Abstract: Enterprise information systems are increasingly being conceived as a combination of existing systems and to work as a part of an ecosystem of software products. This change demands methods and tools to deal with the challenging semantic interoperability issues. OntoUML is a well-founded modeling language that allows modelers to formalize world-views in a technologically neutral way, aiding in the solution of such interoperability challenges. In this paper, we present an overview of the OntoUML Lightweight Editor (OLED), our model-based environment to build, evaluate and implement OntoUML models, alongside with its main features and application scenarios.

Abstract: The rise of micro services as architectural pattern creates a bunch of interesting opportunities for software architectures of modelling editors and additional services. Main advantages are the scalability in collaborative distributed scenarios and enhanced possibilities regarding service development and operation. Throughout this article, we will illustrate how modelling editors and additional services can be build based on micro services. Our tooling will focus on business process modelling. We will also strive to highlight how architectures of this kind can enact collaborative modelling techniques, increase reuse of utilized service components and improve their integration into lightweight user interfaces, for example in mobile devices.

Abstract: Over the past few years, cloud computing has been more and more attractive as a new computing paradigm due to high flexibility for provisioning on-demand computing resources that are used as services through the Internet. In cloud computing, the unique characteristics in cloud services such as dynamic and diverse services offered at different levels, together with the lack of standardized description languages pose significant challenges for effective cloud service discovery. In this paper, we propose a cloud service search engine that exploits a novel ontology-based technique for identifying cloud service categories to improve the accuracy of cloud services searching in real environments. Our approach has the capability to automatically identify and categorize cloud services by detecting cloud service concepts from cloud service sources. Initially, we focus on building the cloud service ontology by using NIST (US National Institute of Standards and Technology). Then, we utilize our cloud service categorization method to investigate cloud service ontology's concepts in a real-world cloud services dataset which contains the metadata of 5,883 real cloud services. After that, we generate cloud service clusters by using cosine similarity to build the cloud service categorization. Our cloud service categorization is helpful in determining whether a given web source is a cloud service. Furthermore, the new web resource which has been categorized as a cloud service can be used to boost knowledge of cloud service categorization cumulatively. The proposed approach is validated by using real-world cloud services available on the World Wide Web and the experimental results show the effectiveness of the approach in cloud service discovery.

Abstract: Social media crises pose significant challenges for organizations in terms of their rapid propagation and deterioration of brand parameters and can have sustained negative business impacts. This paper reports a multiple case study of four different corporate social media crises. The multiple case study was informed by crisis communication and management theories and employed multiple methods consisting of the novel approach to big social data analytics-social set analysis, nenography, and manual sentiment analysis and topic discovery. Empirical findings show the voluminous but also transient nature of social media crises, reveal the different strategies employed by the organizations to manage the crises and their outcomes, and a diversity of aggregate user behavioural patterns. Based on the findings, we recommend that companies should choose a response strategy that is suitable for the type of crisis they are experiencing as well as the industry sector they belong to. In summary, this paper is the first demonstration of the suitability and effectiveness of Social Set Analysis for conceptualizing, formalizing and analyzing big social data from content-driven social media platforms like Facebook for event studies such as unexpected crises and/or coordinated marketing campaigns.

Abstract: In the past few years several business process compliance frameworks based on temporal logic have been proposed. In this paper we investigate whether the use of temporal logic is suitable for the task at hand: namely to check whether the specifications of a business process are compatible with the formalisation of the norms regulating the business process. We provide an example inspired by real life norms where the use of linear temporal logic produces a result that is not compatible with the legal understanding of the norms in the example.

Abstract: Enterprise Architecture (EA) is an approach where models of an enterprise are used for decision support. An important part of EA is enterprise IT architecture. Creating models of both types can be a complex task. EA can be difficult to model due to unavailable business data, while in the case of enterprise IT architecture, there can be too much IT data available. Furthermore, there is a trend of a growing availability of data possibly useful for modeling. We call the process of making use of available data, automatic modeling. There have been previous attempts to achieve automatic model creation using a single source of data. Often, a single source of data is not enough to create the models required. In this paper we address automatic modeling when data from multiple heterogeneous sources are needed. The paper looks at the potential data sources, requirements that the data must meet and proposes a four-part approach. The approach is tested in a study using the Cyber Security Modeling Language in order to model a lab setup at KTH Royal Institute of Technology. The lab aims at mirroring a small power utility's IT setup. The paper demonstrates that it is possible to create timely and scalable enterprise IT architecture models from multiple sources, and that manual modeling and data quality related problems can be resolved using known data processing methods.

