Metadata Community Profiles for the Semantic Web

Bermúdez, Luis; Piasecki, Michael

doi:10.1007/s10707-006-7577-2

Cited by 20 publications

(7 citation statements)

References 14 publications

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“…In designing the water resources component ontology, we used the widely accepted skeletal methodology described by Uschold and Gruninger [], which has been successfully applied for building many ontologies [e.g., Kim , ; Brilhante and Robertson , ; Patil et al ., ; Biletskiy et al ., ; Bermudez and Piasecki , ]. The approach (summarized in Figure ) begins by first defining the purpose of the ontology and its design requirements.…”

Section: Methodsmentioning

confidence: 99%

An ontology for component‐based models of water resource systems

Elag

Goodall

2013

Water Resources Research

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[1] Component-based modeling is an approach for simulating water resource systems where a model is composed of a set of components, each with a defined modeling objective, interlinked through data exchanges. Component-based modeling frameworks are used within the hydrologic, atmospheric, and earth surface dynamics modeling communities. While these efforts have been advancing, it has become clear that the water resources modeling community in particular, and arguably the larger earth science modeling community as well, faces a challenge of fully and precisely defining the metadata for model components. The lack of a unified framework for model component metadata limits interoperability between modeling communities and the reuse of models across modeling frameworks due to ambiguity about the model and its capabilities. To address this need, we propose an ontology for water resources model components that describes core concepts and relationships using the Web Ontology Language (OWL). The ontology that we present, which is termed the Water Resources Component (WRC) ontology, is meant to serve as a starting point that can be refined over time through engagement by the larger community until a robust knowledge framework for water resource model components is achieved. This paper presents the methodology used to arrive at the WRC ontology, the WRC ontology itself, and examples of how the ontology can aid in component-based water resources modeling by (i) assisting in identifying relevant models, (ii) encouraging proper model coupling, and (iii) facilitating interoperability across earth science modeling frameworks.Citation: Elag, M., and J. L. Goodall (2013), An ontology for component-based models of water resource systems, Water Resour.

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Section: Methodsmentioning

confidence: 99%

An ontology for component‐based models of water resource systems

Elag

Goodall

2013

Water Resources Research

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“…Today science problems are solved by performing cross domain collaborations. Scientific data is served by various organizations and sources, including the previously mentioned citizen science; however, semantic heterogeneity makes it difficult to discover and merge data (Bermudez and Piasecki 2006). For example, air pollution from trash dumpsters can cause negative effects in health (Sheehan et al 2010).…”

Section: Linked Data and Semantic Webmentioning

confidence: 99%

New frontiers on open standards for geo-spatial science

Bermúdez

2017

Geo-spatial Information Science

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The process of sharing of data has become easier than ever with the advancement of cloud computing and software tools. However, big challenges remain such as efficient handling of big geospatial data, supporting and sharing of crowd sourced/citizen science data, integration with semantic heterogeneity, and inclusion of agile processes for continuous improvement of geospatial technology. This paper discusses the new frontiers regarding these challenges and the related work performed by the Open Geospatial Consortium, the world leading organization focused on developing open geospatial standards that "geo-enable" the Web, wireless, and location-based services and mainstream IT.

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“…In the domain of e-learning, the contribution of ontologies in the design of ITS has been amply demonstrated [6]. These ontologies were the basis of navigation offering forms of acquisition other than those proposed in the course of classical learning which are generally linear type [7].…”

Section: Ontologies and Education Systems 41 Contributions Of Ontolomentioning

confidence: 99%

Design of an Intelligent Tutorial System based on Ontologies

Mhouti¹,

Nasseh²,

Erradi³

2014

IJCA

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Today, environments of e-learning aim increasingly to give the learner an active role in learning in order to build their knowledge. They allow thereby integrating a more learnercentered vision. However, learners show differences between learning modes that suits them best. The problem posed is how to propose to the learner a teaching sequence adequate to his/her profile.This work is at the heart of this issue. It is interested in contributing on ontologies and cognitive theories to describe the learning preferences within the Intelligent Tutorial Systems (ITS). The objective of this paper is to propose a model of ITS, based on ontologies and cognitive theories, for adapting the learning resources proposed to a learner according to his/her learning preferences. The determination of these preferences is done through the analysis of learner behavior relying on his/her indicator MBTI (Myers Briggs Type Indicator). The proposed model integrates the main functionalities of an ITS: profiling, updating of the profile, selection, adaptation and presentation of adequate resources.

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Metadata Community Profiles for the Semantic Web

Cited by 20 publications

References 14 publications

An ontology for component‐based models of water resource systems

An ontology for component‐based models of water resource systems

New frontiers on open standards for geo-spatial science

Design of an Intelligent Tutorial System based on Ontologies

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