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The Enterprise Ontology" The Knowledge Engineering Review
... The enterprise ontology acts as an interactive medium or platform between different people, such as users, designers, and planners in various organizations [37]. ...
... Researchers represent different ontology models for different applications. This article selects pioneering research such as TOVE 1 [35], [39], context-based enterprise ontology [40], and the enterprise ontology TEO 2 [37]. These projects and other researchers are recognized as pioneers in this article. ...
Enterprise ontology serves as a foundational framework for semantically comprehending the nature of organizations and the essential components that uphold their integrity. The systematic and conceptual understanding of organizations has garnered significant attention from researchers due to its pivotal role in various domains, including business modeling, enterprise architecture, business process management, context-aware systems, application development, interoperability across diverse systems and platforms, knowledge management, organizational learning and innovation, and conflict resolution within organizations. Achieving a consensus on the concepts related to the fundamental elements that constitute an organization is therefore critical. This study aims to conduct a comprehensive analysis and comparison of existing conceptual models of enterprises as documented in scholarly articles published over the past decade. We discuss the strengths and weaknesses of each model and introduce a robust framework for their evaluation. To facilitate this evaluation, we propose several pertinent criteria derived from established methodologies for assessing ontologies. Furthermore, we identify contemporary challenges and issues that have been overlooked in prior studies, offering insights and suggestions for future research directions in enterprise modeling. This article ultimately presents a roadmap for enhancing the systematic understanding of organizations through refined enterprise ontology frameworks.
... Enterprise Ontologies (Dietz, 2006) contain definitions of business concepts and relationships among them. Although various Enterprise Ontologies (Fox et al., 1996;Uschold et al., 1998;Dietz, 2006;Leppänen, 2005;Bertolazzi et al., 2001) exist, they have not yet achieved a standardization. ...
... Enterprise Ontologies contain a shared conceptualization of enterprise aspects. There exist several Enterprise Ontologies such as the Toronto Virtual Enterprise (TOVE) (Fox et al., 1996); The Enterprise Ontology (Uschold et al., 1998); Context-Based Enterprise Ontology (Leppänen, 2005); Core Enterprise Ontology (CEO) (Bertolazzi et al., 2001); and Resource-Event-Agent (REA) McCarthy, 2000, 2002). Enterprise Architectures also describe concepts and relations of an enterprise. ...
Many enterprises face the increasing challenge of sharing and exchanging data from multiple heterogeneous
sources. Enterprise Ontologies can be used to effectively address such challenge. In this paper, we present
an Enterprise Ontology called ArchiMEO, which is based on an ontological representation of the ArchiMate
standard for modeling Enterprise Architectures. ArchiMEO has been extended to cover various application
domains such as supply risk management, experience management, workplace learning and business process
as a service. Such extensions have successfully proven that our Enterprise Ontology is beneficial for enterprise
applications integration purposes.
... Precisely, ontology is one of the knowledge structures with great adoption in different domains. As Uschold et al. [16] define: "An ontology may take a variety of forms, but necessarily it will include a vocabulary of terms, and some specification of their meaning. This includes definitions and an indication of how concepts are inter-related which collectively impose a structure on the domain and constrain the possible interpretations of terms." ...
... Table 6 presents a summary of the features defined as relevant and irrelevant by feature selection approaches. In Breast Cancer dataset, Chi 2 defined the highest number of features as relevants (7), while the Expert Knowledge was the approach that considered the highest number of features as relevants in the datasets Primary tumor (16) and CNS (236). ...
Recently, available data has increased explosively in both number of samples and dimensionality. The huge number of high dimensional data generates the presence of noisy, redundant and irrelevant dimensions. Such dimensions can increase the time and computational cost in the learning process and even degenerate the performance of learning tasks. One of the ways to reduce dimensionality is by Feature Selection (FS). The aim of this paper is study the feature selection based on expert knowledge and traditional methods (filter, wrapper and embedded) and analyze their performance in classification tasks. Three datasets related to cancer domain in humans were used for feature selection: Breast Cancer (BC), Primary Tumor (PT) and Central Nervous System (CNS). C4.5, K-Nearest Neighbors, Support Vector Machine and Multi Layer Perceptron were trained with the best subset of features for each cancer dataset. The subset of features selected by the wrapper method presents the best average accuracy in the datasets BC and PT, while the subset of features selected by the embedded method reaches the highest average accuracy in the CNS dataset.
... El análisis de las características generales y de las características que describen el contenido de la ontología de los artículos revisados y de algunos más como Uschold et al. (1998), Lemaignan et al. (2006) y Raileanu et al. (2014), se resume en la Tabla 1 clasificados según su contribución: abundante (•), mínima (•) o ninguna ( ), contrastando al final con la propuesta otológica definida de forma resumida en las siguientes secciones de este documento. ...
... Para cumplir el objetivo planteado se analizan diversas metodologías: Methontology (Gómez-Pérez et al., 1996), Uschold and Kingís Ontology (Uschold et al., 1998), Ontology Development 101 (Noy and McGuinness, 2001), entre otras. Cada una de estas propuestas describen las fases del desarrollo de una ontología a diferentes niveles de conocimiento. ...
Holonic manufacturing systems are formed by holons that are capable of behaving in an autonomous, cooperative, selforganized and reconfigurable way to adopt different structures under normal and emergency operating conditions. These holons possess: (1) a representation of the world in which they live, (2) a distributed and decentralized control unit, and (3) a coordination module. The object of interest of the present research is the conception of a unified ontology in manufacturing domain, that guarantees the requirements in the formalism of the knowledge model of a holonic system. Unlike the ontological models found in the literature, the proposed knowledge representation scheme integrates roles and behaviors, which are validated through a case study of a manufacturing cell from a university laboratory. The results show that by using a common vocabulary, it is possible to represent knowledge coherently so that all kinds of holons in a holarchy can exchange, share and retrieve information.
... El análisis de las características generales y de las características que describen el contenido de la ontología de los artículos revisados y de algunos más como Uschold et al. (1998), Lemaignan et al. (2006) y Raileanu et al. (2014), se resume en la Tabla 1 clasificados según su contribución: abundante (•), mínima (•) o ninguna ( ), contrastando al final con la propuesta otológica definida de forma resumida en las siguientes secciones de este documento. ...
... Para cumplir el objetivo planteado se analizan diversas metodologías: Methontology (Gómez-Pérez et al., 1996), Uschold and Kingís Ontology (Uschold et al., 1998), Ontology Development 101 (Noy and McGuinness, 2001), entre otras. Cada una de estas propuestas describen las fases del desarrollo de una ontología a diferentes niveles de conocimiento. ...
p>Los sistemas holónicos de manufactura son integrados por holones capaces de comportarse de una manera autónoma, cooperativa, auto-organizada y reconfigurable para adoptar estructuras distintas en condiciones de operación normales y de emergencia. Dichos holones cuentan con: (1) una representación del conocimiento, (2) una unidad de control distribuido y descentralizado, y (3) un módulo de coordinación. El objeto de interés de la presente investigación es la concepción de una ontología unificada en el dominio de manufactura, que garantice los requisitos en el formalismo del modelo de conocimiento de un sistema holónico. A diferencia de los modelos ontológicos encontrados en la literatura, el esquema de representación del conocimiento propuesto integra roles y comportamientos, mismos que son validados mediante un caso de estudio de una celda de manufactura de un laboratorio universitario. Los resultados muestran que al hacer uso de un vocabulario común, es posible representar coherentemente el conocimiento para que toda clase de holones en una holarquía puedan intercambiar, compartir y recuperar información.</p
... The TOVE, Toronto Virtual Enterprise project (Fadel et al., 1994), defines a domain-specific formal ontology for enterprise modeling which is not connected to foundational ontologies. The Enterprise Ontology provides "a collection of terms and definitions relevant to business enterprises to enable coping with a fast changing environment through improved business planning, greater flexibility, more effective communication and integration" (Uschold et al., 1998). The goal of the Process Interchange Format project (PIF) (Lee et al., 1998) is to support the exchange of business process models across different formats and schemas. ...
