Ontology development by domain experts (without using the “O” word)

2017 ◽  
Vol 12 (3-4) ◽  
pp. 299-311 ◽  
Author(s):  
Andrea Westerinen ◽  
Rebecca Tauber
Keyword(s):  
Ontology Development ◽  
Domain Experts

scholarly journals An Ontology-Based Model for Treatment Guidelines of Internet and Games Addiction

2019 ◽  
Vol 8 (2S2) ◽  
pp. 113-117
Keyword(s):  
Risk Factors ◽  
Recommendation System ◽  
Treatment Guidelines ◽  
Difficult Problem ◽  
Ontology Development ◽  
The Internet ◽  
Evaluation Result ◽  
Domain Experts ◽  
States Data ◽  
Profile Characteristics

Internet and games addiction will become a difficult problem for the parents, because the internet and games easier to access and has more contents. Thus, the number of internet and games addiction will be increasing in the future. This study recommends ontology expansion for treatment guidelines of internet and games addiction that will use as the component of recommendation system in web technology. This study’s methodology can be condensed into three states; data collection ontology development, and evaluation. This ontology included seven main classes, there are profile, characteristics, risk factors, devices, treatment, and GAST. The evaluation result that conducted by domain experts included a highly-superior concentration of 88.34%, which confirms that this ontology may be employed for developing a recommendation system.

scholarly journals OOPS! (OntOlogy Pitfall Scanner!)

2014 ◽  
Vol 10 (2) ◽  
pp. 7-34 ◽  
Author(s):  
María Poveda-Villalón ◽  
Asunción Gómez-Pérez ◽  
Mari Carmen Suárez-Figueroa
Keyword(s):  
Empirical Analysis ◽  
Description Logics ◽  
Ontology Development ◽  
Evaluation Tools ◽  
Domain Experts ◽  
Development Platform ◽  
Ontology Evaluation ◽  
Modeling Errors

This paper presents two contributions to the field of Ontology Evaluation. First, a live catalogue of pitfalls that extends previous works on modeling errors with new pitfalls resulting from an empirical analysis of over 693 ontologies. Such a catalogue classifies pitfalls according to the Structural, Functional and Usability-Profiling dimensions. For each pitfall, we incorporate the value of its importance level (critical, important and minor) and the number of ontologies where each pitfall has been detected. Second, OOPS! (OntOlogy Pitfall Scanner!), a tool for detecting pitfalls in ontologies and targeted at newcomers and domain experts unfamiliar with description logics and ontology implementation languages. The tool operates independently of any ontology development platform and is available online. The evaluation of the system is provided both through a survey of users' satisfaction and worldwide usage statistics. In addition, the system is also compared with existing ontology evaluation tools in terms of coverage of pitfalls detected.

Ontology based knowledge representation: Case study from agriculture domain

2021 ◽  
Vol 25 (1) ◽  
pp. 97-108
Author(s):  
Nidhi Malik ◽  
Deena Hijam ◽  
Aditi Sharan
Keyword(s):  
Knowledge Representation ◽  
Large Scale ◽  
Relevant Information ◽  
Ontology Development ◽  
Common Data Model ◽  
Domain Experts ◽  
Agriculture Sector ◽  
Time Usage ◽  
Representation Scheme

The growth of web has touched everyone’s life from an economist, entrepreneur, and academician to a farmer. The agriculture sector is quite important for any country’s growth. Farmers can also be benefited if they are provided with relevant information they need. The reason that it is not happening on a large scale is due to many reasons. Information is available in different formats, platforms and it is highly unstructured. The availability and real time usage of this information is prohibited mainly by the way it is represented. Recently, Ontology has emerged as one of very expressive knowledge representation scheme which enables gathering information from heterogeneous sources and creates a common data model that is shared and agreed upon in diverse domains. The interoperability and deduction capabilities that Ontology offers are very useful for generating new knowledge. Most of the work pertaining to ontology development in agriculture domain is crop specific, where information about fertilizers is confined to a particular crop only. In this paper, we have designed and developed a generic ontology for fertilizers. Fertilizer itself is a concept which should be modeled independently. Even for crop specific ontology, fertilizer is one of the most important concept to be captured. So, it needs to be represented independently. Finding this research gap, an ontology in fertilizer subdomain is developed, taking into account the various issues that are faced while constructing an ontology and the enormous amount of data that is available but is not easy to structure and present in the form of ontology. We have also validated the Ontology using an available tool and domain experts have also validated the developed Ontology.

