Meta Object Facility Research Articles

Digital Twins Verification and Validation Approach through the Quintuple Helix Conceptual Framework

The concept of digital twins has been in the field for a long time, constantly challenging the specification, modeling, design, implementation, and exploitation of complex cyber–physical systems. Despite the various foundations, standards, and platforms in systems engineering, there are ongoing challenges with verification and validation methodology. This study aims to establish a generic framework that addresses the various aspects of digital twinning. The multifaceted nature of the problem requires raising the abstraction level in both the real (actual) and virtual domains, effective dissemination of information resources, and a design inspired by verification and validation. The proposed framework combines the quintuple helix model with the problem and operational domains of a real (actual) twin, the solution and implementation domains of a virtual twin, and the execution domain as the bridge that links them. Verification and validation dimensions follow the meta object facility abstraction layers (instance, model, meta-model, and meta-meta-model) mapping over five helices. Embedding the complexity reduction mechanisms in the proposed framework builds a suite for extendible and verifiable digital twinning in simulation and real-time scenarios. The application of main conceptual framework mechanisms in a real-world example study aids the verification of this research’s intentions. The validation is a matter of further research endeavors.

Управление информационной инфраструктурой малого предприятия с учетом дизайна продукции

The relevance of managing the enterprise information infrastructure, including the introduction of new modules into the existing architecture, is governed by the necessity to ensure a high degree of information protection and to improve the business process efficiency. 
 The article discusses modelling and implementing a new product design coordination module at several levels of a small enterprise’s infrastructure. Specific methods for managing the built infrastructure include business process automation, vulnerability analysis, information security, monitoring and managing changes. Examples of infrastructure management at different levels are considered, as well as the methods for implementing a new module and controlling it based on standards. To create a new module, a model development was carried out at the hardware level, which made it possible to optimise the system structure and reduce the load on the servers. Such standards as GOST R ISO / IEC 27001-2013 and GOST R ISO / IEC 27002-2015 were used, which ensured the security and protection of company data, as well as the Meta Object Facility (MOF) standard was applied, which made it easy to integrate the new module into the existing infrastructure. The study results show that introducing a new module can improve the enterprise’s information infrastructure, reduce the time for approval and improve the product quality, as well as decrease the likelihood of errors and information leaks and diminish the enterprise’s costs. It is recommended to use ISO/IEC and ITIL standards for efficient management of the enterprise’s information infrastructure.

Управление информационной инфраструктурой малого предприятия с учетом дизайна продукции

The relevance of managing the enterprise information infrastructure, including the introduction of new modules into the existing architecture, is governed by the necessity to ensure a high degree of information protection and to improve the business process efficiency. 
 The article discusses modelling and implementing a new product design coordination module at several levels of a small enterprise’s infrastructure. Specific methods for managing the built infrastructure include business process automation, vulnerability analysis, information security, monitoring and managing changes. Examples of infrastructure management at different levels are considered, as well as the methods for implementing a new module and controlling it based on standards. To create a new module, a model development was carried out at the hardware level, which made it possible to optimise the system structure and reduce the load on the servers. Such standards as GOST R ISO / IEC 27001-2013 and GOST R ISO / IEC 27002-2015 were used, which ensured the security and protection of company data, as well as the Meta Object Facility (MOF) standard was applied, which made it easy to integrate the new module into the existing infrastructure. The study results show that introducing a new module can improve the enterprise’s information infrastructure, reduce the time for approval and improve the product quality, as well as decrease the likelihood of errors and information leaks and diminish the enterprise’s costs. It is recommended to use ISO/IEC and ITIL standards for efficient management of the enterprise’s information infrastructure.