... The goal of the Process Interchange Format project (PIF) (Lee et al., 1998) is to support the exchange of business process models across different formats and schemas. Finally, the Plinius project (van der Vet et al., 1994) aims to define a domain-specific ontology for mechanical properties of ceramic material. ...
... A challenge faced by information systems is over 90% [11] of data in any enterprise lack structure [11][12][13], hence making access and analyzing difficult. Interoperability, which has become the basic requirement for the designs of information systems over the past two decades [14][15][16][17], requires not only access to organizational resources but to assemble them meaningfully. This requires coordination of multiple workflows for information exchange using approaches that vary from integration to mediation and brokering[14]. ...
... Support for Interoperability -Direct integration requires coding, configuration or explicit linking such as hypertext navigation which is both laborious and inflexible to changes [36]. Interoperability, instead of direct integration, is a more popular approach [16]. IEEE defines 'interoperability' as the ability of two or more systems or components to exchange information and to use the information that has been exchanged. ...
Information with bearing on process safety can be mined from various work flows of a plant. This information is often found in reports, plant layouts and activity logbooks, which format is not structured. Hence, some information become obscured and tracking changes that compromise process safety become difficult. Whilst there are works to address access to unstructured sources, another following-up challenge is to compose information extracted from various sources meaningfully. This paper proposes a knowledge-based model to integrate safety-related information from multiple workflow sources to multiple sinks. The work provides an architectural perspective to improve visibility and interoperability of safety information within a plant environment.
... An example of an application ontology can be the ontology of Web sites, including concepts such as headings, paragraphs of text, links, etc. In the literature on working with knowledge, it is not uncommon to assert that the educational environment is not yet ready to use an ontological approach, technologies based on ontologies, that the possibilities of describing knowledge with the help of the field of ontology belongs to the section "the future in knowledge management technologies" [14]. ...
... E o termo explícito refere-se ao tipo de conceitos usados e às restrições ao seu uso, formal pelo fato de que a conceituação deve ser legível por máquina e compartilhada, pois a ontologia captura o conhecimento consensual (Studer;Fensel, 1998, tradução nossa). Almeida e Bax (2003) reforçam que ontologias são utilizadas em diversas áreas para organizar a informação, relacionando duas ontologias para empresas: i) a Enterprise Ontology, coleção de termos e definições relevantes para empresas e negócios, conhecimento sobre atividades, processos, organizações, estratégias e marketing (Uschold et al., 1998), e; ii) a TOVE (Toronto Virtual Enterprise), criação de um modelo de dados fornecendo uma terminologia compartilhada para as empresas, definição de termos, implementação semântica que permite deduções sobre a empresa e definição de simbologia para representação em grafos (Fox, 1988). Os autores reforçam que as ontologias, por permitirem formas de representação baseadas em lógica, possibilitam o uso de mecanismos de inferência para a criação de novo conhecimento e, portanto, são uma evolução em relação a técnicas tradicionais. ...
Para compreensão dos modelos de negócio do tipo plataforma digital e a utilização de ontologias para a organização das informações e do conhecimento gerados nestes negócios, foi realizada uma Revisão Sistemática de Literatura, evidenciando oportunidades de pesquisa a partir de abordagens estruturadas para estes modelos. Como principal objetivo, buscou-se apresentar uma proposta inicial, a partir de um projeto-piloto e aplicação em outros três casos de uso, de ontologia em um modelo de negócio do tipo plataforma digital para a obtenção, organização e compartilhamento dos dados e informações gerados através dos seus processos, permitindo identificar padrões nestes modelos de negócio. Esta pesquisa é considerada como aplicada, qualitativa, explicativa e de estudo de casos múltiplos. Foi utilizada a Metodologia de Desenvolvimento de Ontologia 101 para a obtenção do modelo preliminar genérico. Os resultados demonstram a aplicabilidade da ontologia proposta como estrutura capaz de melhor representar o conhecimento no domínio escolhido, permitindo o desenvolvimento de um arcabouço conceitual preliminar que estabeleça a relação entre diferentes tipos de dados em modelos de negócio do tipo plataforma digital com a possibilidade de perpassar por diferentes sistemas promovendo a interoperabilidade.
... E o termo "explícito" refere-se ao "tipo de conceitos usados e as restrições ao seu uso", "formal" pelo fato de que a conceituação "deve ser legível por máquina" e "compartilhada" pois a ontologia "captura o conhecimento consensual" (STUDER; BENJAMINS; FENSEL, 1998, tradução nossa). Almeida e Bax (2003) reforçam que ontologias são utilizadas em diversas áreas para organizar a informação, relacionando duas ontologias para empresas: i) a Enterprise Ontology (coleção de termos e definições relevantes para empresas e negócios, conhecimento sobre atividades, processos, organizações, estratégias e marketing (USCHOLD et al., 1998) ...
Para compreensão dos modelos de negócio do tipo ‘plataforma digital’ e a utilização de ontologias para a organização das informações e do conhecimento gerados nestes negócios, foram realizadas três Revisões Sistemáticas de Literatura, evidenciando oportunidades de pesquisa a partir de abordagens estruturadas para estes modelos. Como principal objetivo, buscou-se apresentar uma proposta inicial, a partir de um “projeto-piloto”, de aplicação de ontologia em um modelo de negócio do tipo ‘plataforma digital’ para a obtenção, organização e compartilhamento dos dados e informações gerados através dos seus processos. Foi utilizada a Metodologia de Desenvolvimento de Ontologia 101 (NOY & McGUINNESS, 2001) como arcabouço de pesquisa. Os resultados demonstram a aplicabilidade da ontologia proposta como estrutura capaz de melhor representar o conhecimento no domínio escolhido, permitindo o desenvolvimento de um arcabouço conceitual preliminar que estabeleça a relação entre diferentes tipos de dados em modelos de negócio do tipo ‘plataforma digital’ com a possibilidade de perpassar por diferentes sistemas promovendo a interoperabilidade. A realização deste estudo se justifica, (i) do ponto de vista teórico-acadêmico, como oportunidade para a Ciência da Informação ampliar seus horizontes sobre esta temática, e (ii) do ponto de vista organizacional, por viabilizar condições para o surgimento posterior de uma interface visual, dedicada, mais acessível, sobre decisões e desempenho de modelos de negócio do tipo plataforma digital.
... The Design cycle enabled the iterative development of a multi-level ontology using some details from top-level and production systems ontologies, for example, enterprise ontology [16], the concepts of strategies across the manufacturing facility [17], concepts of capabilities and processes from [5], and concepts related to parties and supply chains [18]. [19] leveraged the ideas of competency questions and test-before software development. ...
... Another major classification system is useful to differentiate reference and domain ontologies, and focuses on topic coverage. The Enterprise Ontology (Uschold et al., 1998), the Process Specification Language (Grüninger, 2004) and Core Ontology for Robotics and Automation (CORA) (Schlenoff et al., 2012) are examples that fall into this classification. There are different ways to classify topics as shown by the variety of library classification systems around the world. ...
It has been demonstrated many times that modern robotic platforms can generate competent bodily behavior comparable to the level of humans. However, the implementation of such behavior requires a lot of programming effort, and is often not feasible for the general case, i.e., regardless of the situational context in which the activity is performed. Furthermore, research and industry have an enormous need for intuitive robot programming. This is due to the high complexity of realizing an integrated robot control system, and adapting it to other robots, tasks and environments. The challenge is how a robot control program can be realized that can generate competent behavior depending on characteristics of the robot, the task it executes, and the environment where it operates. One way to approach this problem is to specialize the control program through the context-specific application of abstract knowledge.
