This document discusses the challenges of implementing semantic web technologies based on an empirical analysis of 98 applications, highlighting issues such as integrating noisy data, missing standards, and mismatched data models. It presents a reference architecture and offers approaches to mitigate these challenges, including delegating functionality to external services and using frameworks for application assembly. The findings aim to support real-world adoption of semantic web technologies by outlining common obstacles and potential solutions.

1. Digital Enterprise Research Institute www.deri.ie
Implementing Semantic Web applications:
reference architecture and challenges
Benjamin Heitmann, Sheila Kinsella,
Conor Hayes, and Stefan Decker
Workshop on Semantic Web Enabled Software Engineering 2009
♥ Copyright 2009 Digital Enterprise Research Institute. All rights reserved.
Chapter

2. Introduction
Digital Enterprise Research Institute www.deri.ie
Focus of Semantic Web research until now:
benefits of Semantic Web technology
Less research on:
costs, effort, challenges of Semantic Web technology
Result:
estimating cost/benefit offset for Semantic Web technologies is
difficult
obstacle for uptake of Semantic Web technologies by real-world
projects
Our contributions:
identify main challenges and outline Software Engineering
solutions
Benjamin.Heitmann
slide 2 of 14
@deri.org

3. Overview
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Empirical Analysis of 98 Semantic Web applications
architectural analysis + app functionality questionnaire
Reference Architecture for Semantic Web
applications
Main challenges of implementing Semantic Web
technologies
and their effect on an example application
Approaches for mitigating the challenges
Benjamin.Heitmann
slide 3 of 14
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4. Empirical analysis - Architectural
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Goal: identify common functionality
Result: components, allow comparison between apps
98 papers about apps from SemWeb challenge 2003-2008
& Scripting for SemWeb challenge 2006-2008
Benjamin.Heitmann
slide 4 of 14
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5. Reference Architecture for
Semantic Web applications
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Empirical basis: architectural analysis
provides standard decomposition criteria
allows comparing of functionality
Benjamin.Heitmann
slide 5 of 14
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6. Empirical analysis - Functionality
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Goal: characterise capabilities of components
Result: statistics about the range of variations for
each component
Results for 37 apps validated by authors
Survey covers 27 properties in 7 areas of
functionality
Benjamin.Heitmann
slide 6 of 14
@deri.org

7. Empirical analysis - Functionality
Functionality Variations(examples)
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Data Interface: data sources used
(external/decentralised/evolving ?)
Persistent Storage: Semantic Web standards
supported (e.g. RDF, OWL, SPARQL ?)
User Interface: generic/domain specific
Data Integration: manual/automatic
Search Service: structured/unstructured data
Authoring: read-only/edit/create new data
Crawling: one-time/continuous
Benjamin.Heitmann
slide 7 of 14
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8. Implementation challenges (1)
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1. Integrating noisy and heterogeneous data
integration service is very common (72%)
expensive: 80% require manual intervention
76% allow updating data after initial integration
Reasons:
use of non-standard terms
incorrect usage of vocabularies
multiple URIs for the same objects and incorrect
merging
Benjamin.Heitmann
slide 8 of 14
@deri.org

9. Implementation challenges (2)
Digital Enterprise Research Institute www.deri.ie
2. Missing or belated conventions and standards
70% allow access or importing of external data
60% can export data or are reusable as source
only 1/3 allow creation of new data
Reason: standards are just emerging:
Linked Data principles: 2006, ~8 years after RDF (1999)
RDFa for embedding RDF in HTML: finalised 2008
GRDDL for converting (X)HTML to RDF: finalised 2007
SPARQL update: not finalised
RDF forms and RDF pushback: not finalised
Benjamin.Heitmann
slide 9 of 14
@deri.org

10. Implementation challenges (3)
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3. Mismatch of data models and APIs between
components:
components have different data models (majority)
object oriented (92%), relational database, graph based
slow, non-native APIs between components
4. Distribution of application logic across multiple
components
Logic included not just in code but queries, rules,
formal vocabularies
58% using inferencing, 24% using queries
Result of 3+4: higher maintenance costs,
performance loss due to non-native API overhead
Benjamin.Heitmann
slide 10of 14
@deri.org

11. Example Application: SIOC explorer
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1 - Integration: all data
is RDF+SIOC, still 2
integration steps
required
2 - Unclear best
practices: every SIOC
exporter requires
different crawling
3 - Mismatched data models: graph/relational/OO
Mismatched APIs: ruby<->java, SPARQL (slow)
4 - distributed app logic: crawler, integration, primary app logic
Benjamin.Heitmann
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12. Mitigating the challenges (1)
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1. Delegating generic functionality to external providers
72% implement integration, 3 components
required
Delegating generic integration simplifies architecture
Drawback: application specific integration may still be
necessary
Benjamin.Heitmann
slide 12of 14
@deri.org

13. Mitigating the challenges (2)
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2. Assembling applications from components:
most apps in survey created on case-by-case basis:
multiple libraries
multiple programming languages
mismatch of native APIs
distributed application logic
provide frameworks / software factories to assemble
and customise complete applications
provide generic data integration
implement best practices and guidelines
centralise application logic
allow app specific customisation
inspiration: Ruby on Rails, PHPCake, Django
(Python), Struts (Java)
Benjamin.Heitmann
slide 13of 14
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14. Summary
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main challenges of implementing SemWeb tech
cost of integrating noisy or heterogeneous data
(non-RDF and RDF data)
missing or belated standards and conventions
mismatch of data models and APIs between components
distribution of application logic across components
approaches to mitigate the challenges:
delegate generic functionality to external services
support assembly of complete applications with
frameworks
empirical foundation: analysis of 98 Semantic Web
applications
Benjamin.Heitmann
slide 14of 14
@deri.org