MyUI: Mainstreaming Accessibility through Synergistic User

MyUI: Mainstreaming Accessibility through
Synergistic User Modelling and Adaptability
Context Ontology, User Modelling Concept and Context Management
Public Document / VUMS Cluster Document
Deliverable number
Date of delivery
WP1- User and Context Modelling
FZI (Peter Wolf, Oliver Strnad, Heiko Haller, Andreas Schmidt),
FHG-IAO (Matthias Peißner), UC3M (José Alberto Hernández), PCL
(Roy van de Korput)
Context; Context Management; Architecture; Ontology; User Model,
User Profile
This deliverable describes the MyUI Context Ontology and the Context
Management Architecture. A major part of the document is dealing with
the dynamic MyUI User Profile which serves as the basis for MyUI’s
adaptive user interfaces.
© 2010-2012 MyUI Consortium
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Table of Contents
INTRODUCTION ................................................................................................................. 3
RESPONDING TO REVIEW RECOMMENDATION ..................................................................... 3
THIS DOCUMENT.............................................................................................................................. 3
CONTEXT MANAGEMENT APPROACH....................................................................... 4
2.1 COLLECTION OF SENSOR INFORMATION .............................................................................. 5
2.2 CONTEXT AUGMENTATION .................................................................................................. 5
2.3 USER MODEL ....................................................................................................................... 6
Toward an Up-to-date Representation of Current Context.......................................... 6
CONTEXT ONTOLOGY..................................................................................................... 8
3.1 METHOD............................................................................................................................... 8
3.2 USER PROFILE ONTOLOGY .................................................................................................. 9
Structure ....................................................................................................................... 9
Properties and User Profile Variables....................................................................... 11
The User Profile as basis for the individual user interface generation ..................... 15
3.3 SENSOR ONTOLOGY ........................................................................................................... 16
Structure ..................................................................................................................... 16
Example Modelling of MyUI sensors ......................................................................... 18
3.4 APPLICATION SPECIFIC DATA ............................................................................................ 19
CONTEXT MANAGEMENT IMPLEMENTATION ..................................................... 20
DESCRIPTION OF THE COMPONENTS .................................................................................. 20
OPENAAL .......................................................................................................................... 20
EXTENSIONS TO OPENAAL ............................................................................................... 21
REALISATION OF MYUI SCENARIOS ........................................................................ 22
5.1 EMAIL CLIENT SCENARIO .................................................................................................. 22
Scenario Walkthrough ................................................................................................ 22
5.2 OTHER SCENARIOS ............................................................................................................ 24
Virtual User Lab......................................................................................................... 24
User Adaptive Connected Television Interface .......................................................... 24
Cognitive Games ........................................................................................................ 25
Supporting Physiotherapists in Customizing and Monitoring Progress of Stroke
Patients 25
Stroke Patient Physiotherapy Reinforcement ............................................................. 25
Supporting Healthy Exercise for the Elderly and Digital Picture Frames ................ 25
CONCLUSION.................................................................................................................... 26
REFERENCES ............................................................................................................................... 27
APPENDIX A – EMAIL CLIENT SCENARIO STORIES ....................................................... 29
APPENDIX B – GLOSSARY OF TERMS IN MYUI ................................................................ 30
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1. Introduction
MyUI aims at providing support for user interfaces that dynamically adapt to the needs of the user
and the characteristics of the user’s environment, i.e., the context of a user. Towards that end, we
need the following
A structured representation of the context, often labelled as “user model” and
“environment model”. For this representation, we need to define the formalism, available
features and possible values. Within MyUI we have chosen a ontology-based approach
allowing the project team to collaboratively develop the context ontology.
Methods and algorithms for deriving the context (at an abstraction level that forms the
basis for adaptation strategy) from low-level input (physical sensors, user actions). This
process has often been called “user modelling”, context “abstraction”, “aggregation”, or
“augmentation” (see [SchmidtContext]). In this deliverable, we call this context
A technical infrastructure for providing other components in the MyUI system with a
consistent view on the current context of the user using the vocabulary and constraints of
the context ontology. This is achieved through the context management implementation.
Responding to review recommendation
Following the M6 review results and recommendations, the overall plan of WP1 has shifted from a
more analytic approach where algorithms are designed based on analysis of existing knowledge
and user studies towards a rapid-prototyping approach in which we develop a running system as a
basis for experimenting and gathering runtime experiences. Therefore, we have concentrated our
work in year 1 on (a) the fundamentals of modelling as the basic enabler and (b) on providing
components for the first demonstration for M12. To take advantage of this approach, the
development of methods for deriving context information from low-level sensor information has
been limited to basic heuristics in year 1 and will be more experimental within year 2.
Furthermore, the approach to ontology modelling has been thoroughly reassessed, resulting in a
more lightweight and less diagnosis-centred approach that has been found to be more suitable for
the problem at hand.
General Approach to MyUI’s Context Management Solution and Outline of this
As described in the previous section, this deliverable aims for 3 distinct results: description of the
general method and ideas behind the MyUI context and user profile management framework,
presentation and discussion of the current MyUI context modelling with a focus und the user
modelling and a brief presentation of the implementation of the context management solution.
As shown in chapter 3.1, work on this task started with the analysis of the requirements identified
in deliverable D2, as well as the scenarios described in D4.1. This resulted in the selection of the
email client application scenario as first demonstrator, since this scenario is able to exemplify all
major contributions of the project without requiring extensive implementation efforts. Based on
technical background knowledge in the context management and user modelling domain from
projects like LIP, Agent-Dysl, SOPRANO, and openAAL, a first approach to user profiling based
on ontology based context management was derived for this scenario and discussed within the
project consortium. This was the starting point to a process of iterative refinement of the technical
concepts, where each iteration result was presented to the consortium and where feedback was
gathered and incorporated into the concept; until a stable technical concept was reached.
This stable version of the technical concept is presented in the upcoming sections of this
deliverable. While section 2 gives an overview and discusses the general concepts underlying the
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MyUI context management framework, section 3 gives more details towards the context ontology
and the user profile ontology. After reaching this stable technical concept for the first demonstrator,
it was informally evaluated based on all scenarios, indicating feasibility and possibility of
improvements. This step is presented in section 5. Finally, the subsequent implementation for the
first demonstrator is briefly discussed in Section 4.
In the future the technical concept will be extended to a solution for all scenarios that are selected
for demonstration, leading to a generic context management solution for MyUI. The resulting
solution is going to be evaluated in the upcoming user tests. Results of the user tests will
continually improve the technical concepts based on real-life data; leading the way to a final
As agreed at the VUMS cluster meeting in Prague in November 2010, a common glossary of terms
should be provided by all cluster projects within the single projects’ M12 deliverables related to
user modelling. In case of MyUI this is D1.1; hence the list of terms to be defined in the glossary is
attached to this document as Appendix B.
2. Context Management Approach
As already stated in section 1, MyUI aims at providing support for user interfaces that dynamically
adapt to the needs of the user and the characteristics of the user and the user’s environment i.e., the
context of a user. More specifically, context can be defined as
any information that can be used to characterize the
situation of an entity. An entity is a person, place, or object that is
considered relevant to the interaction between a user and an application,
including the user and applications themselves.[DeyContext]
The role of context management in adaptive systems is best understood by referring to the general
model of adaptive system described in D2.1 based on the work of (Weibelzahl et al, 2004;
summarizing Totterdell & Rautenbach, 1990; Oppermann, 1994 and Jameson, 2001). The model
describes the three typical stages involved when providing adaptive behavior:
1. Afference – collection of observational data about the user.
2. Inference – creating or updating a user model based on that data.
3. Efference – deciding how to adapt the system behavior.
Typically, context management integrates the stages of afference and inference with the goal of
providing a useful representation of contextual information that enables efference. Seen from the
viewpoint of context management, we can characterize afference as providing a shared sensor data
repository where sensor events are collected. On top of this, inference is the integration and
management of different context augmentation services. The goal of augmentation is to gather
information about the user. This information must be useful to enable adaptive behavior in the
phase of afference. Information about the user is structured according to the user model and stored
in the user profile. While the user model describes the information collected about users in terms of
a schema, the user profile is the instantiation of the user model for a concrete user. Both, the user
model and the user profile, will be discussed in the course of the subsequent sections. The next
three subsections will also further examine the role of context management in the light of this 3
stage model.
