In a model-driven organization, all stakeholders are able to deal with information about an organization in the way that best supports their goals and tasks. In other words, they are able to select models of the organization at the optimal level of abstraction (e.g. platform independent) in the optimal form (e.g. graph-based) and with the optimal scope (e.g. a single component). However, no approach exists today that seamlessly supports this capability over the entire life-cycle of organizations and the IT systems that drive them. Enterprise architecture modeling approaches focus on supporting model-based views of the static architecture of organizations (i.e. enterprises) but generally provide little if any support for operational views. On the other hand, business intelligence approaches focus on providing operational views of organizations and usually do not accommodate static architectural views. In order to fully support the model-driven organization (MDO) vision, therefore, these two worlds need to be unified and a common, natural and uniform approach for defining and supporting all forms of views on organizations, at all stages of their life-cycles, needs to be defined and implemented in an efficient and scalable way. This paper presents a vision for achieving this goal based on the notions of deep and orthographic modeling. After explaining the background to the problem and introducing these two paradigms, the paper presents a novel approach for unifying them, along with a prototype implementation and example.
{"title":"Supporting the Model-Driven Organization Vision through Deep, Orthographic Modeling","authors":"Christian Tunjic, C. Atkinson, D. Draheim","doi":"10.18417/emisa.13.7","DOIUrl":"https://doi.org/10.18417/emisa.13.7","url":null,"abstract":"In a model-driven organization, all stakeholders are able to deal with information about an organization in the way that best supports their goals and tasks. In other words, they are able to select models of the organization at the optimal level of abstraction (e.g. platform independent) in the optimal form (e.g. graph-based) and with the optimal scope (e.g. a single component). However, no approach exists today that seamlessly supports this capability over the entire life-cycle of organizations and the IT systems that drive them. Enterprise architecture modeling approaches focus on supporting model-based views of the static architecture of organizations (i.e. enterprises) but generally provide little if any support for operational views. On the other hand, business intelligence approaches focus on providing operational views of organizations and usually do not accommodate static architectural views. In order to fully support the model-driven organization (MDO) vision, therefore, these two worlds need to be unified and a common, natural and uniform approach for defining and supporting all forms of views on organizations, at all stages of their life-cycles, needs to be defined and implemented in an efficient and scalable way. This paper presents a vision for achieving this goal based on the notions of deep and orthographic modeling. After explaining the background to the problem and introducing these two paradigms, the paper presents a novel approach for unifying them, along with a prototype implementation and example.","PeriodicalId":186216,"journal":{"name":"Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127881471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Modern organisations are faced with the very challenging problem of rapidly responding to continual external business pressures in order to sustain their competitiveness or to effectively perform mission-critical services. Difficulties arise because the continual evolution of systems and operational procedures that are performed in response to external pressures eventually lead to suboptimal configurations of systems and processes that drive the organisation.
{"title":"Introduction to the Special Issue on Model-Driven Organisations","authors":"T. Clark","doi":"10.18417/emisa.13.3","DOIUrl":"https://doi.org/10.18417/emisa.13.3","url":null,"abstract":"Modern organisations are faced with the very challenging problem of rapidly responding to continual external business pressures in order to sustain their competitiveness or to effectively perform mission-critical services. Difficulties arise because the continual evolution of systems and operational procedures that are performed in response to external pressures eventually lead to suboptimal configurations of systems and processes that drive the organisation.","PeriodicalId":186216,"journal":{"name":"Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model.","volume":"26 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120981514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Capability-oriented enterprise modelling can provide effective solutions to face changing business context. In the business domain, the notion of capability has gained a lot of attention since it guides the activities of service specification and design. Simultaneously, the research community has been promoting the integration of model-driven development (MDD) approaches with enterprise modelling to support the link between enterprise and software specifications. This integration has becoming vital to ensure the traceability of enterprise models and software implementations, acceleration of software time to market, quality assurance, and enterprise model evolution support. The capability-driven development (CDD) method has been recently developed and applied in various industrial use cases. But, the link between the CDD method and strong funded MDD approaches has not been explored. In this paper we explore the integration of the CDD method with the Communication Analysis method (a communication-oriented business process modelling method), which is supported by means of MDD frameworks. Among the advantages to add the communicational perspective to the CDD method, we want to highlight the possibility to offer a high level analysis of business process models that focus on the communications between different organisational actors, as so as to offer further transformation facilities into software components. With this integration, we give the first steps to offer automation facilities to capability-driven environments.
