Representing Knowledge About Information Systems in Telos

Mylopoulos, John; Borgida, Alex; Jarke, Matthias; Koubarakis, Manolis

doi:10.1007/978-3-642-84875-9_2

Cited by 174 publications

(222 citation statements)

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“…ConceptBase [12,14] is a metamodeling system based on Datalog and the Telos data model [21]. All explicit information (objects, classes, metaclasses) are represented with a single extensional predicate P(id,from,label,to).…”

Section: Implementation In Conceptbasementioning

confidence: 99%

Dual Deep Instantiation and Its ConceptBase Implementation

Neumayr

Jeusfeld

Schrefl

et al. 2014

Advanced Information Systems Engineering

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Abstract. Application integration requires the consideration of instance data and schema data. Instance data in one application may be schema data for another application, which gives rise to multiple instantiation levels. Using deep instantiation, an object may be deeply characterized by representing schema data about objects several instantiation levels below. Deep instantiation still demands a clear separation of instantiation levels: the source and target objects of a relationship must be at the same instantiation level. This separation is inadequate in the context of application integration. Dual deep instantiation (DDI), on the other hand, allows for relationships that connect objects at different instantiation levels. The depth of the characterization may be specified separately for each end of the relationship. In this paper, we present and implement set-theoretic predicates and axioms for the representation of conceptual models with DDI.

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Section: Implementation In Conceptbasementioning

confidence: 99%

Dual Deep Instantiation and Its ConceptBase Implementation

Neumayr

Jeusfeld

Schrefl

et al. 2014

Advanced Information Systems Engineering

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“…The frames were used for communication purposes and Stakeholder validation, but did not contribute to further automation in software development. − Logical languages were used in ERAE [7,8], RML [9,10], Telos [11,12], FRORL [13], and PML [14] projects. These languages require technical training for their use and elaboration, which Stakeholders do not have.…”

Section: Overview Of Knowledge Representationmentioning

confidence: 99%

Pre-conceptual Schema: A Conceptual-Graph-Like Knowledge Representation for Requirements Elicitation

Jaramillo

Gelbukh

Isaza

2006

Lecture Notes in Computer Science

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Abstract. A simple representation framework for ontological knowledge with dynamic and deontic characteristics is presented. It represents structural relationships (is-a, part/whole), dynamic relationships (actions such as register, pay, etc.), and conditional relationships (if-then-else). As a case study, we apply our representation language to the task of requirements elicitation in software engineering. We show how our pre-conceptual schemas can be obtained from controlled natural language discourse and how these diagrams can be then converted into standard UML diagrams. Thus our representation framework is shown to be a useful intermediate step for obtaining UML diagrams from natural language discourse.

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“…Knowledge sharing in this setting is primarily a social process [9,46,20]. The SECI model makes a basic distinction between tacit and explicit knowledge [40,38,35,26,27]. The processes include the related media specific operations: transcription, localization, and addressing.…”

Section: Fig 1 Transcription Creates Interpretations Of Media In Mediamentioning

confidence: 99%

Pattern-Based Cross Media Social Network Analysis for Technology Enhanced Learning in Europe

Klamma

Spaniol

Cao

et al. 2006

Innovative Approaches for Learning and Knowledge Sharing

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Abstract. It is extremely challenging to get an overview of the current state-of-the-art in technology enhanced learning in Europe. Rapid technological and pedagogical innovations, constantly changing markets, a vivid number of small and medium enterprises, complex policy processes, ongoing political and societal debates on the pros and cons of technology enhanced leaning, combined with many languages and different cultures, make it almost impossible for people to be informed. We want to introduce the media base and the measure tools for pattern-based cross media social network analysis, created by the PROLEARN network of excellence in professional learning. The main goal of this endeavour is the reduction of complexity for actors in digital social networks by applying ideas from social software and already successful methods for complexity reduction, such as information visualization, social network analysis and pattern languages.

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Representing Knowledge About Information Systems in Telos

Cited by 174 publications

References 0 publications

Dual Deep Instantiation and Its ConceptBase Implementation

Dual Deep Instantiation and Its ConceptBase Implementation

Pre-conceptual Schema: A Conceptual-Graph-Like Knowledge Representation for Requirements Elicitation

Pattern-Based Cross Media Social Network Analysis for Technology Enhanced Learning in Europe

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