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Context augmentation
Adaptation Engine (WP2)
Sensor Data User Profile
Figure 1: Approach to an adaptive system in the light of context management
Collection of Sensor Information
Looking at the problem of afference in more detail, we can distinguish implicit afference, i.e.
collecting data in the background without direct involvement of the user, and explicit afference, i.e.
actively involving the user in data collection. Since unobtrusive collection of user-related data
without influencing the user in his or her normal interaction with the system cannot be discarded as
a requirement in MyUI, the architecture of the context management solution has to account for both
Implicit afference can be achieved by using sensors to unobtrusively detect observational data
about the user. Unfortunately, individual sensors seldom deliver information that can be used
directly to make useful statements about the user. Usually, sensor events must be connected,
aggregated and augmented to arrive at information that can be used to populate a user profile.
This leads us to a generic context management architecture for adaptive systems where sensor
events are collected in a sensor data repository. This shared data repository is filled by virtual and
physical sensors that store their sensor events into the data repository. Physical sensors are pieces
of hardware equipment placed in the surrounding of the user that are able to detect certain
characteristics that are useful to infer user profile information. On the other hand, virtual sensors
are pure software based sensors that detect information by analyzing the user’s interaction with the
MyUI system.
In the inference stage context augmentation algorithms are then accessing this shared sensor data
repository and are trying to derive user profile information from sensor events, additional
background knowledge and historic context information.
For more information on sensor modeling and the sensor data repository, please refer to Section 3.
Context Augmentation
As described in [Kobsa 2004] rule-based approaches, probalistic reasoning, data mining, predictive
reasoning, and other machine-learning approaches might be used to derive useful information about
the user. These different approaches each have different drawbacks and benefits, e.g. probabilistic
methods might have benefits in activity recognition, whereas rule-based approaches are easier to
maintain and implement. To account for different possibilities the general context management
architecture should be able to incorporate different reasoning mechanisms.
This can be achieved by a data-centric integration architecture. As analyzed by Winogard in
[WinogardContext], blackboards are the architecture of choice for this problem. In such blackboard
architecture, sensor events and other useful information are published on a shared blackboard.
Context augmentation services that represent different reasoning and inference techniques and
algorithms can then access the information on the blackboard and derive useful user profile
information. Compared to other approaches such architecture focuses on a separation of the shared
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descriptive data that is captured in sensor data repository and user profile from the algorithmic and
processual knowledge that is needed to infer additional information. Consequently, context
augmentation services and therefore reasoning algorithms can be replaced independently. This
enables fast prototyping, by easily experimenting with different reasoning approaches.
User Model
Capabilities and limitations of humans change over time, i.e. during the process of aging. As
described in the deliverable D2.1 (section one example is the ability of hearing, which
decreases over time. Although it is common that abilities decrease during aging, there is no uniform
pattern of the steady cognitive decline. Sometimes it is also possible that a loss of cognitive
abilities can be reversed. This induces that the user profile is never fixed at a certain point in time.
Rather the user profile has to be continuously adapted to the user it is associated to.
In MyUI context management enables adaptive user interfaces by providing a continuously
updated user profile. Of course, to enable efference the user model must provide information that is
able to trigger and drive adaptation. Since MyUI is dealing with the adaptation of user interfaces,
MyUI’s user model is focusing on impairments and disabilities with regards to human computer
For more information on the actual content of the user model please refer to Section 3. The next
two subsection deal with the important interrelated technical concept of providing an up-to-date
representation of the user’s current context.
Toward an Up-to-date Representation of Current Context
Independently of the content that is concretely modelled within a user profile, the notion of the
current context is an important concept of context-aware systems. Representing the current context
of a user is a non-trivial task in domains where conflicting information might be available. This
could be due to sensor information indicating two different values for a user model concept at the
same point in time. Conflict-resolution therefore deals with the provision of a conflict free
representation of the user profile based on possibly conflicting input information.
Especially, in an approach where the user profile is adapted continuously, there is a need for a
strategy to prevent or diminish the effect of false updates. In the most simplistic case the
measurement of two sensors could result in the update of the user profile with a positive fact, and
the other sensor would measure a negative fact, nearly at the same time. In an open-architecture
like MyUI, where different sensor technologies, context augmentation services, UIs and
applications are supported, it is impossible to clearly prohibit the occurrences of wrong or
conflicting updates to the user profile.
Other types of conflicts would be to violate cardinalities. This would be the case if there are more
facts (which correspond to statements in the wording of MyUI) in a set of facts, where there are
multiple occurrences of one given characteristic. In this case there would be no way to “know” the
right value of the characteristic, since only one user model concept can be valid at one time. For
example one could consider having multiple instances of the fact “user A has a visual acuity of B”.
In any case, a method for dealing with conflicting updates is needed. The solution is to derive a
conflict-free representation of the current context. This can be achieved by evaluating a user profile
update as soon as it occurs (conflict-resolution on storing) or it can be done when conflict-free
information is requested (conflict-resolution on query). In order to resolve these conflicts there are
multiple strategies possible. Conflict resolution is done by a so called conflict resolution operator,
which is a function that transforms a set of context facts into a set of conflict-free context facts.
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For the demonstration of the first prototype the conflict-resolution on query approach was chosen,
because this allows us to keep all context information inside the internal storage longer than in the
conflict-resolution on storing approach. Possible operators can include:
• ” most recent” – considering only the last update
• “average” – considering the average over a period of time
• complex combinations of both
• etc.
Which operator or combination of operators is chosen, is closely connected to the way the user
profile will be updated. If irregular updates with no or few conflicts occur the most-recent strategy
can be best. If updates occur in high-frequency with some conflicts or errors an approach based on
averaging is suitable. The way of how the user profile is updated, is referred to as update strategy.
An update strategy describes the general approach to updating the user profile. For MyUI the
update strategy can be summarized as accumulating multiple minor incremental updates, whereas
every sensor event is translated into such an update by means of a context augmentation
Email Client Example:
The user is interacting with the email client application by using a user interface that is based on a
generic design pattern The generic design pattern is described as suitable for people with mildlylimited visual acuity. The distance sensor is detecting that the user is leaning forward when
interacting with the information on the screen. A software component is analysing all this
information and comes to the conclusion that the user must have slightly worse than mildly-limited
visual acuity. The component, therefore, slightly adapts the corresponding value in the user profile.
This minute change will later on lead to the selection of different generic design pattern that, in
turn, will lead to a different user interface experience.
Based on available sensor information gathered from virtual and physical sensors, it is hard to
determine whether the user’s ability to interact with the system has improved. Therefore, this
approach will manifest in repeated adaptation of user model concepts in the user profile, indicating
a deterioration of user characteristics.
To overcome this problem there has to be a mechanism that continuously adapts the values saved in
the user profile in a way that indicates an increase of the user’s interaction capabilities. One
possible mechanism would be to detect not only the problems a user has with a specific user
interface, but also to detect if a user has no problem or does actually very well in using a specific
interface. Although this would be the preferred method it is very hard to detect whether a user has
no problems with a user interface. Doing so would imply that every user uses a user interface in an
equal way and with the same efficiency.
Another mechanism discussed inside the project is to have a decay mechanism periodically
adapting all values stored in a user profile by a small constant value. Although, this approach is
very easy to understand and implement; it will be hard to find the correct parameters for it. If the
user profile is updated too often by this mechanism the user’s limitations are constantly underrated
which would lead to a user interface not suitable for the user. On the other hand; an infrequent
update of the user profile would neutralize the effect such a decay mechanism would provide.
Additionally to the decay mechanism it would also be possible to regularly analyse historic sensor
events. I.e. if the distance- / gesture-sensor hasn’t detected a lean-forward gesture during a given
timespan the system could try to decrease user profile variables again.
Currently there is no implementation or concretization of such a mechanism included in MyUI.
This is the case, because the overall plan of WP1 has shifted from a more analytic approach where
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algorithms are designed based on analysis of existing knowledge and user studies towards a rapidprotyping approach in which we develop a running system as a basis for experimenting and
gathering runtime experiences. Within year 2 of myUI, WP1 will develop further concrete
heuristics for deriving user context information based on the data gathered from sensors and
expected results.