An Earth Observation Task Representation Model Supporting Dynamic Demand for Flood Disaster Monitoring and Management

A comprehensive, accurate, and timely expression of earth observation (EO) tasks is the primary prerequisite for the response to and the emergency monitoring of disasters, especially floods. However, the existing information model does not fully satisfy the demand for a fine-grain observation expression of EO task, which results in the absence of task process management. The current study proposed an EO task representation model based on meta-object facility to address this problem. The model not only describes the static information of a task, but it also defines the dynamics of an observation task by introducing a functional metamodel. This metamodel describes the full life cycle of a task; it comprises five process methods: birth, separation, combination, updating, and extinction. An earth observation task modeling and management prototype system (EO-TMMS) for conducting a remote sensing satellite sensor observation task representation experiment on flooding was developed. In accordance with the results, the proposed model can describe various EO tasks demands and the full life cycle process of an EO task. Compared with other typical observation task information models, the proposed model satisfies the dynamic and fine-grain process representation of EO tasks, which can improve the efficiency of EO sensor utilization.

A methodology for constructing the aircraft design schema

Aircraft collaboration design is based on a unified set of schemas containing data and model representations and interfaces across disciplines. The aircraft design schema is a central data model that specifies the paradigm for the representation of a full lifecycle model of aircraft design. The construction of the schema currently lacks theoretical guidance. This paper designs a novel methodology to construct the aircraft design schema, a fully functional, logical, and self-consistent methodology. The methodology defines a schema matrix that includes implementation strategies, principles, processes, meta-object facility, views, scenarios, and products. The aircraft conceptual design schema is constructed according to the methodology, which is a hands-on approach to help understand the concept and implementation. The features of the methodology are analyzed, and the methodology and the aircraft conceptual design schema are presented to address the pain points of multiple solution trade-offs, multiple iterations, and multidisciplinary coupling in aircraft conceptual collaboration design.

A method for structuring complex clinical knowledge and its representational formalisms to support composite knowledge interoperability in healthcare

IntroductionThe use and interoperability of clinical knowledge starts with the quality of the formalism utilized to express medical expertise. However, a crucial challenge is that existing formalisms are often suboptimal, lacking the fidelity to represent complex knowledge thoroughly and concisely. Often this leads to difficulties when seeking to unambiguously capture, share, and implement the knowledge for care improvement in clinical information systems used by providers and patients. ObjectivesTo provide a systematic method to address some of the complexities of knowledge composition and interoperability related to standards-based representational formalisms of medical knowledge. MethodsSeveral cross-industry (Healthcare, Linguistics, System Engineering, Standards Development, and Knowledge Engineering) frameworks were synthesized into a proposed reference knowledge framework. The framework utilizes IEEE 42010, the MetaObject Facility, the Semantic Triangle, an Ontology Framework, and the Domain and Comprehensibility Appropriateness criteria. The steps taken were: 1) identify foundational cross-industry frameworks, 2) select architecture description method, 3) define life cycle viewpoints, 4) define representation and knowledge viewpoints, 5) define relationships between neighboring viewpoints, and 6) establish characteristic definitions of the relationships between components. System engineering principles applied included separation of concerns, cohesion, and loose coupling. ResultsA “Multilayer Metamodel for Representation and Knowledge“ (M*R/K) reference framework was defined. It provides a standard vocabulary for organizing and articulating medical knowledge curation perspectives, concepts, and relationships across the artifacts created during the life cycle of language creation, authoring medical knowledge, and knowledge implementation in clinical information systems such as electronic health records (EHR). ConclusionM*R/K provides a systematic means to address some of the complexities of knowledge composition and interoperability related to medical knowledge representations used in diverse standards. The framework may be used to guide the development, assessment, and coordinated use of knowledge representation formalisms. M*R/K could promote the alignment and aggregated use of distinct domain-specific languages in composite knowledge artifacts such as clinical practice guidelines (CPGs).

