Data Mesh: Motivational Factors, Challenges, and Best Practices

With the increasing importance of data and artificial intelligence, organizations strive to become more data-driven. However, current data architectures are not necessarily designed to keep up with the scale and scope of data and analytics use cases. In fact, existing architectures often fail to deliver the promised value associated with them. Data mesh is a socio-technical concept that includes architectural aspects to promote data democratization and enables organizations to become truly data-driven. As the concept of data mesh is still novel, it lacks empirical insights from the field. Specifically, an understanding of the motivational factors for introducing data mesh, the associated challenges, best practices, its business impact, and potential archetypes, is missing. To address this gap, we conduct 15 semi-structured interviews with industry experts. Our results show, among other insights, that industry experts have difficulties with the transition toward federated governance associated with the data mesh concept, the shift of responsibility for the development, provision, and maintenance of data products, and the concept of a data product model. In our work, we derive multiple best practices and suggest organizations embrace elements of data fabric, observe the data product usage, create quick wins in the early phases, and favor small dedicated teams that prioritize data products. While we acknowledge that organizations need to apply best practices according to their individual needs, we also deduct two archetypes that provide suggestions in more detail. Our findings synthesize insights from industry experts and provide researchers and professionals with guidelines for the successful adoption of data mesh

SLA-Based Continuous Security Assurance in Multi-Cloud DevOps

Multi-cloud applications, i.e. those that are deployed over multiple independent Cloud providers, pose a number of challenges to the security-aware development and operation. Security assurance in such applications is hard due to the lack of insights of security controls ap- plied by Cloud providers and the need of controlling the security levels of all the components and layers at a time. This paper presents the MUSA approach to Service Level Agreement (SLA)-based continuous security assurance in multi-cloud applications. The paper details the proposed model for capturing the security controls in the o ered application Se- curity SLA and the approach to continuously monitor and asses the controls at operation phase. This new approach enables to easily align development security requirements with controls monitored at operation as well as early react at operation to any possible security incident or SLA violation.The MUSA project leading to this paper has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 644429

AN INFORMATION SYSTEM DESIGN THEORY FOR GREEN INFORMATION SYSTEMS FOR SUSTAINABILITY REPORTING - INTEGRATING THEORY WITH EVIDENCE FROM MULTIPLE CASE STUDIES

Du to increasingly noticeable environmental impacts of business activities and consequntly rising demands for environmental information by organizational stakeholders, reliable sustainability reporting (SR) is ever more important for firms. As the task of detailed sustainability reporting is complex and involves gathering and processing of a considerable amount of data, green information systems (Green IS) are seen as suitable to support this task. While some Green IS for SR are commercially available, their adoption is low. One reason is that there is a lack of knowledge of how to design these IS. This paper seeks to provide guidance for the design of Green IS for SR by suggesting an information system design theory (ISDT), which is a set of primarily prescriptive statements describing how to construct the class of Green IS for SR. Therefore, we synthesize knowledge gained from organizational and management theories with insights from 29 case studies conducted in a variety of industries. In result we derived a specific ISDT for Green IS for SR, that contributes to solve the trade-offs between environmental data transparency, complexity and data collection effort. Thus, the proposed ISDT paves the way for future improved Green IS for SR and sustainable development

Organizational Adaptation

Organizational adaptation is equivocal. On the one hand, the concept is ubiquitous in management research and acts as the glue binding together the central issues of organizational change, performance, and survival. On the other hand, it lurks around in various guises (e.g., “fit,” “alignment,” “congruence,” and “strategic change”) studied from multiple theoretical streams (e.g., behavioral, resource based, and institutional) and at different levels of analysis (e.g., organization and industry levels). In a novel approach to reviewing 443 adaptation articles that leverages both computational and hand-coded analysis, we produce an interactive visual of the themes most studied by adaptation scholars. We inductively draw out a definition of adaptation as intentional decision making undertaken by organizational members, leading to observable actions that aim to reduce the distance between an organization and its economic and institutional environments. We then review the literature across three main areas of inquiry and six theoretical perspectives that surfaced from our analysis and identify 11 difficulties that have hampered adaptation research in the past 50 years. Our review suggests ways to address these difficulties to enable future research to develop and cumulate

