Facets and Pivoting for Flexible and Usable Linked
Data ExplorationJosep Maria Brunetti, Rosa Gil,
Roberto García
Interacting with Linked Data Workshop, ILD’12
Crete, Greece, May 28th 2012Human-Computer Interaction and
Data IntegrationResearch Group
Universitat de LleidaSpain
Starting Point
• RhizomerSemantic Web Data publishing
MetadataStore
RhizomerApp
GE
T
PU
T
PO
ST
DE
L
SPARQL or LinkedData new edit delete
Jena, Virtuoso, OWLIM,…
HTML+RDFa
“semantic” FORMS
Interacting
• Useful for computers…but also for lay users?
• User tests:– Typical questions:
• Where do I start? • Where do I go now?• What is this data about?
– What do we offer? • Text search, type URI, SPARQL query,…
…but they usually don’t answer lay users needs
Interacting
• Example: What to do with DBPedia? – 3.5 million things described
• Ontology: 257 classes y 1276 properties
Proposal
Information Architecture Components
[Morville]
Interaction Patterns for Data Analysis
[Shneiderman]
Overview Menus, Sitemaps,…
Zoom & Filter Facets
Details Lists, Maps, Timelines…
Ontologies and dataset structure
IA Components. Menus
– Hierarchical structure for dataset ontologies• For each class
– URI, label, # instances, subclasses
– Flatten to desired # entries and subentries• When there is room, divide class with most
instances
• When too many options, group classes with less instances
IA Components. Menus
AutomaticGeneration
7 menus with 10 submenus
IA Components. MenusNavigation bar provides overview for DBPedia… …but what to do with 12.334 birds now?
IA Components. Facets
• Pre-computed list of facets/class
– Ontologies + class instances
– Facet metrics: frequency, #values, most common value cardinality…
• DBPedia Birds class:– 226 different properties
•dbo:kingdom, 100%, 3 values, 6846 (Animalia),…
Evaluation
• Evaluation with lay users as part of RITE1 development process– Iteration test with 6 users
– LinkedMDB dataset
1 Rapid Iterative Testing and Evaluation
User Task:“Find three films where Woody Allen is director and also actor”.
Evaluation
• Seemed easy but…no user completed task without help
• Really, just 1 issue: – Users started from “Actor” instead than from
“Film”, and got lost from there
• User interaction is too constrained by underlying “explicit” data structure
• Lack of context while browsing graph
Proposals
• Facet for all inverse properties (explicit or implicit)– Actor actor – Film:
• Actor has facet “is actor of Film”
• Breadcrumbs show “query” built so far– Click Film, then for facet “Actor”
search “Woody Allen”:• Display:
“Showing Film has actor where actor name is Woody Allen”
Proposals
• What about getting from Actors to Films to restrict by director?
• Add Actor facet “directed by”?– DANGER: facets explosion
• Director facet “continents of countries where films directed”!
Proposals
• Pivoting: switch from faceted view to related faceted view (keeping filters)– E.g.: from Actors facets move to Films facets
through “is Actor of Film” facet
• For each class facet also compute:– Most specific class for target instances
• Actor “is Actor of” Film and TV Episode Work
– Pivot that facet to get:• Faceted view for target class • … + filters so far
Conclusions
• Menus – Dataset classes (topics) overview
• Facets– Per class properties and values, filter
• Pivoting– Switch faceted views, carry on filters
Conclusions
• Users build queries without SPARQL or dataset structure knowledge
• Example: – Who has directed more films in Oceania?– SELECT DISTINCT ?r1 WHERE {
?r1 a movie:Director . ?r2 movie:director ?r1 . ?r2 a movie:Film.?r2 movie:country ?r3 . ?r3 movie:country_continent ?r3var0 FILTER(str(?r3var0)="Oceania") }
Future Work
• User evaluation– Explore the best way to provide pivoting,
and un-pivoting…
• Specialised facets: – Range dependent: histogram for numbers,
calendar for dates,…
• Other IA components: sitemaps
• …
Thanks for your attention
Roberto Garcíahttp://rhizomik.net/~roberto/
Human-Computer Interaction and Data IntegrationResearch Group
Universitat de Lleida