1. INTRODUCING CULTURAL PROMPTS IN A SEMANTIC
DATA BROWSER
Dhaval Thakker, Vania Dimitrova, Gaye Ediboğlu
International Workshop on Intelligent Exploration of Semantic Data
SD) 2012

2. Exploitation of digital traces
as a source for informal learning

3. Exploitation of digital traces
as a source for informal learning
Exploration
Environment
digital
traces
digimind.com
Taming Semantic Web Technologies
•Retrieve • Semantic Data browsers
•Aggregate • Semantic Nudges
•Organise

4. Semantic Data Browser
Focus Concept
Facts
Eye Contact is Body Language
Social
Content

5. Semantic Data Browser

6. Processing Pipeline:
Semantic Data Browser
Digital Traces
Collection
Semantic
Augmentation &
Browsing &
Query Interaction
Bespoke
Ontologies Ontology
& Linked Underpinning
Data Cloud

7. Semantic Data Browser for
Learning
• Data browsers Limitations:
• Cognitive onus on Learner
• Not always possible to decide best course of action
for him/her.
•Influence options in a way that
will support choosers to act in
their own interest, preserving
freedom of choice
•Signposting & Prompts
Thakker, D., Dimoklis, D.,Dimitrova, V., Lau, L., Brna, P. (2012) Taming Digital Traces for Informal Learning: A
Semantic-Driven Approach. EC-TEL 2012, pp. 348--362. Springer, Heidelberg, Saarbrücken (Germany), 18 - 21
September 2012.

8. Semantic Nudges:
Signposting

9. Semantic Nudges: Prompts

10. So far…Semantic Data Browser
Interaction Digital Traces +
User: Country of origin, visited, Focus Semantic Tags
residence
Semantic Data Browser
Digital Traces Ontology

11. • Hofstede: “[culture is] the collective programming of the human
mind that distinguishes the members of one human group from
those of another. Culture in this sense is a system of collectively
held values.” [12].
• National culture is fundamental for distinguishing the people of
one country from other people from other countries.
• Intercultural communication – cultural differences in terms of
personal distance, gestures, body language, norms
http://geert-hofstede.com/geert-hofstede.html

12. Culture awareness & Exposure
• Cultural awareness is “..
understanding some key facts
about a particular culture”.
• Cultural exposure is
experience of culture by
visit/origin/residence.
• Aim: Inform users about
cultural aspects (basics,
intercultural dimensions –
such as gestures)

13. Cultural Models for National
Cultures: Hofstede Model
http://geert-hofstede.com/national-culture.html

14. Power Distance
(The degree to which power differentials within society and
organizations are accepted.)

15. United Kingdom & China
IDV LTO
In Individualist The extent to
societies people which a society
are supposed to shows a
look after pragmatic
themselves and future-oriented
their direct perspective
family only. rather than a
conventional
In Collectivist historical short-
societies people term point of
belong to ‘in view.
groups’ that take
care of them in
exchange for
loyalty.

16. Stereotypical Information from
Hofstede model - for UK
• Power distance
• At 35 Britain sits in the lower rankings of PDI – i.e. a society that believes that
inequalities amongst people should be minimized.
• Individualism
• At a score of 89 the UK is amongst the highest of the individualistic scores, beaten only
by some of the commonwealth countries it spawned i.e. Australia and the USA.
• Masculinity / Femininity
• At 66 Britain is a masculine society – highly success oriented and driven. A key point of
confusion for the foreigner lies in the apparent contradiction between the British culture
of modesty and understatement which is at odds with the underlying success driven
value system in the culture.
• Uncertainty avoidance
• At 35 the UK has a low score on uncertainty avoidance which means that as a nation
they are quite happy to wake up not knowing what the day brings and they are happy to
‘make it up as they go along’ changing plans as new information comes to light.
• Long term orientation
• At 25 the UK scores as a short term oriented society which drives a great respect for
history and tradition as well as a focus on quick results in the future.

17. Grouping countries in clusters
for measuring exposure to more abstract
level
• Hofstede Model: K-mean Clustering
Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5
Netherlands, El Salvador, Turkey, China, Indonesia, Malaysia, Panama, Mexico,
Chile, Portugal, Ghana, Nigeria,
Norway, Sweden, Philippines, India Venezuela,
Uruguay, Greece, Singapore, Hong
Denmark, Finland Spain Ecuador,
Kong, Kenya Colombia
Cluster 6 Cluster 7 Cluster 8 Cluster 9 Cluster 10
Egypt, Iraq, Kuwait, France, Poland, USA, Australia, UK, South Africa, Peru, Thailand,
Lebanon, Libya, Belgium, Czech Ireland, New Germany, Pakistan, Taiwan,
UAE, Saudi Arabia, Republic, Japan, Italy, Zealand Switzerland, Austria South Korea
Brazil, Iran Argentina, Hungary
Available from : http://imash.leeds.ac.uk/publications/support/culturalprompts/