Abstract: We present a methodology to extract legal norms from regulatory documents for their formalisation and later compliance checking. The need for the methodology is motivated from the shortcomings of existing approaches where the rule type and process aspects relevant to the rules are largely overlook. The methodology incorporates the well -- known IF. THEN structure extended with the process aspect and rule type, and guides how to properly extract the conditions and logical structure of the legal rules for reasoning and modelling of obligations for compliance checking.

Abstract: Strategic planning aims at improving both the financial and behavioral performance of an enterprise. It concerns the enterprise and its desired future, helping set priorities, concentrate capabilities and resources on key operations, ensure that stakeholders are working toward common goals and assess and adjust the enterprise's direction. Although it motivates and drives Enterprise Architecture (EA) choices, strategic planning is currently not explicitly reflected in EA models. This paper addresses this gap by presenting a principled approach to support strategic planning modeling in EA. We first analyze the strategic planning literature, developing a conceptual model for strategic planning that is aligned with a foundational ontology. We then propose a language metamodel that incorporates the conceptual model into the Archi Mate modeling language. In order to show the usefulness of our approach, we use our proposed language constructs to model the strategic plan of a medium-to-large pension fund.

Abstract: Monitoring the performances of a business process is a key issue in many organizations, especially when predefined constraints exist on them, due to contracts or internal requirements. Several approaches were defined recently in the literature for predicting the performances of a single process instance. However, in many real situations, process-oriented performance metrics and associated constraints are defined in an aggregated form, on a time-window basis. This work right addresses the problem of predicting whether (the process instances in) each time window will infringe an aggregate performance constraint, at a series of checkpoints within the window. To this end, at each checkpoint, three kinds of measures are to be estimated: what performance outcome each ongoing process instance will yield, how many process instances will start in the rest of the window, and what their aggregate performance outcomes will be. The approach proposed is general (it can reuse a wide range of regression methods), and it can be embedded in a continuous monitoring-and-learning scheme. Tests on real-life logs showed its validity in terms of prediction accuracy.

Abstract: Conceptualizing the organizational structure domain requires considering multiple levels of classification, with both types and types of types included in the domain of enquiry (e.g., Types of organizational units and particular organizational units). In this paper we propose a semantic foundation for the organizational structure domain that is capable to address the multi-level modeling issues. We present a core organizational structure ontology built with the combination of a foundational ontology (UFO) and a multi-level modeling theory (MLT). This ontology serves to provide semantic foundations for enterprise modeling languages but also as a basis for the development of enterprise-specific ontologies. We discuss our contributions with respect to existing multi-level modeling approaches and with respect to a number of prominent enterprise modeling frameworks, languages and enterprise ontologies.

Abstract: Due to the global digitalization, fast shifting business models and short technology lifecycles, modern enterprises need a strategy how to deal with those unpredictable changes in order to stay competitive. The concept of capability driven management like capability-based-planning or investment gets more and more attention by executives and scientists. In the last decade IS and management journals as well as conferences were publishing an increasing number of capability related articles, but a common understanding corresponding the identification of capabilities, their management, types or elements seems to be not existing. This work encapsulates the body of capability literature to provide an overview about capability research investigations over the last 15 years.

Abstract: The operational support of knowledge-intensive business processes constitutes a big challenge. In particular, these processes are driven by knowledge workers utilizing their skills, experiences, and expertise. Regarding coordination and synchronization, in turn, knowledge workers still rely on simple task lists (e.g., To-do lists or checklists) and established communication software (e.g., email). While these means are prevalent and intuitive, they are ineffective and error-prone as well. Neither tasks are made explicit, synchronized, personalized, nor are they independent from media breaks. Most important, a task management lifecycle is not provided, i.e., The efforts and knowledge invested by the knowledge workers in task management are not preserved for comparable future endeavors. This work introduces the pro Collab approach proposing a systematic and lifecycle-based task management support for knowledge workers. To establish a sound task management lifecycle, in particular, we apply process mining to analyze knowledge workers' changes applied to task lists in order to derive optimizations task list templates. To demonstrate feasibility and benefits, a proof-of-concept prototype was developed and applied. Overall, the integrated, systematic and lifecycle-based task management support is prerequisite for the effective IT support of KiBPs.

