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International Joint Conference on Knowledge Discovery, Knowledge Engineering, and Knowledge Management

IC3K 2014: Knowledge Discovery, Knowledge Engineering and Knowledge Management pp 556–570Cite as

Ontology Methodology Building Criteria for Crowdsourcing Innovation Intermediaries

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 553))

Abstract

Crowdsourcing innovation intermediaries are organizations that mediate the communication and relationship between companies that aspire to solve some problem or to take advantage of any business opportunity with a crowd that is prone to give ideas based on their knowledge, experience and wisdom. A significant part of the activity of these intermediaries is carried out by using a web platform that takes advantage of web 2.0 tools to implement its capabilities. Thus, ontologies are presented as an appropriate strategy to represent the knowledge inherent to this activity and therefore the accomplishment of interoperability between machines and systems. In this paper we present an ontology roadmap for developing crowdsourcing innovation ontology of the intermediation process. We start making a literature review on ontology building, analyze and compare ontologies that propose the development from scratch with the ones that propose reusing other ontologies, and present the criteria for selecting the methodology. We also review enterprise and innovation ontologies known in literature. Finally, are taken some conclusions and presented the roadmap for building crowdsourcing innovation intermediary ontology.

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Author information

Authors and Affiliations

  1. School of Management and Industrial Studies, Polytechnic Institute of Oporto, Vila do Conde, Portugal

    Cândida Silva

  2. Information Systems Department, School of Engineering, University of Minho, Guimarães, Portugal

    Isabel Ramos

  3. Center Algoritmi, University of Minho, Guimarães, Portugal

    Cândida Silva & Isabel Ramos

Authors
  1. Cândida Silva
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  2. Isabel Ramos
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Corresponding author

Correspondence to Cândida Silva .

Editor information

Editors and Affiliations

  1. Instituto de Telecomunicações, Lisboa, Portugal

    Ana Fred

  2. Delft University of Technology, Delft, Zuid-Holland, The Netherlands

    Jan L. G. Dietz

  3. University of Madeira, Funchal, Portugal

    David Aveiro

  4. Henley Business School, University of Reading, Reading, United Kingdom

    Kecheng Liu

  5. INSTICC, Setubal, Portugal

    Joaquim Filipe

Appendix

Appendix

 

Aim

Method

Phases

Activities

Language

Tool

Build

cooperation

Cyc KB - Knowledge Base [32]

Capture a large portion of what people normally considered consensus knowledge about the world

From scratch: bottom-up

1. Manual extraction of common sense knowledge; 2. Codification: Computer aided extraction of common sense language; 3. Computer managed extraction of common sense knowledge

Implementation; Knowledge acquisition; Documentation

CycL, an augmentation of first-order predicate calculus, with extensions to handle equality, reasoning, skolemisation, and some second-order features

 

No

Uschold and King [33]

Enterprise modeling processes

From scratch: middle-out

1. Identify purpose; 2. Building: Capture; Coding; Integrating

3. Evaluation; 4. Documentation

Requirements; Implementation; Knowledge acquisition; Verification and validation; Documentation

Ontolingua

Ontolingua Server

No

Grüninger and Fox [34]

Business processes and activities modeling; support design-in-large scale projects

From scratch

1. Capture of motivating scenarios; 2. Formulation of informal competency questions; 3. Specification of the terminology of the ontology within a formal language; 4. Formulation of formal competency questions using the terminology of the ontology; 5. Specification of axioms and definitions for the terms in the ontology within the formal language; 6. Establish conditions for characterizing the completeness of the ontology

Requirements; Design; Implementation; Knowledge acquisition; Verification and validation; Documentation

KIF (Knowledge Interchange Format), first-order logic

 

No

KACTUS [35]

Complex technical systems development

From scratch: up-down; modifying other existing ontologies of application development

1. Specification of the application; 2. Preliminary design based on relevant top-level ontological categories; 3. Ontology refinement and structuring

Requirements; Design; Implementation; Maintenance

CML (Chemical Markup Language); Express; Ontolingua

KACTUS toolkit

No

METHONTOLOGY [36]

Support application development process

Re-engineering

1. Project management activities (Schedule; Control; Quality assurance); 2. Development-oriented activities (Specification; Conceptualization; Formalization; Implementation; Maintenance); 3. Support activities (Knowledge acquisition; Integration; Evaluation; Documentation; Configuration management)

Project monitoring and control; Requirements; Design; Implementation; Maintenance; Knowledge acquisition; Verification and validation; Ontology configuration management; Documentation

OWL,DAML + OIL; RDF; XML; OCML

ODE (Ontology Design Environment) and WEB-ODE

No

On-To-Knowledge [28]

Knowledge management of heterogeneous sources in the internet

From scratch

1. Kick-off: requirements capture and specification; 2. Refinement; 3. Evaluation; 4. Maintenance

Project initiation; Project monitoring and control; Ontology quality management; Concept exploration; Requirements; Design; Implementation; Maintenance; Knowledge acquisition; Verification and validation; Ontology configuration management; Documentation

OIL (Ontology-based Inference Layer); XML; RDF

OntoEdit

No

SENSUS [37]

Natural language processing for developing machine translators

From scratch: up-down

1. Identify seed terms; 2. Link seed terms to SENSUS by hand; 3. Include nodes on the path to root; 4. Add some complete sub-trees

Requirements; Implementation

DL: LOOM

Ontosaurus

No

NeOn [38]

It provides guidance for all key aspects of the ontology engineering process, that is, collaborative ontology development, reuse of ontological and non-ontological resources, and the evolution and maintenance of networked ontologies, through nine scenarios.

Re-engineering

1. Initiation (Requirements specification; Scheduling; Evaluation); 2. Reuse (Non-Ontological Resource (NOR) Reuse; Search; Reuse; Statements Reuse; Evaluation); 3. Merging (Aligning; Evaluation); 4. Re-engineering (NOR Reengineering; Modularization; Evaluation); 5. Design (Conceptualization; Evolution; Localization; Evaluation); 6. Implementation (Evaluation; Maintenance; Evaluation)

Project monitoring and control

Requirements

Design

Implementation

Maintenance

Knowledge acquisition

Verification and validation

Ontology configuration management

Documentation

OWL (Web Ontology Language)

NTK – NeOn Toolkit

Yes

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Silva, C., Ramos, I. (2015). Ontology Methodology Building Criteria for Crowdsourcing Innovation Intermediaries. In: Fred, A., Dietz, J., Aveiro, D., Liu, K., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2014. Communications in Computer and Information Science, vol 553. Springer, Cham. https://doi.org/10.1007/978-3-319-25840-9_34

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  • DOI: https://doi.org/10.1007/978-3-319-25840-9_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25839-3

  • Online ISBN: 978-3-319-25840-9

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