18. National Culture Models: Globe
project
• Cross-cultural research effort – wider in scope,
depth, duration.
• Nine units of measurement – cultural
dimensions
Performance Uncertainty Humane
Orientation Avoidance Orientation
Institutional In-Group
Assertiveness
Collectivism Collectivism
Gender Future
Power Distance
Egalitarianism Orientation
http://www.grovewell.com/pub-GLOBE-intro.html

19. Globe Cultural Model: Clusters
Anglo - 7 Latin Europe - 6
Nordic Europe - 3 Germanic Europe - 5
Eastern Europe - 8 Latin America - 10
Sub-Saharan Africa - 5 Middle East - 5
Southern Asia - 6 Confucian Asia - 6

20. …Semantic Data Browser +
Cultural Model
Cultural Models
Culture dimensions Stereotypical Culture
Information clusters
Interaction Digital Traces +
User: Country of origin, visited, Focus Semantic Tags
residence
Semantic Data Browser
Digital Traces Ontology

21. User Model : Culture exposure of
user mapped to Cultural Models
• U = < Corigin, Cresidence, Cvisited, Ehof, Eglobe>
• Ehof & Eglobe = Mapping Corigin, Cresidence, Cvisited to Hofstede Clusters and Globe Clusters
• For example, a user who has visited Egypt, Iraq, Kuwait, Lebanon, Libya,
India
Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5
Netherlands, El Salvador, Turkey, China, Indonesia, Malaysia, Panama, Mexico,
Chile, Portugal, Ghana, Nigeria,
Norway, Sweden, Philippines, India Venezuela,
Uruguay, Greece, Singapore, Hong
Denmark, Finland Spain Ecuador,
Kong, Kenya 33% Colombia
Cluster 6 Cluster 7 Cluster 8 Cluster 9 Cluster 10
Egypt, Iraq, Kuwait, France, Poland, USA, Australia, UK, South Africa, Peru, Thailand,
Lebanon, Libya, Belgium, Czech Ireland, New Germany, Pakistan, Taiwan,
UAE, Saudi Arabia, Republic, Japan, Italy, Zealand Switzerland, Austria South Korea
Brazil, Iran Argentina, Hungary
56%

22. …Semantic Data Browser +
Cultural Model + User Model
User Model Cultural Models
User Model Culture dimensions Stereotypical Culture
Information clusters
Interaction Digital Traces +
User: Country of origin, visited, Focus Semantic Tags
residence
Semantic Data Browser
Digital Traces Ontology

23. …Semantic Data Browser + Cultural
Model + User Model = Prompt Model
User Model Cultural Models
User Model Culture dimensions Stereotypical Culture
Information clusters
Prompt Model
Interaction Digital Traces +
User: Country of origin, visited, Focus Semantic Tags
residence
Semantic Data Browser
Digital Traces Ontology

24. Goals of Prompts
• G1. Create awareness of cultural aspects. In the cases when the
evidence (from user model) suggests that no exposure to a particular
cultural cluster exist, i.e. Ehof<ClusterHofi, Val) ∧ Val = ϕ ∨ Eglobe<ClusterGloi,
Val) ∧ Val = ϕ.
• G2. Expand awareness on certain cultural aspects. In the cases when
the evidence (from user model) suggests that there is a limited
exposure to a particular culture cluster, where the limit is some
threshold θ
• G3. Reflect on cultural awareness. In the cases when the evidence
(from user model) suggests that there is good exposure to a particular
culture cluster

25. Prompt Model: Using User
Model, Globe Model
• User Model: No exposure to Globe cultural
cluster (‘Eastern Europe’)
• General Goal: Create Awareness
• Aim: to create awareness for the ‘Eastern
Europe’ cluster and influence the content user
browses.

26. Prompt Model: Using User
Model, Globe Model

27. Prompt Model: Using User
Model, Hofstede Model
• User Model: The user has exposure to countries with
contrasting power distance index (PDI- as defined by
Hofstede)
• General Goal: Create Awareness
• Aim: to create awareness by informing about contrasting PDI

28. Prompt Model: Using User
Model, Hofstede Model
• User Model: The user has exposure to countries with
contrasting power distance index (PDI- as defined by
Hofstede)
• General Goal: Create Awareness
• Aim: to create awareness by informing about contrasting PDI

29. Prompt Model: Using Interaction
Focus, Hofstede/Globe Model
• Interaction Focus: The user is at an Entity page, that contains
comment mentioning countries.
• Condition: countries mentioned in comment are within a
cluster
• Specific Goal: Inform the user about countries belonging to a
specific cluster

30. Future work
• Prompt Model
– Type of the prompts and list so far is what can be
generated
– Which prompt to display & when (e.g. more than
one matching specific goal) is not worked out yet
– “WHAT, HOW” is answered but not “WHEN”
– Interaction history can be important
– Evaluation

31. 1. Learning context:
– Informal Learning is important
– Social spaces and user generated content offer
new opportunities
2. Technology:
– Semantic Nudges to empower exploration in
Semantic Data Browser
– Cultural Prompts for introducing cultural aspects in
semantic data browser
Thank You!
Dr Dhaval Thakker, Research Fellow, University of Leeds
D.Thakker@leeds.ac.uk
http://www.imreal-project.eu/