Multi-level modeling with LML : A contribution to the Multi-level Process Challenge

This paper presents a solution to the MULTI Process Challenge which was first posed to the participants of the MULTI workshop at the MODELS conference in 2019 and subsequently adapted for this special issue of the EMISA Journal. The structure of the paper therefore follows the guidelines laid out in the Challenge description. The models are represented in the Level-agnostic Modeling Language LML and the DOCL constraint language using the Melanee deep modeling tool. After first outlining the case study and documenting which aspects are supported in the LML solution, the paper presents multi-level models for both the insurance and the software engineering domains. This is followed by a discussion of the strengths and weaknesses of the approach. The presented model covers all mandatory and optional aspects of the Challenge case study

Multi-level conceptual modeling:Theory, language and application

In many important subject domains, there are central real-world phenomena that span across multiple classification levels. In these subject domains, besides having the traditional type-level domain regularities (classes) that classify multiple concrete instances, we also have higher-order type-level regularities (metaclasses) that classify multiple instances that are themselves types. Multi-Level Modeling aims to address this technical challenge. Despite the advances in this area in the last decade, a number of requirements arising from representation needs in subject domains have not yet been addressed in current modeling approaches. In this paper, we address this issue by proposing an expressive multi-level conceptual modeling language (dubbed ML2). We follow a principled language engineering approach in the design of ML2, constructing its abstract syntax as to reflect a fully axiomatized theory for multi-level modeling (termed MLT*). We show that ML2 enables the expression of a number of multi-level modeling scenarios that cannot be currently expressed in the existing multi-level modeling languages. A textual syntax for ML2 is provided with an implementation in Xtext. We discuss how the formal theory influences the language in two aspects: (i) by providing rigorous justification for the language's syntactic rules, which follow MLT* theorems and (ii) by forming the basis for model simulation and verification. We show that the language can reveal problems in multi-level taxonomic structures, using Wikidata fragments to demonstrate the language's practical relevance.</p

Multi-Level Design of Process-Oriented Enterprise Information Systems:Essential Guidelines and two Case Studies based on the FMMLx and the XModelerML

This paper presents prototypical multi-level models of two uses cases. They comprise models of business processes and models that represent the context required to execute a business process. On the one hand, the context consists of the organizational units that are responsible for the execution of processes. They are represented by a model of organizational structures. On the other hand, the context includes the artifacts that are needed or manipulated by processes. The models serve to demonstrate the specific power of multi-level modeling. First, they integrate models on higher levels, which correspond to domain-specific modeling languages, with those on lower levels. Second, models are supplemented with objects on L0 to demonstrate how these can be integrated. Third, the models are executable without the need to generate code, since models and corresponding program code share the same representation, thus demonstrating the possibility of advanced application system architectures, which allow users to navigate a comprehensive representation of the system they work with at runtime. The presentation of the models is supplemented with a general evaluation of multi-level concepts. The design of the models was inspired by the EMISA process challenge. Therefore, they are evaluated against the requirements defined with the challenge. In addition, a challenge is discussed that goes beyond the challenge, that is, the design of multi-level models of behavior

DeepTelos for ConceptBase : A contribution to the MULTI process challenge

DeepTelos is a straightforward extension of the Telosmodeling language to allow some form of multi-level modeling. A variant of Telos has been implemented in the ConceptBase system on top of a Datalog engine. Telos defines the concepts of instantiation, specialization and attribution/relations by means of axioms. In addition, the user can define new constructs by deductive rules, integrity constraints, and so-called query classes. In this paper, we tackle the process challenge formulated for the MULTI 2019 workshop to see to which extent DeepTelos is ableto represent the requirements of this challenge.KK Stiftelsen Synergy project: Knowledge-driven decision support via optimizationEU ISF Project A431.678/2016 ELVIR