This book constitutes the refereed proceedings of the 42nd International Conference on Conceptual Modeling, ER 2023, held in Lisbon, Portugal, during November 6-9, 2023. The 21 full papers were carefully reviewed and selected from 121 submissions. Additionally, the book contains 4 keynote speeches and 3 tutorials, and one invited paper corresponding to one of the keynote speeches.
Business modelling can be used as a starting point for business analysis. The core of a business model is information about resources, events, agents, and their relations. The motivation of a business model can be found in the goals of an enterprise and those are made explicit in a goal model. This paper discusses the alignment of business models with goal models and proposes a method for constructing business models based on goal models. The method assists in the design of business models that conform to the explicit goals of an enterprise. Main benefits are clear and uniform goal formulations, well founded business model designs, and increased traceability between models.
The EMMSAD (Exploring Modeling Methods for Systems Analysis and Development) conference series organized 24 events from 1996 to 2019, associated with CAiSE (Conference on Advanced Information Systems Engineering). From 2009, EMMSAD has become a two-days working conference. From 2017, EMMSAD best papers are invited to submit extended versions for considering their publication in the Journal of Software and Systems Modeling (SoSyM). The main topics of the EMMSAD series have the focus on models and modeling methods for software and information systems development, requirements engineering, enterprise modeling and architecture, and business process management. The conference further addresses evaluation of modeling methods through a variety of empirical and nonempirical approaches.
The need for organizations to operate in changing environments is addressed by proposing an approach that integrates organizational development with information system (IS) development taking into account changes in the application context of the solution. This is referred to as Capability Driven Development (CDD). A meta-model representing business and IS designs consisting of goals, key performance indicators, capabilities, context and capability delivery patterns, is being proposed. The use of themeta-model is validated in three industrial case studies as part of an ongoing collaboration project, whereas one case is presented in the paper. Issues related to the use of the CDD approach, namely, CDD methodology and tool support are also discussed.
This short paper examines the concept of cyber resilience from an organizational perspective. Cyber resilience is defined as “the ability to continuously deliver the intended outcome despite adverse cyber events”, and this definition is systematically described and justified. The fundamental building blocks of cyber resilience are identified and analyzed through the contrasting of cyber resilience against cybersecurity with regards to five central characteristics.
Artificial Intelligence (AI) continuously paves its way into even the most traditional business domains. This particularly applies to data-driven AI, like machine learning (ML). Several data-driven approaches like CRISP-DM and KKD exist that help develop and engineer new ML-enhanced solutions. A new breed of approaches, often called canvas-driven or visual ideation approaches, extend the scope by a perspective on the business value an ML-enhanced solution shall enable. In this paper, we reflect on two recent ML projects. We show that the data-driven and canvas-driven approaches cover only some necessary information for developing and operating ML-enhanced solutions. Consequently, we propose to put ML into an enterprise context for which we sketch a first framework and spark the role enterprise modeling can play.
The CaaS project will elaborate the Capability Driven Development (CDD) approach that will allow digital enterprises to exploit the notion of 'capability' as a means of both designing for services and with services. This deliverable defines an initial set of requirements for CDD. These requirements are provided by the industrial partners through exploration of their use cases. The goal of this deliverable is to identify potential benefits that the CaaS approach could bring to the use cases as well the features to be included the CDD methodology. The requirements are elicited from the use case partners during semi-structured interviews. They are documented in a form of goal models, actor models and concept models for each partner separately. Information documented in these models is used to define envisioned capabilities to be design and delivered during the project as well as to establish the scope of each use case. The use case scope definition focuses on use case goals, causes of capability delivery variability, capability delivery context, functions to be provided in the use case as well as potential capability delivery adjustments. The use case specific models are combined together to obtain a preliminary set of general requirements for CDD. These requirements show CDD goals, types of stakeholders, types of context and types of adjustments. The deliverable ends with concluding remarks about the partners’ expectations for CDD. The requirements for the use cases described in this deliverable will be further elaborated in the final requirements document deliverable D1.4 and will be iteratively refined during the use case elaboration performed in work packages WP2, WP3 and WP4.
