Building Information Science Ontology (OIS) with Methontology and Protégé

Sawsaa, Ahlam F.; Lu, Joan

doi:10.20533/jitst.2046.3723.2012.0014

Cited by 9 publications

(7 citation statements)

References 9 publications

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“…Is the "chain of command" thus asymmetric, and why, or are there missing concepts? As such this formal approach could be combined with OntoClean, METHONTOLOGY or other ontology engineering approaches [4,10].…”

Section: Future Researchmentioning

confidence: 99%

Active Semantic Relations in Layered Enterprise Architecture Development

Baxter

Polovina

Laurier

2021

Lecture Notes in Computer Science

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Enterprise Architecture (EA) metamodels align an organisation’s business, information and technology resources so that these assets best meet the organisation’s purpose. The Layered EA Development (LEAD) Ontology enhances EA practices by a metamodel with layered metaobjects as its building blocks interconnected by semantic relations. Each metaobject connects to another metaobject by two semantic relations in opposing directions, thus highlighting how each metaobject views other metaobjects from its perspective. While the resulting two directed graphs reveal all the multiple pathways in the metamodel, more desirable would be to have one directed graph that focusses on the dependencies in the pathways. Towards this aim, using CG-FCA (where CG refers to Conceptual Graph and FCA to Formal Concept Analysis) and a LEAD case study, we determine an algorithm that elicits the active as opposed to the passive semantic relations between the metaobjects resulting in one directed graph metamodel. We also identified the general applicability of our algorithm to any metamodel that consists of triples of objects with active and passive relations.

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Section: Future Researchmentioning

confidence: 99%

Active Semantic Relations in Layered Enterprise Architecture Development

Baxter

Polovina

Laurier

2021

Lecture Notes in Computer Science

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“…WebGov fulfils the key requirements for a public services ontology to be useful [16]. Firstly, it covers multiple aspects of services, including administrative responsibility, involved documents, legislation and meta-data etc... Secondly, since it is designed and implemented based on METHONLOGY [17] method, the proposed ontology is fully extensible in the sense that it facilitates incremental ontology development, by incorporating basic concepts and relationships at an initial phase and then defining new ones, or creating instances as needed. The semantically rich network of interrelated concepts formulating by WebGovis mainly used in supporting the e-Government service composition tasks.…”

Section: Recommendation Layer: Machine Learning Based Personalizationmentioning

confidence: 99%

Artificial Intelligence based Composition for E-Government Services

Adadi

Berrada

Akkad³

2019

Proceedings of the Third International Conference on Computing and Wireless Communication Systems, ICCWCS 2019, April 24-25, 20

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Given the complex nature of the public sector with several distributed governmental institutions and manifold semantic differences of interpretation, the achievement of interoperability and integration is a key challenge for a comprehensive and effective Electronic Government (e-Government). Promising technologies that could be used to tackle this issue are: the powerful concept of ontology and the advanced Artificial Intelligence (AI) systems. Ontologies contribute to a common understanding of heterogeneous resources, while AI techniques make process integration dynamic and automated. However, up until now the use of AI along with ontologies has been fairly limited in e-Government. There is still, then, untapped potential in this field which worth to be exploited. In this paper, we present a dynamic approach for semantically integrating e-Government Web services based on AI techniques. The overall objective of our approach is to improve the citizen centric e-Government vision by providing a conceptual framework for automatically discovering, composing and optimizing e-Government services. Within the proposed approach, special emphasis is put on personalization aspects and evaluation criteria for e-Government platform.

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“…Among these approaches to building an ontology, methontology and NeOn are two systematic and comprehensive methods. Methontology has proven to be a comprehensive method for modeling a development process and building ontologies from the beginning (Fernández-L opez et al, 1997), and it has been implemented in several studies, for example, e-Government ontology (Dombeu and Huisman, 2011), information science ontology (Sawsaa and Lu, 2012), legal ontologies (Corcho et al, 2005), online learning (Guinebert et al, 2017) and others. The NeOn Methodology is an approach that supports making use of existing resources (e.g.…”

Section: Ontology Building Approachmentioning

confidence: 99%

Linking historical collections in an event-based ontology

Zou

Park

2018

DLP

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Purpose This study aims to explore a way of representing historical collections by examining the features of an event in historical documents and building an event-based ontology model. Design/methodology/approach To align with a domain-specific and upper ontology, the Basic Formal Ontology (BFO) model is adopted. Based on BFO, an event-based ontology for historical description (EOHD) is designed. To define events, event-related vocabularies are taken from the Library of Congress’ event types (2012). The three types of history and six kinds of changes are defined. Findings The EOHD model demonstrates how to apply the event ontology to biographical sketches of a creator history to link event types. Research limitations/implications The EOHD model has great potential to be further expanded to specific events and entities through different types of history in a full set of historical documents. Originality/value The EOHD provides a framework for modeling and semantically reforming the relationships of historical documents, which can make historical collections more explicitly connected in Web environments.

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Building Information Science Ontology (OIS) with Methontology and Protégé

Abstract: Abstract

Cited by 9 publications

References 9 publications

Active Semantic Relations in Layered Enterprise Architecture Development

Active Semantic Relations in Layered Enterprise Architecture Development

Artificial Intelligence based Composition for E-Government Services

Linking historical collections in an event-based ontology

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