A Heterogeneous Access Metamodel for Efficient IoT Remote Sensing Observation Management: Taking Precision Agriculture as an Example

Standard remote sensing observation (RSO) access and formulization is essential to Internet of Things (IoT) data management, such as in precision agriculture (PA). Because of the heterogeneous characteristics and the petabyte data size of RSO, massive remote sensing processing in RSO management has been hampered. Here, we present a heterogeneous access metamodel for efficient RSO management (HAMERM) and verify it in PA. The structure of basic metadata components is defined. A five-tuple metadata structure based on the metaobject facility is designed. HAMERM consists of identification, platform, observation, product, and access, which represent the five aspects of RSO metadata information. In addition, the flatMap/reduceByKey algorithms and the table structure have been proposed under Sensor Web and Geographic Information Science (GIS) techniques. Intensive experiments in Guangdong Province, China are conducted to test the proposed method. Two RSO metadata formulization instances were conducted to examine the ability of sheltering the differences of multisource and heterogeneous RSO. Experiments containing data storage and data soil moisture (SM) mapping were performed. The results suggest that the HAMERM method achieved a performance 30.1 times higher than that of Hadoop and three times higher than that of Spark (stand-alone). Consequently, the proposed HAMERM can be applied to achieve efficient SM mapping within PA, which is helpful for efficient RSO management for the IoT.

Towards a Model-Based Multi-Layered Approach to Describe Traffic Scenarios on a Technical Level

Highly automated vehicles are increasingly gaining the public’s attention. To achieve broad acceptance for the deployment of such vehicles, it is necessary to ensure their functionality and safety. One approach that has become popular in research is the scenario-based approach. However, manual testing of such complex systems is impractical and time-consuming. Using simulations to run and evaluate such scenarios appears to be the most viable approach. This, in turn, raises new challenges, especially in modeling the scenarios to be tested simulatively and incorporating the system under test as part of these. Since existing solutions do not solve these challenges satisfactorily—due to the strict separation of scenario and simulation model, among other reasons—this work addresses the need for a standardized, holistic, and extensible approach for modeling traffic scenarios to be executed simulatively. Requirements for such an approach are identified with focus on its application in simulation- and scenario-based verification and validation. Based on these, a model-based multi-layered approach is proposed. The foundations of this are then implemented utilizing a Meta Object Facility based heavyweight extension of the Unified Modeling Language metamodel. The resulting metamodel is used to demonstrate the applicability of the proposed approach by modeling a maritime traffic scenario.

On the automation-supported derivation of domain-specific UML profiles considering static semantics

In the light of standardization, the model-driven engineering (MDE) is becoming increasingly important for the development of DSLs, in addition to traditional approaches based on grammar formalisms. Metamodels define the abstract syntax and static semantics of a DSL and can be created by using the language concepts of the Meta Object Facility (MOF) or by defining a UML profile.Both metamodels and UML profiles are often provided for standardized DSLs, and the mappings of metamodels to UML profiles are usually specified informally in natural language, which also applies for the static semantics of metamodels and/or UML profiles, which has the disadvantage that ambiguities can occur, and that the static semantics must be manually translated into a machine-processable language.To address these weaknesses, we propose a new automated approach for deriving a UML profile from the metamodel of a DSL. One novelty is that subsetting or redefining metaclass attributes are mapped to stereotype attributes whose values are computed at runtime via automatically created OCL expressions. The automatic transfer of the static semantics of a DSL to a UML profile is a further contribution of our approach. Our DSL Metamodeling and Derivation Toolchain (DSL-MeDeTo) implements all aspects of our proposed approach in Eclipse. This enabled us to successfully apply our approach to the two DSLs Test Description Language (TDL) and Specification and Description Language (SDL).