This issue is following the 14th International Conference on Research Challenges in Information Science (RCIS’20) that was held 22–25 September 2020 in an online fashion, organized by the University of Cyprus. Since its foundation, RCIS aims to bring together researchers and practitioners from a wide range of information science fields and to provide opportunities for knowledge sharing and dissemination. The scope of RCIS 2020 is summarized by the following 8 thematic areas:(i) information systems and their engineering;(ii) user-oriented approaches;(iii) data and information management;(iv) business process management;(v) domain-specific information systems engineering;(vi) data science;(vii) information infrastructures; and (viii) reflective research and practice. The theme of the 2020 edition was Information Science in the Days of Artificial Intelligence.
This book constitutes the proceedings of the 14th International Conference on Research Challenges in Information Sciences, RCIS 2020, held in Limassol, Cyprus, during September 23-25, 2020. The conference was originally scheduled in for 2020, but the organizing committee was forced to postpone the conference due to the outbreak of the COVID-19 pandemic. The scope of RCIS 2020 is summarized by the thematic areas of information systems and their engineering; user-oriented approaches; data and information management; business process management; domain-specific information systems engineering; data science; information infrastructures, and reflective research and practice. The 26 full papers and 3 work in progress papers presented in this volume were carefully reviewed and selected from 106 submissions. They were organized in topical sections named: Data Analytics and Business Intelligence; Digital Enterprise and Technologies; Human Factors in Information Systems; Information Systems Development and Testing; Machine Learning and Text Processing; and Security and Privacy. The volume also contains 12 poster and demo-papers, and 4 Doctoral Consortium papers.
The success of process-aware information systems and web services heavily depends on their ability to work as catalysts for the business values that are being exchanged in a business model. The motivation of a business model can be found in the goals of an enterprise which are made explicit in a goal model. From the IT perspective, goal and business models form part of a chain of models, ending with an information system model. Thereby, analyzing and establishing the alignment of business models with goal models is a starting task on the way to a business-aware information system. This paper discusses the alignment of value-based business models with system-oriented goal models. The result is a set of transformation rules between the two models. A case study from the health sector is used to argument the way we ground and apply our contribution.
Competitiveness and growth on an international market is for many businesses tightly coupled to their ability of quickly implementing new company strategies, business services and products or market entries. Capability management is among the approaches proposed to tackle these challenges. A feature is capturing the context of capability delivery and providing mechanisms for configuring the delivery. Among the work on capability management is the capability-driven design and delivery (CDD) approach that has been proposed by the EU-FP7 project CaaS. The aim of this paper is to contribute to CDD by (i) introducing different strategies for capability modelling, (ii) elaborating on the differences between these strategies, and (iii) contributing to an understanding of what strategy should be used under what preconditions. The paper addresses these aspects by describing the strategies and initial experiences gathered with them.
Ubiquitous digitalization has led to the continuous generation of large amounts of digital data, both in organizations and in society at large. In the requirements engineering community, there has been a growing interest in considering digital data as new sources for requirements elicitation, in addition to stake-holders. The volume, dynamics, and variety of data makes iterative requirements elicitation increasingly continuous, but also unstructured and complex, which current agile methods are unable to consider and manage in a systematic and efficient manner. There is also the need to support software evolution by enabling a synergy of stakeholder-driven requirements elicitation and management with data-driven approaches. In this study, we propose extension of agile requirements elicitation by applying situational method engineering. The research is grounded on two studies in the business domains of video games and online banking.
Alignment between business strategies and the resources engaged ensuring their realization, has been a continuous concern of enterprises of all kinds in last few decades. Commonly, enterprises fail to establish the traceability from business strategies towards operational tasks carried by employees. From the requirements engineering perspective this problem leads also to a misalignment between business and IT assets. In this study, we argue that for communicating high-level intentions and strategies down to the operational perspective, i.e. tasks and resources, the core necessity is to have a rich and well-defined language for modeling business strategies. Such a language could be further utilized for facilitating formalizations and a constructive analysis of high-level business aspects of enterprises, as well for comparing and unifying existing intentional modeling languages from the business and requirements engineering domains. As a reference proposal for formalizing business strategies, we consider the well-established strategy maps [1] from the Management Information Systems community which provide textual concepts of strategy-related notions establishing causal relationships between them. We have set an effort to formalize strategy maps in the form of a meta-model, usage scenarios and constraints, providing a systematic basis for obtaining a unified language/ontology for business strategy modeling.