Abstract: Over the years, different development waves have shaped the Web. Introduced as a tool to browse Web sites, the Web now is a dynamic and robust platform upon which enterprises conduct e-Business. One of these waves known as Web 2.0 (or social Web) is putting pressure on how enterprises should ensure a productive use of Web 2.0 applications such as Facebook and Twitter. Misuse cases of these applications are on the rise and the lack of guidelines and awareness is a main reason. This paper presents an approach for "controlling" the social actions that Web 2.0 applications allow users to execute. These actions are identified after analyzing some representative Web 2.0 applications and then defined in terms of stakeholders, content, and tools. The control over these actions is defined with UML Object Constraint Language (OCL) and then demonstrated through a prototype system.

Abstract: Enterprise agility, generally defined as the ability of an enterprise to detect and respond to changes timely and effectively, is a core imperative for effective change management and optimal performance in contemporary enterprises. It can improve operational efficiency, and enhance competitive ability. At the same time, it is elusive, challenging, and difficult to achieve. A data centric approach can support change management process by providing an avenue to capture, store, and manage information, activities, and knowledge relating to changes. In addition, it can provide an avenue for re-using previous (successful) change management strategies to adapt to similar changes in the future. In this paper, we examine change management concepts and requirements, integrate them into a conceptual data model. To demonstrate utility of this data model, we apply it to real world industry case study. Results show that this approach can be useful to enterprise change management by providing information and intelligence to support change management decisions.

Abstract: During the last years, several enterprise modeling languages became de-facto standards in their particular field of application. This dissemination increased the need for extending these languages in order to both specify concepts domain-specifically and integrate additional concepts. However, only the minority of enterprise modeling languages provides an extension mechanism and even those defining one, reveal some syntactical shortcomings. This issue can be also observed in the context of the well-known meta modeling language MOF and its correspondingly defined enterprise modeling languages like BPMN. This position paper therefore elaborates an adaptation of the profile mechanism from UML for generic extensions of meta models in the field of enterprise modeling. Therefore, the characteristics of profiling are abstracted to the meta meta model layer and comprehensively integrated within an framework for the integrated definition of meta models. The Stereotype concept is thereby applied to several parts of meta models including also aspects of the concrete syntax as well as semantics. The proposed framework serves as reference architecture for the derivation of meta modeling language specific implementations (e.g., Within MOF).

Abstract: Currently available business process monitoring solutions usually rely on applications' business logic, which hampers the separation between the business logic and the business rules. Existing solutions address the issue from only the modeling perspective at design-time. However, modern business process systems are required to be adaptive to the constant changes of the business rules at runtime. In this paper, we propose a comprehensive Model-Driven Business Process Compliance and Monitoring (MDBPCM) framework that allows for (1) Modeling and monitoring of functional and non-functional requirements of business process, (2) Compliance validation at both design and runtime, (3) Dynamic adaption of business rules, and (4) Separation of business rules and business logic. Our framework has been successfully implemented to support the design, execution and monitoring of BPEL processes.

Abstract: The proliferation of tools for different aspects of cloud resource configuration processes encourages DevOps to design end-to-end and automated configuration processes that span across a selection of best-of-breed tools. But heterogeneities among configuration knowledge representation models of such tools pose vital limitations for acquisition, discovery and curation of configuration knowledge for federated cloud application and resource requirements. We propose an embryonic data-model for representing cloud resource configuration knowledge artifacts. We also propose a rule based recommender service, which empowers (1) incremental knowledge acquisition and curation, and (2) declarative context driven knowledge recommendation. The paper describes the concepts, techniques and current implementation of the proposed system. Experiments on 36 real-life cloud resources show efficient re-use of configuration knowledge by our approach compared to traditional techniques.

Abstract: Software development faces challenges from high expectation of software qualities, complexity of software and long development cycle. While Domain Specific Modeling (DSM) is helping developers overcome many of these challenges in many domains, it is not generally applied in the computer game domain. DSM can be hard to apply in the computer game domain because of the complexity of computer game domain knowledge and the peculiarity of traditional computer game development process. Without fully understanding these issues and properly solving them, the strength of DSM approaches will be constrained and game developers will be reluctant to use DSM. In this article, we investigate the development process and explore the feasibility of fitting DSM tasks in traditional computer game development in a compact way to lower cost and improve software quality. We introduce the workflow and illustrate the usage of it by presenting a case study. Further, we discuss the benefits and costs of involving DSM solutions in computer game development. Finally, we present the limitations and future work.

