| Description |
1 online resource (xii, 105 pages) : illustrations |
| Series |
Synthesis lectures on the semantic web, theory and technology ; #4 |
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Synthesis lectures on the semantic web, theory and technology ; #4.
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| Contents |
Semantic data management : a human-driven process -- Fundamentals of motivation and incentives -- Case study : motivating employees to annotate content -- Case study : building a community of practice around web service management and annotation -- Case study : games with a purpose for semantic content creation |
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Preface -- 1. Semantic data management: a human-driven process -- 1.1 Fundamentals of semantic data management -- 1.2 Creating, managing, and using semantic data -- 1.2.1 Overview of the scenarios -- 1.2.2 Developing ontologies -- 1.2.3 Creating instance data -- 1.2.4 Supporting ontology development -- 1.3 Attracting human contributions -- 1.4 Examples of incentivized semantic web applications -- 1.4.1 The social semantic web -- 1.4.2 The Onto Tube video annotation game -- 1.4.3 The taste it! Try it! Restaurant reviewing application -- 1.5 Structure of the book |
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2. Fundamentals of motivation and incentives -- 2.1 Introduction -- 2.2 Defining motivation -- 2.3 The concept of motivation in organizational studies -- 2.4 Relevant variables for semantic content creation tasks -- 2.4.1 The goal of semantic content creation -- 2.4.2 The tasks -- 2.4.3 The social structure -- 2.4.4 The nature of the good -- 2.5 The framework |
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3. Case study: motivating employees to annotate content -- 3.1 Aims and objectives -- 3.2 Methods used -- 3.3 Case study description: the OK enterprise -- 3.3.1 First and second phases -- 3.3.2 Third phase -- 3.3.3 Fourth phase: preliminary results -- 3.3.4 Fourth phase: the first laboratory experiment -- 3.3.5 Fourth phase: the gamification of the task -- 3.3.6 Fourth phase: the second laboratory experiment -- 3.3.7 Fourth phase: the field experiment -- 3.4 Results and lessons learned |
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4. Case study: building a community of practice around web service management and annotation -- 4.1 Aims and objectives -- 4.2 Methods used -- 4.2.1 Usability test -- 4.2.2 Interviews -- 4.2.3 Workshop -- 4.3 Case study description -- 4.3.1 Initial requirement analysis -- 4.3.2 Applying open participatory design -- 4.3.3 Increase user participation by utilizing crowdsourcing mechanisms -- 4.3.4 Web service annotation wizard for MTurk -- 4.4 Results and lessons learned |
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5. Case study: games with a purpose for semantic content creation -- 5.1 Aims and objectives -- 5.2 Methods used -- 5.3 Case study description -- 5.3.1 Core components of GWAPs -- 5.3.2 SpotTheLink -- 5.3.3 Phrase detectives -- 5.3.4 WhoKnows? -- 5.3.5 Matchin -- 5.3.6 Universe game -- 5.3.7 TubeLink -- 5.4 Building new games -- 5.4.1 The OntoGame generic gaming toolkit -- 5.4.2 Design principles and open issues |
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Conclusions -- Bibliography -- Authors' biographies |
| Summary |
While many Web 2.0-inspired approaches to semantic content authoring do acknowledge motivation and incentives as the main drivers of user involvement, the amount of useful human contributions actually available will always remain a scarce resource. Complementarily, there are aspects of semantic content authoring in which automatic techniques have proven to perform reliably, and the added value of human (and collective) intelligence is often a question of cost and timing. The challenge that this book attempts to tackle is how these two approaches (machine- and human-driven computation) could be combined in order to improve the cost/performance ratio of creating, managing, and meaningfully using semantic content. To do so, we need to first understand how theories and practices from social sciences and economics about user behavior and incentives could be applied to semantic content authoring. We will introduce a methodology to help software designers to embed incentives-minded functionalities into semantic applications, as well as best practices and guidelines. We will present several examples of such applications, addressing tasks such as ontology management, media annotation, and information extraction, which have been built with these considerations in mind. These examples illustrate key design issues of incentivized SemanticWeb applications that might have a significant effect on the success and sustainable development of the applications: the suitability of the task and knowledge domain to the intended audience, and the mechanisms set up to ensure high-quality contributions, and extensive user involvement |
| Analysis |
semantic content creation |
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ontology engineering |
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media annotation |
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information extraction |
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Web service annotation motivation |
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incentives |
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mechanism design |
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participatory design |
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games with a purpose |
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gamification |
| Notes |
Part of: Synthesis digital library of engineering and computer science |
| Bibliography |
Includes bibliographical references (pages 93-104) |
| Notes |
Online resource; title from PDF title page (Morgan & Claypool, viewed on February 17, 2013) |
| Subject |
Semantic Web.
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Semantic computing.
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Data structures (Computer science)
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COMPUTERS -- Online Services -- Resource Directories.
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COMPUTERS -- System Administration -- Storage & Retrieval.
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Data structures (Computer science)
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Semantic computing
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Semantic Web
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| Form |
Electronic book
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| Author |
Cuel, Roberta.
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Stein, Martin (Computer scientist)
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| ISBN |
9781608459964 |
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1608459969 |
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1608459950 |
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9781608459957 |
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9783031794414 |
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3031794419 |
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