3. Context Ontology
User context is the system-side representation of a user’s situation as far as it is relevant to the
system, framework or application at hand (see [SchmidtContext]). In MyUI, context information is
used to drive the automatic adaptation of user interfaces, i.e., it is focussed on those aspects of a
situations that (a) can be captured with the help of sensors and (b) are useful for deciding upon
adaptation strategies. Compared to other projects in VUMS cluster, most notably the GUIDE
project, this leads to a different approach in designing a user context ontology. In GUIDE, the
ontology (called “user model”) is aimed at a description of the user in a form that is as realistic and
complete as possible and enables use of the model for simulation of user experience. While in
theory such an approach is very powerful, it inevitably introduces a level of complexity when it
comes to runtime instantiation of such a model for a concrete user, based on a concrete set of
sensors, and for a concrete set of adaptation strategies. The amount of heuristics required typically
makes testing and fine-tuning of such a system very challenging.
Within MyUI, we have therefore deliberately focused on those aspects that “make a difference”
when it comes to adaptation strategies. The most promising approach was based on modelling
disabilities for which UI designers develop patterns, based on which we select appropriate patterns
at runtime, and which we can derive from combining sensors and user interaction data or can easily
get static input.
Following the state of the art in computer science, an ontology is “a formal, explicit specification of
a shared conceptualization [StuderOntology]. Ontologies are used to derive data structures and
schemas as well as software interfaces providing access to information represented in those
schemas. Developing a “good” ontology is always an iterative process in which we have to find
out the appropriate representation, which is formal enough to enable automated actions, useful for
describing the problem at hand, and which represents a shared understanding of those using the
ontology. Therefore we have adapted the approach illustrated in fig. 1 which further described in
[SchmidtPhD09] to the needs of the MyUI project. The given method has already been used in
other EU-projects like LIP (Learning In Process), Agent-DYSL and SOPRANO.
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Would this information
change the way we would
like to adapt the UI?
requirements &
device UI
What are
D1.1 / Final
What are we
likely able to
Figure 2: Iterative development of the MyUI context ontology
Within MyUI usefulness of user profile was mainly based on input of D2.1 and an initial evaluation
of the project scenario as described D4.1 leading to an initial set of user disabilities and
impairments in relation to human computer interaction. In several discussions with different
consortium members Availability and Device Capabilities have been checked leading to a iterative
refinement of the initial list of valuable user characteristics. These steps have been repeatedly
followed as part of several project discussions guided by a conceptual evaluation based on the
MyUI scenarios (see Section 4 for more information).
This has resulted in identifying three distinct parts of the context ontology:
- the user profile ontology, describing properties of an end-user of the MyUI system
- the sensor ontology, describing
- and application-specific ontologies
These three areas are further described in the following sections
User Profile Ontology
In general, a MyUI user profile is collection of information about an end-user of the MyUI system.
This includes personal information like email address, first name, last name, etc. as well as
information about user capabilities and characteristics as far as they are relevant to determine the
human computer interaction (HCI) abilities of a user. The general idea is to collect and
continuously adapt HCI-relevant user information, so that human computer interfaces (also called
user interfaces) can be dynamically adapted to the current capabilities, needs and limitations of a
In more technical terms and based on the RDF data model. RDF describes relationships in terms of
resources. Resources can be differentiated into subjects, predicates, objects and statements. A
statement is a triple consisting of subject, predicate and object. An RDF-statement roughly
translates to a data representation of a simple natural language sentence that captures statements
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about the subjects. In RDF resources are referenced by Uniform Resource Identifiers URIs. In
relation to MyUI a statement always addresses a user capability, characteristic or short property of
a user. The user is the subject. The property is the predicate. The value that is stated for this
property is the object of the statement.
Based on this a MyUI user profile is a collection of statements referring to the same user URI, i.e.,
one user profile is always connected to one and only one user. The allowed properties and possible
values are defined in the MyUI User Profile Ontology, which describes the constraints under which
a user profile is considered valid. Only valid user profiles can be processed by the MyUI system.
Two constraints have already been defined in the previous section, namely:
C1: A MyUI user profile must be a collection of statements.
C2: A MyUI user profile must consist of statements referring to a specific user URI. One
user URI must always uniquely refer to one specific user.
When it comes to adaptation (WP2), we are using the term “user profile variable”. This
corresponds to a statement where the subject is the specific user this variable belongs to. The
property, which can be seen as the predicate in a RDF-statement, is also called “user profile
variable name”, and the object is called “user profile variable value”.
C3: Every property in a MyUI user profile must correspond to a specific characteristic of
the user, which is called “user profile variable name”.
In short, one could say that the property must be the name of a user profile variable. A detailed
overview of the currently defined user profile variables and a description of the method used to
define these variables is provided in chapter 3.2.2. This list is not fixed yet which means the user
profile variables (and therefore the properties) are not fixed yet and might change in the future of
the project.
Although MyUI’s modelling does not rely on OWL conceptual it is closely linked to the GUMO
modelling principles described in [HeckermannGumo] as
In contrast to GUMO, MyUI is aiming for a much more task-oriented user profile, where
information capturing disabilities and impairments in relation to human computer interaction are
captured. This makes it impossible to simply reuse the high-level user model dimensions proposed
by GUMO. Therefore, MyUI is extending the GUMO model with the user variable concept.
The range of a property defines which values can be used as an object in a statement (i.e. it defines
the type of the corresponding user profile variable). We can distinguish the following three cases:
Numerical Literal: We use numerical literals to represent user profile variables which are
ratio-scale. In this case one value is selected from a predefined, continuous interval for a
user profile variable of this type. In the current ontology this interval is considered to be
the same for all ratio-scaled user profile variables (in contrast to nominal-scaled user
profile variables where a different set of possible values is defined for each user profile
variable). The interval is specified to be [0,4] (i.e. all possible values between 0 and 4
including 0 and 4 can be assigned). Although, we want to avoid an exact medical
definition, 0 can roughly be mapped to “not limited or normal”, 2 can roughly be mapped
to “mildly limited” and 4 can roughly be mapped to “severely limited”. This kind of type is
typically assigned to user profile variables that represent limitations and capabilities of the
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user like hand precision, visual acuity. Assigning a value of 0 to hand-precision, therefore,
maps to the statement that this user’s hand-precision is not limited or normal. The default
value is 0. However the above mapping exists, this doesn’t have to be applicable for all
user profile variables. The user profile variable “ambient light” for example uses another
mapping (0 translates to no ambient light meaning absolute darkness, 4 translates to very
high ambient light). Concluding it can be said that the meaning of the values of a numerical
literal depends on the concrete user profile variable. The mapping for each defined user
profile variable can be found in Table 1. Using a continuous, ratio-scaled interval has the
advantage that there exists a strong order between the distinct values for a user profile
variable. Furthermore using continuous values is helpful by providing the possibility to
have a fine-grained differentiation.
String Literal: This corresponds to a free-text user profile variable. This means any value
can be assigned to this kind of user profile variable as long as it is a string. This user
profile variable type is used for user characteristics like first name, last name and email
address. Although, in principle any value is accepted (as opposed to a set or interval of
values), the format of the string might be constrained in a clearly defined way. For
example, the email address must be a syntactically correct email-address; or the first name
must not exceed a certain number of letters. The default value for a user profile variable of
this kind is an empty string.
Enumeration: This means a subset from a set of predefined values (represented as concept
instances) can be assigned to a user profile variable which is nominal-scaled. This user
profile variable type is used to specify the languages that are accepted by a person. In a
collection of statements, an “assigned subset” maps to a set of statements with the
corresponding property for that user profile variable. The collection must not be empty if it
is explicitly assigned. Enumerations also support default values, which are used when
there is no corresponding statement. The default value is one specifically marked value of
the set of possible values (since only subsets can be assigned, technically it would be a set
containing only this single element).
All this can be condensed into the following constraints.
C4: A property with a string literal range must appear at most once. Its value can be any string that
complies with the format restriction of the corresponding user profile variable. The default value is
an empty string.
C5: A property that corresponds to a nominal-scaled variable can appear multiple times. Its value
must be selected from the instances of an assigned range concept. If there is no property instance,
the specified default value is used.
C6: A property that corresponds to a ratio-scaled user profile variable must appear at most once. Its
value must be selected from an (currently common) interval. The default value is 0.
The resulting defined ontology formalism can be seen as RDF plus a subset of RDFS (concept and
property hierarchies) which is interpreted as constraints, i.e. range definitions constrain the allowed
values for certain properties.
Properties and User Profile Variables
In MyUI, a function-based user modelling approach is used. Hence, user profile variables are
connected to specific user interaction abilities and constraints subdivided into perceptual, cognitive
and motor attributes. Variables relevant for MyUI have been initially selected from the WHO ICF
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guidelines. Further sources, e.g. the ISO 22411 standard and major requirements determined in
D2.1 (Requirements for User Interface Adaptation), are also considered.
