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The MIRROR User Profile: A Concept
for App-independent User Modelling
and Support
Angela Fessl, Gudrun Wesiak,
Marina Bratic and Granit Luzhnica
KNOW-Center GmbH

© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu
MIRROR – Reflective Learning at Work

Informal
learning in the
workplace
through
reflection on
work experience.
Scientificpartners

EU IST FP7 Integrated Project

© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu

Test-bedpartners
User models

User
models

• A model of a user in a
computer system

Learner models

• A user model in a
learning environment

Open learner
models

• A learner model where
users have full access
to their data

MIRROR user
profiles

• Based on open learner
models extended for
reflective learning

© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu
MIRROR User Profiles

MIRROR user profiles
Data from
MIRROR Apps

Data from
MIRROR Users

Experiences, activities, artefacts of work,
moods, notes, insights, workpractices,
sensordata, ...

© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu
MIRROR User Profile Concept
•Huge data sets
•Reusability and sharing
•Privacy and security
•Accessibility via user interfaces

MIRROR
MIRROR
MIRROR
MIRROR
Apps
Apps
Apps
App

© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu

MIRROR
Spaces
MIRROR User Profile Concept

MIRROR
MIRROR
MIRROR
Apps
MIRROR
Apps
Apps
App

Reflection
Analysis
Service

Prompting
Service

Data
Administration Service

Service Layer

© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu

User Profile
Service

User
ProfilesApp

MIRROR
Spaces
MIRROR User Profile Concept

MIRROR
MIRROR
MIRROR
Apps
MIRROR
Apps
Apps
App

Reflection
Analysis
Service

Prompting
Service

Data
Administration Service

User Profile
Service

User
ProfilesApp

Service Layer

The reflection analytics service …
• aggregates data from different apps
• compares data along a timeline and/or different users
• detects patterns to create triggers for reflection
Development:
1. Statistical analysis
2. Analysis of data captured by various apps
© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu

MIRROR
Spaces
MIRROR User Profile Concept

MIRROR
MIRROR
MIRROR
Apps
MIRROR
Apps
Apps
App

Reflection
Analysis
Service

Prompting
Service

Data
Administration Service

User Profile
Service

User
ProfilesApp

Service Layer

The prompting services…
• is filled with detected triggers by the reflection analysis
service
• delivers prompts to the Apps

© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu

MIRROR
Spaces
MIRROR User Profile Concept

MIRROR
MIRROR
MIRROR
Apps
MIRROR
Apps
Apps
App

Reflection
Analysis
Service

Prompting
Service

Data
Administration Service

User Profile
Service

User
ProfilesApp

Service Layer

The data administration service…
• serves as interface between Apps and MUP
• takes the data from the Apps and stores it in the
spaces.
• fetches information from the spaces that are requested
by the Apps.
© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu

MIRROR
Spaces
MIRROR User Profile Concept

MIRROR
MIRROR
MIRROR
Apps
MIRROR
Apps
Apps
App

Reflection
Analysis
Service

Prompting
Service

Data
Administration Service

User Profile
Service

User
ProfilesApp

Service Layer

The User Profile Service …
• administers general user information in the spaces and
in the Apps
The User Profile App …
• gives users full control over their data
© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu

MIRROR
Spaces
MIRROR
ReflectiveLearning
at Work
DI Angela Fessl
afessl@know-center.at

Know-Center GmbH
Inffeldgasse 13
8010 Graz
http://www.mirror-project.eu/

© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu
© MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu

