Accidental knowledge discoveries occur most frequently during capricious and unplanned search and browsing of data. This type of undirected, random, and exploratory search and browsing of data results in Serendipity – the art of unsought finding. In our previous work we extracted a set of serendipity-fostering design features for developing intelligent user interfaces on Semantic Web and Linked Data browsing environments. The features facilitate the discovery of interesting and valuable facts in (linked) data which were not initially sought for. In this work, we present an implementation of those features called FERASAT. FERASAT provides an adaptive multigraph-based faceted browsing interface to catalyze serendipity while browsing Linked Data. FERASAT is already in use within the domain of science, technology & innovation (STI) studies to allow researchers who are not familiar with Linked Data technologies to explore heterogeneous interlinked datasets in order to observe and interpret surprising facts from the data relevant to policy and innovation studies. In addition to an analysis of the related work, we describe two STI use cases in the paper and demonstrate how different serendipity design features are addressed in those use cases.

1. FERASAT
A Serendipity-fostering Faceted Browser for Linked Data
Ali Khalili, Peter van den Besselaar, Klaas Andries de Graaf
-
<http://ferasat.ld-r.org>

2. Anatomy of the Unsought Finding. Serendipity:
Origin, History, Domains, Traditions, Appearances,
Patterns and Programmability
- Pek van Andel, The British Journal for the Philosophy of Science, 1994

3. Anatomy of the Unsought Finding. Serendipity:
Origin, History, Domains, Traditions, Appearances,
Patterns and Programmability
- Pek van Andel, The British Journal for the Philosophy of Science, 1994

4. Anatomy of the Unsought Finding. Serendipity:
Origin, History, Domains, Traditions, Appearances,
Patterns and Programmability
- Pek van Andel, The British Journal for the Philosophy of Science, 1994

5. Anatomy of the Unsought Finding. Serendipity:
Origin, History, Domains, Traditions, Appearances,
Patterns and Programmability
- Pek van Andel, The British Journal for the Philosophy of Science, 1994
The Three Princes of Serendip

6. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 3Ali Khalili
Introduction
"Serendipiteit, de ongezochte vondst", Pek van Andel, ISBN 9789046817575
A correct interpretation
A surprising observation
Serendipity: the Art of Unsought Finding
P. van Andel. Anatomy of the unsought finding. serendipity: Origin, history, domains, traditions,
appearances, patterns and programmability. Br J Philos Sci, 45(2):631–648, June 1994.

7. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 4Ali Khalili
Serendipity in the wild
Introduction
- Most scientific breakthroughs have come out of serendipity.
- Serendipity has played a pivotal role in the discovery of many drugs.
- Major types of psychotropic drugs (effecting mental activity and behavior)
such as Lithium, Chlorpromazine and Imipramine were serendipitously
discovered in the 1950s and 1960s.
- 24% of all pharmaceuticals on the market and in particular 35.2% of all the
anticancer drugs in clinical use were discovered by serendipity*.
* E. Hargrave-Thomas, B. Yu, and J. Reynisson. The effect of serendipity in drug discovery and development. Chemistry in New Zealand, 2012.
https://youtu.be/CSDQc3qkXo4?t=16s

8. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 5Ali Khalili
The Importance of Serendipity in Data Science
Introduction
- The goal of Data Science is to gain insight from data and
to create new knowledge
- Data science is driven by hypotheses
- The more data and the more data variety, the more chance
encounter (thereby more hypotheses)
- Hypotheses of greater variety require a more complete search
of the space of data
Data Science Big Data AI

9. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 6Ali Khalili
Human-LinkedDataInteraction
Linked (Open) Data as a platform for Serendipity
http://lod-cloud.net
Introduction Serendipity Linked Data

10. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 7Ali Khalili
Human-LinkedDataInteraction
Introduction Serendipity Linked Data Example

11. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 7Ali Khalili
Human-LinkedDataInteraction
Universities
participatedIn
locatedIn
foundationYear
Projects
Locations
years
type
OrgTypes
subType
OrgSubTypes
funding
Funding
Programs
name names
country
Countries
partnerWith
Organizations
type
label
labels
years
closureYear
name
names
published
Publications
title
year
years
titles
ranking
Rankings
international
Collaboration
rankings
administrative
boundary Admin
Boundaries
code
polygon
codes
polygons
Resource
Object Value
Property
Dataset
An example of the Linked Data scattered over
multiple graphs (datasets) in the STI
(Science, Technology & Innovation) domain.
Introduction Serendipity Linked Data Example

12. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 8Ali Khalili
Human Data InteractionIntroduction
Three ways in which people discover and acquire information
during their interaction with a data space:
Information Retrieval
Toms, Elaine G. "Serendipitous Information Retrieval." In DELOS Workshop: Information Seeking, Searching and Querying in Digital Libraries, pp. 17-20. 2000.

13. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 8Ali Khalili
Human Data InteractionIntroduction
Three ways in which people discover and acquire information
during their interaction with a data space:
Information Retrieval
1. Purposive search
A directed search looking for a definite piece of information.
Toms, Elaine G. "Serendipitous Information Retrieval." In DELOS Workshop: Information Seeking, Searching and Querying in Digital Libraries, pp. 17-20. 2000.

14. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 8Ali Khalili
Human Data InteractionIntroduction
Three ways in which people discover and acquire information
during their interaction with a data space:
Information Retrieval
2. Exploratory search and browsing
A general purpose semi-directed search & browsing of data deliberately looking
for an object of interest that cannot be fully described
1. Purposive search
A directed search looking for a definite piece of information.
Toms, Elaine G. "Serendipitous Information Retrieval." In DELOS Workshop: Information Seeking, Searching and Querying in Digital Libraries, pp. 17-20. 2000.

15. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 8Ali Khalili
Human Data InteractionIntroduction
Three ways in which people discover and acquire information
during their interaction with a data space:
Information Retrieval
2. Exploratory search and browsing
A general purpose semi-directed search & browsing of data deliberately looking
for an object of interest that cannot be fully described
3. Capricious search and browsing*
An undirected random search & browsing of information without a defined goal.
*Accidental knowledge discoveries occur most frequently during this type of unplanned
investigative search and browsing.
1. Purposive search
A directed search looking for a definite piece of information.
Toms, Elaine G. "Serendipitous Information Retrieval." In DELOS Workshop: Information Seeking, Searching and Querying in Digital Libraries, pp. 17-20. 2000.

16. 9Ali Khalili FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
40 Patterns of Serendipity by Pek van Andel
One single surprising observation is done and correctly explained Heaping of cases
Several different surprising observations reveal the same surprising phenomenon
One surprising observation of an analogy in the sàme context
One surprising observation of an analogy in a different context
Bionics Inverted bionics
A surprising observation through ‘personal analogy’ A surprising observation thanks to a crucial new
scientific instrument
A surprising observation with a control
A surprising observation in a control
A surprising observation done by A, correctly explained by B
Predicted by A, and independently ànd surprisingly found by B
Two different surprising observations made by two different observers lead to the same finding
Successful error
Successful error of an assistant
Successful accident
From side-effect to main effect
From byproduct to main product
Experiment of nature
Alternative use
‘Wrong’ hypothesis offers a surprising observation
Inversion
Enigma
‘Folklore’ as source of surprises
Animal, child, student, outsider
A crucial chance encounter between expertsDisturbance as source a surprising observation
Quantitive anomalies
Scarcity
An improvisation becomes eternal
Interruption of work
Play leads to the surprise
Joke leads to novelty‘Hasard intime, de lecture, et de la plume’
The surprising finding appears revolutionary
An unexpected effect of a wanted intervention
Supposed serendipity, presented as true
Fabricated serendipity
Serendipity applied, but nòt noticed as such by the finder himself
Serendipity Patterns