The following key questions have been underlain the selection process:
1. Does a certain attribute affect the interaction with ICT products?
2. Can user interface adaptation overcome or weaken the interaction constraints?
If both questions can be answered with “yes” the attribute has been included as additional user
profile variable to the MyUI user model.
The initial list of user profile variables used in the current version of the MyUI system is presented
below. Each variable is shortly explained, appropriate valid value ranges and references to existing
standards are given. Possible methods of resolution are not detailed here, but will be part of D2.2
(Adaptation concept and Multimodal User Interface Patterns Repository).
User Profile
visual acuity
ability to perceive
what is displayed
on the screen
[0, 4]
0 - normal;
4 - severely
WHO ICF b2100 visual acuity
functions, b21022 contrast
sensitivity, b21020 light
ISO 22411
field of
ability to
colours (without
any limitation
such as e.g. redgreen, blueyellow blindness)
ability to perceive
without limited
vision in certain
ambient light
ability to hear
0 - colours can
be distinguished
1 – not all
colours can be
[0, 4]
0 - normal;
4 - severely
[0, 4];
0 - no ambient
light, absolute
4 - very high
ambient light
level, e.g.
dazzling sun
light on the
[0, 4]
0 - normal;
4 - severely
URS07, URS09
WHO ICF b21021 colour vision
ISO 22411
WHO ICF b2101 visual field
ISO 22411
WHO ICF b21020 light
ISO 22411
WHO ICF b2300 sound detection
ISO 22411
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g abstract
long term
ICT skills
ICT literacy
D1.1 / Final
ambient noise
[0, 4];
0 - normal;
4 - high noise
ability to
written or spoken
[0, 4]
0 - normal;
4 - severely
ability to produce
written or spoken
[0, 4]
0 - normal;
4 - severely
ability to
abstract symbols
or icons
selective, focused
and divided
[0, 4]
0 - normal;
4 - severely
[0, 4]
0 - normal;
4 - severely
ability to process
information in an
appropriate time
[0, 4]
0 - normal;
4 - severely
ability to
remember exact
sequencing of
procedures and to
orientate oneself
in long sequences
of steps
ability of learning,
storing and
retrieving new
skills and
experiences in
using current ICT
user interfaces
[0, 4]
0 - normal;
4 - severely
WHO ICF b2300 sound detection
ISO 22411
WHO ICF b1670 reception of
ISO 22411
WHO ICF b1671 expression of
ISO 22411
URC07 (limited literacy)
WHO ICF b140 attention
ISO 22411
WHO ICF b1470 psychomotor
ISO 22411
WHO ICF b1440 Short-term
ISO 22411
[0, 4]
0 - normal;
4 - severely
[0, 4]
0 - normal;
4 - severely
WHO ICF b1441 long-term
ISO 22411
1 selective attention: ability to attend to one thing without losing control of another one
focused attention: ability to concentrate on only one thing at a time and get not distracted by irrelevant information
divided attention: ability to split attention to more than one thing at a time
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need for
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importance to
which security is
needed including
ability to move
hands according
to visual feedback
ability to
articulate speech
ability to move
the fingers
ability to move
the hands
[0, 4]
0 - normal;
4 – particularly
[0, 4]
0 - normal;
4 - severely
[0, 4]
0 - normal;
4 - severely
[0, 4]
0 - normal;
4 - severely
[0, 4]
0 - normal;
4 - severely
WHO ICF b1471 Quality of
psychomotor functions
ISO 22411
URC 19
WHO ICF b310 voice functions,
b320 articulation functions
ISO 22411
WHO ICF d440 fine hand use
ISO 22411
FRP01, FRP03
WHO ICF b730 muscle power
WHO ICF d4453 Turning or
twisting the hands or arms
WHO ICF d4402 Manipulating
ISO 22411
ability to move
the arms
contact grip
ability to apply a
force by a finger,
the thumb or the
hand [according
to ISO 22411],
e.g. by touching
or operating via
ability to hold the
control by the
fingers and/or
thumb without
clenching the fist
hand [according
to ISO 22411],
e.g. when holding
sth between the
pinch grip
[0, 4]
0 - normal;
4 - severely
[0, 4]
0 - normal;
4 - severely
WHO ICF d4453 Turning or
twisting the hands or arms
WHO ICF b265 Touch function
ISO 22411
[0, 4]
0 - normal;
4 - severely
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WHO ICF d440 fine hand use,
d4400 Picking up
ISO 22411
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clench grip
General data
first name
last name
D1.1 / Final
ability to use all
fingers wrapped
around a control
[according to ISO
[0, 4]
0 - normal;
4 - severely
first name
last name
email address
any string
any string
any well-formed
email address
WHO ICF d4402 Manipulating
ISO 22411
Table 1: Already defined MyUI user profile variables. Default values are written in bold.
The User Profile as basis for the individual user interface generation
Generic design patterns refer to certain user profile variables stored in the user profile in order to
set global user interface features as font size. In this way, an individual user interface profile is
created. The individual user interface is composed by different user interface elements. Each user
interface element is described by a related interaction design pattern which in turn is based on
specific global variables from the user interface profile and the current interaction situation.
In general, design patterns (generic and interaction-) are selected if their preconditions (rules that
define tolerance intervals or tolerated values for the relevant user profile- and global variables
respectively) are fulfilled. The preconditions are illustrated in the following on the example of
generic design patterns.
As can be seen form the user profile variables table in the previous section, string-based user
profile variables only appear in the general data part of the user profile – which can be considered
as static during the interface adaptation process.
The majority of the remaining user profile variables are ratio-scaled, some are nominal-scaled. For
these two data types, examples are presented for simple preconditions:
Ratio-scaled user profile variables:
A simple precondition of a generic design pattern could define an interval restricting
allowed values for a certain ratio-scaled user profile variable. If a user’s individual
assignment of this ratio-scaled user profile variable is included in the given interval, then
the precondition is met and the generic design pattern selected.
For example, considering a pattern suitable for people having normal or slightly limited
hand precision. So, the precondition is “IF 0<= hand_precision <=2”. In consequence, for
all users that have a value less-than or equal-to 2 assigned to this user profile variable this
generic design pattern is applied.
Nominal-scaled user profile variables: here a simple precondition might check the
presence or absence of a specific user profile variable. If a user’s individual assignment of
this user profile variable equals the hypothesis, the generic design pattern is selected.
Concerning the interaction design patterns, similar preconditions are used. The only difference is
that they refer to global user interface profile variables and a specific interaction situation.
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Sensor Ontology
The MyUI framework should enable dynamic user interfaces that adapt to the changing capabilities
of end users. This dynamic behaviour is based on a dynamic user profile that is continuously
updated to reflect the current status of the user. To efficiently and unintrusively sense the current
status of the user, sensors need to be installed in the direct environment of the user. Sensors can
detect and measure information about the user. This information can be used to derive the current
situation of the user.
As explained in the previous section the MyUI context mainly consists of information about user
capabilities, limitations and characteristics as far as they are relevant to determine the human
computer interaction (HCI) abilities of a user. This kind of context information must be derived
from sensor data.
In MyUI, sensors are roughly be mapped into two categories:
physical sensors that require a piece of hardware and software and
virtual sensor that just analyse and report the interaction of the user with the system.
Both types can be modelled in the same simple fashion.
The key modelling approach is that a sensors measures sensor events. Sensor events usually are
modelled as triples composed of a sensor URI, a property defining what has been measured and the
value that has been measured for the property. This approach of effectively modelling sensor states
has been derived from the state based modelling shown in [BoninoDogOnt].
Sensor Event = (sensor id, measured property, measured value for that property)
The MyUI sensor modelling is limited to this simple modelling approach to allow for flexibility
and easy extensibility. As with the list user profile variables also the list of measurable properties
and the values that can be measured for a certain property is not fixed yet and most properly is to
be extended when more and more scenarios are implemented. Figure 2 shows an abstract graphical
overview of the sensor ontology.
Currently the project integrated a RFID reader for user identification, an IR-sensor for the remote
control, and a gesture-/distance sensor (based on a web-camera). These physical sensors are
modelled as sensor objects. To allow measurements the following measureable properties have
been defined:
• RFID-tag In Range
This property states that the RFID reader detected a transponder. The value associated with
this property contains the identifier of the detected transponder.
• Remote Control Keypress
This property states that a button on the remote control has been pressed. The associated
value contains the code or identifier of the pressed button.