Abstract: In the development of complex and large scale software systems, it is important to detect and fix the deviations of systems' behaviors at different abstraction levels in early phases. Our main focus here is the containment checking -- a special type of consistency checking -- that verifies whether the behavior (or functions) described by a low-level behavior model encompasses those specified in the high-level counterpart. As shown in our previous work, containment checking can be realized based on model checking, but not always the costly exhaustive searches employed by model checking are necessary for addressing the containment checking problem, leading to potentials for optimization. In addition, model checking and similar techniques often yield the checking results as true (satisfied) or false (unsatisfied) with error traces (e.g., Counter-examples). Unfortunately, such feedback is rather not helpful for users with limited background on the underlying formal methods to analyze and understand the causes of consistency violations. In this paper, we propose a lightweight graph-based approach for addressing the aforementioned problems of containment checking. The theoretical complexity of our approach is a cubic polynomial of the number of elements of the input behavior models. Additionally, we aim at generating feedbacks that are relevant and easy-to-understand for the stakeholders. Our approach is illustrated and evaluated on UML activity diagrams -- that are widely used for modeling behaviors of software systems -- using use cases derived from industrial scenarios.

Abstract: Efficient resource management is an important requirement for many process-oriented applications. Typically, work items are assigned to resources through their work lists. There are many reasons for reordering work items in a resource's work list. For process scheduling, for example, swapping process instances constitutes a mean to keep due times. At the same time, reducing the throughput time of the global process is typically not the primary goal. For process optimization, in turn, the implications of reordering work items on the overall temporal performance of the process might be crucial. In this paper, we investigate how reordering work items affects performance parameters that are typically associated with a first-in-first-out processing mechanism at resources. The analysis is conducted for single process tasks and for typical control flow patterns such as sequence as well as parallel and alternative branchings. It is shown that the implications on the global throughput time are less than expected, while the effects on instance based parameters strongly depend on the control-flow pattern in which the reordering mechanism is implemented. The results are supported by means of a simulation.

Abstract: In-memory databases have become a mainstay of enterprise computing offering significant performance boosts for OLAP and OLTP workloads as well as improved prospects for application integration through an efficient, shared database layer. Despite significant RaD investments into in-memory data management, limited insights are available on the impacts of middleware platforms for application integration, i.e., How they need to evolve to leverage in-memory database capabilities. This paper provides a first exposition into how in-memory databases impact Business Process Management, as a mission-critical model-driven application integration middleware. Through it, we discuss how in-memory databases will render some prevalent uses cases of BPM middleware obsolete, while opening up prospects for tighter application integration, better process automation performance and some entirely new BPM capabilities such as process-based application customization. To validate the feasibility of an in-memory BPM, we develop a surprisingly simple BPM runtime embedded into SAP HANA and providing for BPMN-based process automation capabilities.

Abstract: Insufficient data visualization in current social media tools is hampering opportunities to make effective meaning and take decisive action from social data. This paper presents the technical architecture of a prototype tool for Social Business Intelligence (SBI) under development. Adopting an Action Design Research approach, the goal of the 'Social Newsroom' is to provide practitioners with user interfaces for leveraging such affordances. The construction of specific interfaces is detailed including monitoring dashboards and insights pillars for visual analytics.

Abstract: Cloud computing has opened new horizons for organisation to meet increasing demand of computing and storage resources without huge upfront investment. Public and private Cloud infrastructures are two of the most common deployment models. Whilst public clouds led the trend of Cloud computing adoption, there is an increasing trend to build and manage private cloud infrastructures for several reasons with security, privacy, and data location management being the predominant concerns. However, there is not much guidance on building, operating, trouble-shooting, and managing a secure and scalable private cloud infrastructure, especially for public agencies. Drawing on our extensive research on architecting and implementing cloud-based systems and experience of building private cloud infrastructures using Open Source Software such as Open Stack technologies, this tutorial will discuss the architectural and technological challenges and solutions for designing and implementing cloud systems. This tutorial will provide the participants with important knowledge and understanding about the theoretical principles and practical techniques for implementing and managing secure and scalable private cloud infrastructures for business- and mission-critical systems. The presenters will also describe the technical strengths and limitations of Open Stack cloud software and its related tools for designing and implementing a dynamically reconfigurable Cloud computing infrastructure. We will share our experiences from experimentally building and evaluating private cloud infrastructures using Open Stack cloud software (such as Rack space, Mirant is Fuel, and Dev Stack), different virtualization software (such as KVM and VMware's ESXi), and bare metal provisioning tools (such as Razor and Clone Zilla). The tutorial will also share some lessons learned from a recent completed Rad project aimed at building a private cloud infrastructures using Open Stack technologies, different hypervisors, and baremetal provisioning tools. The participants will have an opportunity to get involved in practical exercises for deploying and experimenting private cloud infrastructure with Open Stack.

