Abstract: During the last years, many companies established fast IT or digital IT units dedicated to build and operate digital customer-facing services. These units adopted agile methods, new tool chains as well as new organizational settings like BizDevOps teams. BizDevOps teams are responsible for continuously (re-)defining business functionality of certain (micro-)services, (re-)developing and running them. In these new fast IT environments, the role of enterprise architecture management changes dramatically. BizDevOps teams have a high degree of autonomy in designing both, the functionality and the architecture of their (micro-)services and thus contribute to business-IT-alignment in a new way. Nevertheless, a central enterprise architecture management (EAM) function is still required for supporting the teams regarding cross-team and cross-service issues. Furthermore, as many companies still run the traditional IT function side-by-side with the new IT function, the EAM functions of both parts have to cooperate. Based on a single case study, we discuss the emergence of a new EAM function ("fast IT EAM"), changing tasks and processes, implications for EA models and challenges for the integration of the traditional EAM and the fast IT EAM functions.

Abstract: In competitive markets, companies need well-designed business strategies if they seek to grow and obtain sustainable competitive advantage. At the core of a successful business strategy there is a carefully crafted value proposition, which ultimately defines what a company delivers to its customers. Despite their widely recognized importance, there is however little agreement on what exactly value propositions are. This lack of conceptual clarity harms the communication among stakeholders and the harmonization of current business strategy theories and strategy support frameworks. Furthermore, it hinders the development of systematic methodologies for crafting value propositions, as well as adequate support for representing and analyzing them. In this paper, we present an ontological analysis of value propositions based on a review of most relevant business and marketing theories and on previous work on value ascription, grounded in the Unified Foundational Ontology (UFO). Our investigation clarifies how value propositions are different from value presentations, and shows the difference between value propositions at the business level from those related to specific offerings.

Abstract: E-commerce marketplaces are highly dynamic with constant competition. While this competition is challenging for many merchants, it also provides plenty of opportunities, e.g., by allowing them to automatically adjust prices in order to react to changing market situations. For practitioners however, testing automated pricing strategies is time-consuming and potentially hazardously when done in production. Researchers, on the other side, struggle to study how pricing strategies interact under heavy competition. As a consequence, we built an open continuous time framework to simulate dynamic pricing competition called Price Wars. The microservice-based architecture provides a scalable platform for large competitions with dozens of merchants and a large random stream of consumers. Our platform stores each event in a distributed log. This allows to provide different performance measures enabling users to compare profit and revenue of various repricing strategies in real-time. For researchers, price trajectories are shown which ease evaluating mutual price reactions of competing strategies. Furthermore, merchants can access historical marketplace data and apply machine learning. By providing a set of customizable, artificial merchants, users can easily simulate both simple rule-based strategies as well as sophisticated data-driven strategies using demand learning to optimize their pricing strategies.

Abstract: Traditionally, enterprise application integration (EAI) processes structured data. Recent trends such as social and multimedia computing led to an increase in unstructured multimedia data like images and video streams that have to be processed by EAI. This poses challenges to EAI with respect to variety, velocity, and volume of the processed data. Furthermore, multimedia data has more semantic qualities (e.g., emotions) compared to structured data, making the data processing and user interaction more difficult. In this work, we conduct a literature review of industrial and mobile applications with respect to their usage of EAI in multimedia computing. We derive multimedia operations and map them to the enterprise integration patterns (EIPs). We propose a realization that allows to interact with EAI processes taking the multimedia semantics into account, discuss EAI architecture extensions and study message processing challenges.

Abstract: I present a novel definition of services (in particular, public services) which sees each of them as the sum of all activities that realize a public authority's commitment to make available to individuals, businesses, or other public authorities some capabilities intended to answer their needs, giving them some possibilities to control how and when such capabilities should be manifested.

Abstract: Most view-based modelling approaches are today based on a "synthetic" approach in which the views hold all the information modelled about a system and are kept consistent using explicit, inter-view correspondence rules. The alternative "projective" approach, in which the contents of views are "projected" from a single underlying model on demand, is far less widely used due to the lack of suitable conceptual frameworks and languages. In this paper we take a step towards addressing this problem by presenting the foundations of a suitable language and conceptual framework for defining and applying views for projective modelling. The framework leverages deep modeling in order to seamlessly support views that exist at, and span, multiple levels of classification. The viewpoint language was developed in the context of Orthographic Software Modelling (OSM) but is more generally applicable to any projective modelling approach.