Handling nonconforming individuals in search-based model-driven engineering: nine generic strategies for feature location in the modeling space of the meta-object facility

Lately, the model-driven engineering community has been paying more attention to the techniques offered by the search-based software engineering community. However, even though the conformance of models and metamodels is a topic of great interest for the modeling community, the works that address model-related problems through the use of search metaheuristics are not taking full advantage of the strategies for handling nonconforming individuals. The search space can be huge when searching in model artifacts (magnitudes of around $$10^{150}$$ for models of 500 elements). By handling the nonconforming individuals, the search space can be drastically reduced. In this work, we present a set of nine generic strategies for handling nonconforming individuals that are ready to be applied to model artifacts. The strategies are independent from the application domain and only include constraints derived from the meta-object facility. In addition, we evaluate the strategies with two industrial case studies using an evolutionary algorithm to locate features in models. The results show that the use of the strategies presented can reduce the number of generations needed to reach the solution by 90% of the original value. Generic strategies such as the ones presented in this work could lead to the emergence of more complex fitness functions for searches in models or even new applications for the search metaheuristics in model-related problems.

A heterogeneous key performance indicator metadata model for air quality monitoring in sustainable cities

Due to heterogeneous and inconsistent key performance indicators (KPIs) for the quantitative evaluation of a sustainable city's operational status, it is a great challenge to share multidimensional, multi-source and heterogeneous indicators. We propose a heterogeneous KPI capability representation model (HKPM) in our study. Based on the Meta Object Facility architecture, a nine-tuple multi-hierarchical meta-model is formulated to define the metadata components. Nine specific representation element datasets for specific KPIs are proposed to represent the meta-model. Besides, the KPI classification based on Sustainable Development Goals (SDGs) has been accomplished to support HKPM instantiated in concrete application. Experiments are conducted with the multi-type KPIs to validate the feasibility of HKPM, as shown in public service and Air Quality Index KPI instantiation example. Furthermore, the KPIs can be characterized in different dimensions, which can be modelled in a stereoscopic manner, promoting a comprehensive perception of sustainable cities.

EML BASED URBAN FIRE INCIDENT MODELING METHOD AND PROTOTYPE

Abstract. Urban fire disasters are one of the most frequent disasters that threaten public safety and social development in cities. Most urban fire disasters feature dynamics and processes. The locations, time, meteorological conditions and surroundings of each fire incidents are diverse, besides the traffic conditions around the fire place would be changing dynamically. At present, there is no unified modeling language to describe urban fire incidents, which makes it difficult to obtain experience from historical cases and hard to describe. This paper used the Event pattern Markup Language (EML) to model urban fire incidents from an observation perspective based on MetaObject Facility (MOF) framework, designed and implemented an urban fire incident modeling prototype. It can realize the information description of urban fire disasters, and provide descriptions of different observation missions during the process of the fire incidents. The detailed description of the process allows multiple observations based on the expression of EML to be performed, and offer evidence for emergency response phase and post-mortem archiving. The real data of the "12.1" major fire in Tianjin, China in 2017 was used as a use-case to show the modeling results of the entire fire incident in four phases – mitigation, preparedness, response, and recovery. The results show that this modeling method proposed in this paper can represent the dynamic information of urban fire incidents and achieve the dynamic modeling of urban fire incidents.

TOTEM: Reconciling multi-level modelling with standard two-level modelling

Model driven Engineering (MDE) advocates the active use of models throughout the different software development phases. In MDE, models are described using meta-models, one meta-level above. This approach effectively leaves developers with one single meta-level to create their models. However, there are scenarios where the use of multiple meta-levels results in simpler models with less accidental complexity. Hence, to simplify modelling in these cases, several multi-level modelling approaches and tools have recently emerged to increase the flexibility in modelling. While they provide advanced primitives to simplify modelling, there are possibilities to improve interoperability with mainstream two-level modelling approaches based on the Meta-Object Facility (MOF) standard of the Object Management Group (OMG), and achieve wider adoption.For this purpose, we first characterise the design space of multi-level modelling approaches using a feature model. On such a basis, we provide a detailed comparison of existing multi-level modelling tools, identifying gaps and research opportunities. As a result of this gap analysis, we propose a new approach to multi-level modelling that embeds multiple meta-levels within one meta-model (i.e., encoding objects as classes, and instantiation as inheritance), and a tool – called TOTEM – which implements these concepts. The tool capabilities and its benefits in terms of interoperability with mainstream, standard modelling frameworks are illustrated through an example, as well as with empirical and analytical evaluations.