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MIRROR user profile concept

  • 1. The MIRROR User Profile: A Concept for App-independent User Modelling and Support Angela Fessl, Gudrun Wesiak, Marina Bratic and Granit Luzhnica KNOW-Center GmbH © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu
  • 2. MIRROR – Reflective Learning at Work Informal learning in the workplace through reflection on work experience. Scientificpartners EU IST FP7 Integrated Project © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu Test-bedpartners
  • 3. User models User models • A model of a user in a computer system Learner models • A user model in a learning environment Open learner models • A learner model where users have full access to their data MIRROR user profiles • Based on open learner models extended for reflective learning © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu
  • 4. MIRROR User Profiles MIRROR user profiles Data from MIRROR Apps Data from MIRROR Users Experiences, activities, artefacts of work, moods, notes, insights, workpractices, sensordata, ... © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu
  • 5. MIRROR User Profile Concept •Huge data sets •Reusability and sharing •Privacy and security •Accessibility via user interfaces MIRROR MIRROR MIRROR MIRROR Apps Apps Apps App © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu MIRROR Spaces
  • 6. MIRROR User Profile Concept MIRROR MIRROR MIRROR Apps MIRROR Apps Apps App Reflection Analysis Service Prompting Service Data Administration Service Service Layer © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu User Profile Service User ProfilesApp MIRROR Spaces
  • 7. MIRROR User Profile Concept MIRROR MIRROR MIRROR Apps MIRROR Apps Apps App Reflection Analysis Service Prompting Service Data Administration Service User Profile Service User ProfilesApp Service Layer The reflection analytics service … • aggregates data from different apps • compares data along a timeline and/or different users • detects patterns to create triggers for reflection Development: 1. Statistical analysis 2. Analysis of data captured by various apps © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu MIRROR Spaces
  • 8. MIRROR User Profile Concept MIRROR MIRROR MIRROR Apps MIRROR Apps Apps App Reflection Analysis Service Prompting Service Data Administration Service User Profile Service User ProfilesApp Service Layer The prompting services… • is filled with detected triggers by the reflection analysis service • delivers prompts to the Apps © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu MIRROR Spaces
  • 9. MIRROR User Profile Concept MIRROR MIRROR MIRROR Apps MIRROR Apps Apps App Reflection Analysis Service Prompting Service Data Administration Service User Profile Service User ProfilesApp Service Layer The data administration service… • serves as interface between Apps and MUP • takes the data from the Apps and stores it in the spaces. • fetches information from the spaces that are requested by the Apps. © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu MIRROR Spaces
  • 10. MIRROR User Profile Concept MIRROR MIRROR MIRROR Apps MIRROR Apps Apps App Reflection Analysis Service Prompting Service Data Administration Service User Profile Service User ProfilesApp Service Layer The User Profile Service … • administers general user information in the spaces and in the Apps The User Profile App … • gives users full control over their data © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu MIRROR Spaces
  • 11. MIRROR ReflectiveLearning at Work DI Angela Fessl afessl@know-center.at Know-Center GmbH Inffeldgasse 13 8010 Graz http://www.mirror-project.eu/ © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu
  • 12. © MIRROR Project – Co-fundedby EU IST FP7 – www.mirror-project.eu