Business strategy is aimed to support the vision of an enterprise, by paving the way to achieve it through goals that direct the strategy's execution. However, there is a lack of means to establish and assess the alignment of business strategy and goal oriented requirements engineering. The objective of our ongoing research is to model business strategy in order to establish well-defined and traceable links with system requirements. In this paper, we propose a business strategy meta-model for Strategy maps and Balanced Scorecards. The validity of the meta-model is tested through a case scenario using OWL and Telos.
Business strategy aims at supporting the vision of an enterprise, by paving the way to achieve it through goals that direct the strategy’s execution. Aligning business strategy to system requirements requires explicit models from both business strategy and requirements engineering. However, existing business strategy definition approaches are informal and their syntax is based on natural language, therefore, they cannot be used in model-driven alignment. An objective of our research is to define a well-structured business strategy modeling language. In this paper, we propose a business strategy meta-model based on Porter’s work on competition driven strategy and its extension by Stabell and Fjeldstad. Our UML meta-model is formalized in Telos and OWL. An initial validation is performed by instantiating the meta-model using a case scenario.
A core concern within Business-IT alignment is coordinating strategic initiatives and plans with Information Systems (IS). Substantial work has been done on linking strategy to requirements for IS development, but it has usually been focused on the core value exchanges offered by the business, and thus overlooking other aspects that influence the implementation of strategy. One of these, consumer preferences, has been proven to influence the successful provisioning of the business's customer value proposition, and this study aims to establish a conceptual link between both strategy and consumer preferences to system requirements. The core contention is that reflecting consumer preferences through business strategy in system requirements allows for the development of aligned systems, and therefore systems that better support a consumer orientation. The contribution of this paper is an approach to establish such alignment, with this being accomplished through the proposal of a consumer preference meta-model mapped to a business strategy meta-model further linked to a system requirements technique. The validity of this proposal is demonstrated through a case study carried out within an institution of higher education in Sweden.
An important topic in the modeling for IS development concerns quality of obtained models, especially when these models are to be used in global scopes, or as references. So far, a number of model quality frameworks have been established to assess relevant criteria such as completeness, clarity, modularity, or generality. In this study we take a look at how a research process contributes to the characteristics of a model produced during that process. For example: what should be observed; what research methods should be selected and how should they be applied; what kind of results should be expected; how they should be evaluated, etc. We report a result on this concern by presenting how we applied Design Science Research to model business strategy.
Business Strategy encapsulates an organisation's intentions towards the achievement of its vision. As such, business strategy frames the overarching business roadmap towards the accomplishment of strate- gic goals driven by competition, by own capabilities, or by innovation. Consequently, such a roadmap needs to be considered when building systems aimed at supporting the functionality of an enterprise. Intro- ducing business strategy to system's design using models facilitates the propagation of strategic notions to development techniques and methods. This study focuses on bringing a business strategy formulation driven by innovation into system requirements; specically, relating Blue Ocean Strategy to the notions of i*, an established goal modeling technique within requirements engineering.
Current advancements in the business arena necessitate more than ever before the alignment of The Business and IT in organizations, which has been acknowledged as a complex issue to address. Our research is aimed at systematically addressing the linkage between business strategy and information systems (IS). We propose a model-driven approach for alignment, by leveraging the influence of established business strategy formulations from Strategic Management, and model-driven principles used within IS. The objective of this paper is to present the results of an empirical investigation carried out in Sweden on the linkage seeking to obtain insights from practitioners about the relevance of the problem, as well as of our model-driven proposal to address it.