17. 9Ali Khalili FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
40 Patterns of Serendipity by Pek van Andel
One single surprising observation is done and correctly explained Heaping of cases
Several different surprising observations reveal the same surprising phenomenon
One surprising observation of an analogy in the sàme context
One surprising observation of an analogy in a different context
Bionics Inverted bionics
A surprising observation through ‘personal analogy’ A surprising observation thanks to a crucial new
scientific instrument
A surprising observation with a control
A surprising observation in a control
A surprising observation done by A, correctly explained by B
Predicted by A, and independently ànd surprisingly found by B
Two different surprising observations made by two different observers lead to the same finding
Successful error
Successful error of an assistant
Successful accident
From side-effect to main effect
From byproduct to main product
Experiment of nature
Alternative use
‘Wrong’ hypothesis offers a surprising observation
Inversion
Enigma
‘Folklore’ as source of surprises
Animal, child, student, outsider
A crucial chance encounter between expertsDisturbance as source a surprising observation
Quantitive anomalies
Scarcity
An improvisation becomes eternal
Interruption of work
Play leads to the surprise
Joke leads to novelty‘Hasard intime, de lecture, et de la plume’
The surprising finding appears revolutionary
An unexpected effect of a wanted intervention
Supposed serendipity, presented as true
Fabricated serendipity
Serendipity applied, but nòt noticed as such by the finder himself
Serendipity Patterns

18. 9. Facilitate the explanation of surprising observations.
10. Allow sharing of surprising observations among multiple users.
11. Enable reasoning by analogy.
12. Support extending the memory of user by invoking provocative reminders and relevance feedback.
10Ali Khalili
Design Features Related to Explanation of the Observations
Design Features Related to Observations
1. Make surprising observations more noticeable.
2. Make errors in data more visible in order to detect successful errors easier.
3. Allow inversion and contrast.
4. Support randomization and disturbance.
5. Allow monitoring of side-effects when interacting with data.
6. Support detection and investigation of by-products.
7. Support background knowledge and user contextualization.
8. Support both convergent and divergent information behavior.
FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
A. Khalili, P. van Andel, P. V. den Besselaar, and K. A. de Graaf. Fostering serendipitous knowledge discovery using an adaptive multigraph-based faceted browser. In
Proceedings of the Knowledge Capture Conference, K-CAP 2017, Austin, TX, USA, December 4-6, 2017, ACM.
Serendipity Design Features Data-driven Digital Systems

19. Design Features Related to Explanation of the Observations
9. Facilitate the explanation of surprising observations.
10. Allow sharing of surprising observations among multiple users.
11. Enable reasoning by analogy.
12. Support extending the memory of user by invoking provocative reminders and relevance feedback.
11Ali Khalili
Design Features Related to Observations
1. Make surprising observations more noticeable.
2. Make errors in data more visible in order to detect successful errors easier.
3. Allow inversion and contrast.
4. Support randomization and disturbance.
5. Allow monitoring of side-effects when interacting with data.
6. Support detection and investigation of by-products.
7. Support background knowledge and user contextualization.
8. Support both convergent and divergent information behavior.
FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
A. Khalili, P. van Andel, P. V. den Besselaar, and K. A. de Graaf. Fostering serendipitous knowledge discovery using an adaptive multigraph-based faceted browser. In
Proceedings of the Knowledge Capture Conference, K-CAP 2017, Austin, TX, USA, December 4-6, 2017, ACM.
Serendipity Design Features Data-driven Digital Systems

20. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 12Ali Khalili
Pseudo-Serendipity or Inspiration Engine
Introduction
Serendipitous discovery may be facilitated but it is
by definition an emergent process.
What we can offer is to foster the process of
serendipity by providing an incubator-like
environment for serendipity.
Caveat

21. foundation
Year
locatedIn /
boundary
published
type
…
1983
1990
…
x
y
…
a
b
…
uni_1
uni_2
uni_3
uni_4
uni_5
…
Universities
foundationYear
boundary
published
Properties: Facets
Resources: Results
Interactive
Data Visualisation
…
Index
Temporal
closure
Year
Geographical
Research
Etc.
13Ali Khalili
Data-aware UIs
FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
Definition Anatomy
FERASAT (FacEted bRowser And Serendipity cATalyzer)
a) Component-based
b) Data-aware