ExtruOnt: An ontology for describing a type of manufacturing machine for Industry 4.0 systems

Semantic Web ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 887-909
Author(s):  
Víctor Julio Ramírez-Durán ◽  
Idoia Berges ◽  
Arantza Illarramendi
Keyword(s):  
Industry 4.0 ◽  
Development Process ◽  
Extrusion Process ◽  
Ontology Development ◽  
Development Effort ◽  
Close Collaboration ◽  
Domain Experts ◽  
Different Types ◽  
Types Of Information ◽  
Manufacturing Machine

Semantically rich descriptions of manufacturing machines, offered in a machine-interpretable code, can provide interesting benefits in Industry 4.0 scenarios. However, the lack of that type of descriptions is evident. In this paper we present the development effort made to build an ontology, called ExtruOnt, for describing a type of manufacturing machine, more precisely, a type that performs an extrusion process (extruder). Although the scope of the ontology is restricted to a concrete domain, it could be used as a model for the development of other ontologies for describing manufacturing machines in Industry 4.0 scenarios. The terms of the ExtruOnt ontology provide different types of information related with an extruder, which are reflected in distinct modules that constitute the ontology. Thus, it contains classes and properties for expressing descriptions about components of an extruder, spatial connections, features, and 3D representations of those components, and finally the sensors used to capture indicators about the performance of this type of machine. The ontology development process has been carried out in close collaboration with domain experts.

scholarly journals Why and how to engage expert stakeholders in ontology development: insights from social and behavioural sciences

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Emma Norris ◽  
Janna Hastings ◽  
Marta M. Marques ◽  
Ailbhe N. Finnerty Mutlu ◽  
Silje Zink ◽  
...  
Keyword(s):  
Science Studies ◽  
Classification Systems ◽  
Ontology Development ◽  
Main Body ◽  
Behavioural Science ◽  
Domain Experts ◽  
Community Needs ◽  
Advisory Boards ◽  
The Social ◽  
Behavioural Sciences

Abstract Background Incorporating the feedback of expert stakeholders in ontology development is important to ensure content is appropriate, comprehensive, meets community needs and is interoperable with other ontologies and classification systems. However, domain experts are often not formally engaged in ontology development, and there is little available guidance on how this involvement should best be conducted and managed. Social and behavioural science studies often involve expert feedback in the development of tools and classification systems but have had little engagement with ontology development. This paper aims to (i) demonstrate how expert feedback can enhance ontology development, and (ii) provide practical recommendations on how to conduct expert feedback in ontology development using methodologies from the social and behavioural sciences. Main body Considerations for selecting methods for engaging stakeholders are presented. Mailing lists and issue trackers as existing methods used frequently in ontology development are discussed. Advisory boards and working groups, feedback tasks, consensus exercises, discussions and workshops are presented as potential methods from social and behavioural sciences to incorporate in ontology development. Conclusions A variety of methods from the social and behavioural sciences exist to enable feedback from expert stakeholders in ontology development. Engaging domain experts in ontology development enables depth and clarity in ontology development, whilst also establishing advocates for an ontology upon its completion.

scholarly journals Why and how to engage expert stakeholders in ontology development: Insights from social and behavioural sciences

2020 ◽  
Author(s):  
Emma Norris ◽  
Janna Hastings ◽  
Marta M Marques ◽  
Ailbhe Noelle Finnerty ◽  
Silje Zink ◽  
...  
Keyword(s):  
Science Studies ◽  
Classification Systems ◽  
Ontology Development ◽  
Behavioural Science ◽  
Domain Experts ◽  
Community Needs ◽  
Advisory Boards ◽  
Mailing Lists ◽  
The Social ◽  
Behavioural Sciences

Background: Incorporating the feedback of expert stakeholders in ontology development is important to ensure content is scientifically sound, comprehensive, meets community needs and is interoperable with other ontologies and classification systems. However, domain experts are often not formally engaged in ontology development, and there is little available guidance on how this involvement should best be conducted and managed. Social and behavioural science studies often involve expert feedback in the development of tools and classification systems but have had little engagement with ontology development. This paper aims to i) demonstrate how expert feedback can enhance ontology development, and ii) provide practical recommendations on how to conduct expert feedback in ontology development using methodologies from the social and behavioural sciences.Main body: Considerations for selecting methods for engaging stakeholders are presented. Mailing lists and issue trackers as existing methods used frequently in ontology development are discussed. Advisory boards and working groups, feedback tasks, consensus exercises, discussions and workshops are presented as potential methods from social and behavioural sciences to incorporate in ontology development.Conclusion: A variety of methods from the social and behavioural sciences exist to enable feedback from expert stakeholders in ontology development. Engaging domain experts in ontology development enables depth and clarity in ontology development, whilst also establishing advocates for an ontology upon its completion.

scholarly journals Ontology Development for Medical and Health Science Domain in the Quran

2018 ◽  
Vol 7 (4.33) ◽  
pp. 504
Author(s):  
Muhammad Afifi Mohamad Safee ◽  
Madihah Mohd Saudi ◽  
Kamarudin Saadan
Keyword(s):  
Health Science ◽  
Ontology Development ◽  
Domain Experts ◽  
Ontology Evaluation ◽  
Sources Of Knowledge ◽  
Ontology Structure ◽  
Science Domain ◽  
Structure Accuracy ◽  
Future Work ◽  
Different Sources