Aligning business strategy to enterprise models requires explicit models from both areas, mapped to each other. Mapping existing business strategy definition approaches to requirement engineering practices improves strategy dissemination towards development. In this paper we present an illustration of such a mapping using the Strategy Maps and Balanced Scorecards as a business strategy approach and iStar (i*) as a requirements engineering practice exemplified using a case scenario.
IT pervades all sectors of today's organizations. To support efficient business solutions, business-IT alignment has been long-time discussed as a solution. Given the complexity of achieving alignment, in our research we have hypothesized the importance of one partial possible solution, namely, the fit between strategy and information system requirements. To systematically investigate the influence of widely-used business strategy formulations, such as Porter’s Value Chain, Kaplan & Norton’s Strategy Maps, and others, we propose a model-centric approach to strategy-IT alignment where the strategy formulations are represented in the form of models, and mapped to requirements models. The objective of this paper is to present a pilot empirical investigation assessing if strategy-IT alignment is an issue of concern, and seeking to obtain insights from practitioners about relevance of our modelbased view for strategy-IT alignment. The empirical information is collected through a well-prepared questionnaire-based survey.
Business strategy should be well understood in order to support an enterprise to achieve its vision and to define an architecture supporting that vision. While business views are identified in many Enterprise Architecture (EA) proposals, business strategy formulations from the area of Strategic Management are overlooked. Thus, IT solutions cannot be traced back to business strategy in a clear and unambiguous way. Our intended proposal, a Unified Business Strategy Meta-Model (UBSMM), aims at establishing such a link. UBSMM is a formalization of the integration of known business strategy formulations with precise semantics enabling its model-level usage to provide strategic awareness to Enterprise Architecture. In this paper we present the development process of UBSMM, and further, we propose conceptual relationships towards Enterprise Architecture (EA).
A gap in the alignment of business and IT lies between strategy and IS, despite the advancements of enterprise modeling. The objective of our study is to compare various enterprise modeling approaches with respect to their ability to capture and represent strategy notions. This includes identifying strategy notions from established business strategy formulations within Strategic Management, which are expressed in the Unified Business Strategy Meta Model. The interdisciplinary nature of the study constitutes a research challenge due to the significant difference on the levels of abstraction between Strategic Management and IS. To the best of our knowledge, no similar effort has been undertaken, therefore, the outcome of this study will provide the enterprise modeling community with a basis to address strategy and IS alignment linking strategic objectives and intentions to information systems.
The Capability-Driven Development (CDD) methodology supports development, delivery, and management of organization and information system capabilities. This chapter presents an overview of the CDD methodology in terms of the capability meta-model; the overall capability life cycle consisting of capability design, deployment, and feedback cycles; as well as the overall use of the CDD Environment. The way of working with CDD is illustrated with a simple example case from the travel management domain.
Information Systems (IS) of modern organizations and enterprises often rely on a network of partners’ IS to deliver the services. The resilience of this network is the necessary condition for the operation of such ISs. The Digital Business Ecosystem (DBE) theory has emerged as an approach to ensure functioning and resilience in dynamic and open networks. This paper presents three cases of analysis of resilience of DBEs. The objective of the analysis is to assess the resilience of DBEs during its design phase. During this phase, often, only structural information presented in ISs models is available. In order to assess the resilience, the DBE models are analyzed for the potential for fulfilment of typical ecosystem goals and roles. The three DBE cases analyzed are winter road maintenance, digital vaccine, and Covid-19 testing. The paper evaluates the resilience of the DBEs and formulates the practices for uncovering and strengthening it.