In this work, it will be investigated how abstract knowledge, required for flexible and competent robot task execution, can be represented using a formal ontology. To this end, a domain ontology of robot activity context will be proposed. Using this ontology, robots can infer how tasks can be accomplished through movements and interactions with the environment, and how they can improvise to a certain extent to take advantage of action possibilities that objects provide in their environment. Accordingly, it will be shown that parts of the context-specific information required for flexible task execution can be derived from broadly applicable knowledge represented in an ontology. Furthermore, it will be shown that the domain vocabulary yields additional benefits for the representation of knowledge gained through experimentation and simulation. Such knowledge can be leveraged for learning, or be used to inspect the robot's behavior. The latter of which will be demonstrated in this work by means of a case study.
... Deve também abranger definições Sobreira et al. RBIE v. 29 -2021 579 e definições de como os conceitos estão relacionados, o que resulta na estruturação do domínio e nas restrições de possíveis interpretações de seus termos (Uschold, 1996). ...
A popularização da modalidade de Educação a Distância, fomentada pelas flexibilizações das atuais diretrizes legais, bem como o avanço tecnológico dos Ambientes Virtuais de Aprendizagem (AVA), traz uma preocupação com a qualidade do ensino ofertado, que está atrelada à interação efetiva entre os atores do processo de ensino e aprendizagem. Nesse sentido, sabe-se que o tutor é o ator responsável por promover a interação nesses ambientes e o seu desempenho nisto está ligado à participação efetiva dos alunos. Sendo assim, este trabalho propõe um agente de software capaz de recomendar estratégias pedagógicas para tutores a distância em AVA, visando melhorar o seu desempenho em promover uma interação efetiva dos alunos nos AVA. O agente desenvolvido faz as recomendações por meio de um modelo de conhecimento, representado por uma ontologia (desenvolvida através da metodologia 101), que mapeia as estratégias pedagógicas que visam promover a interação nos AVA. As estratégias pedagógicas utilizadas pelo agente foram levantadas por meio de uma Revisão Sistemática da Literatura e a aplicação de um questionário com profissionais da área da educação, mais precisamente na Educação a Distância (EaD). Para validação, o modelo de conhecimento do agente foi submetido a testes de corretude e completude. Foi desenvolvida também uma aplicação para amostragem das estratégias recomendadas pelo agente. Para ambas validações, foram alimentadas com dados históricos cedidos pela Secretaria de Educação a Distância de uma Universidade Pública Federal. Os resultados apontaram que o modelo de conhecimento do agente está operando de forma correta, sem nenhuma inconsistência, bem como as estratégias estão mostradas de forma clara pelo sistema desenvolvido.
... To overcome this limit, more precise descriptions of the enterprise and production system are needed, requiring adapted ontologies. Paying attention to the enterprise business organisation, the Enterprise Ontology (EO) provides most of the terms necessary to describe business areas, strategy and process organisation (see Fig. 2.8) [94]. ...
To fit the renewed globalized economic environment, enterprises, and mostly SMEs, have to develop new networked and collaborative strategies, focusing on networked value creation (instead of the classical value chain vision), fitting the blue ocean context for innovative products and service development. Even if collaborative organizations have been studied for decades, the closer connection of information systems involved by the so-called “Industry 4.0” developed by leading industries in Europe, US and Asia requires to set new IT models to support agile and evolving collaborative Business Process (BP) enactment, integrating both traditional Information Systems (IS) and production control processes. By now, these product/service ecosystems are mostly supported by software services, which span multiple organizations and providers, and on multiple cloud-based execution environments, increasing the call for openness, agility, interoperability and trust for both production and Information System organization. These requirements are well supported by SOA, Web 2.0 and XaaS technologies for Information Systems. Taking advantage of IoT, services and Cloud technologies, the development of Cloud of Things (CoT) changes the way control application are engineered and developed moving from a dedicated design and development of control applications to a Control as a Service vision. This vision requires developing a new architecture to connect physical and logical objects as well as integrating basic control patterns to organize a consistent control service orchestration. To fit this challenge, we propose a multi-layer Control as a Service architecture to describe control systems in a holistic way. Our Control service model is built according to an event-driven orchestration strategy. Thanks to the integration of a context manager, analyzing continuously the system environment as well as the control system behavior, these context-aware control services can be deployed
... An enterprise ontology is defined as "[...] the essential knowledge of the construction and the operation of the organization of an enterprise, completely independent of the ways in which they are realized and implemented" [12]. In the literature there are several examples of enterprise ontologies, some of the most well-known are in chronological order: the TOronto Virtual Enterprise (TOVE) [13], the Enterprise Ontology [52], Core Enterprise Ontology (CEO) [4], Context-Based Enterprise Ontology [32], and the ontology-based enterprise architecture [27]. ...
The goal of this paper is to demonstrate the feasibility of combining visualization and reasoning for business model design by combining the machine-interpretability of ontologies with a further development of the widely accepted business modeling tool, the Business Model Canvas (BMC). Since ontologies are a machine-interpretable representation of enterprise knowledge and thus, not very adequate for human interpretation, we present a tool that combines the graphical and human interpretable representation of BMC with a business model ontology. The tool connects a business model with reusable data and interoperability to other intelligent business information systems so that additional functionalities are made possible, such as a comparison between business models. This research follows the design science strategy with a qualitative approach by applying literature research, expert interviews, and desk research. The developed AOAME4BMC tool consists of the frontend, a graphical web-based representation of an enhanced BMC, a web service for the data exchange with the backend, and a specific ontology for the machine-interpretable representation of a business model. The results suggest that the developed tool AOAME4BMC supports the suitability of an ontology-based representation for business model design.
... Business ontologies partially describe consumer/customer and related concepts, for instance, The Enterprise Ontology of Edinburgh [14] contain the "Marketing" section; business model ontology describes "Client Segment", "Marketing Channels", "Client Relations" [15]; ontology of [16] discuses consumer needs and desires; ontology of [17] discusses the consumer role in value co-creation. However, such business ontologies discuss consumer/ customer and their knowledge, but not in enough detail. ...
Knowledge economy and further development of the information society made knowledge of all market interaction participants a key factor of consumption, adding value, including joint generation of value and innovation. Alongside with general increase in information volumes and decrease in consumer trust to it, the very products and services, as well as consumption technology and culture have become more complex and, thus, demonstrate relevance of managing consumer knowledge. Such complexity requires to teach consumers and to exchange knowledge with them. Consumer knowledge is of paramount importance for innovative products and services, as it is a key factor of innovation-decision process. Consumer knowledge practice needs clear understanding of this concept ("consumer knowledge"), its kinds and features, processes of acquiring and changing this knowledge, its influence on consumer behaviour, as well as company’s capabilities to establish consumer knowledge. Such understanding will be provided by creating ontology of innovative products and services’ consumer knowledge. Such ontology will help to resolve a whole range of enterprise engineering tasks: design of innovative products and services, as well as ecosystem surrounding them; design of an interaction system between a company and a consumer during a whole customer journey. This paper describes main requirements on ontology, discusses some existing ontologies, as well as contains primary results of ontology conceptualisation.
... The Enterprise Ontology (EO). The enterprise ontology (Uschold et al., 1998) was developed within the Enterprise Project that aimed at designing a modeling framework that uses executable process models to help users perform their tasks. EO is composed of five sub-ontologies: (1) Meta-ontology and Time, (2) Activities and processes, (3) Organization, (4) Strategy, and (5) Marketing. ...
