Deep Meta-modelling with MetaDepth

Lara, Juan de; Guerra, Esther

doi:10.1007/978-3-642-13953-6_1

Cited by 99 publications

(121 citation statements)

References 17 publications

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“…MetaDepth [18,20] is a meta-modelling tool that incorporates deep instantiation. The practical experiences with MetaDepth [19] fit well with our own findings.…”

Section: Related Workmentioning

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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“…MetaDepth [18,20] is a meta-modelling tool that incorporates deep instantiation. The practical experiences with MetaDepth [19] fit well with our own findings.…”

Section: Related Workmentioning

confidence: 99%

Dual Deep Instantiation and Its ConceptBase Implementation

Neumayr

Jeusfeld

Schrefl

et al. 2014

Advanced Information Systems Engineering

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“…Early approaches were materialization [19] and power types [18]. Many current approaches [6,20,12,16] to multi-level modeling assign potencies to relationships, attributes, and classes. Potencies constrain how many times the respective concept can be instantiated until it can no further be instantiated.…”

Section: Introductionmentioning

confidence: 99%

“…The result is DeepTelos, a language and system for Deep Metamodeling (combining metamodeling and multilevel modeling), akin to MetaDepth [12]. What sets DeepTelos apart are the strenghts inherited from Telos and ConceptBase:…”

Section: Introductionmentioning

confidence: 99%

DeepTelos: Multi-level Modeling with Most General Instances

Jeusfeld

Neumayr

2016

Conceptual Modeling

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Abstract. Multi-level modeling aims to reduce redundancy in data models by defining properties at the right abstraction level and inheriting them to more specific levels. We revisit one of the earliest such approaches, Telos, and investigate what needs to be added to its axioms to get a true multi-level modeling language. Unlike previous approaches, we define levels not with numeric potencies but with hierarchies of so-called most general instances.

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“…From these fragments, a meta-model is automatically induced, which can be refactored if needed. Finally, the resulting meta-model is compiled into a given technology (e.g., EMF or MetaDepth [8]), optimized for a particular purpose (visual or textual language, transformation) and a particular tool (e.g., xText or GMF). Paper organization.…”

Section: Introductionmentioning

confidence: 99%

Bottom-Up Meta-Modelling: An Interactive Approach

Cuadrado

Lara

Guerra

2012

Lecture Notes in Computer Science

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Esta es la versión de autor de la comunicación de congreso publicada en: This is an author produced version of a paper published in: Abstract. The intensive use of models in Model-Driven Engineering (MDE) raises the need to develop meta-models with different aims, like the construction of textual and visual modelling languages and the specification of source and target ends of model-to-model transformations. While domain experts have the knowledge about the concepts of the domain, they usually lack the skills to build meta-models. These should be tailored according to their future usage and specific implementation platform, which demands knowledge available only to engineers with great expertise in MDE platforms. These issues hinder a wider adoption of MDE both by domain experts and software engineers. In order to alleviate this situation we propose an interactive, iterative approach to meta-model construction enabling the specification of model fragments by domain experts, with the possibility of using informal drawing tools like Dia. These fragments can be annotated with hints about the intention or needs for certain elements. A meta-model is automatically induced, which can be refactored in an interactive way, and then compiled into an implementation meta-model using profiles and patterns for different platforms and purposes.

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Deep Meta-modelling with MetaDepth

Cited by 99 publications

References 17 publications

Dual Deep Instantiation and Its ConceptBase Implementation

Dual Deep Instantiation and Its ConceptBase Implementation

DeepTelos: Multi-level Modeling with Most General Instances

Bottom-Up Meta-Modelling: An Interactive Approach

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