The overall objective of the CaaS project is to create an integrated approach consisting of methods, tools and reusable best practices that allow digital enterprises to take advantage of changes in business context and technologies. This deliverable primarily contributes to CaaS Objective 1, namely, “to elaborate a methodology and supporting methods for Capability Driven Development (CDD) which is adopted by the industrial partners involved in the project and their customers”. To this end the deliverable presents the final version of the CDD methodology, which consists of a number of method components supporting different aspects of the CDD process. More specifically, methodology components addressing capability design, enterprise and business process modelling, context modelling, supporting reuse, as well as adjusting capability delivery at run-time have been developed. Furthermore, there is a method component supporting the decision making about whether or not CDD is suitable and how to get started. The methodology also includes method extensions for specific application domains, namely business process outsourcing, collaborative software development and project management office. The deliverable reflects the modular and incremental approach to methodology engineering and documentation in CaaS, which is manifested in the methodology components and extensions. The modularity allows for the users to focus only on those parts of the methodology that are needed for their work. The CDD methodology is described from three conceptual aspects – (1) The modelling languages in terms of concepts and notations used to represent the modelling product, i.e. the models and capability designs created. (2) The way of working, the procedures and tools used, in order to arrive at a capability design that fits organization’s needs, i.e. the modelling process. (3) The technical foundation and formal definition of algorithms for run-time adjustments of capabilities. The deliverable also includes extensive examples of capability design, context modelling and run-time adjustments. These examples are meant to support understanding and selection of the method components.
Capability Driven Development (CDD) is a capability-based method for developing context-aware and adaptive systems. This paper proposes to extend CDD to address security and resilience concerns in organizational networks. A method extension defining modeling concepts and development procedure is elaborated. It includes development of a data-driven digital twin, which represents the security and resilience concerns of the network and is used to diagnose security incidents and to formulate a resilient response to these incidents. Application of the proposed method extension is illustrated using examples of secure computer network governance and secure supplier onboarding.
An ICT system consists of multiple interrelated software and hardware components as well as related services. They are often produced by a complex network of suppliers the control of which is hard, time consuming and in many cases almost impossible for a single company. Hence, it is a common practice for malicious actors to target the ICT product supply chain assuming that some members have lax security practices or lag behind in terms of using the latest solutions and protocols. A single company cannot assure the security of complex ICT systems and cannot evaluate risks and therefore, to be successful it needs to tap into a wider network of ICT product developers and suppliers, which in essence leads to forming an ecosystem. We propose in this study that such an ecosystem should be established and managed on the bases of its members capabilities, which in this means capacity to meet desired goals, i.e., security and privacy requirements in a dynamic business context. The proposal is illustrated on the case of the ICT product called IoTool, which is a lightweight IoT gateway. The IoTool uses various third-party components such as sensors and actuators supplied by different vendors.
One of the key tasks of the CDD methodology concerns designing capabilities starting from existing business requirements, enterprise models, and other kinds of organizational designs. As described in this chapter, the CDD methodology contains three complementary strategies for the design of capabilities: goal-first, process-first, and concept-first strategies. The view of the goal-first strategy is that capabilities exist as means to fulfill an organization’s long-term business objectives. The process-first strategy considers that capabilities are delivered through the execution of well-established business processes and therefore should be designed based on such processes. The concept-first strategy views stable information structures as the primary means for capability design. All three strategies for capability design shares four generic phases: scoping, identification, interlinking, and contextualizing and adapting. Each phase involves the use of some of the main CDD concepts in the capability design, such as goals, processes, context elements, or delivery patterns, as well as their relationships, with the final aim to obtain a well-defined model of one or several capabilities. Documentation of capabilities designed by the strategies is supported by the CDD environment, in particular the CDT tool support, a model-driven design.
Increased digitalization and the pervasiveness of Big Data, along with vastly improved data processing capabilities, have led to the consideration of digital data as additional sources of system requirements, complementing conventional stakeholder-driven approaches. The volume, velocity and variety of these digital sources present numerous challenges which existing system development methods are unable to manage in a systematic and efficient manner. We propose a holistic and data-driven framework for continuous and automated acquisition, analysis and aggregation of heterogeneous digital sources for the purposes of requirements elicitation and management. The proposed framework includes a conceptualization in the form of a meta-model and a high-level process for its use; the framework is illustrated in a real case of an enterprise software.