Business process (BP) modeling is an active area of research due to its multiple applications. For systems that support/monitor operators to perform their tasks (i.e., tasks of a given BP), a formal representation is essential. Various BP ontologies are available to formally represent BP. In this paper, we review and compare a set of nine BP ontologies according to their ability to represent process specification and process execution in a fine-grained way to enable task monitoring. The comparison shows that, on the one hand, ontologies developed from scratch establish a clear distinction between process specification and process execution, but do not allow to represent workflow constraints required for process execution. On the other hand, most of the ontologies, that are ontological versions of existing BP modeling languages, focus only on process specifications but do not represent process execution, or mix the representation of BP specification and execution.
... There are three main steps to engineer ontologies from scratch Uschold, King, House, Moralee, & Zorgios, 1995): 1. Identifying the purpose by examination of motivationg scenarios; 2. Capturing the concepts and their relationships; 3. ...
Human psychology plays an important role in organizational performance. However, understanding our employees is a difficult task due to issues such as psychological complexities, unpredictable dynamics, and the lack of data. Leveraging evidence-based psychology knowledge, this paper proposes a hybrid machine learning plus ontology-based reasoning system for detecting human psychological artifacts at scale. This unique architecture provides a balance between system's processing speed and explain-ability. System outputs can be further consumed by graph science and/or model management system for optimizing business processes, understanding team dynamics, predicting insider threats, managing talents, and beyond.
... Для сетевого пред-приятия в этом слое очень важ-но отразить отношения между участниками предприятия, язык их общения -как для людей, так и для технических элементов системы. Поэтому в качестве механизма постро-ения информационной модели сетевого предприятия предла-гается использовать онтологии [19,20,21,22]. Особенно это важно для описания инфор-мационных взаимосвязей на этапе разработки изделия, в который вовлечены специали-сты различных направлений -владельцы продуктов в тер- ...
The subject of the study is the formation of the structure of a network enterprise, considered as a set of interacting enterprises in a networked Internet environment that implements a value chain. To build the structure of the network enterprise, it is proposed to use and support the ontology of the network enterprise, which conceptually reflects the models of products and related production and business processes throughout the life cycle. At the same time, the focus is on the implementation of flexible processes for creating innovative products using intelligent model-oriented technologies.
The purpose of the study is to build an algorithm for forming the structure of a network enterprise that would ensure the best implementation of the value chain with minimal risks of mismatch of designs and production processes with qualitative value characteristics and requirements for an innovative product. The construction of an algorithm for forming the structure of a network enterprise involves solving the problems of modeling the structure of an innovative product based on an analysis of qualitative value characteristics and requirements for product components, its creation processes, distribution of roles of enterprise participants and analysis of their capabilities.
Methods. As the main research method is the method of constructing a model of “digital thread” of creating an innovative product. The most complete application of this method is carried out as part of the reference model of enterprise architecture for Industrie 4.0 (RAMI). The resulting conceptual model of an innovative product and related production and business processes is implemented using an ontological approach. It is proposed to use a combination of QFD (Quality Function Deployment) methods for deploying the structure of a network enterprise and analyzing the types and consequences of potential FMEA (Failure Mode and Effects Analysis) inconsistencies.
The main results of the study are ontology and the algorithm for forming the structure of the network enterprise. A distinctive feature of the proposed ontology of the network enterprise is a clear separation of the valuable qualitative characteristics of the product and the requirements for its creation, as well as the allocation of the abilities of participants in enterprises to implement the necessary processes. The novelty of the presented algorithm for the formation of the structure of a network enterprise lies in the combined application of the QFD and FMEA methods, as well as in the iteration of modeling the structure of an innovative product from the position of the best implementation of quality value characteristics and functional requirements.
Conclusions, prospects. The proposed algorithm for creating the structure of a network enterprise allows you to get the best decisions on the criterion for assessing the highest rating for the implementation of quality characteristics and requirements for the components of the value chain and its participants, provided that minimal risk assessments of the mismatch between the designs and processes of creating innovative products are obtained. The developed ontology and the algorithm for forming the structure of the network enterprise is of practical importance for creating an intelligent system for supporting the adoption of innovative decisions for the dynamic construction of network enterprises in the Internet environment.
... The resources are participating in the activities according to a specific role that requires qualifications and competencies. Similar models are existing in the literature that proposes a classification of organizational concepts such for example the enterprise ontology proposed in (Uschold et al. 1998) and the Enterprise Architecture Model developed with UML formalism in (Sousa et al. 2007). ...
Product-service systems (PSS) result from the integration of heterogeneous components covering both tangible and intangible aspects(mechanical, electrical, software, process, organization, etc.). The process of developing PSS is highly collaborative involving a wide variety of stakeholders. This interdisciplinary nature requires standardized semantic repositories to handle the multitude of business views and facilitate the integration of all heterogeneous components into a single system. This is even more complex in the case of customizable PSS in the industrial sector. Despite the many methodologies in literature, the management of the development processes of the PSS is still limited to face this complexity. In this context, Systems Engineering (SE) could bean advantageous solution in terms of its proven qualities for the modeling and management of complex systems. This thesis aims at exploring the potentials of Systems Engineering (SE) as a conceptual foundation to represent various different business perspectives associated with the life cycle of the PSS. In this context, a meta-model for PSS is proposed and verified in industrial cases. An ontological model is also presented as an application of a part of the model to structure the common repository of the ICP4Life platform.
... Uschold ve King [5], Enterprise Ontology [6] isimli ontolojinin geliştirim sürecinde elde ettikleri deneyimler doğrultusunda bir süreç iskeleti önermiştir. Ana süreç, amaçların belirlenmesi, ontolojinin geliştirilmesi, değerlendirme ve dokümantasyon olmak üzere dört adımdan oluşmaktadır. ...
Ontolojilerin bilgisayar bilimleri alanında yaygınlaşmasıyla birlikte, ontoloji geliştirme metodolojilerine yönelik çalışmalar da artmıştır. Genellikle ontoloji geliştirme deneyimlerinden ortaya çıkan bu metodolojiler, geliştirme süreçlerini farklı bakış açılarıyla ele almıştır. Ancak yazılım mühendisliğinde olduğu gibi olgunlaşmış ve kabul görmüş bir süreçten bahsetmek hala mümkün değildir. Bunun yanı sıra ontoloji geliştirme metodolojilerinin çözüm sağlayamadığı yeniden kullanım gibi bazı konular, ontoloji mühendisleri için önemli bir sorun olmaya devam etmektedir. Bu çalışmada mevcut yöntemlerin eksiklikleri dikkate alınarak, çevik ve yeniden kullanım tabanlı bir ontoloji geliştirme metodolojisi önerilmiştir.
... (4) de Kruijff and Weigand [6] propose a BC domain ontology, arguing for a clear separation of concerns by following the so-called "Enterprise Ontology" providing a collection of terms and definitions relevant to business enterprises, developed in the course of a project by Uschold et al. [18]. On that basis, BC concepts are separated into 3 top-level categories, covering a (i) datalogical layer describing transactions at the technical level and their relationships to, e.g., blocks and nodes, an (ii) infological layer containing transactions acting on an (immutable) open ledger and finally, the (iii) essential/business layer considering the economic meaning of transactions. ...
Since the emergence of Bitcoin, blockchains (BCs) have been applied not only in the finance sector, but also in various other domains like health care, education or Industry 4.0 resulting in numerous different BC platforms and substantial research work. This plenty of efforts yielded to several valuable scientific surveys classifying and evaluating existing BC platforms. Although each of them puts forward a somewhat consolidated view on the field, it is still challenging to get rid of the "blockchain muddle" preventing even a common perception of the core functionality of BCs. Instead of providing yet another BC overview we conduct a meta survey of existing BC studies and report on lessons learned in this paper, being the basis for our vision towards a UML-based reference model considering both, structural and behavioral aspects of BCs and thereby identifying the nucleus of BCs.