Abstract: In spite of the proliferation of the business process and data compliance checking approaches, in practice, regulatory compliance management still demands considerable manual intervention. Previous research in the field of compliance has established that the manual specification/tagging of the regulations not only fails to ensure their proper coverage but also negatively affects the turnaround time both in proving and maintaining the compliance. Our contribution is an (semi-) automated transformation of the legal NL (English) text to SBVR Model via authoring of Structured English (SE) rules. The key benefit of our approach is the direct involvement of the domain experts to specify regulations using SE, which is close to English, rather than a formal specification language. We substantiate the approach using an example from industry regulations in banking and financial services domain.

Abstract: Digital innovation (DI), Internet of Things (IoT) and Cyber-Physical Systems (CPS) offer new opportunities for enterprises but also cause new challenges for Enterprise Architecture Management. Based on an industrial case from power garden products illustrating potentials and challenges of DI and IoT, this paper investigates the integration of product-IT into enterprise architectures. Product-IT includes the embedded IT-systems in physical products and services, components for operations, maintenance or evaluation purposes. The paper investigates the suitability of traditional enterprise architecture layers for structuring product-IT, identifies problems in product-IT and enterprise-IT integration and challenges for the field of EAM. The main contributions of the paper are (1) to position the area of product-IT in the field of EAM, (2) to identify challenges from real-world cases regarding integration of product-IT into EA and (3) outline potential ways to approach the challenges.

Abstract: Organisations typically have to cope with large numbers of business rules and existing regulations governing the business in which they operate. Due to the size and complexity of those rules, maintenance is difficult and it is increasingly complicated to ensure that each business process adheres to those rules. As such, automated extraction of business processes from rules has a number of clear advantages: (1) visualisation of all possible executions allowed by the rules, (2) automated execution and compliance by design, (3) identification of "inefficiencies" in the business rules. Existing approaches, however, only allow to generate partial traces based on input specifications and cannot handle many different input cases resulting in a full process. This paper presents a formal method to visualise and operationalise such sets of rules as a verifiable business process that is compliant by design and allows us to analyse all possible execution paths. In addition, it maintains information of all distinct input cases, to preserve dependencies between consecutive exclusive paths.

Abstract: Models are perceived as effective tools for stakeholder communication and analysis concerning a given system. Enterprise Architecture assists organizational change with the creation and maintenance of models as a means to mitigate the business-IT misalignment and supporting decision-making regarding the strategic vision of the enterprise. Literature has acknowledged the topic of enterprise architecture evolution as a relevant issue that requires research efforts. In particular, how can enterprise architecture models be used not only for capturing both the current and future states of the enterprise but also as tools for documenting and analyzing the rationale behind an enterprise architecture evolution, thus supporting decision-making and communication. This paper proposes a model-based viewpoint, as an extension of the enterprise architecture model, defining the concepts and relationships that express the evolution-specific concerns with respect to the architecture of the enterprise.

Abstract: In addition to in-house applications, networked enterprises are increasingly using data and services from various external sources. Conversion of data to useful information and IT alignment with business goals are big challenges faced by these enterprises. Integration platforms (IPs) aid enterprises in solving such challenges. However, the large number of commercial and academic IPs currently available have created a new problem for enterprises, namely whether to build their own IP or buy/rent a existing IP. Also, how to choose from the plethora of different design/solution options that are available? This paper presents a study and analysis of 31 IPs to bring out best practices in IP design. Following a commonality analysis of IPs from different research domains, an IP reference architecture is proposed. The reference architecture will aid enterprises in making better IP design/solution choices. It can also contribute to IP research by acting as a common reference point for future IP analysis.

Abstract: As a result of growing complexities in business processes, information systems, and the technical infrastructure, a key challenge for enterprise architecture management (EAM) is to guide stakeholders from different hierarchical levels with heterogeneous concerns. EA deliverables, such as models or frameworks, are often highly comprehensive and standardized. However, these can hardly be applied without greater adaption. Although the literature selectively covers approaches for tailoring EA deliverables closer to the concerns of affected stakeholders, these approaches are often vague or not very differentiated. In the paper at hand, we aim at introducing a stakeholder perspective to EAM research that considers stakeholder concerns on EAM across hierarchical levels. To this end, we conduct a case study: Our results show homogenous concerns among stakeholders on EA deliverables. In turn, we found different concerns on the role of EAM in applying these deliverables, dependent on the hierarchical level of stakeholders. These findings stress the necessity for a more differentiated understanding of stakeholder concerns on EAM. Finally, we discuss the implications of our findings for an exemplary EAM approach.

