Ontology-based information model development for science information reuse and integration

Hughes, J. Steven; Crichton, Daniel J.; Mattmann, Chris A.

doi:10.1109/iri.2009.5211603

Cited by 8 publications

(10 citation statements)

References 12 publications

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“…However, these approaches do not involve a series of steps as identified in the problem statement approach and logical decomposition modelling techniques for identification and structuring of the thesaurus terminologies. Ontologybased modelling has been widely used for defining concepts (Hughes et al, 2009;Duan et al, 2009;Liu et al, 2010 The construction of ontologies has recently benefited from the implementation of tools based on semantic web standards, allowing people to work collectively. The A System of Systems is an integration of a finite number of constituent systems which are independent and operable, and which are networked together for a period of time to achieve a certain higher goal(s) (Jamshidi, 2009) A SYSTEM OF SYSTEMS is an integration of a finite number of constituent systems which are independent and operable, and which are networked together for a period of time to achieve a certain higher goal(s) Collaborative Protégé tool (Tudorache et al, 2008), a plugin of the Protégé environment devoted to the construction of ontologies (Gennari et al, 2003), offers functionalities adapted to community approaches.…”

Section: Traditional Approaches and Ontology Editorsmentioning

confidence: 99%

Systems of systems engineering thesaurus approach: from concept to realisation

Doğan¹,

Barot²,

Henshaw³

et al. 2014

IJSSE

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Abstract:The developing discipline of Systems of Systems Engineering (SoSE) Michael Henshaw is Professor of Systems Engineering; he is head of the Systems Division and leads the Engineering Systems of Systems (EsoS) Research Group at Loughborough University. His research focuses on integration and management of complex socio-technical systems, with a particular emphasis on the challenges of through-life management of systems and capabilities.Carys Siemieniuch is Professor of Enterprise Systems Engineering at Loughborough University. Carys has both UK professional and European CREE registration as an ergonomist, with expertise across the full range of systems-related human factors topics. Her key skills are in knowledge lifecycle management systems, organisational and cultural aspects of enterprise modeling techniques, organisational systems architectures, dynamic allocation of function and the design of complex systems. She is active in both the military and civilian domains.Murray Sinclair is now a Visiting Fellow at Loughborough University, as well as a Visiting Academic at the University of Sydney. He is a Systems Ergonomist of some 40 years standing, having been an academic member of Loughborough University since 1970. His interests have evolved from the understanding of organisational processes of manufacturing from the shopfloor, through manufacturing systems engineering to design processes and the management of knowledge. Latterly, due to the steady infiltration of information technology into society and its pervasiveness in the lives of individuals, his interests now include the assurance of ethical behaviour by autonomous and semiautonomous systems, such as robots, healthcare systems and the like.

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Section: Traditional Approaches and Ontology Editorsmentioning

confidence: 99%

Systems of systems engineering thesaurus approach: from concept to realisation

Doğan¹,

Barot²,

Henshaw³

et al. 2014

IJSSE

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“…Ontology-based modelling for information and knowledge management has been widely used (Hughes et al 2009;Duan et al 2009;Dongmin et al 2010;Liu et al 2010). Generally, an ontology is defined as an explicit specification of a conceptualisation where concepts and their relations are extracted from the real world (Studer et al 1998;Duan et al 2009).…”

Section: Ontology-based Approachesmentioning

confidence: 99%

“…• ontology-based conceptual knowledge representation model (Kourlimpinis et al 2008); • ontology-based information model development for science information reuse and integration (Hughes et al 2009); • ontology-based knowledge modelling framework for intangible cultural heritage (Tan et al 2009); • domain ontology life-cycle engineering framework for modular product design (Duan et al, 2009;Liu et al 2011); and • ontology for product-service system by Cranfield University (Annamalai et al 2010). Annamalai et al (2010) discusses methodologies for developing an ontology through analysing various approaches and argued that "there is no one correct way to model a domain and that ontology development is necessarily an iterative process".…”

Section: Ontology-based Approachesmentioning

confidence: 99%

7.5.1 An incremental hybridisation of heterogeneous case studies to develop an ontology for capability engineering

Doğan

Henshaw

Johnson

2012

INCOSE International Symp

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Abstract. An analysis of perspectives for "capability engineering" has been conducted by the INCOSE UK Capability Working Group (CWG). This paper is a continuation of this study led by the CWG ontology work stream that aims to develop a single shared ontology for the concept of capability engineering to enable semantic interoperability and to support a formal and explicit specification of a shared conceptualisation. Case study material from the different domains of rail, defence and information services was used. The ontology development was executed in three phases; (1) pre-analysis, (2) ontology modelling and (3) post-analysis. The pre-analysis involved literature reviews, requirements specification, systems engineering process utilisation; and resource identification i.e. examination of the case study material. The ontology modelling phase comprised information extraction and classification in addition to modelling and code representation using a mark-up tool, MS Excel and Protégé. The post-analysis involved validation workshops through using expert focus groups.

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“…The PDS4 architecture has two primary components: the information architecture and the software/technical architecture. The PDS4 Information Architecture (Hughes et al, 2009Crichton et al, 2011) defines the system's informational requirements and institutes a multi-governance scheme for management of the architecture components. The PDS4 Information Model (Hughes et al, 2009, the core component of the architecture, is based on the ISO 14721 (ISO 14721, 2003) and ISO/IEC 11179 standards (ISO/IEC 11179, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…The PDS4 Information Architecture (Hughes et al, 2009Crichton et al, 2011) defines the system's informational requirements and institutes a multi-governance scheme for management of the architecture components. The PDS4 Information Model (Hughes et al, 2009, the core component of the architecture, is based on the ISO 14721 (ISO 14721, 2003) and ISO/IEC 11179 standards (ISO/IEC 11179, 2008). It was designed to be extensible across science disciplines and to promote interoperability that facilitates data sharing internationally.…”

Section: Introductionmentioning

confidence: 99%

Enabling interoperability in planetary sciences and heliophysics: The case for an information model

Hughes

Crichton

Raugh

et al. 2018

Planetary and Space Science

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A B S T R A C TThe Planetary Data System has developed the PDS4 Information Model to enable interoperability across diverse science disciplines. The Information Model is based on an integration of International Organization for Standardization (ISO) level standards for trusted digital archives, information model development, and metadata registries. Where controlled vocabularies provides a basic level of interoperability by providing a common set of terms for communication between both machines and humans the Information Model improves interoperability by means of an ontology that provides semantic information or additional related context for the terms. The information model was defined by team of computer scientists and science experts from each of the diverse disciplines in the Planetary Science community, including Atmospheres, Geosciences, Cartography and Imaging Sciences, Navigational and Ancillary Information, Planetary Plasma Interactions, Ring-Moon Systems, and Small Bodies. The model was designed to be extensible beyond the Planetary Science community, for example there are overlaps between certain PDS disciplines and the Heliophysics and Astrophysics disciplines. "Interoperability" can apply to many aspects of both the developer and the end-user experience, for example agency-to-agency, semantic level, and application level interoperability. We define these types of interoperability and focus on semantic level interoperability, the type of interoperability most directly enabled by an information model.

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Ontology-based information model development for science information reuse and integration

Abstract: Abstract

Cited by 8 publications

References 12 publications

Systems of systems engineering thesaurus approach: from concept to realisation

Systems of systems engineering thesaurus approach: from concept to realisation

7.5.1 An incremental hybridisation of heterogeneous case studies to develop an ontology for capability engineering

Enabling interoperability in planetary sciences and heliophysics: The case for an information model

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