Toward Automatic Generation of Column-Oriented NoSQL Databases in Big Data Context

The growth of application architectures in all areas (e.g. Astrology, Meteorology, E-commerce, social network, etc.) has resulted in an exponential increase in data volumes, now measured in Petabytes. Managing these volumes of data has become a problem that relational databases are no longer able to handle because of the acidity properties. In response to this scaling up, new concepts have emerged such as NoSQL. In this paper, we show how to design and apply transformation rules to migrate from an SQL relational database to a Big Data solution within NoSQL. For this, we use the Model Driven Architecture (MDA) and the transformation languages like as MOF 2.0 QVT (Meta-Object Facility 2.0 Query-View-Transformation) and Acceleo which define the meta-models for the development of transformation model. The transformation rules defined in this work can generate, from the class diagram, a CQL code for creation column-oriented NoSQL database.

Satori: Toward a Global Augmented Intelligence Architecture

Satori is a proposed design framework that optimizes the intelligence carrying capacity of messages within and between systems. Closer inspection yields a Meta Object Facility (MOF), similar to CORDA, but for decentralized intelligence systems. The design goal of this framework is to reduce costs and operating risks while optimizing business intelligence in the financial services and the integral role these play in adjacent sectors. At maturity, the notional MOF architecture can discern domain expert intents without extrinsic rules or intrinsic attribute dependencies. With the appropriate expert and sovereign jurisdictional attribution in place, such a MOF should enable decentralized intelligence systems to function as oracles of jurisprudential intent that can scale with the potentially asymptotic tokenization of new securities and asset classes for physical and digital systems. TOPICS:Currency, portfolio construction, wealth management

Metamodelling for Design of Mechatronic and Cyber-Physical Systems

The paper presents the issue of metamodeling of Domain-Specific Languages (DSL) for the purpose of designing complex mechatronics systems. Usually, one of the problems during the development of such projects is an interdisciplinary character of the team that is involved in this endeavour. The success of a complex machine project (e.g., Computer Numerically Controlled machine (CNC), loading crane, forestry crane) often depends on a proper communication between team members. The domain-specific modelling languages developed using one of the two approaches discussed in the work, lead to a machine design that can be carried out much more efficiently than with conventional approaches. Within the paper, the Meta-Object Facility (MOF) approach to metamodeling is presented; it is much more prevalent in modern modelling software tools than Graph-Object-Property-Relationship-Role (GOPRR). The main outcome of this work is the first presentation of researchML modelling language that is the result of more than twenty ambitious research and development projects. It is effectively used within new enterprises and leads to improved traceability of the project goals. It enables for fully-featured automatic code generation which is one of the main pillars of the agile management within mechatronic system design projects.

Developing a decision support system for Disaster Management: Case study of an Indonesia volcano eruption

Disaster Management activities often focus on specific tasks (e.g. evacuation, logistic or coordination) and are confined to one specific DM phase (e.g. Preparedness or Response). New awareness about an external change, be it environmental or organisational, typically act as a trigger for such focussed activities. A variety of views or stakeholders are also involved in those activities, and their various concerns get often intertwined. This work advocates the use of a Decision Support System (DSS) that can be deployed as a single access point. Such a system requires a sufficient amount of representative knowledge, and facilities to avail the knowledge to the appropriate stakeholders in an appropriate form. With the multitude of stakeholders and their varying knowledge requirements, the system will need to present the knowledge differently according to the stakeholders needs in their decision making process. Such processes can vary, e.g. whether for policy making or for operational real time responses. This paper presents a hybrid of knowledge elicitation and retrieval mechanisms, some are top down and others are bottom up. The mechanisms make use of the Meta Object Facility (MOF) to structure and present the knowledge appropriately according to different interests and roles. A case study of the recent Mt. Agung volcano eruption in Bali Indonesia is successfully used to demonstrate the efficacy of the mechanisms proposed and the resultant DSS.