Notas del editor

  1. IST ... Information Society and Technogies
  2. Purpose is to guide and support ...User profilesis to guide and support reflection by mirroring user data in the form of activities, experiences or artefacts of work, notes and insights, moods, work practices, and other concrete data sources back to the user Creation of user profiles is a mixture of automated methods and manual management - the process of editing or updating the captured data may be explicitly trigger reflection.
  3. Taking into account the analysation of the Y3 Apps, the results of the conducted evaluations as well as using the existing MIRROR spaces framework as underlying architecture and after having conducted a literature research – user models, learner models, open learner models and visualisaton of user models - we developed the MIRROR User Profile Concept!Datastored in the MUP can be divided into three different types, namely data about the user herself, private data, and shared data Data about the user: available to all Apps employed by this user and consists of general information about the user (e.g. name or email address) Data implicitly captured by the MIRROR Apps (e.g. contacts in CaReflect or work history in KnowSelf) as well as data explicitly inserted by the user (e.g. mood in the MoodMap or notes in a Virtual Tutor App) it is essential that the user has full control over her data by deciding for each type of captured data, whether it is private or can be shared. private data is only available for aggregations on an individual level, shared data can be used, reused, aggregated or visualized in corresponding Apps and for baselines For all shared data the user has to decide whether or not the data should be used anonymisedReusabilitymajor potential benefits of the MUP storing the data according to a defined data format, Apps are able to use and reuse data stored in the MUP shared data cannot only be reused by the App it was captured from, but also by other Apps and other users SharingSharingdata is of major relevance for reflection on the individual as well as on the collaborative and organisational level To account for different levels of sharing, settings should be very fine-grained. In order to differentiate between various types of data and ways of sharing, four different sharing options are relevant: (a) which data a user wants to share (e.g. moods are shared but not the corresponding notes), (b) for which purposes data is shared (e.g. for statistical purposes or for collaborative reflection), (c) how the data is shared (anonymously or not), and (d) with whom the data is shared Privacy and SecurityPrivacy and security are a major concern when storing data in the MIRROR spaces. - It has to be ensured that the privacy settings defined by the user via different Apps are met at all times and by all Apps. - Aggregations and visualisations based on private data should only be accessible by the individual user. - Under consideration of the specific sharing settings, shared data can be used for aggregations by all Apps and can be presented to a wider group of users (e.g. the team or the organization). - Additionally, the UP has to be secured by the developed MIRROR security arrangements. Accessibility to User Interfaces - MUP has to ensure for users complete accessibility and interaction with their data. - All MIRROR Apps have to provide user interfaces, which give users full control of their MUP and all data gathered explicitly or implicitly by the Apps. - The interface serves to manage sharing, privacy, and security settings and to visualize data.
  4. Taking into account the analysation of the Y3 Apps, the results of the conducted evaluations as well as using the existing MIRROR spaces framework as underlying architecture and after having conducted a literature research – user models, learner models, open learner models and visualisaton of user models - we developed the MIRROR User Profile Concept!Datastored in the MUP can be divided into three different types, namely data about the user herself, private data, and shared data Data about the user: available to all Apps employed by this user and consists of general information about the user (e.g. name or email address) Data implicitly captured by the MIRROR Apps (e.g. contacts in CaReflect or work history in KnowSelf) as well as data explicitly inserted by the user (e.g. mood in the MoodMap or notes in a Virtual Tutor App) it is essential that the user has full control over her data by deciding for each type of captured data, whether it is private or can be shared. private data is only available for aggregations on an individual level, shared data can be used, reused, aggregated or visualized in corresponding Apps and for baselines For all shared data the user has to decide whether or not the data should be used anonymisedReusabilitymajor potential benefits of the MUP storing the data according to a defined data format, Apps are able to use and reuse data stored in the MUP shared data cannot only be reused by the App it was captured from, but also by other Apps and other users SharingSharingdata is of major relevance for reflection on the individual as well as on the collaborative and organisational level To account for different levels of sharing, settings should be very fine-grained. In order to differentiate between various types of data and ways of sharing, four different sharing options are relevant: (a) which data a user wants to share (e.g. moods are shared but not the corresponding notes), (b) for which purposes data is shared (e.g. for statistical purposes or for collaborative reflection), (c) how the data is shared (anonymously or not), and (d) with whom the data is shared Privacy and SecurityPrivacy and security are a major concern when storing data in the MIRROR spaces. - It has to be ensured that the privacy settings defined by the user via different Apps are met at all times and by all Apps. - Aggregations and visualisations based on private data should only be accessible by the individual user. - Under consideration of the specific sharing settings, shared data can be used for aggregations by all Apps and can be presented to a wider group of users (e.g. the team or the organization). - Additionally, the UP has to be secured by the developed MIRROR security arrangements. Accessibility to User Interfaces - MUP has to ensure for users complete accessibility and interaction with their data. - All MIRROR Apps have to provide user interfaces, which give users full control of their MUP and all data gathered explicitly or implicitly by the Apps. - The interface serves to manage sharing, privacy, and security settings and to visualize data.
  5. Two phases:1: We will focus on statistical analysis to extract information regarding the number of different Apps used by a user, provide a chronological overview of the Apps used, present the number of entries in various diaries, and further statistical analyses. 2. We will concentrate on the different types of data captured by the various Apps, in order to provide analysis on the combination of data. Combining the usage of the MoodMap App with data captured by KnowSelf, or the IAA/IMA, would also lead to new insights regarding reflection.
  6. Closely connected to the reflection analytic service, is the prompting service (see D6.3), which has already been developed by WP6 and can be included in the various Apps. It provides the possibility to trigger users to perform a certain action or a task. This service can either be fed by the developers themselves, to show the prompts according to the captured data, or it can use the results of the reflection analytics service to give the user’s prompts via the related Apps.
  7. The data administration service basically serves as interface between Apps (and thus the users) and MUP. On the one side, the service takes the data from the Apps and stores it in the relevant spaces, on the other side it fetches information from the spaces that are requested by the Apps. Depending on the App, it could either visualize or use the data corresponding to the Apps tasks. For all data transfers the service has to account for security and privacy settings defined in MIRROR spaces and the MSAM.
  8. The User Profile Service administers general user information, using both the user profile features provided by the underlying XMPP framework and the MIRROR Spaces concept. It is linked to a User-Profile App, which gives users full control over their data. The User Profile Service also allows the user to specify his general privacy settings, i.e., settings that are applicable to all Apps (e.g. share aggregated data with team members only). Additionally, organizational structures can be set by defining different groups (e.g. team division vs. organization) which are then used as options for sharing the captured data. Further, more fine-grained privacy and sharing settings are highly App-dependent (i.e. which type of captured data is shared with whom and in which way) and are therefore stored within the App-profiles.