Abstract: In this paper, we define three key performance indicators (KPI) to measure the health of application portfolios (AP) and use the business capability map (BCM) as a visualization lens. Based on a literature review of AP management and BCM practices, we conduct a case study with a large European automotive company to develop three KPIs related to AP complexity, AP quality, and AP impact. The application of the KPIs is illustrated for the BCM of our case study partner and evaluated by conducting expert interviews with ten enterprise architecture experts of the company. Our results provide further insights on AP management practices that are enabled by using the BCM as a holistic visualization tool.

Abstract: Process-aware Information Systems (PAIS) have become ubiquitous in companies. Thus the amount of data that can be used to analyze and monitor process executions is vast. The event logs generated by PAIS might contain information about decision making processes and can support the understanding and improving of procedures in companies. Mining decisions and constraints from logs has already been investigated, but so far only for each instance in a separate manner. However, in many practical settings instances are connected to each other if they share, for example, the same resources. Therefore, we present an approach for discovering Instance-Spanning Constraints (ISC) from event logs. The main idea is to identify instance-spanning attributes in the logs and to separate the logs accordingly. Based on these projections, classification algorithms are applied in order to obtain ISC candidates. The feasibility and applicability of the approach is evaluated based on artificial as well as real-life logs. The discovered ISC candidates are then assessed by domain experts.

Abstract: The increasing amount of gathered sensor data in Industry 4.0 allows comprehensive data analysis software that creates value-adding opportunities. As companies often cannot implement such software by themselves and as they typically don't want to give their data to external scientists, they commission them to build the required software in order to execute it locally. However, installing, configuring, and running complex third party software on another company's infrastructure and linking them to local data sources challenges the responsible administrators due to an immense technical complexity. Moreover, standards-based approaches for automation are missing. In this paper, we present three TOSCA-based deployment modelling approaches for function shipping that enable modelling data analysis software in a way that enables (i) its automated deployment and execution in a remote, foreign IT infrastructure including (ii) the wiring with the data sources that need to be processed in this environment. We validate the practical feasibility of the presented modelling approaches by a case study from the domain of manufacturing, which is based on the open-source TOSCA ecosystem OpenTOSCA, which provides a modelling tool, a runtime, as well as a self-service portal for TOSCA.

Abstract: Some companies are willing to execute their business processes (BP) in the cloud for enjoying its benefits. However, they are also reluctant because of the new security risks that using cloud resources introduces. Security risk includes many dimensions, but this work focus on preserving the privacy of the logic of a BP deployed in a multi-cloud context by preventing a coalition of malicious clouds to re-construct important information from this logic. More precisely, the paper presents a BP logic privacy metric directly supporting the evaluation of the risk a company has its logic hacked in a particular multi-cloud configuration.

Abstract: Re-engineering is essential for maintaining the competitiveness of enterprises. Enterprise re-engineering involves addressing (emergent) changes, re-organizing, outsourcing, realigning, etc. In this paper, we investigate how to re-engineer enterprises by coupling high-level requirements and the data warehouse, leading to a process re-design that makes the business layer of an enterprise more effective. More specifically, we propose an approach to reasoning about enterprise’s strategy together with data mining rules extracted from the data warehouse of the enterprise in order to make design-time changes to its business processes, primarily by means of eliminating redundant tasks and re-ordering inefficiently-located tasks. As such, the redesign is enabled by high-level strategic elements and driven by the enterprise data warehouse. The rationale behind this realignment is to combine yesterday’s behavioral facts (i.e., mining enterprise’s operational data) with today’s operationalization possibilities (e.g., goals), which results in tomorrow’s business model. We report our work on the enterprise architecture developed for a retailer of low-cost domestic airfare.

