Presented at IUI 2010 Paper can be downloaded at http://dl.acm.org/citation.cfm?id=1720005

1. Designing a Thesaurus-based
Comparison Search Interface for
Linked Cultural Heritage Sources
Alia Amin, Michiel Hildebrand,
Jacco van Ossenbruggen, Lynda Hardman
Firstname.lastname@cwi.nl

2. Background
The MultimediaN E-Culture Project
 Support cultural heritage experts’
information seeking needs
 Data
 heterogeneous
 structured and unstructured
 text and images
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3. Cultural Heritage Experts
Information Seeking Tasks*
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 Most Experts Information Seeking Tasks are complex
information gathering tasks
e.g. Comparison, Relationship,
Topic search, Exploration,
Combination
 Experts search in
multiple sources
* Amin et al., JCDL 2008

4. Research Goal and Approach
 Research goal: support comparison search in
multiple sources.
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User
(Curators,
Art historians)
Identify Needs
Design requirementsPreliminary Study

5. Research Goal and Approach
 Research goal: support comparison search in
multiple sources.
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User
(Curators,
Art historians) Design & implementation
Identify Needs
Design requirements
Evaluate solutionEvaluation Study
Preliminary Study

6. Preliminary Study
 Goal: to understand comparison search
practice performed by CH experts and explore
support for comparison search across
multiple sources.
 7 Experts (curators, art historians)
 Semi-structured interview, natural
environment, voice recording
 Gather comparison search use cases
 Get feedback on initial application ideas
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7. Preliminary Study: Key Findings
 When do experts conduct comparison
search?
 Quantitative and qualitative comparisons
 Learning about collections
 Planning an exhibition
 Museometry
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8. Preliminary Study: Key Findings
 Main challenges in comparison search
 Search
 Name aliases
 Multiple languages
 Multiple terms
 Compare
 …idem
 Comparing many sets
 Single and multiple property comparison
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9. Design Requirements
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 Search
Need guided search to support:
name aliases, multiple languages, multiple terms
 Select
Need to be able to select and group multiple artworks
 Compare
Comparing many sets
Single and multiple property comparison

10. Design and Implementation
• Thesaurus-based comparison search: LISA
• Web platform: ClioPatria
• Interface: HTML, CSS, Javascript, Flash (amChart)
• Dataset
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Collection
RKD Archive 82.781 Objects
Thesauri
RKD Thesaurus 11.995 terms
TGN (geographical) 89.000 terms
ULAN (artist) 13.000 people
AAT (art and architecture) 31.000 terms
IconClass (iconographic) 24.331 terms

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19. Evaluation Study
 Goal: to evaluate how well the search, select
and compare features support comparison
search tasks
 12 CH experts: researchers, curators,
librarians, museum managers
 Setup
 Compare LISA vs. baseline (RKDimages)
 Introduction
 User experiment
 Post experiment interview
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20. Evaluation Study
 14 comparison tasks/participant
Compare all paintings from the museum Stedelijk Museum De Lakenhal
with
all paintings from the museum Bredius
(1) how many artworks were created in 1650? (single property
comparison)
(2) how many artworks were created in 1830 by the artist Jacobus
Ludovicus Cornet? (dual properties comparison)
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 Tested different comparison tasks:
few artworks (2) v.s. many artworks (30)
single property v.s. dual properties
Table, bar chart and scatterplot visualization

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22. Evaluation Study Results: Search
 Search and selection activities are highly
interdependent
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Time (t) to search and select tLisa – few ≈ tLisa – many
tbaseline – few < tbaseline – many
Ease of Use (EoU)
EoUbaseline-few < EoULisa-few
EoUbaseline-many < EoULisa-many

23. Evaluation Study Results: Compare
 Compare artworks using baseline and Lisa:
Table, Barchart, Scatterplot
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Time (t) to compare
a Single property
tLisa -few ≈ tbaseline -few
tLisa – many ≈ tbaseline – many
Time (t) to compare
Dual properties
tLisa -few ≈ tbaseline –few
t Lisa-Scatterplot – many < tLisa-Table – many <
tbaseline – many
Ease of Use (EoU) EoUbaseline < EoULisa

24. User Feedback
 EOU vs. time.
 Autocompletion helped user search for
many artworks easier
 Different visualizations allow different
perspectives
 Comparison using a visualization tool is
unfamiliar and requires learning time
 Additional features requested:
 more interactivity with the visualization
 Bookmarking 24

25. Lessons learned
 Requirements for the metadata
 inconsistent data, incomplete metadata,
estimated data
 Tackle through different angles
 Data solutions: better annotations
 Technical solutions: thesauri alignment, semantic
backend, automatically enrich metadata
 Interface solutions: transparency on aggregation
rules, allow feedback
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26. Acknowledgements
 Centraal Museum Utrecht
 Digital Heritage Netherland (DEN)
 Efgoed Nederland
 Netherlands Collection Institute (ICN)
 Publiek Archief Eemland
 Netherlands Institute for Art History (RKD)
 Rijksmuseum Amsterdam
 Tropenmuseum
 University of Amsterdam
 Hyowon Lee, DCU
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http://e-culture.multimedian.nl/lisa/session/compsearch