developing an ontology for enterprise crowdsourcing
DESCRIPTION
The improvement of the efficacy of enterprise crowdsourcing activities is heavily dependent on finding, sharing, and integrating the right information for certain use cases. These efforts may include activities such as recommending a crowdsourcing task to a competent worker or evaluating an ongoing or completed crowdsourcing project. However, to pave the way for intelligent enterprise crowdsourcing platforms, the semantic richness of the data must be improved. Therefore, an ontology including a wide set of classes and properties is proposed in this paper. The ontology development is based on the ontology engineering methodology. A first general assessment of the ontology is given at the end of the paper, which describes how it addresses major crowdsourcing requirements.TRANSCRIPT
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
MKWI 2014, Paderborn, February the 26th, 2014 Lars Hetmank
Developing an Ontology for Enterprise Crowdsourcing
Slide 2 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
Agenda
1 Enterprise Crowdsourcing
2 Current Situation & Problem Relevance
3 Anticipated Benefits & Requirements
4 Research Objective & Methodology
5 CSM Ontology
6 Conclusion & Future Work
Slide 3 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
Enterprise Crowdsourcing
(Brabham, 2013)
problem-solving and production modelthat leverages the collective intelligence of online communitiesto serve specific organizational goals.
An online, distributed“
”
Slide 4 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
Current Situation & Problem Relevance
(source: Amazon Mechanical Turk)
Slide 5 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
Benefits & Requirements
Key requirements in enterprise crowdsourcing environments (source: own illustration)
Slide 6 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
Research Objective:- Development of a lightweight and extensible
ontology for capturing, storing, utilizing, and sharing crowdsourcing data that improves the automation and interoperability in enterprise crowdsourcing environments
- Semantic Web vocabulary
Methodology:- Design Science
- Ontology Engineering
February 26th, 2014
Research Objective & Methodology
Slide 7 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
Ontology Engineering
Slide 8 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
Literature Review (Source 1)
Article Dimension Semantic Entity
Nature of collaboration
Type of target problem
Design of incentive mechanism
Task complexity
Approach to combine solutions
Method to evaluate users
Role of human users
Type of architecture
Degree and distribution of manual effort
Impact of contribution
Interaction mode
Type of action
Reward and incentive mechanism
Complexity Level
Type of aggregation
Evaluation mechanism
Human requirement
Technical requirement
Type of aggregation, evaluation mech.
Impact Level
Crowdsourcing systems on the World-Wide Web(Doan, Ramakrishnan, & Halevy, 2011)
… … …
Slide 9 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
Literature Review (Preliminary Result 1)
Slide 10 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
microtask
design
open innovation and co-creation
job marketplace
crowdfunding software testing & translation
February 26th, 2014
System Analysis (Source 2)
Slide 11 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
Platform
Task properties User properties(requester and
participant)Task specification Task allocation Workflow and
quality control
Task description Time andpriority
Reward Evaluation Requester-oriented Participant-Oriented
Amazon mTurk project name, task title, task description, keywords, task type (categorize, collect data, moderate, get sentiment, survey, tag, transcribe, create content), instructions
duration, expiration, approval time after completion,
reward per assignment
- qualification type, approval rate, number of approved tasks
creation date, task available, reward amount, expiration date, duration
number of assignments per task, status (in progress, for review, reviewed)
name, login name, contact address information, prepaid balance
Atizio title, description, image, additional information (text, document), important information, acceptance criteria, thank-you text, visibility
duration (start and end date/time)
amount of (alternative) reward,
- - reward, accepted languages (de, fr, en), duration
user activity (ideas, projects, comments, comment evaluation, idea evaluation, time of membership)
first name, last name, address (street, zip code, city, country), age, about me, website, interests, profession, job status, educational level, languages, references, career/CV, contact list
crowdSPRING project title, project description, external resources
end date amount of payment
- specialization, country, language
product category, activity score, award, time, contributions, status
user activity (reputation score, projects, awarded projects)
first name, last name, about me, address (city, state, postal code, country), language, time zone, specialization, profile image, email, portfolio items
… ... … … … … … … …
February 26th, 2014
System Analysis II
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Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
Standards and Semantic Web Vocabularies (Source 3)
people, organizations, and information objects
social networks and online communities
events and contextual information
business processes and workflows
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Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
A shared crowdsourcing model (CSM) to describe the key conceptual entities: user, project, task, requirement, reward mechanism, evaluation mechanism, and contribution
Includes 24 classes, 22 object properties and 30 datatype properties + several named individuals
Implemented in OWL using Protégé
February 26th, 2014
CSM Ontology I
Slide 14 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
CSM Ontology II
Slide 15 | 18
Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
CSM Ontology Specification
http://www.purl.org/csm/
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Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
Example: Translate Technical Specification
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Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
February 26th, 2014
Example SPARQL Query
Which type, nature and amount of reward is appropriate for a translation task which lasts approximately 30 minutes?
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Faculty of Business and Economics | Chair of Business Informatics, especially Information Management
Developing an Ontology for Enterprise Crowdsourcing
Balancing between simplicity and semantics of the crowdsourcing ontology remains a key challenge
Reuse of existing standards and vocabularies
Further evaluation steps to achieve successive adjustment and improvement
Dissemination in research in practice(standardization process)
February 26th, 2014
Conclusion & Future Work