Abstract: Ontologies play a key role in semanticinteroperability projects, capturing the conceptualizationunderlying the various systems to be integrated. In the case oflarge information systems landscapes, a single monolithicontology often becomes hard to design and maintain. In thissetting, it is common to divide the ontological model inconsistently interlinked modular ontologies, forming anontology network. This paper explores the role of EnterpriseArchitecture (EA) models in defining the ontologies in anontology network. We report on an exploratory study in thescope of an e-Government interoperability project in the areaof public security. In the reported study, an EA model providesguidance in the modularization of the ontology network.

Abstract: To increase flexibility, object-aware process management systems enable data-driven process execution and dynamic generation of form-based tasks at run-time. Therefore, a powerful access control concept becomes necessary to define which data elements users may read or write at a given point in time during process execution. The access control concept we present in this paper has been realized in the context of the PHILharmonicFlows framework, which provides a distributed data-driven process execution engine. We present solutions that allow for complex as well as fine-grained permissions and roles, which are granted depending on the states of processes and data elements. We show how one can resolve authorization queries in real-time over multiple business objects and process instances. This constitutes a significant advantage over centralized access control systems.

Abstract: Knowledge-intensive processes (KiPs) are driven by knowledge workers utilizing their skills, experiences and expertise. As KiPs are emergent and unpredictable by nature, their operational support is challenging. For coordinating and synchronizing their work, usually, knowledge workers rely on simple task lists like to-do lists or checklists. Though these instruments are intuitive and prevalent, their current implementations tend to be ineffective and error-prone. Tasks are neither made explicit nor are they synchronized. In addition, no task lifecycle support is provided and media disruptions aggravate task management. As a consequence, the efforts knowledge workers spent in task management are not exploited for optimizing future KiPs. This work presents the proCollab approach, focusing on its stateful and customizable components of processes, task trees, and tasks. proCollab processes may constitute KiPs in the shape of projects and cases, while generic task trees and tasks support required digital task lists of any kind. To enable domain-specific task support, the proCollab state management allows to integrate domain-specific procedure models (e.g., Scrum) and to enrich proCollab components with customized states. Finally, this customizable task management support fosters knowledge workers' coordination, increases work awareness, reduces media disruptions, and enables the reuse of valuable coordination efforts and knowledge.

Abstract: The debate on advantages and disadvantages of declarative versus procedural process modeling languages for different usage scenarios has been intense. Procedural languages are more suited for describing operational processes while declarative ones for expressing regulations/guidelines and, in many situations, the need of combining the benefits of the two rises. Instead of forcing modelers to use a hybrid language, we envisage to keep the two specifications separate and propose a technique that automatically adapts procedural models so as to comply with sets of declarative rules. This not only fits scenarios where, e.g., company processes have to be modified according to changing external rules, but, more in general, it presents a way to take advantage of the flexibility of declarative while maintaining the high level of support provided by procedural languages. Furthermore, by comparing the original and the resulting procedural models, the impact of rules is clearly exposed. In this paper, we frame the problem above by providing its theoretical characterization and propose an automata-based solution, which is then evaluated against approaches leveraging state-of-the-art techniques for process discovery and model repair.

Abstract: Architecture models mainly have three functions; 1) document, 2) analyze, and 3) improve the system under consideration. All three functions have suffered from being timeconsuming and expensive, mainly due to being manual processes in need of hard to find expertise. Recent work has however automated both the data collection and the analysis. In order for enterprise architecture modeling to finally become free of manual labor the design function also needs to be automated. In this position paper we propose the Automatic Designer. A solution that employs machine learning techniques to realize the design of (near) optimal architecture solutions. This particular implementation is focused on security analysis, but could easily be extended to other topics.

Abstract: Earlier research has identified network analysis techniques, methods, and models used to analyze structural aspects of an enterprise architecture (EA) modeled as a network or graph. However, there is still no common set of conceptual elements for such research that could allow one to identify the information requirements needed to perform this type of analysis. In the present research, we organize foundational conceptual elements in a meta-model as a step towards fostering the development of this research field and creating alignment among researchers. As a second contribution, we classify the existing knowledge about network analysis in an EA context through a systematic literature review, according to the proposed meta-model; this results in a library of 74 network analysis initiatives (e.g., metrics or methods) for EA, which we evaluate reasoning about their efficacy and utility and also surveying experts. Our work thus identifies and systematizes the state of art of network science as a toolset to be applied in the EA context.