• Head To Display Distance
During the usage of the MyUI system, the distance and gesture sensor continuously
measures the distance between the head of the user and the camera which is normally the
distance between the head of the user and the display. Measurements are periodically
reported as sensor events with the “Head To Display Distance”-property. The associated
value states the absolute distance in centimetres.
• Gesture
The sensor measuring the distance between head and camera also continuously analyses
the user’s movement to determine special gestures. Two gestures currently implemented
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are the lean-forward, respectively lean-backward gesture. This property states that one of
these two gestures has been detected by the sensor and the value associated with the
property contains either “forward” or “backward”.
How these properties are used to alter the user profile is described in chapter 4.
To enable automatic augmentation based on sensor events, background knowledge must be
provided for the augmentation process. Consider, for example, a RFID reader that is detecting
whether a transponder is in range or not. Although this information itself is not very significant, it
is possible to derive further information if additional information is present. For example it would
be possible to derive that a specific person entered a room if there are two additional statements:
1. The detected transponder is connected / carried by a given person A
2. The RFID reader is mounted at a specific room B.
With this information one can derive that person A entered room B. Facts like the two
abovementioned facts about the RFID reader are called meta-statements. These meta-statements
indicate how the sensor is connected to its environment which, in turn, defines how sensor events
can be interpreted. To allow for reasoning over sensor information this meta-information must also
be captured as part of the user profile. In particular, it must be defined when a new sensor with its
sensor id is incorporated into the system. In general, such meta-information must be known about
sensors and other physical devices in order to make sense of the sensor events that the sensors
deliver. Additionally, though, it might also be useful to specify such information about other things
that are not sensors, e.g. physical objects that participate in a sensor measurement like an RFID-tag.
Therefore, the concept of a physical object was created to indicate things that might require specific
meta-information, in order to make sense out of them.
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Figure 3: The MyUI Sensor Ontology; purple colours indicate measureable properties, orange
colours indicate concrete sensors, red colours indicate abstract physical objects, and blue colours
indicate the highest level of abstraction.
Example Modelling of MyUI sensors
Since sensor information is concrete and not abstract information, it is very likely that the list of
sensors and measurable properties needs to be extended regularly when new applications and
scenarios are implemented (in contrast to the user profile whose list of user profile variables is
abstract and will therefore most likely converge into a fixed list over time). This example should
therefore guide future MyUI system administrators when extending the sensor ontology.
Distance Sensor Example:
As it has already been mentioned in section 3.3.1 the distance sensor detects the distance between
the user’s head and the display that is used for interaction. Hardware wise the sensor is based on a
camera system, software wise the sensor will deliver information about the distance in centimetres.
This information could be easily mapped into sensor events like this:
Distance Sensor Event = (“Some distance sensor id”, “Distance to head”, “60”)
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In this example, the MyUI framework would know that sensor id “Some distance sensor id” maps
to a distance sensor and that the “Distance to head” property requests a numerical value that
indicates the distance in centimetre. In order to derive useful information from this sensor event, a
distance sensor must also be connected to some display via a meta-statement. Furthermore, either
the display or the distance sensor must be connected to the user whose head is indicated in the
measurement. Only with this additional meta-information, the system is able to infer information
about the distance of a user’s head to a real display.
For various reasons it might be beneficial to abstract the sensor event as much as possible. For
example, MyUI is using the distance sensor to detect the leaning forward and backward gesture of
a person interacting with a display. Therefore, a more suitable sensor event representation might
Distance Sensor Event = (“Some distance sensor id”, “Lean-forward or lean-backward gesture
detected”, “forward” (or “backward”))
In this case the measurable property “Lean-forward or lean-backward gesture detected” is
requesting one of two possible values: “forward” or “backward”. One obvious benefit of this type
of modelling to one presented before is, that much less data needs to be exchanged between the
sensor and the sensor data manager, since there is no continuous stream of distance sensor events
like they have been introduced at first. The “Lean-forward or lean-backward gesture detected”event would only be triggered if the user performed either a lean-forward or a lean-backward
Application Specific Data
In addition to storing sensor and user profile specific information, the analysis of the scenarios also
indicated a need for storing application specific data. Applications provide a service to the end
user. In MyUI, applications only specify the general outline of user interaction by specifying
interaction situations and deal with “content” that is handled by the application; the creation of user
interfaces and other tasks have been shifted into other components of the MyUI framework, with
the goal of making application development easier.
The analysis of the scenarios and the underlying applications indicated that every application needs
to store at least some application specific data. For the MyUI email client application this could be
login information for the underlying email server, for the physiotherapy application this could be
more complex information about individual exercises or reference to exercise videos. Since the
need for an application specific storage capability was so ubiquitous, it was decided to add the
functionality for storing application specific data to the context manager; and, therefore,
simplifying the burden of the application developer even further.
The concrete ontology for application specific data has to be defined by the application developer;
since needs of applications cannot be foreseen in an architecture that is open for new applications.
As with the other two parts of the context manager the general modelling paradigm is based on a
key-value pair approach. This means one data entry, specific to one application and one user, is
modelled as a collection of key-value pairs.
Application Data Entry = (user id, application id, collection of key-value pairs)
For the above mentioned email client application the entry could look like this:
Email Client Data Entry = (“some user id”, “email client application id”, (“gmail user name” =
“peter”, “gmail password” = “peter”))
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Any client software that knows the user id and the application id can access this application
specific collection of key value pairs. An application developer can simply add a new collection of
key-value pairs for an individual user by specifying the user id and the id of the application.
4. Context management implementation
Description of the components
The MyUI context management consists of three components: the Sensor Data Manager, the User
Profile Manager and the Application Data Manager. Their interfaces will be exposed to the other
subsystems of the MyUI architecture via XML-RPC. This accounts for interoperability between the
different components and allows for distribution over multiple connected computers (e.g. via the
As discussed in chapter 3.4 the MyUI framework provides applications running on top of it with
the ability to manage data in an application-specific ontology. This is accomplished by the
implementation of the Application Data Manager that provides methods for getting, setting and
deleting application-specific data.
Furthermore there exists the User Profile Manager. This module handles storage and updating of
the user profile variables for every user. (see chapter 3.2). To update a user profile variable, other
components from inside and outside the Context Management have to provide a valid – in terms of
the user profile ontology – statement about the user (e.g. “Arthur has-visual-acuity-and-sensitivity
2.3”). Updates can be provided either directly by external components or from internal components
like the Sensor Data Manager. With this architecture it is also possible to account for virtual
sensors, where applications provide feedback about the user’s behaviour while navigating through
the application and update the user profile accordingly. For example an application can detect if the
user navigates through the application in loops, which could indicate that the user has a severely
impaired working memory and update the user profile variable of the user directly via the User
Profile Manager.
Besides storing and updating the user profile the User Profile Manager keeps track about the
history of the user profile and provides the ability to retrieve a complete list of user profile
variables with their respective values for one user.
The third component is the Sensor Data Manager, which is responsible for the transformation of
sensor events into user profile statements as mentioned in chapter 3, and calling the User Profile
Manager to update a given user profile. In order to do this it exposes a method publishSensorEvent
via XML-RPC that other components in the MyUI system can call. The Sensor Data Manager
receives its input from the Event Processor which publishes for example a detected lean-forward
gesture. The transformation of sensor events into updates of the user profile is done rule-based, but
more advanced techniques can be employed in a later stage of the project.
All components mentioned beforehand have access to an object-oriented storage which is used in
order to store all kinds of statements and which can be queried by all components inside the
Context Management. This accounts for the need to persist context information and the usage of
past context data during the analysis of the context.
The implementation of the MyUI context manager is based on the open-source software openAAL2
(see also [WolfopenAAL]). openAAL has been developed within the European-funded project
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SOPRANO3 (see also [WolfSoprano]). It is supported by an active community and has been
released in several versions since its initial release. openAAL is currently used in the following
projects: FZI Living Lab AAL4, Mirror 5and EasyCare6. Furthermore, it is considered as input
project into the standardization activities of the European-funded project universAAL7.
OpenAAL has been chosen because it was originally designed with a focus on context management
for applications similar to the ones to be achieved in MyUI. Since OpenAAL also utilizes the
methodical workflow afference, inference, efference, introduced in chapter 2, the adaptation costs
to the requirements of MyUI are minimal. Furthermore the rapid prototyping approach of MyUI
applications is enabled, since FZI has as the main contributor of OpenAAL has a lot of experience
on the adaption of this software.