Abstract: Business process (or workflow) management is vital in enterprise application systems. Current workflow management systems (WfMSs) do not provide a clear separation between execution management and data management, such a lack of separation causes serious difficulties in managing data consistency and process change. This paper argues for an "execution independence" principle of isolating the two and thus their respective concerns. Following this principle, "universal artifacts" and a new conceptual architecture for WfMSs are developed, which help addressing many challenging issues in application development with the current WfMSs.

Abstract: Data visualizations play a prominent role in enterprise information systems in various flavors. Traditional bar, line, or pie charts, or timelines, heat maps, geographical maps, dashboard gauges, and complex relationship mappings are examples of visualizations that are frequently used in business application scenarios. Despite their extensive use, however, there is only few theoretic reflection on how characteristics of data visualizations can be described on an abstract level independent from concrete graphical rendering. This is an obstacle when it comes to consciously reflecting about the use of visualizations for communicating information, because in order to gain a justified understanding of what "good" and "appropriate" visualizations for specific use cases are, at least a common terminology for characteristics of different visualization types is required. This paper introduces a description mechanism for conceptual and perceptual characteristics of data visualizations, which abstracts from concrete visual characteristics, but incorporates a joint notion of the underlying conceptual information displayed by visualizations, together with perceptual qualities of the way visualizations are cognitively processed by the human mind. The suggested solution describes each visualization type as a multidimensional abstract space, with specific scale characteristics attached to each of its axes.

Abstract: In recent years, artifact-centric business process modeling is gaining momentum with its improved flexibility and extensibility. In order to support the rapid translation of the traditional activity-centric processes into this new type of processes, this paper proposes a novel approach to automatically transforming an activity-centric process model into a group of lifecycles of artifacts and their interactions, which represent the behavior of its corresponding artifact-centric process model. Algorithms on translating an activity-centric process model into a tree model, finding the dependencies between two object/artifact states based on the tree model, and synthesizing the lifecycles of artifacts have been proposed. Throughout the paper, we illustrate our approach with an order processing running scenario.

Abstract: This paper describes key modelling concepts for events, event patterns and related concepts needed to develop a distributed software framework for real-time business analytics. These concepts are specified by means of a minimal meta-model, whose implementation can enable better interoperability between different event processing systems. This in turn can support better, distributed, collaborative analytics applications in many domains. We show an implementation of our solution approach using a case study of several business analytics problems in finance.

Abstract: This paper describes work in progress on the design and implementation of an SQL-like language for performing complex queries on event streams. This language aims at providing a simple, intuitive and fully non-procedural syntax, while still preserving backwards compatibility with traditional SQL. The syntax and informal semantics of the language are introduced, multiple examples of scenarios taken from past literature are then presented, and used to compare the expressiveness and intuitiveness of the proposed language with respect to existing Complex Event Processing engines.

Abstract: In order to achieve efficiency and effectiveness gains, concepts such as standardization and automation originating in the manufacturing industry are adopted by IT service providers. ERP systems are tools to implement such concepts in manufacturing companies. This research examines if and how ERP systems are used by IT service providers. To answer this question, an interview-based exploratory multiple-case study is conducted because only very limited findings on the topic exist. Representatives of 24 IT service providers and ERP vendors were interviewed. We found that ERP systems are used by the studied companies: 21 out of 24 use ERP systems. Seven selected companies are presented in greater detail: one that doesn't use an ERP system and six that do. We describe which functional areas are covered by their ERP systems and which ones are covered by other application systems. For instance, all of the six companies use the material management module of their ERP system, but four out of five cases used a non-ERP standard application system for ticketing. Finally, we found no case that used traditional production and planning capabilities of ERP systems as suggested by previous design science work.