I urval från Stockholms universitets publikationsdatabas

• Holistic data-driven requirements elicitation in the big data era

  2022. Aron Henriksson, Jelena Zdravkovic. Software and Systems Modeling 21 (4), 1389-1410

  Artikel

  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.

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• Modeling Digital Business Ecosystems: A Systematic Literature Review

  2022. Chen Hsi Tsai, Jelena Zdravkovic, Janis Stirna. Complex Systems Informatics and Modeling Quarterly (30), 1-30

  Artikel

  The changing business landscapes urge organizations to collaborate and combine their expertise to stay competitive. Organizations establish partnerships and collaborate via the Internet, which often happens dynamically and at fast pace resulting in formation of Digital Business Ecosystems (DBEs). DBEs are complex and their management requires having explicit and up-to-date information about them. Modeling enables thorough visual analysis and facilitates the understanding and formation of DBEs. It also allows viewing DBEs through multiple perspectives, as well as exploring alternatives in the course of DBE formation or management. This systematic review aims to synthesize existing studies pertaining to Conceptual Modeling for analysis, design, and management of DBEs. A total of 94 studies were included in the review. The findings suggest that there is a scarcity of existing Conceptual Modeling methods and tools supporting DBEs. Additionally, the extensive emphasis on DBEs’ actors in modeling leads to an urgent need for the methods to be extended to support the establishment of holistic views for integrating multiple perspectives of DBEs. Future research should focus on these areas to facilitate the transformation of how organization’s collaborations are viewed – from a single-organization to a multitude of viewpoints on organizational networks of collaboration, coexistence, and competition. Such models also need to support the key features of DBEs, such as resilience and automation.

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• Data-Driven Requirements Elicitation: A Systematic Literature Review

  2021. Sachiko Lim, Aron Henriksson, Jelena Zdravkovic. SN Computer Science 2 (1)

  Artikel

  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.

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• Data-Driven Agile Requirements Elicitation through the Lenses of Situational Method Engineering

  2021. Xavier Franch (et al.). 2021 IEEE 29th International Requirements Engineering Conference (RE), 402-407

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  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.

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• A Foundation for Design, Analysis, and Management of Digital Business Ecosystem through Situational Method Engineering

  2021. Chen Hsi Tsai, Jelena Zdravkovic. The Practice of Enterprise Modeling, 134-149

  Konferens

  Digital Business Ecosystem (DBE) supports organizations to combine their expertise in a novel collaborative network through information and communications technology. Despite its beneficial aspects, a DBE is intricate and difficult to manage due to the dependent interactions and interrelationships among actors. Modelling, as a proven way to deal with complex problems in organisational settings, can support the capturing and documenting of a DBE. This can enhance the level of abstraction of the DBE to aid the analysis and decision-making. However, current scientific literature shows a lack of methodological guidance for modelling in support of the analysis, design, and management of DBEs. Hence, in this study, we have proposed a foundation for a DBE design, analysis, and management method based on Situational Method Engineering (SME). Using the requirements empirically collected from a number of industrial practitioners and experts, the main concepts and intentions relevant to DBE design, analysis and management were defined. Based on them, using the SME approach, we modelled and presented several method process parts that layout fulfilment of the intentions for the concepts’ development using different, situation-related, strategies (i.e. method chunks).

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• A Data-Driven Framework for Automated Requirements Elicitation from Heterogeneous Digital Sources

  2020. Aron Henriksson, Jelena Zdravkovic. The Practice of Enterprise Modeling, 351-365

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  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.

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• A Survey of Roles and Responsibilities in Digital Business Ecosystems

  2020. Chen Hsi Tsai, Jelena Zdravkovic. Proceedings of the Forum at Practice of Enterprise Modeling 2020 co-located with the 13th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling (PoEM 2020), 44-53

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  Digital Business Ecosystem is an emerging phenomenon aimed to reflect the behavior of natural ecosystems as a networked and online business model involving heterogeneous actors being engaged in a shared business vision and its implementation. Such as in an ecosystem, in a DBE, the actors are highly dependent on each other in terms of their capabilities and resources. It is, therefore, one of the essential needs for the research on DBEs to advance in understanding of which roles and responsibilities are entailed in enabling a DBE to function and sustain on a long-term basis. We have, in this study, performed a survey on the existing scientific studies related to the roles within DBEs, classified the collected results, and integrated them to a unified proposal. Using a recently developed and functioning DBE concerning the improvement of preventive healthcare by provisioning, exchanging, and using of a set of relevant resources, we have presented an initial validation of the correctness and fit of the proposal for the roles of actors and their responsibilities.