Extensions to OpenAAL
One major adaptation to be applied to openAAL with regards to the requirements of the MyUI
project is the addition of web service capabilities to the framework. That is, MyUI specific user
profile-, application data- and sensor-manager interfaces need to be published as web services.
Due to ease-of-use aspects and ubiquitous availability of client libraries for different programming
languages (java, c++ and php) and operating systems, XML-RPC was chosen as web service
Figure 4: Context Manager Component Architecture
As one can see in Figure 3, the application data manager is directly implemented on top of the
Db4O8 database framework. Db4O provides an easy-to-use and scalable object-oriented database
and has been chosen because it was also used in the implementation of the openAAL framework.
The sensor and interaction analysis component is an internal part of the context manager. As
exemplified in the scenario section, its major purpose is to interpret incoming sensor events in
relation to existing background information with the goal of inferring meaningful updates, referred
to as context augmentation, to the user profile. It is based upon openAAL’s uplifter framework
which provides support for simple Event-Condition-Action rules (see [KresserReasoning]).
3 (only German)
6 (only German)
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5. Realisation of MyUI scenarios
The following sections exemplify the use of the MyUI context manager with the help of the MyUI
demonstrator scenarios. The next section provides a step by step walk through of the email client
scenario. This scenario has been selected for the first demonstrator and is, therefore, treated with
special care. The thereon following section provides a short overview about relevant concerns
taken from all the other scenarios that are presented in D4.1 and shows how they can be handled
with the context management approach presented in this deliverable.
Email Client Scenario
This section provides a step by step email client scenario walkthrough. After each step the
realization with MyUI’s context manager approach is indicated. The scenario text was taken from
the email client scenario stories document that can be found as Appendix 1. It only depicts a very
simple adaptation case based on one user profile variable and two type of sensor information; just
to exemplify the general approach.
5.1.1 Scenario Walkthrough
“Arthur wants to use his new Net TV to see if his daughter has sent him an email. He starts the Net
TV by pressing the „on“-Button on his remote of which he knows the position. Arthur selects the
email service by choosing the relevant button on the screen by pressing the according number on
the remote. The screen shows 3 Messages with the name of the sender and the subject of the mail in
big letters …”
When selecting the email service the email application is started. The email application is
asking the context manager for the current profile of the user. For this purpose a user id
must be communicated to the application when the application is requested. This id is used
to request the user profile from the context manager. In the scenario, the user profile does
already contain non-default values for some of its user profile variables; probably because
it was initialized in that way after a user examination. Especially the user profile variable
“visual acuity” does contain a non-default value of 2.5, indicating that the person has
limited vision. The value of the user characteristic “visual acuity” now gets translated into
an appropriate value of the global variable “font size” by a generic design pattern. In case
of Arthur medium font size is set. Based on the global setting for font size (and possibly
other global variables settings) and the current interaction situation (displaying the listing
of received emails) the best-fitting generic design pattern is selected from the bundle of
interaction design patterns offering different presentation styles for the list of received
emails. For Arthur 3 emails are listed on the screen with senders’ names and the email’s
subject presented in medium font size.
“… but Arthur cannot read both of the texts. He tries to get nearer to the Net TV (leans forward) to
see if he might be able to read the text from a lesser distance. The Net TV recognizes his movement
Arthur cannot read the text and leans forward. This forward movement is detected by a
sensor and the information is sent to the sensor data manager by an event processor
translating the raw events received from the sensor into statements the sensor data manager
can handle. Recognizing the new sensor event, the sensor data manager tries to aggregate
and combine sensor information with other available information to make meaningful
updates to the user profile.
In this case, the component is accessing the currently selected interaction design pattern
checking for underlying user profile variables that are connected to the lean-forward
gesture (by means of the context augmentation services. It reasons that “visual acuity” is
the major underlying user characteristic and examines the related maximally tolerated
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value of 3 (access is provided by the interaction design pattern). Based on this information
the context augmentation service concludes that the visual acuity of the user must actually
be worse than the value of 3 derived from the pattern. Accordingly, the component updates
the user profile to a value of 3.1 for visual acuity. Therefore, the user profile variable is
updated from a value of 2.5 to a value of 3.1.
Note that the delta by which the variable is increased needs to be adapted according
experience gathered in user trials. Also, this example is only covering a very simple
inference step based on one single sensor event.
“… and increases the font size.”
The user profile has been updated to a value of 3.1 for visual acuity. The generic design
pattern that was selected before had a maximally tolerated value of 3.0 for visual acuity.
Consequently, this pattern does not fit the user profile anymore; a new generic design
pattern from the bundle of generic design patterns for font-size is selected. Hence, also
another interaction design pattern gets active presenting the list of received emails in a
different layout. When the page is reloaded, the subjects and senders of the 3 listed emails
are presented in an even bigger font size.
Note, that an immediate change of the font size is hard to achieve when relying on web
technologies. User tests must show if a regular page reload every few seconds or minutes is
tolerated or whether changes are only accepted when the application is requested anew.
“Still, Arthur cannot read the text so he tries to decrease the distance again. The Net TV sees that it
does not help to increase the font size any further and switches to pictures of the sender and a
button to open the mail.”
It is recognized that Arthur still is not able to read the text which leads to an image only
presentation mode as a further increase in font size is not supported by the system.
Note that the decision to switch into an image only mode is not necessarily computed on
the Net TV as indicated in the scenario description. Anyway, the mechanics work in the
same way as above, only that this time the sensor data manager component also has access
to past sensor events and past conclusions in relation to the current user. After an inference
step similar to the one described above the user profile variable for visual acuity is updated
again to a value of 3.5 indicating a severe impairment of visual acuity. When the page is
reloaded the layout will be changing again presenting all the information in an image only
“Arthur recognizes one of the pictures as his daughter and presses the according button on the
remote. The Net TV switches to the message screen where the text as well as a button to read the
message and different reply buttons are shown. The message is read by the system (Text2Speech)
automatically. After the system has read him his daughter’s message he also describes the options
available to Arthur (audio menu).”
New or subsequent user interfaces are also created from interaction design patterns that
match the current interaction situation. Depending on the global user interface variables set
by the individual user profile entries, a certain variant from the bundle of interaction design
patterns foreseen for each new interaction situation is selected. Therefore, if the user profile
settings and with it the global user interface variables stay unchanged, the variants chosen
in different interaction situations will be based on the same interaction modes (e.g. solely
presenting text or using images or audio output).
Accordingly, text-2-speech is activated by the interaction design pattern that is selected for
presenting the content of the email. (Any other pattern does not fit to a value of 3.5 for
visual acuity.)
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“His daughter asks him if a pickup for grocery shopping next Monday, 4 pm is okay for him, but
since he has visitors at the time; he presses the button “record message” to record a reply to his
daughter. The Net TV tells him that he can start to record after the „beep“; and also tells him how
to stop the recording when he is finished.”
Similar to the explanation above speech recognition is activated by the generic design
pattern that is selected for answering the email.
“Arthur waits for the „beep“ and starts to speak his message. After the email is sent, a written
dialogue pops up to ask Arthur if the changes made to the interface while using the Net TV were
acceptable to him.”
Obviously, the self-evaluation interface that pops up at the end is based in a different selfevaluation application; and is not necessarily part of the email application. Every
application that is serving a specific user and knows this user’s id has access to the
individual user profile and is able to adapt it via the interfaces to the user’s profile.
Considering this, the self-evaluation application should probably not present its content as
text and instead better request an appropriate interface from the adaptation engine.
Considering the current user profile of Arthur, this interface would probably not be based
on text.
Other Scenarios
This section provides a brief overview about all the other demonstrator scenarios presented in D4.1
and describes the role of the context manager in those scenarios.
Please note that the “Reading Emails and Messages” scenario has already been discussed in the
previous section and is not considered again in this section.
5.2.1 Virtual User Lab
In the Virtual User Lab scenario, a company is using MyUI Virtual User Lab to evaluate and test
an application.
In relation to the user profile the scenario mentions that the company should be able to test user
interfaces and application with different user profile instances. Also it should be possible to
experiment with different values for different user profile variables. MyUI’s open web service
based architecture makes it easily possible to create and update user profiles; even by just reusing
an existing context manager instance that is hosted remotely. Currently, though, only an API is
provided to interact with the user profile. To further enhance usage, a web-based user interface for
handling the context manager might be necessary. This will be considered in later stages of
5.2.2 User Adaptive Connected Television Interface
This scenario exemplifies the capabilities of an interactive television set up as part of a MyUI
One aspect of the scenario, exemplifies how such a television can be used in an initial assessment
of the user capabilities. This initial assessment can lead to a very reliable initial user profile.
