GI (for example, Shapefiles, KML) dominate over-dedicated/designed
formats (for example, NTF,GML)? What can we learn from successful/unsuccessful formats?
How should we name and classify features (improved semantics)?
Trust and value
What influences users’ trust in GI? When and how do users understand (or care) where data has
come from or how up to date it is?
What is the value of different data to different users (with diverse purpose for use, expertise with GI,
age)? And what motivates different users to use particular data (for example, motivations for VGI)?
Conclusions and ways forward
Returning to the question heading this paper, in order to understand what usable GI means to end-users,
many elements of data, systems, user profiles and their relationships in the context of use need to be
understood.
Key elements highlighted include technological and user diversity, interfaces, data content and structure,
information value relative to context, motivations to use data, communicating metadata in ways meaningful
to types of users, trust in data and interfaces.
There is a need for interface independent methods for specifying user requirements and evaluating GI
usability. For instance, methods that address the cognitive aspects of decision making are needed to help
understand how data is used and understood. At the same time, assessing usability needs to take into
account contexts of use, including technologies of interaction and levels of user experience.
Interfaces may be viewed as closely coupled with information, in that any information is communicated via
some kind of interface. Increasingly, however, the end user does not necessarily interact directly with
source information but with derived or processed information. The usability of both source information and
that derived from it needs consideration with respect to user context.
The value of bringing together perspectives from different disciplines and working together with different
user groups on pursuing some of the research issues identified is evident and the authors are keen to take
this further.
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Environmental Systems Research Institute, Inc. Flickr is a registered trademark of Yahoo! Inc. Google and
YouTube are registered trademarks of Google Inc. iPhone is a registered trademark of Apple Inc. OGC is a
registered trademark of Open Geospatial Consortium, Inc. Ordnance Survey and Strategi are registered
trademarks and Meridian is a trademark of Ordnance Survey, the national mapping agency of Great
Britain.UCL is a registered trademark of University College London. University of Glasgow is a registered
trademark of The University Court of the University of Glasgow. Windows Live is a registered trademark of
Microsoft Corporation. OpenStreetMap is a trademark of Steve Coast.