... However, they are far from being complete and it is questionable whether logic-based formalisms are suitable for the inherent complexity (and as a consequence imprecision) of the management domain. An example of a management-oriented ontology that uses Ontolingua Server is the Enterprise Ontology developed at the Artificial Intelligence Applications Institute at the University of Edinburgh(Uschold et al. 1998). The ontology currently consists of 92 core concepts related to an enterprise. ...
... Ontology is used as unifying framework for different points of view. It clarifies a terminology and a conceptualization shared by a given community in organization (Uschold, King, Moralee & Zorgios, 1998). In concrete terms, ontology enables that the "cap" of the pen should not be confused with the "cap" of the clothing domain. ...
This paper develops the concept of knowledge and its exchange using Semantic Web technologies. It points out that knowledge is more than information because it embodies the meaning, that is to say semantic and context. These characteristics will influence our approach to represent and to treat the knowledge. In order to be adopted, the developed system needs to be simple and to use standards. The goal of the paper is to find standards to model knowledge and exchange it with an other person. Therefore, we propose to model knowledge using UML models to show a graphical representation and to exchange it with XML to ensure the portability at low cost. We introduce the concept of ontology for organizing knowledge and for facilitating the knowledge exchange. Proposals have been tested by implementing an application on the design knowledge of a pen.
... Many approaches have been proposed for formally developing ontologies. Uschold and King is among the first ontology development methods published (Uschold et al., 1998). The approach uses an iteration through the following stages -identify domain vocabulary, purpose, intended use, end-users, scope, terms; capture and code textual concepts and relationships into formal ontological language; evaluate requirements; and document results from each stage to aid the next iteration of ontology development. ...
The growth of solar energy resources in recent years has led to increased calls for accurate forecasts of solar irradiance for the reliable and sustainable integration of solar into the national grid. A growing body of academic research has developed models for forecasting solar irradiance, identified metrics for comparing solar forecasts, and described applications and end users of solar forecasts. Ontologies are explicit and formal vocabulary of terms and their relationships that facilitate better communication, improve interoperability, and refine knowledge reuse by experts and users of the domain. This paper describes a step towards using ontologies to describe the knowledge, concepts, and relationships in the domain of solar irradiance forecasting to develop a shared understanding for diverse stakeholders that interact with the domain. A preliminary ontology on solar irradiance forecasting, SF-ONT, was created and validated on three use cases.
... In literature, the term "enterprise ontology" refers to an ontology that has its origins in economic and business theory, and that is not specific to a particular business. Well-known examples are the Enterprise Ontology (Uschold et al. 1996), and Toronto Virtual Enterprise Ontology TOVE (Fox 1992). ...
Within an enterprise, different conceptual models, such as process, data, and goal models, are created by various stakeholders. These models are fundamentally based on similar underlying enterprise (domain) concepts, but they have a different focus, are represented using different modeling languages, take different viewpoints, utilize different terminology, and are used to develop different enterprise artefacts (such as documents, software, databases, etc.); therefore, they typically lack consistency and alignment. Another issue is that modelers have different vocabulary selections and different modeling styles. As a result, the enterprise can find itself accumulating a pile of models which cover similar aspects in different manners. Those models are not machine-readable and cannot be processed automatically. Enterprise-Specific Ontologies (ESOs) aim to solve this problem by serving as a reference during the conceptual model creation. Using such a shared semantic repository makes conceptual models semantically aligned and facilitates model integration. However, managing those ontologies is complicated; an enterprise is an evolving entity, and as it changes, the ESO might become outdated. During the years of research dedicated to this dissertation, the Recommendation-Based Conceptual Modeling and Ontology Evolution (CMOE+) framework was developed. This framework establishes a symbiotic relationship between the Ontology engineering and the Conceptual modeling fields. CMOE+ consists of two cycles: the Ontology Evolution cycle and the Conceptual Modeling cycle. The Ontology Evolution cycle is responsible for setting up the initial version of the ESO and updating it as the knowledge within the enterprise evolves. Additionally, this cycle encapsulates recommendation services to perform ontology look-up and to present the most relevant ESO concepts in support of the modeler. The Conceptual Modeling cycle is responsible for the creation of conceptual models in different modeling languages based on the ESO. This cycle is also concerned with the quality evaluation of the created models. CMOE+ was developed based on requirements identified as a result of a literature review and a case study. The development process follows the Design Science Research Methodology (DSRM). After the initial version of CMOE+ was put forward, our focus was narrowed towards the recommendation-based conceptual modeling part of CMOE+, and we continued to gradually improve the framework in iterations until it reached its current state. The Ontology Evolution Cycle is not fully addressed within the scope of this dissertation. In order to demonstrate the performance and usability of CMOE+, it was exemplified for process modeling using BPMN and goal modeling using i*. This thesis presents a detailed instantiation, and explains steps to be performed in order to instantiate CMOE+ for other modeling languages. In order to evaluate the process modeling instance of CMOE+, a CMOE+BPMN tool was implemented. This tool incorporates a BPMN modeler, facilitates storage and access of the ESO, and includes all algorithms functioning within CMOE+ for the BPMN modeling language (as some of the algorithms are language dependent). Next, CMOE+ was exemplified using the i* goal modeling language. Finally, we demonstrated the ability of CMOE+ to perform alignment between i* and BPMN models, in order to show that CMOE+ is indeed beneficial in achieving interoperability among models created in different modeling languages and covering distinct aspects of the enterprise.
... The semantic representation for EIPs proposed by us is not stand-alone, and the power of semantic web and linked data enables us to find other ontologies which can be integrated with the proposed approach to provide greater value. Such ontologies include the semantic sensor network ontology and the enterprise ontology [144]. The sensor network ontology can be used to represent sensor data measurements, such as those from smart meters, and the Enterprise ontology can represent organizations, people, groups and various other associated enterprise components. ...
The ubiquitous nature of sensors and smart devices collecting more and more
data from industrial and engineering equipment (such as pumps and compressors
in oilfields or smart meters in energy grids) has led to new challenges in faster
processing of temporal data to identify critical happenings (events) and respond
to them. We deal with two primary challenges in processing events from temporal
sensor data: (i) how to comprehensively model events and related happenings
(event modeling), and (ii) how to automatically recognize event patterns from raw
multi-sensor data (event recognition).
The event modeling problem is to build a comprehensive event model enabling
complex event analysis across diverse underlying systems, people, entities, actions
and happenings. We propose the Process-oriented Event Model for event processing
that attempts a comprehensive representation of these processes, particularly
those seen in modern energy industries and sensor data processing applications.
This model brings together, in a unified framework, the different types of entities
that are expected to be present at different stages of an event processing workflow
and a formal specification of relationships between them.
Using event models in practice requires detailed domain knowledge about a
variety of events based on raw data. We propose to learn this domain knowledge automatically by using recent advances in time series classification and shape mining,
which provide methods of identifying discriminative patterns or subsequences
(called shapelets). These methods show great potential for real sensor data as
they don’t make assumptions about the nature, source, structure, distribution, or
stationarity of input time series, provide visual intuition, and perform fast event
classification. By combining shape extraction and feature selection, we extend
this temporal shape mining paradigm for processing data from multiple sensors.
We present evaluation results to illustrate the performance of our approaches on
real-world sensor data.
... Modern human activity is interdisciplinary, with people, organizations and software agents operating in a common space. Due to differing technical backgrounds, expertise , knowledge hierarchies, agents in the same environment may lack a shared understanding of the domain in which they interact [98]. As an example, solar forecasting models integrate knowledge from fields like cloud physics, statistical mechanics, artificial intelligence, machine learning and statistics. ...