Abstract: ICT systems have become an integral part of business and life. At the same time, these systems have become extremely complex. In such systems exist numerous vulnerabilities waiting to be exploited by potential threat actors. pwnPr3d is a novel modelling approach that performs automated architectural analysis with the objective of measuring the cyber security of the modeled architecture. Its integrated modelling language allows users to model software and hardware components with great level of details. To illustrate this capability, we present in this paper the metamodel of UNIX, operating systems being the core of every software and every IT system. After describing the main UNIX constituents and how they have been modelled, we illustrate how the modelled OS integrates within pwnPr3d's rationale by modelling the spreading of a self-replicating malware inspired by WannaCry.

Abstract: Conceptual elevation of data in business process modeling was first formulated in 2003. The research community responded to this new idea enthusiastically. In the past decade, there have been numerous research activities concerning the interactions between business processes/activities and data in many aspects of business process management. Many of the advancements have or will have impacted on design/modeling, analysis, implementation of business processes in practice. However, there is still a lack of techniques for developing a suite of "interrelated" processes realizing a business service. Interrelated processes are a cluster of processes that share data and other resources, are collectively constrained by regulations and policies, influence KPIs as a group. Many current practical applications of business workflow systems are in urgent need for tools and techniques for process clusters. In this paper, we formulate a broad notion of an "Enterprise Process Framework" (EPF) to address this need and outline several interesting research challenges arising from EPFs.

Abstract: The increasing number, complexity, and variability of business rules in today's enterprises introduces the need for their effective and flexible management. In several research fields, such as the semantic web, library science, and data tailoring, effective organization of knowledge is enabled by contexts. We previously proposed a static structure model for context-based business rule management. To enable flexibility, we complement this model by atomic and composed modification operations. Each atomic modification operation is associated with one of four roles: rule repository administrator, rule developer, user, and domain expert. This enables effective separation of tasks and responsibilities promoting efficient rule management. Composed modification operations describe combinations of atomic modification operations relevant in practice. We apply the proposed approach to the real-world use case of classifying aeronautical messages.

Abstract: The fourth industrial revolution is driven by the integration and analysis of a vast amount of diverse data. Thereby, data about production steps, overall manufacturing processes, and also supporting processes is gathered to enable holistic analysis approaches. These approaches promise to provide new insights and knowledge by revealing cost saving possibilities and also automated adjustments of production processes. However, such scenarios typically require analytics services and data integration stacks since algorithms have to be developed, executed and therefore be wired with the data to be processed. This leads to complex setups of overall analytics environments that have to be installed, configured and managed according to the needs of different analysis scenarios and setups. The manual execution of such installations is time-consuming and error-prone. Therefore, we demonstrate how the different components of such combined integration and analytics scenarios can be modelled in order to be reused in different settings, while enabling the fully automated provisioning of overall analytics stacks and services.

Abstract: High-level enterprise services are considered as wrappers of business processes and ICT capabilities in enterprise architecture. Enterprise services have distinctive features that are not typically observed in Web services, e.g. signicant portions of the functionality of these services might be executed in a human-mediated fashion. As such, a service level agreement should be described as a mixture of human-mediated functionality (e.g., service penalty) and computer-interpretable factors (e.g., reliability, payment). This paper reports our preliminary work in defining a taxonomy for co-relating SLAs with elements of enterprise architecture. It gives insight into the alignment between what the enterprise in questions contractually agrees with its partners (or customers) and what it possesses to be able to fulfill the agreement. We define the service level agreement formally. We adopt the ArchiMate – a widely used language for modeling and analyzing enterprise architectures. We then propose the corelation between items in the agreement with elements in the enterprise architecture. We showcase our work using a real-life case-study in the retailing market of domestic airfare.

Abstract: In a process collaboration, changes rarely confine themselves to a single company, but can spread over the network of partners, resulting in a whole process of negotiation. This paper employs techniques from the domains of multiple criteria decision making (MCDM) and group decision to deal with change negotiation in process collaborations. In particular, it utilizes multi-criteria reasoning to model preferences of collaborators over different criteria. A particular issue in this context is scaling since in a collaboration of heterogeneous partners, identical outcomes might have different meanings for partners. A role-play experiment has been conducted with students from computer science and business administration in order to simulate change negotiation using realistic process collaboration scenarios. The experiment results have been analyzed and in turn, compared to the different normative solutions, representing various approaches to fairness and efficiency of group solutions.