22. 14Ali Khalili FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
Serendipity Design Features
F1: Make surprising observations more noticeable
- A single surprising observation, especially if it is repeatedly
done, or multiple different surprising observations, when they
refer to the same phenomenon, can trigger serendipity.
- Users often need to look at the same data from different
perspectives. Therefore, tools that allow data summarization
and tools that provide different views on data can foster
serendipity.
- Data-aware User Interfaces

23. 15Ali Khalili FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
Serendipity Design Features
Data-aware User Interfaces
User Profile
View
Browse
Data
Semantics
Reasoning
Personalisation
Interactive
UI
Components
User
Customization
Selection
Search
Querying
Background
Knowledge
Adaptation EngineData Layer UI LayerInteraction Layer
Enrichment
1) can understand users’ data
&
2) can interact with users accordingly
A Data-aware UI is a type of adaptive UI that
Khalili, Ali, and Klaas Andries de Graaf. "Linked data reactor: Towards data-aware user interfaces." Proceedings of the 13th
International Conference on Semantic Systems. ACM, 2017.

24. 16Ali Khalili
Web Components Application User InterfaceLinked Data
RDF
components
Scopes
&
Config
Linked Data Reactor (LD-R) http://ld-r.org Architecture
FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
Khalili, Ali, Antonis Loizou, and Frank van Harmelen. "Adaptive linked data-driven web components: Building flexible and reusable semantic web interfaces." ESWC, 2016.

25. 17Ali Khalili FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
Serendipity Design Features
F8: Support both convergent and divergent information behavior
- When users move through an information space they may change
directions and behavior several times as their information needs and
interests develop.
- Convergent (depth first, focused, not easily distracted) behavior is
supported by zooming in and narrowing the vision of users while
divergent (breadth first, creative, but easily distractible) behavior is
supported by zooming out and broadening the vision of users.
Research Organizations

26. 18Ali Khalili FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
Serendipity Design Features
F10: Allow sharing of surprising observations among multiple users
Khalili, Ali, and Albert Merono-Penuela. "WYSIWYQ–What You See Is What You Query." VOILA@ISWC 2017
- A surprising observation done by user A, when correctly
explained by user B, can result in positive serendipity.
- WYSIWYQ (What You See Is What You Query) for visual
collaborative querying on Linked Data.
UI
Query
?

27. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 19Ali Khalili
Use Cases
FERASAT
- FERASAT is integrated into the SMS (Semantically Mapping Science)
platform as the technical core within the RISIS.eu project
- It is actively used to browse data related to Science, Technology &
Innovation (STI) studies.
- The SMS platform has already 442 registered users varying from
senior and experienced to junior researchers (professors, postdocs,
PhD students), but also policy makers, librarians, etc.)
http://sms.risis.eu/usecases

28. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 20Ali Khalili
Analyzing change in the research/Higher Education (HE) systems
FERASAT Use Cases

29. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 21Ali Khalili
Evaluating research portfolios with regards to current societal challenges
FERASAT Use Cases
- Assessing relevance of research: finding how research links to the grand societal challenges.

30. 22Ali Khalili
Implementation http://sms.risis.eu
FERASAT: a Serendipity-fostering Faceted Browser for Linked Data
FERASAT
https://youtu.be/S_U4aYGvfe8
Demo

31. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 23Ali Khalili
Related Work
Tools/Features F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12
FERASAT
SemFacet
VisiNav
/facet
LD Query Wizard
gFacet
Sparklis
supported partly supported not supported
FERASAT

32. FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 24Ali Khalili
Conclusion
FERASAT
Lay User
Sem
antic
W
eb
Expert
Linked Data
SPARQL

33. Any Questions?
FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 25Ali Khalili
“Unless you expect the unexpected you will never find [truth],
for it is hard to discover and hard to attain.” - Heraclitus
FERASAT http://ferasat.ld-r.org

34. Any Questions?
FERASAT: a Serendipity-fostering Faceted Browser for Linked Data 25Ali Khalili
“Unless you expect the unexpected you will never find [truth],
for it is hard to discover and hard to attain.” - Heraclitus
FERASAT http://ferasat.ld-r.org