{"title":"Capability-based Communication Analysis for Enterprise Modelling","authors":"Ó. Pastor, M. Ruiz, H. Koç, Francisco Valverde","doi":"10.18417/emisa.13.4","DOIUrl":"https://doi.org/10.18417/emisa.13.4","url":null,"abstract":"Capability-oriented enterprise modelling can provide effective solutions to face changing business context. In the business domain, the notion of capability has gained a lot of attention since it guides the activities of service specification and design. Simultaneously, the research community has been promoting the integration of model-driven development (MDD) approaches with enterprise modelling to support the link between enterprise and software specifications. This integration has becoming vital to ensure the traceability of enterprise models and software implementations, acceleration of software time to market, quality assurance, and enterprise model evolution support. The capability-driven development (CDD) method has been recently developed and applied in various industrial use cases. But, the link between the CDD method and strong funded MDD approaches has not been explored. In this paper we explore the integration of the CDD method with the Communication Analysis method (a communication-oriented business process modelling method), which is supported by means of MDD frameworks. Among the advantages to add the communicational perspective to the CDD method, we want to highlight the possibility to offer a high level analysis of business process models that focus on the communications between different organisational actors, as so as to offer further transformation facilities into software components. With this integration, we give the first steps to offer automation facilities to capability-driven environments.","PeriodicalId":186216,"journal":{"name":"Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model.","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121931023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Modern enterprises are large complex systems operating in an increasingly dynamic environment and are tasked to meet organisational goals by adopting suitable course of actions or means. This calls for deep understanding of the enterprise, the operating environment, and the change drivers reactive as well as proactive. Traditionally, enterprises have been relying on human experts to perform these activities. However, the sole reliance on humans for decision making is increasingly unviable given the large size of modern enterprises, fast dynamics, and the prohibitively high cost of incorrect decisions. To address this challenge, we propose a method that leverages existing enterprise modelling (EM) tools to improve the agility of organisational decision-making as well as reducing the analysis burden on human experts. The proposed method artifact employs a design science research methodology and the method is validated using a realistic industrial case to bring out its strengths as well as limitations.
{"title":"Towards Improved Organisational Decision-Making - A Method and Tool-chain","authors":"Souvik Barat, V. Kulkarni, B. Barn","doi":"10.18417/emisa.13.6","DOIUrl":"https://doi.org/10.18417/emisa.13.6","url":null,"abstract":"Modern enterprises are large complex systems operating in an increasingly dynamic environment and are tasked to meet organisational goals by adopting suitable course of actions or means. This calls for deep understanding of the enterprise, the operating environment, and the change drivers reactive as well as proactive. Traditionally, enterprises have been relying on human experts to perform these activities. However, the sole reliance on humans for decision making is increasingly unviable given the large size of modern enterprises, fast dynamics, and the prohibitively high cost of incorrect decisions. To address this challenge, we propose a method that leverages existing enterprise modelling (EM) tools to improve the agility of organisational decision-making as well as reducing the analysis burden on human experts. The proposed method artifact employs a design science research methodology and the method is validated using a realistic industrial case to bring out its strengths as well as limitations.","PeriodicalId":186216,"journal":{"name":"Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132370398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In model-driven organizations enterprise models are used to represent and analyze the current and future states of aspects such as strategies, business processes or the enterprise architecture. Thereby, the scope of representation and analysis depends on the used modeling method. Although adaptations of modeling methods are frequently conducted to meet requirements emerging from business changes, such modifications may not be favorable due to potential side effects on other enterprise systems, e.g. through inconsistencies with existing standards and resulting conflicts in algorithmic processing. In the paper at hand we therefore propose the use of semantic annotations of enterprise models for dynamically extending the representation and analysis scope of enterprise modeling methods. Through a loose-coupling between enterprise models and formal semantic schemata, additional information can be represented and processed by algorithms without changes in the original modeling language. In this way, the evolution of information requirements of an organization can be satisfied while maintaining the consistency of the used enterprise modeling languages. For illustrating the feasibility of the approach we describe a use case from the area of risk management. The use case is realized using the SeMFIS platform that supports the annotation of enterprise models and the subsequent machine-based analysis of annotations.