The growth of solar energy resources in recent years has led to increased calls for accurate forecasts of solar irradiance for the reliable and sustainable integration of solar into the national grid. A growing body of academic research has developed models for forecasting solar irradiance, identified metrics for comparing solar forecasts, and described applications and end users of solar forecasts. In recent years, many disciplines are developing ontologies to facilitate better communication, improve inter-operabiity and refine knowledge reuse by experts and users of the domain. Ontologies are explicit and formal vocabulary of terms and their relationships. This report describes a step towards using ontologies to describe the knowledge, concepts and relationships in the domain of solar irradiance forecasting to develop a shared understanding for diverse stakeholders that interact with the domain. A preliminary ontology on solar irradiance forecasting was created and validated on three use cases.
... They suggest conceptual foundations for conceiving enterprises. Among the rich literature in the field, two prominent approaches are Uschold's enterprise ontology [22] and McCarthy's Resource/Event/Agent generalized accounting model [14]. The Business Motivation Model [16] is a standard that defines business plans by starting from the motivations of a company. ...
... The purpose of ontologies in enterprise modelling is to formalize and establish the sharing, reuse, assimilation and dissemination of information across all organizations and departments within an enterprise. Developing enterprise ontologies started in the 1990s with TOVE [12], The Edinburgh Enterprise Ontology [33] and the organizational memory [1]. ...
In this paper we present a hybrid modeling approach
which supports the continuous alignment of business and IT in
the cloud. Business Process as a Service provides the end-to-end cloud support for business processes instead of single applications. A graphical modelling environment allows non-technical modelers to design business processes and to specify requirements in human-interpretable way. Via semantic lifting, the graphical models can be annotated with classes and values from an enterprise ontology. The BPaaS Ontology contains the relevant classes for the smart Business and IT-Cloud alignment. It supports the modeler in using a standard terminology and thus ensures consistent modeling.
... They mainly differ regarding their possible reusability. Thus, general ontologies are reusable across several domains, domain ontologies are reusable within the domain they are built for (e.g., the enterprise ontology by [Uschold et al., 1998]), whereas application ontologies work only in the specific context of an application. Various methodological approach exist for building ontologies, yet it seems there is no completely mature proposal for building ontologies out so far [Fernández-López and Gómez-Pérez, 2002]. ...
The thesis at hand addresses the challenge to identify and measure expertise of individuals. This task is highly relevant since the location of individuals’ expertise is crucial to organizations in order to assign the most appropriate people to given tasks. Such effective assignments support organizations in sustaining competitive advantage as well as in fostering innovation. However, the elicitation of expertise is challenging since knowledge resides first and foremost in the heads of individuals and thus is inherently elusive.
We iteratively develop a method to quantify users’ expertise based on their submissions to online communities. An online community offers a communication platform to its users that facilitates the informal exchange of knowledge. As a consequence, when people share their experiences in problem-solving contexts, they demonstrate expertise regarding certain topics. The proposed method aggregates data obtained from such an online community and automatically generates users’ expertise models containing expertise topics along with users’ expertise levels. Thereby, expertise levels correspond to numerical values on an absolute scale. Expertise levels mapped on an absolute scale allow to compare one’s expertise with others’ as well as to staff teams according to the expertise levels needed.
To evaluate the proposed method we conduct a series of experiments with students at our university. Since the method constitutes a composite of various calculation steps, each experiment covers either a specific step or several steps of the proposed method. We set up hypotheses that are based on each other to systematically explore both the characteristics of the method and the value of users’ submissions to reliable expertise calculation. The method’s calculation accuracy is measured by comparing the calculated expertise levels with the participants’ self-assessments.
... The purpose of ontologies in enterprise modelling is to formalize and establish the shareability, re-usability, assimilation and dissemination of information across all organizations and departments within an enterprise. Describing enterprise architecture as an ontology started in the 1990s with TOVE [9], The Edinburgh Enterprise Ontology [30] and the organizational memory [1]. More recent work is the Context Based Enterprise Ontology [19]. ...
Business processes can benefit from cloud offerings, but bridging the gap between business requirements and technical solutions is still a big challenge. We propose Business Process as a Service (BPaaS) as a main concept for the alignment of business process with IT in the cloud. The mechanisms described in this paper provide modelling facilities for both business and IT levels: (a) a graphical modelling environment for processes, workflows and service requirements, (b) an extension of an enterprise ontology with cloud-specific concepts, (c) semantic lifting of graphical models and (d) SPARQL querying and inferencing for semantic alignment of business and cloud IT.
... Several standard frameworks for enterprise models exist such as TOGAF [14], the Zachman framework ( [13], [15] and [16]) and ARIS [4]. Similar work on semantic enterprise models such as [17] has also been conducted. ...
Processes count to the most important assets of companies. Ensuring the compliance of processes to legal regulations, governance guidelines, and strategic business requirements is a sine qua non condition to controlling business behavior. Implementing business process compliance requires means for modeling and enforcing compliance measures. In this work, we motivate the need for automation in compliance management and introduce the role of policies. We then distinguish eight requirements for a compliance management framework. We also discuss different ways of conducting compliance checking. Finally, we propose a policy-based framework for business process compliance management. We eventually proceed to a discussion of the soundness and practicability of our approach, followed by an investigation of the main challenges ahead of our approach to policy-based semantic business process compliance management.
... Learning design is applied to describe the coordination of learning events and activities. An ontology provides the vocabulary (terminology or names) for referring to the terms in a subject area, as well as the logical statements that describe what the terms are, how they are related to each other, how components and contexts can or cannot be classified and relate to each other, as well as rules for combining terms and relations to define extensions to the vocabulary (Hendler, 2001;Uschold, King, Moralee & Zorgios, 1998). With ontologies we can formalize conceptual models and automatically perform semantic operations. ...
In this paper the authors present an e-learning management system with metadata that serves as a general template for the situation of Thai learners. Basically it is an ontology-driven e-leaning system for Thai learning environment (O-DEST). The system comprises an ontology for the e-learning process, such as course syllabus, teaching methods, learning activities, and learning styles. O-DEST helps teachers, students and administrative personnel to set up and maintain the course material as well as the course administration, to go through the learning content, and to administer student and teacher data. Ontologies for the knowledge domain specific teaching subjects will enable the usage of the teaching contents in the Semantic Web.
... It also concern with only the essence of operation of an organization and not minding the current situation of operation in the organization. The theory of the enterprise ontology is based on the work by [6,26]. ...
In developing countries, the health care spending has been constantly increasing in the last decades, and statistics has shown a lot of lapses in the running of the affairs of the health care systems. As a result, there is serious need to introduce new and innovative way of doing certain transaction in the hospitals in order to improve the total efficiency of the hospitals. To address this, we propose a method based on Ontology knowledge map to locate the unnecessary transactions that must be redesigned to improve the healthcare management. We carefully choose this methodology to address the problem statement because it tend to gives a better understanding of the general and dynamic situation of the Hospital emergency unit (EU), and at the same time provides a good alignment between the operation and enterprise design. The method was tested in the EU of the state specialist Hospital Damaturu, where we have succeed in locating some transactions that can be redesign or removed. Evaluation of this methodology was done by means of observations, interviews and feedback from practitioners.. A result shows that there are a lot of unnecessary process in the emergency unit which we are able to removed/redesign, it is also observe that there is also need for the hospital to deploy Electronic Health Record (EHR) to reduce error due to manual recording and reduce time response as well.
