Knowledge Engineering: Practice and Patterns

1. Front Matter

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2. Knowledge Engineering: Alignment and Identity

   1. Pattern-Based Mapping Refinement

      • Fayçal Hamdi, Chantal Reynaud, Brigitte Safar

      Pages 1-15

   2. Practical Considerations on Identity for Instance Management in Ontological Investigation

      • Kouji Kozaki, Satoshi Endo, Riichiro Mizoguchi

      Pages 16-30

3. Knowledge Acquisition

   1. Involving Business Users in Formal Modeling Using Natural Language Pattern Sentences

      • Jeroen van Grondelle, Ronald Heller, Emiel van Haandel, Tim Verburg

      Pages 31-43

   2. Knowledge Acquisition from Sources of Law in Public Administration

      • Alexander Boer, Tom van Engers

      Pages 44-58

   3. Enriching the Gene Ontology via the Dissection of Labels Using the Ontology Pre-processor Language

      • Jesualdo Tomas Fernandez-Breis, Luigi Iannone, Ignazio Palmisano, Alan L. Rector, Robert Stevens

      Pages 59-73

4. Collaboration in Knowledge Engineering

   1. Ontology Development for the Masses: Creating ICD-11 in WebProtégé

      • Tania Tudorache, Sean Falconer, Natalya F. Noy, Csongor Nyulas, Tevfik Bedirhan Üstün, Margaret-Anne Storey et al.

      Pages 74-89

   2. RDFauthor: Employing RDFa for Collaborative Knowledge Engineering

      • Sebastian Tramp, Norman Heino, Sören Auer, Philipp Frischmuth

      Pages 90-104

5. Knowledge Engineering: Patterns

   1. Pattern-Based Ontology Transformation Service Exploiting OPPL and OWL-API

      • Ondřej Šváb-Zamazal, Vojtěch Svátek, Luigi Iannone

      Pages 105-119

   2. Experimenting with eXtreme Design

      • Eva Blomqvist, Valentina Presutti, Enrico Daga, Aldo Gangemi

      Pages 120-134

6. Social Aspects and Tagging

   1. Weaving a Social Data Web with Semantic Pingback

      • Sebastian Tramp, Philipp Frischmuth, Timofey Ermilov, Sören Auer

      Pages 135-149

   2. Social People-Tagging vs. Social Bookmark-Tagging

      • Peyman Nasirifard, Sheila Kinsella, Krystian Samp, Stefan Decker

      Pages 150-162

   3. FOLCOM or the Costs of Tagging

      • Elena Simperl, Tobias Bürger, Christian Hofer

      Pages 163-177

7. Semantic Web, Web of Data and Linked Data

   1. Epiphany: Adaptable RDFa Generation Linking the Web of Documents to the Web of Data

      • Benjamin Adrian, Jörn Hees, Ivan Herman, Michael Sintek, Andreas Dengel

      Pages 178-192

   2. Scaling Up Question-Answering to Linked Data

      • Vanessa Lopez, Andriy Nikolov, Marta Sabou, Victoria Uren, Enrico Motta, Mathieu d’Aquin

      Pages 193-210

8. Ontology Evolution / Refinement

   1. Using Semantic Web Resources for Data Quality Management

      • Christian Fürber, Martin Hepp

      Pages 211-225

   2. Using Ontological Contexts to Assess the Relevance of Statements in Ontology Evolution

      • Fouad Zablith, Mathieu d’Aquin, Marta Sabou, Enrico Motta

      Pages 226-240

   3. What Is Concept Drift and How to Measure It?

      • Shenghui Wang, Stefan Schlobach, Michel Klein

      Pages 241-256

9. Knowledge Access

   1. Mobile Cultural Heritage Guide: Location-Aware Semantic Search

      • Chris van Aart, Bob Wielinga, Willem Robert van Hage

      Pages 257-271

   2. Semantic Scout: Making Sense of Organizational Knowledge

      • Claudio Baldassarre, Enrico Daga, Aldo Gangemi, Alfio Gliozzo, Alberto Salvati, Gianluca Troiani

      Pages 272-286

Knowledge Management and Knowledge Engineering is a fascinating ?eld of re- 1 search these days. In the beginning of EKAW , the modeling and acquisition of knowledge was the privilege of – or rather a burden for – a few knowledge engineers familiar with knowledge engineering paradigms and knowledge rep- sentationformalisms.While the aimhasalwaysbeentomodelknowledgedecl- atively and allow for reusability, the knowledge models produced in these early days were typically used in single and very speci?c applications and rarely - changed. Moreover, these models were typically rather complex, and they could be understood only by a few expert knowledge engineers. This situation has changed radically in the last few years as clearly indicated by the following trends: – The creation of (even formal) knowledge is now becoming more and more collaborative. Collaborative ontology engineering tools and social software platforms show the potential to leverage the wisdom of the crowds (or at least of “the many”) to lead to broader consensus and thus produce shared models which qualify better for reuse. – A trend can also be observed towards developing and publishing small but 2 3 4 high-impactvocabularies(e.g.,FOAF ,DublinCore ,GoodRelations)rather than complex and large knowledge models.

• augmented reality
• collaborative ontology engineering
• cultural heritage objects
• data quality management
• data semantics
• evolution
• knowledge
• semantic web

• Cognitive Interaction Technology Excellence Center (CITEC), Universität Bielefeld, Bielefeld, Germany

  Philipp Cimiano

• IST/DEI, INESC-ID, Lisboa, Portugal

  H. Sofia Pinto

Policies and ethics