An ontology for enhancing automation and interoperability in Enterprise Crowdsourcing Environments

Enterprise crowdsourcing transforms the way in which traditional business tasks can be processed by harnessing the collective intelligence and workforce of a large and often diver-sified group of people. At the present time, data and information residing within enterprise crowdsourcing systems and other business applications are insufficiently interlinked and are rarely made publicly available in an open and semantically structured manner – neither to the corporate intranet nor to the World Wide Web (WWW). However, the semantic annotation of enterprise crowdsourcing activities is a promising research and application domain. The Semantic Web and its related technologies, methods and principles for publishing structured data offer an extension of the traditional layout-oriented Web to provide more intelligent and complex services. This technical report describes the efforts toward a universal and lightweight yet powerful Semantic Web vocabulary for the domain of enterprise crowdsourcing. As a methodology for developing the vocabulary, the approach of ontology engineering is applied. To illustrate the purpose and to limit the scope of the ontology, several informal competency questions as well as functional and non-functional requirements are presented. The subsequent con-ceptualization of the ontology applies different sources of knowledge and considers various perspectives. A set of semantic entities is derived from a review of existing crowdsourcing applications and a review of recent crowdsourcing literature. During the domain capture, all partial results of the review are integrated into a consistent data dictionary and structured as a UML data schema. The designed ontology includes 24 classes, 22 object properties and 30 datatype properties to describe the key aspects of a crowdsourcing model (CSM). To demonstrate the technical feasibility, the ontology is implemented using the Web Ontology Language (OWL). Finally, the ontology is evaluated by means of transforming informal to formal competency questions, comparing it to existing semantic vocabularies, and calculat-ing ontology metrics. Evidence is shown that the CSM ontology covers the key representa-tional needs of the enterprise crowdsourcing domain. At the end of the technical report, cur-rent limitations are illustrated and directions for future research are proposed.:Table of Contents I List of Figures III List of Tables IV List of Code Listings V List of Abbreviations VI Abstract VIII 1 Introduction 1 2 Research Objective 4 3 Ontology Engineering 6 4 Purpose and Scope 9 4.1 Informal Competency Questions 10 4.2 Requirements 11 4.2.1 Functional Requirements 12 4.2.2 Non-Functional Requirements 15 5 Ontology Development 18 5.1 Conceptualization 18 5.1.1 System Review 18 5.1.2 Literature Review 21 5.2 Domain Capture 26 5.3 Integration 28 5.3.1 Semantic Vocabularies and Standards 28 5.3.2 Implications for the Design 33 5.4 Implementation 33 6 Evaluation 35 6.1 Transforming Informal to Formal Competency Questions 36 6.2 Comparing the Ontology to other Semantic Vocabularies 42 6.3 Calculating Ontology Metrics 44 7 Conclusion 46 8 References 48 Appendix A (System Review) i Appendix B (Crowdsourcing Taxonomies) v Appendix C (Data Dictionary) ix Appendix D (Semantic Vocabularies) xi Appendix E (CSM Ontology Source Code) xv Appendix F (Sample Data Instance 1) xxxi Appendix G (Sample Data Instance 2) xxxi