A formalism and method for representing and reasoning with process models authored by subject matter experts

Enabling Subject Matter Experts (SMEs) to formulate knowledge without the intervention of Knowledge Engineers (KEs) requires providing SMEs with methods and tools that abstract the underlying knowledge representation and allow them to focus on modeling activities. Bridging the gap between SME-authored models and their representation is challenging, especially in the case of complex knowledge types like processes, where aspects like frame management, data, and control flow need to be addressed. In this paper, we describe how SME-authored process models can be provided with an operational semantics and grounded in a knowledge representation language like F-logic in order to support process-related reasoning. The main results of this work include a formalism for process representation and a mechanism for automatically translating process diagrams into executable code following such formalism. From all the process models authored by SMEs during evaluation 82% were well-formed, all of which executed correctly. Additionally, the two optimizations applied to the code generation mechanism produced a performance improvement at reasoning time of 25% and 30% with respect to the base case, respectively

The Privacy Pillar -- A Conceptual Framework for Foundation Model-based Systems

AI and its relevant technologies, including machine learning, deep learning, chatbots, virtual assistants, and others, are currently undergoing a profound transformation of development and organizational processes within companies. Foundation models present both significant challenges and incredible opportunities. In this context, ensuring the quality attributes of foundation model-based systems is of paramount importance, and with a particular focus on the challenging issue of privacy due to the sensitive nature of the data and information involved. However, there is currently a lack of consensus regarding the comprehensive scope of both technical and non-technical issues that the privacy evaluation process should encompass. Additionally, there is uncertainty about which existing methods are best suited to effectively address these privacy concerns. In response to this challenge, this paper introduces a novel conceptual framework that integrates various responsible AI patterns from multiple perspectives, with the specific aim of safeguarding privacy.Comment: 10 page

Method Engineering as Design Science

In this paper, we motivate, devise, demonstrate, and evaluate an approach for the research-based development of information systems development methods (ISDMs). This approach, termed “method engineering as design science” (ME-DS), emerged from the identified need for scholars to develop ISDMs using proper research methods that meet the standards of both rigor and relevance. ISDMs occupy a position of central importance to information systems development and scholars have therefore invested extensive resources over the years in developing such methods. The method engineering (ME) discipline has developed different frameworks and methods to guide such development work and, for that purpose, they are well-suited. Still, there remains a need for applications and evaluations of ISDMs based on the demands for knowledge justification. Unfortunately, in many cases, scholars come up short with regard to how ISDMs are generated and empirically validated. While design science (DS) stresses knowledge justification, prominent DS approaches seem to be biased toward the development of IT artifacts, making this approach ill-suited for the development of method artifacts. We therefore propose eight principles that marry ME and DS, resulting in a process model with six activities to support research-based development of ISDMs. We demonstrate and evaluate ME-DS by assessing three existing research papers that propose ISDMs. These retrospectives show how ME-DS directs attention to certain aspects of the research process and provides support for future ISDM development

Towards a Virtual Collaborator in Online Collaboration from an Organizations’ Perspective

In this empiric study, we present the specifications of virtual collaboration in times of the Covid-19 pandemic in an organization that worked mostly co-located beforehand, and requirements for a virtual collaborator (VC) resulting from those specifications. Related work shows that a VCs can support virtual teams in achieving their goals and promote creative work. We extend this with insights from practice by observing creative and collaborative workshops in the automotive industry and conducting interviews with facilitators and participants of these workshops. Subsequently, we identify the challenges that participants face in virtual collaboration, and derive design guidelines for a VC to address them. Main problems arise due to the virtual interaction lacking nonverbal communication and in the preparation phase that requires more planning and effort. A VC could help by influencing group cohesion and build networks between the participants, influencing the virtual working environment as well as contributing to the contents