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• Using Open Data to Support Organizational Capabilities in Dynamic Business Contexts

  2018. Jelena Zdravkovic, Janis Kampars, Janis Stirna. Advanced Information Systems Engineering Workshops: CAiSE 2018, 28-39

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  In essence, Open Data (OD) is the information available in a machine-readable format and without restrictions on the permissions for using or distributing it. Open Data may include textual artifacts, or non-textual, such as images, maps, scientific formulas, and other. The data can be publicized and maintained by different entities, both public and private. The data are often federated, meaning that various data sources are aggregated in data sets at a single “online” location. Despite its power to distribute free knowledge, OD initiatives face some important challenges related to its growth. In this paper, we consider one of them, namely, the business and technical concerns of OD clients that would make them able to utilize Open Data in their enterprise information systems and thus benefit in terms of improvements of their service and products in continuous and sustainable ways. Formally, we describe these concerns by means of high-level requirements and guidelines for development and run-time monitoring of IT-supported business capabilities, which should be able to consume Open Data, as well as able to adjust when the data updates based on a situational change. We illustrated our theoretical proposal by applying it on the service concerning regional roads maintenance in Latvia.

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• Modelling Business Capabilities and Context Dependent Delivery by Cloud Service

  2013. Jelena Zdravkovic (et al.). Advanced Information Systems Engineering, 369-383

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  Contemporary business environments are changing rapidly, organizations are global, and cloud-based services have become a norm. Enterprises operating in these conditions need to have the capability to deliver their business in a variety of business contexts. Capability delivery thus has to be monitored and adjusted. Current Enterprise Modeling approaches do not address context-dependent capability design and do not explicitly support runtime adjustments. To address this challenge, a capability-driven approach is proposed to model business capabilities by using EM techniques, and to use model-based patterns to describe how software applications can adhere to changes in the execution context. A meta-model for capability design and delivery is presented with the consideration to delivering solutions as cloud services. The proposal is illustrated with an example case from an energy efficiency project. A supporting architecture for the capability development and the delivery in the cloud is also presented.

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• Capturing consumer preferences as requirements for software product lines

  2015. Jelena Zdravkovic, Eric-Oluf Svee, Constantinos Giannoulis. Requirements Engineering 20 (1), 71-90

  Artikel

  Delivering great consumer experiences in competitive market conditions requires software vendors to move away from traditional modes of thinking to an outside- in perspective, one that shifts their business to becoming consumer-centric. Requirements engineers operating in these conditions thus need new means to both capture real preferences of consumers and then relate them to requirements for software customized in different ways to fit anyone. Additionally, because system development models require inputs that are more concrete than abstract, the indistinct values of consumers need to be classified and formalized. To address this challenge, this study aims to establish a conceptual link between preferences of consumers and system requirements, using software product line (SPL) as a means for systematically accommodating the variations within the preferences. The novelty of this study is a conceptual model of consumer preference, which integrates generic value frameworks from both psychology and marketing, and a method for its transformation to requirements for SPL using a goal-oriented RE framework as the mediator. The presented artifacts are grounded in an empirical study related to the development of a system for online education.

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• Towards Data-Driven Capability Interface

  2019. Jelena Zdravkovic, Janis Stirna. IFAC-PapersOnLine 52 (13), 1126-1131

  Artikel

  In computing, interface is the notion used for exposing the business logic of a software component for consumption. The interface of a component is deliberately defined separately from the component’s implementation to define entry points, and at the same time prevent access to the component’s internal resources and logic. Another advantage is that replacing the implementation of one component with another that has a same interface enables continuous consumption because how a component internally meets the requirements of the interface is irrelevant to its consumer. This paper investigates the possibilities to introduce the notion of interface in capability-oriented IS engineering. Capability Driven Development (CDD) is an example of a methodological approach for configuring dynamic, context aware, re-deployable business capabilities on top of existing enterprise information systems to enable continuous delivery of business for varying situational contexts. CDD relies on capability as the central component that integrates other elements of organizational design such as goals, KPIs, context information, processes, resources, and software services. These elements produce and use lot of different data, internal as well as external. In order to facilitate the uptake and use of capabilities, most of the necessary data should be made available for the use by the consumers of the capability. In this study, we provide an initial view on how the data interface of the capability component should be defined. The proposal is illustrated on the service concerning a regional roads maintenance.

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