{"title":"Semantic Annotations of Enterprise Models for Supporting the Evolution of Model-Driven Organizations","authors":"Hans-Georg Fill","doi":"10.18417/emisa.13.5","DOIUrl":"https://doi.org/10.18417/emisa.13.5","url":null,"abstract":"In model-driven organizations enterprise models are used to represent and analyze the current and future states of aspects such as strategies, business processes or the enterprise architecture. Thereby, the scope of representation and analysis depends on the used modeling method. Although adaptations of modeling methods are frequently conducted to meet requirements emerging from business changes, such modifications may not be favorable due to potential side effects on other enterprise systems, e.g. through inconsistencies with existing standards and resulting conflicts in algorithmic processing. In the paper at hand we therefore propose the use of semantic annotations of enterprise models for dynamically extending the representation and analysis scope of enterprise modeling methods. Through a loose-coupling between enterprise models and formal semantic schemata, additional information can be represented and processed by algorithms without changes in the original modeling language. In this way, the evolution of information requirements of an organization can be satisfied while maintaining the consistency of the used enterprise modeling languages. For illustrating the feasibility of the approach we describe a use case from the area of risk management. The use case is realized using the SeMFIS platform that supports the annotation of enterprise models and the subsequent machine-based analysis of annotations.","PeriodicalId":186216,"journal":{"name":"Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model.","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122485693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The recent Decision Model and Notation (DMN) establishes business decisions as first-class citizens of executable business processes. This research note has two objectives: first, to describe DMN's technical and theoretical foundations; second, to identify research directions for investigating DMN's potential benefits on a technological, individual and organizational level. To this end, we integrate perspectives from management science, cognitive theory and information systems research.
{"title":"What we know and what we do not know about DMN","authors":"K. Figl, J. Mendling, G. Tokdemir, J. Vanthienen","doi":"10.18417/EMISA.13.2","DOIUrl":"https://doi.org/10.18417/EMISA.13.2","url":null,"abstract":"The recent Decision Model and Notation (DMN) establishes business decisions as first-class citizens of executable business processes. This research note has two objectives: first, to describe DMN's technical and theoretical foundations; second, to identify research directions for investigating DMN's potential benefits on a technological, individual and organizational level. To this end, we integrate perspectives from management science, cognitive theory and information systems research.","PeriodicalId":186216,"journal":{"name":"Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127605910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Most business processes today can be easily modelled and controlled by advanced business process management systems. When it comes to processes, that are driven by outside events and require fast reactions to contingencies in order to stabilize them, e. g., transport or production processes, business process management systems often seem to reach their limits. In this paper we introduce a robustness modelwhich is based on a business process model of an undisturbed transport process and extends it by a generic contingency detection model. We employ a hierarchical organization for deriving corrective actions with least possible modifications to the original transport process.
{"title":"Hierarchical robustness model for business processes","authors":"Natalja Kleiner, P. Lockemann","doi":"10.18417/EMISA.SI.HCM.5","DOIUrl":"https://doi.org/10.18417/EMISA.SI.HCM.5","url":null,"abstract":"Most business processes today can be easily modelled and controlled by advanced business process management systems. When it comes to processes, that are driven by outside events and require fast reactions to contingencies in order to stabilize them, e. g., transport or production processes, business process management systems often seem to reach their limits. In this paper we introduce a robustness modelwhich is based on a business process model of an undisturbed transport process and extends it by a generic contingency detection model. We employ a hierarchical organization for deriving corrective actions with least possible modifications to the original transport process.","PeriodicalId":186216,"journal":{"name":"Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model.","volume":"44 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134087668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-27DOI: 10.18417/emisa.si.hcm.24
Ada Bagozi, D. Bianchini, V. D. Antonellis, Alessandro Marini, D. Ragazzi
Management of large volumes of data, collected from modern Cyber-Physical Systems, is calling for models, tools and methods for data representation and exploration, in order to capture relevant properties of physical objects, and manage them in the cyber-space. In this context, the impact of big data disruptive characteristics (namely, volume, velocity and variety) on data modelling and information systems designneeds further investigation. In particular, data exploration is assuming an ever growing relevance, being a way users/operators can learn from data by inspecting it according to different perspectives. In this paper, we use conceptual modelling for (big) data exploration in a dynamic context of interconnected systems. We rely on a multi-dimensional model, that is suited for properly providing data organization for exploration. Furthermore, we propose a model-driven approach that guides the design of multiple exploration strategies according to different objectives. The model-driven approach exploits a model of relevance, aimed at focusing the attention of the users/operators only on relevant data that are being explored. We describe the instantiation of the proposed concepts through some scenarios in the smart factory context, in order to show how conceptual modelling helps abstracting from implementation details and focusing on semantics of explored data.