Although, this initial assessment software is not provided by the MyUI context manager, the
resulting user profile can easily be instantiated and stored for the particular user for reasons
mentioned above.
Additionally, the scenario indicates that two different user profiles should be available and that it
must be possible to switch from one user profile to the other just by providing a different user id;
through, for example, holding the users RFID card in front of the RFID-reader. Since the context
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manager does not restrict the number of user profiles, this is possible. The possibility of hosting the
user profile remotely on a web server makes it also possible to have one user profile that can be
“used” in different MyUI installations.
5.2.3 Cognitive Games
The cognitive games scenario, in its current form, gives no rise to any specific concerns in relations
to the user profile, besides those already mentioned in the sections above.
5.2.4 Supporting Physiotherapists in Customizing and Monitoring Progress of Stroke Patients
This scenario shows how the MyUI system can support physiotherapist and patients in instantiating
a regular customized exercise regime.
In relation to the context manager this scenario has lot of interesting implications. Foremost it
shows an application that is configured by the physiotherapist that is later on used in the home
installation of the patient. Since the general MyUI architecture is designed around the idea of
providing remote access, it is no problem for the physiotherapist to create a new user profile based
on his initial assessment of the patient from his medical practice. The MyUI installation in the
home of the patient will later on access this user profile as well. Of course, it is also always
possible to host everything on one computing device in the home of the user as it is indicated in the
Additionally, the scenario indicates the need for an application data management. Since not only
the user profile, but also some information on the exercise schedule are configured by the
physiotherapist. The exercise application can store this information in the application data manager.
Please note that the application is responsible to handle application specific data. Currently, only
the responsibility for storage of that data can be shifted to the context manager; especially a user
interface for accessing the data must be provided by the exercise application. Also, the application
data manager does only allow for storage of key-value pairs. Storing of videos, sounds or images is
not possible. Based on the we-based architecture of the system this is not considered a problem,
since, for example, the exercise videos can be stored at any URL and the URL can be stored as part
of the application specific data.
5.2.5 Stroke Patient Physiotherapy Reinforcement
In relation to the context manager, this scenario adds an aspect of automatic exercise recognition to
the scenario analysed above. Automatically evaluating several exercises, adapting the exercise
regime and individual exercises based on that evaluation and giving tailored recommendation to the
user is an extremely complex and application specific task. Such extremely specific reasoning
algorithms are usually highly dependent on a particular sensor infrastructure layout that is
providing the data. This makes it difficult to share such extremely specific algorithms. But the open
sensor data manager interfaces and the web-based design on the context manager do at least not
prohibit a sharing of complex recognition algorithms. Also in contrast to other ontology languages
the MyUI ontologies do not (pre)define what types of reasoning can be applied to context
information (for example, to the OWL ontology language already incorporates reasoning based on
a subset of the predicate calculus). This feature that is inherited from the underlying openAAL
framework makes it, in principle, possible to integrate different reasoning algorithms.
5.2.6 Supporting Healthy Exercise for the Elderly and Digital Picture Frames
In relation to the context manager, these two scenarios do not offer any additional insights into the
usage of the context manager.
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6. Conclusion
This document presented the concepts behind the context ontology and context management
architecture. Further, a detailed look on the MyUI scenarios indicates that model and architecture
do indeed fit the MyUI demands. As already mentioned the results presented in this document are
not complete at the moment, since the development in MyUI follows an iterative process. The
focus concentrates on the rapid development of an early prototype for M12, so that modelling,
implementation and scenario refinement will continue. Small adjustments will be made to the
approach where necessary. However, the presented approach to MyUI context management is
simple and therefore flexible which make further adaptations easy to apply.
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Peter Wolf, Andreas Schmidt, Michael Klein: Applying Semantic Technologies
for Context-Aware AAL Services: What we can learn from SOPRANO.
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Thesis. 2009
Andreas Schmidt. Ontology-based User Context Management: The Challenges of
Dynamics and Imperfection. In Robert Meersman and Zahir Tahiri, editors, On the
Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and
ODBASE. Part I., volume 4275 of Lecture Notes in Computer Science, pages
995–1011. Springer, 2006.
Steffen Staab and Rudi Studer. 2009. Handbook on Ontologies (2nd ed.). Springer
Publishing Company, Incorporated.
Sebastian Rollwage Kresser, Michael Klein and Peter Wolf. Collaborating context
reasoners as basis for affordable AAL Systems. In: 4rd Workshop on Artificial
Intelligence Techniques for Ambient Intelligence (AITAmI09), 2009.
Peter Wolf and Andreas Schmidt and Michael Klein, Applying Semantic
Technologies for Context-Aware AAL Services: What we can learn from
SOPRANO; Workshop on Applications of Semantic Technologies 09, Informatik
Peter Wolf, Andreas Schmidt, Javier Parada Otte, Michael Klein, Sebastian
Rollwage, Birgitta König-Ries, Torsten Dettborn, Aygul Gabdulkhakova
openAAL - the open source middleware for ambient-assisted living (AAL) In:
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Anind Dey, Gergory Abowd; Toward a better understanding of context and
context-awareness; In HUC ’99: Proceedings of the 1st international symposium
on Handheld and Ubiquitous Computing
Sergey Sosnovsky, Darina Dicheva; Ontological technologies for user modeling;
Int. J. Metadata, Semantics and Ontologies, Vol. 5, No. 1, 2010
Terry Winograd; Architectures for Context;
INTERACTION, 2001, Volume 16, pp. 401–419
Hayes-Roth, B.; A blackboard architecture for control; Artificial
Intelligence, 1985, 26, 251-321.
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Browne, D.; Totterdell, P.
Oppermann (1994) Oppermann, R. (1994): Adaptively supported daptability.
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Jameson, A. (2001): Systems that adapt to their Users. Tutorial
presented at IJCAI 2001. Saarbrücken: German Research Center for Artificial
Intelligence (DFKI)
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Information und Dokumentation (5th completely revised edition), München, K. G.
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Schwartz, Boris Brandherm, Michael Schmitz, Margeritta von WilamowitzMoellendorff; User Modeling 2005 (2005), pp. 428-432
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Appendix A – Email Client Scenario Stories
UI/Screen ÆUser action
System knowledge Æsensors
start Net TV
Arthur wants to use his new Net TV to see if his daughter
has sent him an email. He starts the Net TV by pressing
the „on“-Button on his remote of which he knows the
Arthur selects the email service by choosing the relevant
button on the screen by pressing the according number on
the remote.
The screen shows 3 Messages with the name of the
sender and the subject of the mail in big letters but Arthur
cannot read both of the texts.
He tries to get nearer to the Net TV (leans forward) to see
if he might be able to read the text from a lesser distance.
The Net TV recognizes his movement and increases the
font size.
Still, Arthur cannot read the texts so he tries to decrease
the distance again.
The NetTV sees that it does not help to increase the font
size any further and switches to pictures of the sender and
a button to open the mail.
HOME Screen (due to required
font size 30pt only half the options
4 big buttons (apps) with the
according key numbers on the
remote, additional navi button
„next page“
Due to some configuration the
system knows that Arthur has
problems in reading text with a
font size less than 30pt.
Num. Key press: email application
INBOX (3 messages)
Per item: #, name of sender,
subject of the mail in text (40pt),
font size > 30pt
additional navi button „next page“
decreases distance to Net TV
INBOX (3 messages)
Per item: #, name of sender,
subject of the mail in text (40pt),
font size > 40pt
additional navi button „next page“
decreases distance to Net TV
Recognize reduced user distance
INBOX (2 messages)
Per item: #, name of sender,
subject of the mail in text (50pt),
font size > 50pt
additional navi button „next page“
Artur recognizes one of the pictures as his daughter and
presses the according button on the remote.
No user action > 30sec
INBOX (2 messages)
Per item: #, picture of sender,
subject (text 50pt)
The Net TV switches to the message screen where the
text as well as a button to read the message and different
reply buttons are shown.
The message is read by the system (Text2Speach)
automatically. After the system has read him his
daughters message he also describes the options
available to Arthur (audio menu).