Digital transformation stimulates continuous generation of large amounts of digital data, both in organizations and in society at large. As a consequence, there have been growing efforts in the Requirements Engineering community to consider digital data as sources for requirements acquisition, in addition to human stakeholders. The volume, velocity and variety of the data make requirements discovery increasingly dynamic, but also unstructured and complex, which current elicitation methods are unable to consider and manage in a systematic and efficient manner. We propose a framework, in the form of a conceptual metamodel and a method, for continuous and automated acquisition, analysis and aggregation of heterogeneous digital sources that aims to support data-driven requirements elicitation and management. The usability of the framework is partially validated by an in-depth case study from the business sector of video game development.
Deriving from diverse and vastly growing sources, digital data is emerging as the essential resource to organizations, enabling them to by enlarging their body of knowledge advance in highly demanding business situations and markets. The means enabling holistic reasoning and modeling business constellations including varieties of digital sources of data, and the ranges of different contexts covering those data are therefore a challenge in the modelling community. In this paper, we analyze the use of the core i* language for supporting modeling of context-dependent business environments where the contexts’ data is provided by digital actors. We have defined the mappings from the main concepts for the domain of the investigation (such as digital sources, context and capability) to the elements of the i* 2.0. We illustrated our proposal by applying it on the service concerning roads maintenance.
Traditional organizational structures evolve towards online business using modern IT – such as cloud computing, semantic standards, process- and service-oriented architectures. On the technology level, Web services are dominantly used for modeling the interaction points of complex Web applications. So far, development of Web services has matured on the technical perspective considering for example the development of standards for message exchanges and service coordination. However, business concepts, such as economic assets exchanged in transactions between cooperating actors, cannot be easily traced in final Web service specifications. As a consequence, business and IT models become difficult to keep aligned. To address this issue, we propose an MDD approach to elicit business services, and further software services, using REA business model as the starting point. The proposal focuses on a value-explorative elicitation of business services at the top level and model transformations, using UML 2 to the system level, by utilizing well-defined mappings.
Traditional organizational structures evolve towards online business using modern IT – such as cloud computing, semantic standards, and process- and service-oriented architectures. On the technology level, Web services are dominantly used for modeling the interaction points of complex Web applications. So far, development of Web services has matured on the technical perspective considering for example the development of standards for message exchanges and service coordination. However, business concepts, such as economic assets exchanged in transactions between cooperating actors, cannot be easily traced in final Web service specifications. As a consequence, business and IT models become difficult to keep aligned. To address this issue, the authors propose an MDD approach to elicit business services and further software services using REA business model as the starting point. The proposal focuses on a value-explorative elicitation of business services at the top level and model transformations using UML 2 to the system level by utilizing well-defined mappings.
Open Data (OD) is data available in a machine-readable format and without restrictions on the permissions for using or distributing it. OD may include textual artifacts, images, maps, video content, and other. The data can be published and maintained by different entities, both public and private. Despite its power to distribute knowledge freely and availability of a large number of datasets, OD initiatives face important challenges related to its widespread take up. More specifically, OD provisioning is based on a unidirectional linking from OD providers to OD users without considering requirements and preferences of the users. The OD users also lack metadata, and they need to develop specific technical solutions for providing a continuous OD flow and processing, which is particularly difficult when real-time OD are to be used. In this paper, we propose solving these challenges by envisioning a business ecosystem for OD. It is network-based, federated, and supports interplay between OD provisioning and knowledge management. As a methodological solution, we have applied the capability-driven development approach, which allows modeling of OD processing ecosystems, facilitates knowledge exchange about OD usage among members of the ecosystem, and supports configuring information systems for OD processing. The proposal is explicated with a theoretical study of its usability for the service of road maintenance in varying conditions.
Schema matching plays an important role in various fields of enterprise system modeling and integration, such as in databases, business intelligence, knowledge management, interoperability, and others. The matching problem relates to finding the semantic correspondences between two or more schemas. The focus of the most of the research done in schema and ontology matching is pairwise matching, where 2 schemas are compared at the time. While few semi-automatic approaches have been recently proposed in pairwise matching to involve user, current multi-schema approaches mainly rely on the use of statistical information in order to avoid user interaction, which is largely limited to parameter tuning. In this study, we propose a user-guided iterative approach for large-scale multi-schema integration. Given n schemas, the goal is to match schema elements iteratively and demonstrate that the learning approach results in improved accuracy during iterations. The research is conducted in SAP Research Karlsruhe, followed by an evaluation using large e-business schemas. The evaluation results demonstrated an improvement in accuracy of matching proposals based on user’s involvement, as well as an easier accomplishment of a unified data model.