Ontology is known as a knowledge representation and acts as a sharing platform for common ideas within a similar domain. It has a tree structure to ease the information presentation to users. Nowadays, it is very important to have a consistent and systematic way of presenting and retrieving different sources of knowledge such as the Quran and Hadith. Since there is so much useful information that can be retrieved from the Quran, especially for the Medical and Health Science domain, this paper presents the development of ontology for the Medical and Health Science domain in the Quran by adopting the Ontology 101 approach. These include the scope and domain determination, competency question formulation, ontology construction, and ontology evaluation. The proposed ontology in this paper has successfully retrieved the correct answers for Medical and Health Science using related queries via SPARQL-query and has been evaluated by the domain experts. Furthermore, the ontology structure accuracy has also been verified using reasoner, where it detected inconstancy during ontology development. For future work, this research paper can be used as a reference and basis to answer user queries, data integration with other applications or this ontology can be further expanded.  

OOPS!

2018 ◽  
pp. 120-148
Author(s):  
María Poveda-Villalón ◽  
Asunción Gómez-Pérez ◽  
Mari Carmen Suárez-Figueroa
Keyword(s):  
Web Service ◽  
Empirical Analysis ◽  
Web Application ◽  
Description Logics ◽  
Ontology Development ◽  
Evaluation Tools ◽  
Domain Experts ◽  
Development Platform ◽  
Ontology Evaluation ◽  
Modeling Errors

The first contribution of this paper consists on a live catalogue of pitfalls that extends previous works on modeling errors with pitfalls resulting from an empirical analysis of numerous ontologies. Such a catalogue classifies pitfalls according to the Structural, Functional and Usability-Profiling dimensions. For each pitfall, we include the value of its importance level (critical, important and minor). The second contribution is the description of OntOlogy Pitfall Scanner (OOPS!), a widely used tool for detecting pitfalls in ontologies and targeted at newcomers and domain experts unfamiliar with description logics and ontology implementation languages. The tool operates independently of any ontology development platform and is available through a web application and a web service. The evaluation of the system is provided both through a survey of users' satisfaction and worldwide usage statistics. In addition, the system is also compared with existing ontology evaluation tools in terms of coverage of pitfalls detected.

scholarly journals Ontological Methodologies for Counselling Intervention: Do’a and Zikr Al-Mā’thur Corpus

2021 ◽  
Vol 18 (2(Suppl.)) ◽  
pp. 0856
Author(s):  
Roslina Othman ◽  
Siti Fatimah Mohd Tawil
Keyword(s):  
Content Management ◽  
Online Resources ◽  
Ontology Development ◽  
Accurate Information ◽  
Subject Domain ◽  
Domain Experts ◽  
School Counsellors ◽  
Essential Input ◽  
User Assessment ◽  
Counselling Intervention

Do’a and Zikr al-Mā’thur (authentic supplications and remembrance of ALLAH ‘Azza wa Jalla) can be suggested to Muslims to help them deal with challenges or issues in life. Counselling cases affect a person’s feelings. Do’a and Zikr al-Mā’thur are often applied as a counselling intervention. Unfortunately, the authentic Do’a and Zikr al-Mā’thur are dispersed in many resources not visible to users, and the fact that not all online resources offer access to accurate Do’a and Zikr al-Mā’thur to users and the dubious Do’a and Zikr al-Mā’thur frequently credited to the Prophet (pbuh). The goal of this research is to develop an ontology for the purpose of providing credible results to counselling cases in need of relevant Do’a and Zikr Al- Ma’thur. This research focused on presenting how an ontology could support to provide accurate information to cases supervised by high school counsellors. This research developed the ontology for Do’a and Zikr al-Mā’thur for counselling in Protégé. The methodology implemented in the ontology development included the models designed by Fernandez-Lopez et al., Thunkijjanukij, Gomez-Perez et al., and Kreider. The ontology was verified, validated, and evaluated by two subject domain experts. Most concepts were rated as ‘Compliant’ and some as ‘Partially Compliant’. Queries in SPARQL produced answers to the competency questions. Feedbacks from the user assessment proved that the executed results from the Do’a and Zikr al-Mā’thur ontology for counselling succeeded in fulfilling the users’ requirement. It is recommended that the sustainability of the ontology should be secured through constant submission of real cases by counsellors and people with similar roles for query analysis and results. Credible scholars should provide direction to trustworthy sources. Such essential input is valuable for content management and contributes towards very few domain ontologies that deliver support to professional works. It also provides the step-by-step procedures to ontology construction and assessment for Islamic collection for counselling intervention.

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