Evidence of large-scale conceptual disarray in multi-level taxonomies in Wikidata

The distinction between types and individuals is key to most conceptual modeling techniques and knowledge representation languages. Despite that, there are a number of situations in which modelers navigate this distinction inadequately, leading to problematic models. We show evidence of a large number of representation mistakes associated with the failure to employ this distinction in the Wikidata knowledge graph, which can be identified with the incorrect use of instantiation, which is a relation between an instance and a type, and specialization (or subtyping), which is a relation between two types. The prevalence of the problems in Wikidata’s taxonomies suggests that methodological and computational tools are required to mitigate the issues identified, which occur in many settings when individuals, types, and their metatypes are included in the domain of interest. We conduct a conceptual analysis of entities involved in recurrent erroneous cases identified in this empirical data, and present a tool that supports users in identifying some of these mistakes

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

Towards an Ontological Analysis of Powertypes

Abstract In several subject domains, the categorization scheme itself is part of the subject matter. In this case, experts make use of categories of categories in their accounts. This has led to a number of approaches in conceptual modeling and knowledge representation that are called multi-level modeling approaches. An early approach for multi-level modeling is the powertype pattern which introduces &quot;power types&quot; and &quot;base types&quot;. More recently, other proposals for multilevel modeling include &quot;clabjects&quot;, &quot;m-objects&quot;, which admit the existence of entities being somehow, simultaneously, types (classes) and instances (usually associated to objects). Regardless of the choice of approach to perform multi-level modelling, a question remains concerning the ontological status of &quot;base types&quot;, &quot;power types&quot; and &quot;clabjects&quot;. This paper aims to address this question through an ontological analysis. We use here the general term powertype to generally refer to types whose instances exhibit somehow both type-like and instance-like characteristics. We examine alternative accounts for powertype instances: (i) powertype instances as universals (abstract repeatable entities), (ii) powertype instances as mereological sums of instances of an associated type and (iii) powertype instances as variable embodiments. We conclude that the latter is the most promising account for an ontological interpretation of this phenomenon that meets the modelling desiderata for powertypes present in the literature

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

Representation of Multi-Level Domains on The Web

Estratégias de modelagem conceitual e representação de conhecimento frequentemente tratam entidades em dois níveis: um nível de classes e um nível de indivíduos que instanciam essas classes. Em vários domínios, porém, as próprias classes podem estar sujeitas a categorização, resultando em classes de classes (ou metaclasses). Ao representar estes domínios, é preciso capturar não apenas as entidades de diferentes níveis de classificação, mas também as suas relações (possivelmente complexas). No domínio de taxonomias biológicas, por exemplo, um dado organismo (por exemplo, o leão Cecil morto em 2015 no Parque Nacional Hwange no Zimbábue) é classificado em diversos táxons (como, por exemplo, Animal, Mamífero, Carnívoro, Leão), e cada um desses táxons é classificado por um ranking taxonômico (por exemplo, Reino, Classe, Ordem, Espécie). Assim, para representar o conhecimento referente a esse domínio, é necessário representar entidades em níveis diferentes de classificação. Por exemplo, Cecil é uma instância de Leão, que é uma instância de Espécie. Espécie, por sua vez, é uma instância de Ranking Taxonômico. Além disso, quando representamos esses domínios, é preciso capturar não somente as entidades diferentes níveis de classificação, mas também suas (possivelmente complicadas) relações. Por exemplo, nós gostaríamos de afirmar que instâncias do gênero Panthera também devem ser instâncias de exatamente uma instância de Espécie (por exemplo, Leão). A necessidade de suporte à representação de domínios que lidam com múltiplos níveis de classificação deu origem a uma área de investigação chamada modelagem multi-nível. Observa-se que a representação de modelos com múltiplos níveis é um desafio em linguagens atuais da Web Semântica, como há pouco apoio para orientar o modelador na produção correta de ontologias multi-nível, especialmente por causa das nuanças de restrições que se aplicam a entidades de diferentes níveis de classificação e suas relações. A fim de lidar com esses desafios de representação, definimos um vocabulário que pode ser usado como base para a definição de ontologias multi-nível em OWL, juntamente com restrições de integridade e regras de derivação. É oferecida uma ferramenta que recebe como entrada um modelo de domínio, verifica conformidade com as restrições de integridade propostas e produz como saída um modelo enriquecido com informações derivadas. Neste processo, é empregada uma teoria axiomática chamada MLT (uma Teoria de Modelagem Multi-Nível). O conteúdo da plataforma Wikidata foi utilizado para demonstrar que o vocabulário poderia evitar inconsistências na representação multi-nível em um cenário real

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