Process management and optimization play vital role in almost all industries regardless
of different domains. The process managements involves with designing the process and
applying the engineering principles on it in order to reduction of complexities in the
selected system in the domain interested. The process optimization involves with
reduction of time in between processes and possibility to automate the processes. The
legal domain is one of the complex domains in Sri Lanka since more number of
collaborative actors; interoperable issues within the system; complex legislation laws
and rules; and difficult Courts procedures. This research project was initiated and
completed in order to develop an ontology framework model for the service process
management at the District Courts in the legal sector. The ontology framework model
was developed with five aspect models namely action model, process model, object
model, data model and construction model. These all five aspect models deal with five
different views and construction of the ontology framework model. The development
model is named as Design and Engineering Modeling of Organization - Extended
(DEMO-E). The backbone of the DEMO-E is the "transaction" (which is the complete
cycle of one or more coordination acts and a production act to produce an either
material or immaterial output as the result).DEMO-E is a theory to do a construction
and operation of any enterprises. The intended result is provided through the standard
pattern of the transaction (it is series of communication act in order to achieve an output
which cause an effect on social world) via series of communication acts. The legal
domain is rich in more communicational agenda and more number of participants in a
single case. A transaction meta-model was developed in order to apply on the mile stone
events and get the relevant model for the transaction in both within the selected case
filing area and other stages of the casein legal sub domains. A case must passes around
four basic stages such as filing, hearing, case moving or transferring when necessary
and verdict. The case filing major transaction it have many sub-transactions namely
case tender, necessary payments, binding and decision of the judge collectively implies
as case filing. The said each sub transactions obey the generic transaction stages
including both coordination acts such as request, promise, state and accept and
production act such as execution act. In fact all five different ontology aspect models
map the conceptual design of legal process management with easy understanding.
Further, DEMO-E can be successfully applied to the legal domain due to optimal
constructional pattern and the optimal operational acts. More than this, the DEMO
provides re-engineering and re-designing options to the designers. Thus the judicial
Courts procedure and the organization can be restructured for the optimal output and it
leads to break the barrier of complexity and inter-operable issues
Human psychology plays an important role in organizational performance. However, understanding our employees is a difficult task, due to issues such as psychological complexities, unpredictable dynamics, and the lack of data. Leveraging evidence-based psychology knowledge, this paper proposes a hybrid machine learning plus ontology-based reasoning system, for detecting human psychological artifacts at scale. This unique architecture provides a balance between system's processing speed and explain-ability. System outputs can be further consumed by graph science and/or model management system for optimizing business processes, understanding team dynamics, predicting insider threats, managing talents, and beyond.
This volume celebrates the career of Prof. Ricardo de Almeida Falbo on the occasion of his formal retirement. The volume includes reflections from collaborators and former students, casting light on his academic work and contributions. The chapters show how Falbo's original contributions have influenced a number of developments in the application of Software Engineering practices to Ontology Engineering and in the application of Ontologies in Software Engineering. A few personal notes are also offered, and some of the technical essays also include personal notes commemorating his captivating qualities.
The revolution in new sequencing technologies, by strongly improving the production of omics data, is greatly leading to new understandings of the relations between genotype and phenotype. To interpret and analyze data grouped according to a phenotype of interest, methods based on statistical enrichment became a standard in biology. However, these methods synthesize the biological information by a priori selecting the over-represented terms and focus on the most studied genes that may represent a limited coverage of annotated genes within a gene set. During this thesis, we explored different methods for annotating gene sets. In this frame, we developed three studies allowing the annotation of gene sets and thus improving the understanding of their biological context.First, visualization approaches were applied to represent annotation results provided by enrichment analysis for a gene set or a repertoire of gene sets. In this work, a visualization prototype called MOTVIS (MOdular Term VISualization) has been developed to provide an interactive representation of a repertoire of gene sets combining two visual metaphors: a treemap view that provides an overview and also displays detailed information about gene sets, and an indented tree view that can be used to focus on the annotation terms of interest. MOTVIS has the advantage to solve the limitations of each visual metaphor when used individually. This illustrates the interest of using different visual metaphors to facilitate the comprehension of biological results by representing complex data.Secondly, to address the issues of enrichment analysis, a new method for analyzing the impact of using different semantic similarity measures on gene set annotation was proposed. To evaluate the impact of each measure, two relevant criteria were considered for characterizing a “good” synthetic gene set annotation: (i) the number of annotation terms has to be drastically reduced while maintaining a sufficient level of details, and (ii) the number of genes described by the selected terms should be as large as possible. Thus, nine semantic similarity measures were analyzed to identify the best possible compromise between both criteria while maintaining a sufficient level of details. Using Gene Ontology (GO) to annotate the gene sets, we observed better results with node-based measures that use the terms’ characteristics than with edge-based measures that use the relations terms. The annotation of the gene sets achieved with the node-based measures did not exhibit major differences regardlessof the characteristics of the terms used. Then, we developed GSAn (Gene Set Annotation), a novel gene set annotation web server that uses semantic similarity measures to synthesize a priori GO annotation terms. GSAn contains the interactive visualization MOTVIS, dedicated to visualize the representative terms of gene set annotations. Compared to enrichment analysis tools, GSAn has shown excellent results in terms of maximizing the gene coverage while minimizing the number of terms.At last, the third work consisted in enriching the annotation results provided by GSAn. Since the knowledge described in GO may not be sufficient for interpreting gene sets, other biological information, such as pathways and diseases, may be useful to provide a wider biological context. Thus, two additional knowledge resources, being Reactome and Disease Ontology (DO), were integrated within GSAn. In practice, GO terms were mapped to terms of Reactome and DO, before and after applying the GSAn method. The integration of these resources improved the results in terms of gene coverage without affecting significantly the number of involved terms. Two strategies were applied to find mappings (generated or extracted from the web) between each new resource and GO. We have shown that a mapping process before computing the GSAn method allowed to obtain a larger number of inter-relations between the two knowledge resources.
This habilitation thesis deals with leveraging conceptualisation for harmonising software en-
gineering in the context of enterprise engineering. It is based on the research and work done
in the Centre of Conceptual Modelling and Implementation (CCMi) at the Department
of Software Engineering since its foundation by the author in 2012. Theoretical founda-
tions and key methodologies are introduced. Past and ongoing research and applications
based on them are then elaborated on; These consist of several layers: (i) Methodological
Studies, (ii) Methodological Improvements, (iii) Tooling and (iv) Applications. Achieved
results at the levels of bachelor and diploma theses, Ph.D. and post-doc research projects
are discussed. Key international collaborations, both academic and from practice are also
explained. The core of the thesis then consists of chapters being key already-published,
peer-reviewed publications.
The paper contains the proposition of solving the problem of operationalization of the SECI model of knowledge creation in a new scope — i.e., in relation to knowledge about managing an SME enterprise in conditions of uncertainty. This knowledge includes the assessment of the enterprise in the potential — risk space of operational activity. This problem was solved theoretically by developing the original A–E–AE enterprise ontology and practically by constructing the SOK-P1 system, which was used in the advisory practice for SME sector enterprises in the Lubelskie and Podkarpackie voivodships.
Summary of professional achievements presented on the basis of the monothematic publication cycle entitled: " A semantic knowledge management model for assessment of an ability of small enterprises to continue as a going concern".
- presented on Centralna Komisja do Spraw Stopni i Tytułów.
This habilitation thesis deals with leveraging conceptualisation for harmonising software en-
gineering in the context of enterprise engineering. It is based on the research and work done
in the Centre of Conceptual Modelling and Implementation (CCMi) at the Department
of Software Engineering since its foundation by the author in 2012. Theoretical founda-
tions and key methodologies are introduced. Past and ongoing research and applications
based on them are then elaborated on; These consist of several layers: (i) Methodological
Studies, (ii) Methodological Improvements, (iii) Tooling and (iv) Applications. Achieved
results at the levels of bachelor and diploma theses, Ph.D. and post-doc research projects
are discussed. Key international collaborations, both academic and from practice are also
explained. The core of the thesis then consists of chapters being key already-published,
peer-reviewed publications.
Background: Our contemporary understanding of disability is rooted in the idea that disability is the product of human–environment interaction processes. People may be functionally limited, but this becomes a disability only when they engage with their immediate social and physical environments. Any attempt to address issues of mobility in relation to people with disabilities should be grounded in an ontology that encompasses this understanding.
