Presentation at the "Reasoning from experiences on the Web" workshop (WebCBR 2010) at the International Conference on Case Based Reasoning 2010. Abstract: While Case-based reasoning (CBR) has successfully been deployed on the Web, its data models are typically inconsistent with existing information infrastructure and standards. In this paper, we examine how CBR can operate on the emerging Web of Data, with mutual benefits. The expense of knowledge engineering and curating a case base can be reduced by using Linked Data from the Web of Data. While Linked Data provides experiential data from many different domains, it also contains inconsistencies, missing data and noise which provide challenges for logic-based reasoning. CBR is well suited to provide alternative and robust reasoning approaches. We introduce (i) a lightweight CBR vocabulary which is suited for the open ecosystem of the emerging Web of Data, and provide (ii) a detailed example of a case base using data from multiple sources. We propose that for the first time the Web of Data provides data and a real context for open CBR systems.

1. Digital Enterprise Research Institute www.deri.ie
Enabling Case-Based Reasoning
on the Web of Data
(How to create a Web of Experience)
Benjamin Heitmann, Conor Hayes
Digital Enterprise Research Institute (DERI),
National University of Ireland, Galway
Funded by Science Foundation Ireland under
Grant No. SFI/08/CE/I1380 (Líon-2)
 Copyright 2009 Digital Enterprise Research Institute. All rights reserved.
Chapter

2. Motivation
Digital Enterprise Research Institute www.deri.ie
 characterisation of current CBR approaches:
 data storage is domain and use-case specific
 no common data model
 challenges:
 limited interoperability (“data silos”)
 no reuse of cases or knowledge containers
 data acquisition is expensive
 the Web of Data can provide:
1. new sources of experiential data
2. standard way to publish and link experiential data
3. common data model for CBR interoperability
4. opportunity to establish CBR as a standard reasoning
paradigm
Benjamin.Heitmann
slide 2 of 9
@deri.org

3. Overview:
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1. related work in the CBR domain:
 existing approaches for CBR interoperability
2. introduction to the Web of Data:
 main concepts and principles
 current sources for experiential data
3. applying the CBR methodology
to the Web of Data:
 lightweight CBR vocabulary
 example and process for constructing a case base
Benjamin.Heitmann
slide 3 of 9
@deri.org

4. Related work: CBR interoperability
Digital Enterprise Research Institute www.deri.ie
 Case-Based Mark-Up Language (CBML), XML based:
 rigid CBR vocabulary, hard to customise for new domain.
 hard to convert domain data, lack of real data.
 CaseML (RDF based):
 rigid CBR vocabulary
 requires a-priori knowledge of external sources
 C-OWL (RDF based, extends OWL):
 formalisation of distributed reasoning for CBR using rules
 common shortcomings:
 no reuse of domain semantics for cases
 no reuse by linking of case fragments
 high overhead of transforming of external data into case data
Benjamin.Heitmann
slide 4 of 9
@deri.org

5. Background: The Web of Data
Digital Enterprise Research Institute www.deri.ie
 the Web of Data provides:
 structured data, collaboratively
created, about object centred sociality
 domain knowledge through
ontologies (e.g. DBpedia ontology)
 cross-domain links between sources
 Linked Data principles:
1. use URIs “for everything”
2. allow HTTP access to all URIs
3. when accessing a URI, provide
relevant data in RDF
4. include links to URIs from third
parties (background knowledge)
 Linked Data can be very noisy, so CBR
is well suited as a reasoning paradigm (a) July 2007 (b) April 2008 (c) Sep 2009 (d) July 2009
Benjamin.Heitmann
slide 5 of 9
@deri.org

6. Sources of experiential data
from the Web of Data
Digital Enterprise Research Institute www.deri.ie
 DBpedia provides cross- dbpedia:Beck
domain links foaf:name
foaf:homepage
"Beck"
Friend of a Friend (FOAF)
vocabulary:
social relationships and
 social web sites:
http://beck.com information
dbpedia-owl:birthPlace dbpedia: DBPedia ontology
Los_Angeles
 Live Journal dbpprop:genre dbpedia:
DBPedia properties
 MySpace Anti-folk
skos:subject Simple Knowledge Organisation
Facebook & Open Graph API
category:
 Anti-folk_musicians
System (SKOS): vocabulary
for knowledge organisation
Yelp reviews
fbase:Beck
 owl:sameAs
opencyc:en/
Web Ontology Language (OWL):
links to identical resources
Beck_MusicalPerformer
 broadcasters & news: example of structured data from Wikipedia,
demonstrating the Linked Data principles
 BBC program catalogue
 New York Times subject headings
 search engines providing
access to this data:
 Google and Yahoo
 Sindice
Benjamin.Heitmann
slide 6 of 9
@deri.org

7. CBR vocabulary for the Web of Data
Digital Enterprise Research Institute www.deri.ie
CBR vocabulary
Example CBR Case Base
rdf:type Sources:
cbr:CaseBase ex:UserProfiles DBPedia,
Amazon Reviews via Google RDFa,
MySpace via DBTune
cbr:has_casebase
cbr:has_casebase
cbr:has_casebase
rdf:type
deri:Heitmann
cbr:Case deri:Hayes
foaf:interest
foaf:interest
cbr:has_solution foaf:interest foaf:interest
amazon:
amazon: RiverOfGods
GravitysRainbow
myspace: myspace:
cbr:Solution
BobDylan Björk
 modelling decisions:  flexible mapping of cases to
entities
 lightweight approach
 not fixed to domain or use
 intentional simplicity
case
 reuse of existing domain
semantics and vocabularies
 focus on vocabulary and
case knowledge
Benjamin.Heitmann
slide 7 of 9
@deri.org

8. Process for constructing a case base
Digital Enterprise Research Institute www.deri.ie
 Step 1: discovering and aggregating data
 use search engine or custom crawler to discover data
 Step 2: conversion of external data
 transform different RDF serialisations (RDFa, RDF/XML, XHTML) to cases in RDF
 Step 3: authoring and curating of case base
 select relevant cases manually or automatically, via application logic
Benjamin.Heitmann
slide 8 of 9
@deri.org

9. Summary: towards a Web of Experience
Digital Enterprise Research Institute www.deri.ie
 our simple example
illustrates the future potential
 towards a Web of
Experience:
 publish experiential data in RDF
 link it to the Web of Data
 use cases:
 mining experiences from
structured, user generated content.
 open recommender systems
 distributed CBR
Benjamin.Heitmann
slide 9 of 9
@deri.org