His daughter asks him if a pickup for grocery shopping
next Monday, 4 pm is okay for him, but since he has
visitors at the time, he presses the button “record
message” to record a reply to his daughter. The Net TV
tells him that he can start to record after the „beep“ and
also tells him how to stop the recording when he is
finished. Arthur waits for the „beep“ and starts to speak his
additional navi button „next page“
chooses a message (number key press)
Email read out (TTS) and
displayed (30pt font size)
Options (read and Buttons: icons
or text 50 pt):
„repeat message“, „yes“, „no“,
„record reply“
Number key pressed: record message
Audio instructions (talk and stop)
Display button „stop recording“
(incl. keypad reference) – icon/text
Number key pressed: stop recording
Same screen, additionally:
After the email is sent, a written dialogue pops up to ask
Arthur if the changes made to the interface while using the
Net TV were acceptable to him.
Options (read and buttons: icons/
text 50pt):
"playback reply", „back", "record
new message", „send“
TTS, Answering options:
„yes“, „no“
Number key pressed: send reply
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Presence recognition & time-out
Prefer pictures/icons and audio
over text = true
(no font whenever possible)
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Appendix B – Glossary of terms in MyUI
1. User model
The knowledge about the MyUI user and relevant context conditions is represented by an ontology
of user interaction capabilities and constraints. As the main purpose of the MyUI user model is
serving as a basis for user interface adaptations, perceptual, cognitive and motor user characteristics
are deliberately defined in terms of interaction capabilities and constraints rather than on the level
of medical diagnoses.
2. Classification of user models
According to [Dieterich et al., 1993]9 there are three major criteria to distinguish user models:
granularity, temporal extent and representation.
In MyUI, a pragmatic, function-based, common user model for all users is applied. Within the
MyUI user model, user and context characteristics which are relevant in order to adapt the user
interface to users’ needs and preferences are stored and updated. As the MyUI project focuses
primarily on the target user groups of older people and stroke survivors, the current version of the
user model is directed towards these (very heterogeneous) user groups. Hence, the MyUI user
model meets the criteria of granularity (by the common user model for all users – also named
canonical) and temporal extent (by storing the user characteristics beyond the session’s duration –
the so-called long-term user model approach).
A further classification dimension can be the purpose of user modelling. Possible purposes include:
* simulation (e.g. for illustration and evaluation purposes)
* diagnosis
* personalisation (e.g. user interface adaptation, recommender systems, personalised marketing and
MyUI concentrates on individual user interface adaptation, basic simulation approaches are
covered as a secondary target.
3. Application domains covered
MyUI application fields are:
- interactive TV platform services
- healthy exercise
- social communication
- entertainment
- accessibility support for developers and designers
- support for caregivers to create customised exercises
4. User Profile
According to ISO 9241-129 (Guidance on software individualization), paragraph 3.6, a user profile
is defined as a set of attributes used by the system that are unique to a specific user/user group [ISO
9241-151:2008, 3.19].
In MyUI, individual user profiles are derived from the general user model and initial values are
assigned to all attributes provided by the user model. User profile attributes are continuously
updated over time based on the analysis of new sensor data and the individual user’s interaction
9 [Dieterich et al., 1993] H. Dieterich, U. Malinowski, T. Kühme, M. Schneider-Hufschmidt: State
of the Art in Adaptive User Interfaces, Adaptive User Interfaces: Principles and Practice, Elsevier
Science Publishers, 1993, pp. 13-48.
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5. Virtual User
A virtual reality-based representation of an instance of the user model (i.e. a virtual user profile).
6. Virtual Human
A digital human model that may be used to simulate the behaviour and actions of a physical user.
However, simulation is not the main purpose of the MyUI project.
7. Simulation
In MyUI, simulation is understood as a time-based sequence of user interface events that mimics
the behaviour and interaction patterns, actions and sensor readings of a real-life situation for the
purpose of evaluating interface adaptation techniques.
8. Model Validation (Metrics and Process)
Model validation in MyUI is primarily done with regard to the self-adaptive ICT applications
provided by the MyUI system. This is explicitly covered by enabling the user to access and modify
its user profile at any time as needed. Additionally, the foreseen feedback loops to the user in case
of adaptation of the user interface is also considered as an implicit way of model validation during
user interaction with a MyUI application. Thereto different options of adaptation could be offered
to the user or his confirmation could be asked for.
A further indirect way of user model validation can also be included in some of the planned user
studies by collecting established usability and user acceptance measures during the use of MyUI
9. Interface Adaptation
A recurrent, self-controlled process of changing the user interface design at runtime based on
updates in the user profile. This aims at leading to a stepwise improvement of the individual user
interface design according to the user’s needs and preferences.
10. Profile Adaptation
According to [Dieterich et al., 1993]10 incremental updates of the user profile can be either done by
the user or by the system. In MyUI, the refinement of the user profile is controlled by the system.
Each time when new findings are gained from processed sensor input or the current user interaction
behaviour, the MyUI user profile is refined. In this way, the accuracy of a specific user profile is
aimed to be continuously improved at runtime.
Note: MyUI user profiles result from complex sensing/recognition and interpretation algorithms
which are error prone. Therefore, the current values of a MyUI user profile are inherently
probabilistic and have a considerable level of uncertainty. This contrasts to other (more diagnosisoriented) user profiling approaches where user profiles can be determined with much higher levels
of reliability.
11. (User Interface) Design Pattern
Design patterns in MyUI cover all user interface design aspects that need to be adapted in order to
suit the different MyUI users’ requirements. Main components of a pattern include the problem
description, the context and the solution of a specific recurring design problem as well as
references and related patterns. Four different kinds of patterns are distinguished in MyUI:
1. Generic design patterns:
They translate user characteristics into user interface features which are set by global
variables. These features are stored in the user interface profile.
10 [Dieterich et al., 1993] H. Dieterich, U. Malinowski, T. Kühme, M. Schneider-Hufschmidt: State
of the Art in Adaptive User Interfaces, Adaptive User Interfaces: Principles and Practice, Elsevier
Science Publishers, 1993, pp. 13-48.
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2. Interaction design patterns:
They describe variants of controls or elements which are related to a specific interaction
situation and user interface profile.
3. Common patterns:
Basic features of MyUI user interfaces which do not change during the interface adaptation
process are specified in these patterns.
4. Transition patterns:
These describe how to switch between single patterns of a bundle of related generic or
interaction design patterns.
12. User Interaction
User interaction in MyUI is the direct way a user communicates with the applications of the MyUI
system by means of one of the supported input devices. Besides the input from input devices, the
analysis of more “implicit” user interaction is an essential element to determine changes in the user
profile. “Implicit human-computer interaction” refers to human behaviour and actions that are not
explicitly directed towards a computer interface and are recognized and interpreted as a trigger of
system reactions. Examples from the MyUI project include gestures (e.g. lean-to-screen), head
position and gaze direction, time-out, etc.
13. Disablility, capabilities and functional limitations
A note on this contribution:
‘Impairment’ has been added as an additional glossary term, as this is used repeatedly throughout
MyUI documents and is used more widely in conjunction with disability to give nuance to the
different facets of disabled experience. As there is no universally agreed theory of disability, the
following glossary entries draw upon several different epistemologies (the bio-psycho-social model
and the capability approach) to pragmatically account for those facets of disability that are most
relevant to the project. These terms aim to use an ability, rather than deficit, model. For this reason,
Functioning Limitation is re-defined as Functioning. An additional glossary entry for Functioning
Limitation could be added, but we think this is self explanatory – and Impairment may represent a
more accessible term for the same meaning. References are added for information.
Glossary entries:
Capability identifies the freedom of the individual to achieve valuable functionings in a given
circumstance. In this way, capability is not the presence of a physical or a mental ability; instead, it
is understood as a practical opportunity.
(Drawing on: Sen, A. (1999: 74), Development as Freedom. Oxford: Oxford University Press and
Mitra, S. (2006:54) The Capability Approach and Disability, Journal of Disability Policy Studies
2006 16: 236)
Disability is a disadvantage or marginalisation that results from the interaction between people
with impairments and the attitudinal and environmental barriers that obstruct their equal
participation in society. Disability is a social construct, not an attribute of an individual. Society
and context determine who experiences disability.
(Abridged and expanded from UN Convention on the Rights of Persons with Disabilities).
Functioning identifies the cognitive and physical actions available to an individual.
(Based upon WHO (2002) Towards A Common Language For Functioning, Disability and Health
International Classification of Functioning, Disability and Health)
Impairment identifies a physical, sensory or cognitive limit that reduces functioning.
(adapted from WHO, 2002)
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