Purpose: The objective of this study is to provide a methodology to integrate the social and physical environments in the development of a mobility ontology for people with motor disabilities (PWMD).
Methods: We propose to create subclasses of concepts based on a Nature-Development distinction rather than creating separate social and physical subclasses. This allows the relationships between social and physical elements to be modelled in a more compact and efficient way by specifying them locally within each entity, and better accommodates the complexities of the human-environment interaction as well. Based on this approach, an ontology for mobility of PWMD considering four main elements – the social and physical environmental factors, human factors, life habits related to mobility and possible goals of mobility – is presented.
Conclusions: We demonstrate that employing the Nature-Development perspective facilitates the process of developing useful ontologies, especially for defining the relationships between the social and physical parts of the environment. This is a fundamental issue for modelling the interaction between humans and their social and physical environments for a broad range of applications, including the development of geospatial assistive technologies for navigation of PWMD.
• Implications for rehabilitation
• The proposed perspective may actually have much broader interests beyond the issue of disability – much of the interesting dynamics in city development arises from the interaction between human-developed components – the built environment and its associated entities – and natural or organic components.
• The proposed approach facilitates the process of developing useful ontologies, especially for defining the relationships between the social and physical parts of the environment. This is a fundamental issue for modeling the interaction between human -specially people with disabilities -and his social and physical environments in a broad range of domains and applications, such as Geographic Information Systems and the development of geospatial assistive technologies for navigation of people with disabilities, respectively.
Usually, enterprise models consider different aspects and include different abstraction levels of enterprises. It is hence challenging to integrate these models and to maintain their consistency. In the light of these challenges, ontologies seem to be relevant to complement enterprise models since they are intended to support communication, computational inference, consistency checking, querying, and the organization of knowledge. In our contribution, we demonstrate that Enterprise modelling can benefit from these characteristics. In order to check feasibility and pertinence of ontology-based Enterprise Models, we selected the goal modelling part and its relations to actors and resources from the “For Enterprise Modelling” (4EM) method. In more detail, this paper provides (1) a formal OWL representation of the 4EM Goals meta-model; (2) a discussion of goal relations regarding transitivity and domain specific inference; (3) a formalization of the discussed inference rules; and (4) an analysis of an exemplary goals model instance. This paper extends earlier work on the topic by the introduction of inter-model relations, a discussion of formalization alternatives, and a comparison of query results with and without ontology-based reasoning.
Business firms around the world have been generating enormous amounts of domain-related documents. Most of these firms are adapting semantic Web-based techniques into their software systems. Hence, they want to semantically enrich their documents to enable more meaningful querying or processing of the information in the documents. To impart semantics into these documents, ontologies relevant to the business domain should be used. In this context, to populate the domain ontology with the information from the source documents, a method for semi-automatic learning of extraction rules for populating the ontology is presented and implemented in the rule learning system. In addition to the rule learning system, a framework for separating the business logic from application logic and storing the business rules and extraction rules in external user-friendly format is presented in brief. The rule learning system is mainly developed to be a part of the presented framework, but it can be used as a standalone system to learn any decision or association rules too. The framework uses the rule learning system for learning extraction rules. The main idea behind the work presented is to learn extraction rules to be used by an information extraction system (part of the framework) to populate the domain ontology. The extraction rules learned by the rule learning system can be used with any business rules management system (BRMS) with appropriate wrappers to populate the domain ontology.
Agility is arguably one of the most important characteristics of successful Information Age organizations. The study of agility organizations is currently one of the hottest topics in the organization study field. In this paper, we first put forward an agile command and control (C2) organization model and then focus on the robustness of the agile C2 organization. We set a method to measure the C2 organization agility. Then experiment has been taken to verify the method and analysis the agility of a given organization Index Terms—Agility, agile C2 organization, force organizations, robustness.
Software development is a knowledge-intensive business. Different kinds of knowledge are important for software practitioners to support their activities in software organizations, such as that knowledge about the domain for which software is being developed, new technologies, local practices and policies, who knows what in the organization, guidelines, best practices, and previous experiences with techniques, methods and the software process [43]. We have observed this while developing software within different organizations for different domains such as cardiology [32, 33], acoustic propagation [31] and telecommunications [25]. These experiences had shown that a risky situation for the software systems development was the lack of domain knowledge by the software developers. Users usually consider the process of knowledge acquisition and requirements elicitation to be boring and stressful because they need to explain the same basic domain concepts to the computer science personnel for each new software project development. When a software developer starts to work on a software project under development, s-he must understand not only the software products already built, but also, and prior to this, the domain itself. While learning about the domain, the software developers usually have to understand the tasks or activities that are implicitly associated with the concepts of that domain. Those tasks are directly related to the problem that the software system being developed intends to solve. It can get worse when there is a high turnover of software developers in the software project. This basic development scenario, which describes a concrete reality concerned with the building of software projects lacking domain and task knowledge, motivated the investigation of feasible approaches to support the use of such knowledge throughout the software development process. A software development environment (SDE) [1, 15] has already been built for each of the software projects previously mentioned. However, these environments, despite the fact that they were supporting the software development activities by providing integrated case tools, guidance to the software process and common repositories to the development teams, had not provided any kind of knowledge regarding the domain and related tasks. To address this problem we decided to extend this traditional notion of the SDE by introducing into it domain and task knowledge to guide the software developers through the several software development phases [33], which gave rise to the concept of: the Domain Oriented Software Development Environment (DOSDE). After the definition, building and use of DOSDEs within different domains [31, 35, 34, 32] it become possible to observe that besides domain and task knowledge, other kinds of knowledge are also necessary and can be useful during a software project. They include knowledge about the organization itself, and data and experience obtained on previous software development projects within the organization. Another aspect observed was the importance of identifying key personnel in the organization who have the specific knowledge for an activity to be carried out during a software project, as latter highlighted by [43]. Using the DOSDE perspective, having an organizational model, looking at its structure, its processes, and the distribution of knowledge and skills throughout this structure and these processes, could help support such issues. Then, going one step further, the idea of DOSDE was broadened to include an Enterprise-Oriented Software Development Environment (EOSDE). Ontologies represent one of the basic building blocks for DOSDE's and EOSDE's infrastructure. To support the definition and to build the environment's infrastructure, different kinds of ontologies have been used. Although there are different definitions for ontology, that being used in this context is the traditional one proposed by Gruber [19]: "ontology is an explicit specification of a conceptualization". Basically, ontology consists of concepts and relations, their definitions, properties and constraints expressed by axioms [7]. This chapter describes our experience of building SDEs supported by the use of ontologies. So far, the information presented in this chapter intends to build a concise compilation of some research results that have been individually presented in [33, 31, 35, 34, 32, 60, 44, 53, 52, 54]. The intention is to group all these results to give the whole perspective regarding the use of ontologies in the context of real SDEs, which are currently being used by several software organizations in Brazil to support their software development processes. In the following sections we first briefly present SDEs and introduce DOSDE as an extension of them (Sect. 10.2). Then, in Sect. 10.3, we present the features of a DOSDE showing examples from DOSDEs developed for cardiology and acoustic propagation domains. In Sect. 10.4, we present the evolution from DOSDE to EOSDE. Sect. 10.5 describes the EOSDE infrastructure. In Sect. 10.6, we briefly describe the implementation of tools in DOSDE and EOSDE built using the defined ontology. Finally, in Sect. 10.7, we present our conclusions and ongoing work.
Learning Objects (LO) have been used for designing e-learning paradigms. Granularity of learning objects is related with the concept of reusability. The reused learning objects are henceforth used for effective personalization. Personalization based on the learner's intuitiveness is preferred using preference based and correlation based algorithms. Based on the user preference and learning style with domain ontology, the effective personalization can be attained. The performance measures and evaluation aids in deciding the learner's effective personalized experience of the system.
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