Agent-Based Knowledge Analysis Framework in Disaster Management

Disaster Management (DM) is a complex set of interrelated activities. The activities are often knowledge-intensive and time sensitive. Timely sharing of the required knowledge is critical for DM. For recurring disasters (e.g. floods), developed countries tend to have dedicated document repositories of Disaster Management Plans (DISPLANs) that can be accessed as needs arise. However, accessing the appropriate plan in a timely manner, and sharing activities between plans, often requires significant domain knowledge and intimate understanding of the plans in the first place. This paper introduces an Agent-Based (AB) knowledge analysis method to convert DISPLANs into a collection of knowledge units that can be stored into a unified repository. The repository of DM actions then enables the mixing and matching of knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF). We use the flood DISPLANs plans used by SES (State Emergency Service), an authoritative DM agency in New South Wales (NSW) State of Australia (hereinafter referred to as SES NSW) to illustrate and give a preliminary validation of the approach. It is illustrated by using displans along the flood-prone Murrumbidgee river in central NSW.

Disaster Knowledge Management Analysis Framework Utilizing Agent-Based Models: Design Science Research Approach

Disaster Management (DM) knowledge has long been acknowledged as playing a significant role in reducing the impact caused by disasters. It helps people at the decision-making level to produce contextual decisions, as they are produced from the interaction of the involved social entities and their experiences and those who are on the ground to appropriately react towards the disaster. While it is seen as critical the DM activities, its adoption is still challenging due to its complex structure and availability. This paper employs the Design Science Research (DSR) methodology in Information System (IS) research to develop and validate a knowledge transfer analysis framework to unify access to semi-structured DISPLANs (Disaster Management Plans) through a unified repository. In the development, Agent-Based Models (ABMs) are used to code the DISPLANs to enable their transfer into a repository. The Meta Object Facility (MOF) Metamodeling Framework is then used to create a repository that is ready for storing the content of ABMs. This developed framework is then validated using a real case study of the flood DISPLAN of the State Emergency Service (SES) the State of Victoria, Australia. At the end, this paper contributes to: (1) a validated knowledge transfer analysis framework supporting DM resilience endeavors; (2) demonstrate the DSR methodology as a frame for IS research.

An EMOF-Compliant Abstract Syntax for Bigraphs

Bigraphs are an emerging modeling formalism for structures in ubiquitous computing. Besides an algebraic notation, which can be adopted to provide an algebraic syntax for bigraphs, the bigraphical theory introduces a visual concrete syntax which is intuitive and unambiguous at the same time; the standard visual notation can be customized and thus tailored to domain-specific requirements. However, in contrast to modeling standards based on the Meta-Object Facility (MOF) and domain-specific languages typically used in model-driven engineering (MDE), the bigraphical theory lacks a precise definition of an abstract syntax for bigraphical modeling languages. As a consequence, available modeling and analysis tools use proprietary formats for representing bigraphs internally and persistently, which hampers the exchange of models across tool boundaries. Moreover, tools can be hardly integrated with standard MDE technologies in order to build sophisticated tool chains and modeling environments, as required for systematic engineering of large systems or fostering experimental work to evaluate the bigraphical theory in real-world applications. To overcome this situation, we propose an abstract syntax for bigraphs which is compliant to the Essential MOF (EMOF) standard defined by the Object Management Group (OMG). We use typed graphs as a formal underpinning of EMOF-based models and present a canonical mapping which maps bigraphs to typed graphs in a natural way. We also discuss application-specific variation points in the graph-based representation of bigraphs. Following standard techniques from software product line engineering, we present a framework to customize the graph-based representation to support a variety of application scenarios.