{"title":"Big Data Conceptual Modelling in Cyber-Physical Systems","authors":"Ada Bagozi, D. Bianchini, V. D. Antonellis, Alessandro Marini, D. Ragazzi","doi":"10.18417/emisa.si.hcm.24","DOIUrl":"https://doi.org/10.18417/emisa.si.hcm.24","url":null,"abstract":"Management of large volumes of data, collected from modern Cyber-Physical Systems, is calling for models, tools and methods for data representation and exploration, in order to capture relevant properties of physical objects, and manage them in the cyber-space. In this context, the impact of big data disruptive characteristics (namely, volume, velocity and variety) on data modelling and information systems designneeds further investigation. In particular, data exploration is assuming an ever growing relevance, being a way users/operators can learn from data by inspecting it according to different perspectives. In this paper, we use conceptual modelling for (big) data exploration in a dynamic context of interconnected systems. We rely on a multi-dimensional model, that is suited for properly providing data organization for exploration. Furthermore, we propose a model-driven approach that guides the design of multiple exploration strategies according to different objectives. The model-driven approach exploits a model of relevance, aimed at focusing the attention of the users/operators only on relevant data that are being explored. We describe the instantiation of the proposed concepts through some scenarios in the smart factory context, in order to show how conceptual modelling helps abstracting from implementation details and focusing on semantics of explored data.","PeriodicalId":186216,"journal":{"name":"Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model.","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132384820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-27DOI: 10.18417/EMISA.SI.HCM.12
D. Embley, Stephen W. Liddle, Deryle W. Lonsdale, S. Woodfield
Ontological document reading is defined as automatically and appropriately populating a conceptual model representing an ontological conceptualization of some fragment of the real world. Appropriately populating the conceptualization involves not only extracting the information with respect to the declared object and relationship sets of the conceptual model but also involves checking the extracted information for real-world constraint violations, standardizing the data, and inferring the unwritten information that a document author intended to convey. Appropriately populating an ontology may, in addition, require adjustments to the ontology itself. This approach to document reading is presented in terms of an effort to build a system to extract the genealogical information in family history books. The status of the reading system is reported. Also explained is how the generated results can be imported into and thus contribute to the construction of a large repository of world-wide family interrelationships. The reading system’s potential use for constructing similar knowledge repositories in other domains is foreshadowed.
{"title":"Ontological Document Reading: An Experience Report","authors":"D. Embley, Stephen W. Liddle, Deryle W. Lonsdale, S. Woodfield","doi":"10.18417/EMISA.SI.HCM.12","DOIUrl":"https://doi.org/10.18417/EMISA.SI.HCM.12","url":null,"abstract":"Ontological document reading is defined as automatically and appropriately populating a conceptual model representing an ontological conceptualization of some fragment of the real world. Appropriately populating the conceptualization involves not only extracting the information with respect to the declared object and relationship sets of the conceptual model but also involves checking the extracted information for real-world constraint violations, standardizing the data, and inferring the unwritten information that a document author intended to convey. Appropriately populating an ontology may, in addition, require adjustments to the ontology itself. This approach to document reading is presented in terms of an effort to build a system to extract the genealogical information in family history books. The status of the reading system is reported. Also explained is how the generated results can be imported into and thus contribute to the construction of a large repository of world-wide family interrelationships. The reading system’s potential use for constructing similar knowledge repositories in other domains is foreshadowed.","PeriodicalId":186216,"journal":{"name":"Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131664374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-27DOI: 10.18417/EMISA.SI.HCM.22
J. Akoka, I. Comyn-Wattiau
In this article we present a framework describing a roundtrip engineering process for NoSQL database systems. This framework, based on the Model Driven Engineering approach, is composed of a knowledge base guiding the roundtrip process. Starting from a roundtrip generic scenario, we propose several roundtrip scenarios combining forward and reverse engineering processes. We illustrate our approach with an example related to a property graph database. The illustrative scenario consists of successive steps of model enrichment combined with forward and reverse engineering processes. Future research will consist in designing and implementing the main components of the knowledge base.
{"title":"Roundtrip engineering of NoSQL databases","authors":"J. Akoka, I. Comyn-Wattiau","doi":"10.18417/EMISA.SI.HCM.22","DOIUrl":"https://doi.org/10.18417/EMISA.SI.HCM.22","url":null,"abstract":"In this article we present a framework describing a roundtrip engineering process for NoSQL database systems. This framework, based on the Model Driven Engineering approach, is composed of a knowledge base guiding the roundtrip process. Starting from a roundtrip generic scenario, we propose several roundtrip scenarios combining forward and reverse engineering processes. We illustrate our approach with an example related to a property graph database. The illustrative scenario consists of successive steps of model enrichment combined with forward and reverse engineering processes. Future research will consist in designing and implementing the main components of the knowledge base.","PeriodicalId":186216,"journal":{"name":"Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model.","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122083763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：