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Knowledge modelling for integrating semantic web services in e-government applications
Service integration and domain interoperability are
the basic requirements in the development of current
service-oriented e-Government applications. Semantic
Web and, in particular, Semantic Web Service (SWS)
technology aim to address these issues. However, the integration between e-Government applications and SWS is not an easy task. We argue that a more complex semantic layer needs to be modeled. The aim of our work is to provide an ontological framework that maps such a semantic layer. In this paper, we describe our approach for creating a project-independent and reusable model, and provide a case study that demonstrates its applicability
Organizational challenges of the semantic web in digital libraries
The Semantic Web initiative holds large promises
for the future. There is, however, a considerable gap in Semantic Web research between the contributions in the technological field and the research done in the organizational field. This paper examines, from a socio-technical point of view the impact of Semantic Web technology on the strategic, organizational and technological levels. Building on a comprehensive case study at the National Library in Norway our findings indicate that the highest impact will be at the organizational level. The reason is mainly because inter-organizational and cross-organizational structures have to be established
to address the problems of ontology engineering, and a development framework for ontology engineering in digital libraries must be examined
The OCareCloudS project: toward organizing care through trusted cloud services
The increasing elderly population and the shift from acute to chronic illness makes it difficult to care for people in hospitals and rest homes. Moreover, elderly people, if given a choice, want to stay at home as long as possible. In this article, the methodologies to develop a cloud-based semantic system, offering valuable information and knowledge-based services, are presented. The information and services are related to the different personal living hemispheres of the patient, namely the daily care-related needs, the social needs and the daily life assistance. Ontologies are used to facilitate the integration, analysis, aggregation and efficient use of all the available data in the cloud. By using an interdisciplinary research approach, where user researchers, (ontology) engineers, researchers and domain stakeholders are at the forefront, a platform can be developed of great added value for the patients that want to grow old in their own home and for their caregivers
Ontological Investigations of a Pragmatic Kind? A Reply to Lauer
This paper is a reply to Richard Lauer’s “Is Social Ontology Prior to Social Scientific Methodology?” (2019) and an attempt to contribute to the meta-social ontological discourse more broadly. In the first part, I will give a rough sketch of Lauer’s general project and confront his pragmatist approach with a fundamental problem. The second part of my reply will provide a solution for this problem rooted in a philosophy of the social sciences in practice
Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform
Nowadays, most people have limited leisure time and the offer of (cultural) activities to spend this time is enormous. Consequently, picking the most appropriate events becomes increasingly difficult for end-users. This complexity of choice reinforces the necessity of filtering systems that assist users in finding and selecting relevant events. Whereas traditional filtering tools enable e.g. the use of keyword-based or filtered searches, innovative recommender systems draw on user ratings, preferences, and metadata describing the events. Existing collaborative recommendation techniques, developed for suggesting web-shop products or audio-visual content, have difficulties with sparse rating data and can not cope at all with event-specific restrictions like availability, time, and location. Moreover, aggregating, enriching, and distributing these events are additional requisites for an optimal communication channel. In this paper, we propose a highly-scalable event recommendation platform which considers event-specific characteristics. Personal suggestions are generated by an advanced collaborative filtering algorithm, which is more robust on sparse data by extending user profiles with presumable future consumptions. The events, which are described using an RDF/OWL representation of the EventsML-G2 standard, are categorized and enriched via smart indexing and open linked data sets. This metadata model enables additional content-based filters, which consider event-specific characteristics, on the recommendation list. The integration of these different functionalities is realized by a scalable and extendable bus architecture. Finally, focus group conversations were organized with external experts, cultural mediators, and potential end-users to evaluate the event distribution platform and investigate the possible added value of recommendations for cultural participation
Referent tracking for corporate memories
For corporate memory and enterprise ontology systems to be maximally useful,
they must be freed from certain barriers placed around them by traditional
knowledge management paradigms. This means, above all, that they must mirror
more faithfully those portions of reality which are salient to the workings of the
enterprise, including the changes that occur with the passage of time. The purpose
of this chapter is to demonstrate how theories based on philosophical realism can
contribute to this objective. We discuss how realism-based ontologies (capturing
what is generic) combined with referent tracking (capturing what is specific) can
play a key role in building the robust and useful corporate memories of the future
Endurant Types in Ontology-Driven Conceptual Modeling: Towards OntoUML 2.0
For over a decade now, a community of researchers has contributed
to the development of the Unified Foundational Ontology (UFO)
- aimed at providing foundations for all major conceptual modeling constructs.
This ontology has led to the development of an Ontology-Driven
Conceptual Modeling language dubbed OntoUML, reflecting the ontological
micro-theories comprising UFO. Over the years, UFO and OntoUML
have been successfully employed in a number of academic, industrial and
governmental settings to create conceptual models in a variety of different
domains. These experiences have pointed out to opportunities of
improvement not only to the language itself but also to its underlying
theory. In this paper, we take the first step in that direction by revising
the theory of types in UFO in response to empirical evidence. The
new version of this theory shows that many of the meta-types present
in OntoUML (differentiating Kinds, Roles, Phases, Mixins, etc.) should
be considered not as restricted to Substantial types but instead should
be applied to model Endurant Types in general, including Relator types,
Quality types and Mode types. We also contribute a formal characterization
of this fragment of the theory, which is then used to advance a
metamodel for OntoUML 2.0. Finally, we propose a computational support
tool implementing this updated metamodel
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