Traditional, plan-driven, requirements engineering identifies separate phases in the process with well-documented outputs associated with of each of them. The plan-driven system development is suitable for predictable projects where all properties of the end system are known or requested from the start. In many situations, however, the properties of the final system cannot be determined on beforehand requiring thus a basic part of the system to be built fast, and further enable it to evolve. For this reason, it has become more common in recent years to adopt agile development methods, which foster interactive working with customers, in short iterations, and with frequent system changes and releases. Because the plan-driven and agile approaches substantially differ in their main concepts and working steps related to requirements engineering, and the fact that larger projects often blend them, we have identified a need for establishing relationships between them through an integrated meta-model. The final artifact contains the elements of both agile and plan-driven requirements engineering, supporting thus their separate, or hybrid use, which we have illustrated and thereby discussed and concluded this research-in-progress study.
Requirements engineering has traditionally been stakeholder-driven. In addition to domain knowledge, widespread digitalization has led to the generation of vast amounts of data (Big Data) from heterogeneous digital sources such as the Internet of Things (IoT), mobile devices, and social networks. The digital transformation has spawned new opportunities to consider such data as potentially valuable sources of requirements, although they are not intentionally created for requirements elicitation. A challenge to data-driven requirements engineering concerns the lack of methods to facilitate seamless and autonomous requirements elicitation from such dynamic and unintended digital sources. There are numerous challenges in processing the data effectively to be fully exploited in organizations. This article, thus, reviews the current state-of-the-art approaches to data-driven requirements elicitation from dynamic data sources and identifies research gaps. We obtained 1848 hits when searching six electronic databases. Through a two-level screening and a complementary forward and backward reference search, 68 papers were selected for final analysis. The results reveal that the existing automated requirements elicitation primarily focuses on utilizing human-sourced data, especially online reviews, as requirements sources, and supervised machine learning for data processing. The outcomes of automated requirements elicitation often result in mere identification and classification of requirements-related information or identification of features, without eliciting requirements in a ready-to-use form. This article highlights the need for developing methods to leverage process-mediated and machine-generated data for requirements elicitation and addressing the issues related to variety, velocity, and volume of Big Data for the efficient and effective software development and evolution.
The challenge of business and IT-alignment has been a major concern for IT managers over the last few decades, as an increased congruence between the two aspects improves effectivity and results in organizations. Enterprise Architecture (EA) addresses the alignment by providing a holistic model-based view of the organization. However, previous research has revealed some generic discrepancies in prominent EA frameworks regarding their support towards more decentralized organizational structures. Following a case study research of a federated organization this paper analyzes in depth The Open Group Architecture Framework (TOGAF) EA framework, and based on identified discrepancies how it should be extended to provide an adequate support. By enabling the establishment and maintenance of a federated EA, the proposed extension should further increase the business and IT-alignment for federated organizations.
There is a plethora of digital data sources that may be exploited for collecting requirements for system development and evolution. In contrast to human sources, i.e. stakeholders, digital sources continuously generate data that is often not originally created for the purposes of requirements elicitation, e.g. on forums, microblogs, machine-generated trace logs, and sensor data. Streams of large volumes of data can be exploited to enable automation of a continuous requirements elicitation process using AI techniques that combine natural language or machine data processing, with machine learning. On the other hand, the complex characteristics of big data due to its size, lack of structure, high dynamics, and low predictability, present numerous challenges on the process of extracting requirements-related information that would be of a clear value for companies. The purpose of this interview study was to, from the practitioners’ perspective, elicit their overall expectations and needs for a method for the elicitation of system requirements from digital data sources. Semi-structured interviews were conducted with several industrial experts from different business domains and the collected empirical data has been analyzed using thematic analysis. The results lead to the identification of a set of hig-hlevel requirements related to the method for the elicitation from digital data sources.