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This paper aims to present Long4Cloud (long-running workflows execution environment for cloud), a distributed and adaptive LRW execution environment delivered “as a service” solution.

LRWs last for hours, days or even months and their duration open the possibility of changes in business rules, service interruptions or even alterations of formal regulations of the business before the workflow completion. These events can lead to problems such as loss of intermediary results or exhaustion of computational resources used to manage the workflow execution. Existing solutions face those problems by merely allowing the replacement (at runtime) of services associated with activities of the LRW.

LONG4Cloud extends the previous works in two main aspects, namely, the inclusion of dynamic reconfiguration capabilities and the adoption of an “as a service” delivery mode. The reconfiguration mechanism uses quiescence principles, data and state management and provides multiple adaptive strategies. Long4Cloud also adopts a scenario-based analysis to decide the adaptation to be performed. Events such as changes in business rules or service failures trigger reconfigurations supported by the environment. These features have been put together in a solution delivered “as a service” that takes advantage of cloud elasticity and allows to better allocate cloud resources to fit into the demands of LRWs.

The original contribution of Long4Cloud is to incorporate adaptive capabilities into the LRW execution environment as an effective way to handle the specificities of this kind of workflow. Experiments using current data of a Brazilian health insurance company were carried out to evaluate Long4Cloud and show performance gains in the execution of LRWs submitted to the proposed environment.

The application of business process methods in the domain of disaster response management (DRM) is seen as promising approach due to the similarity of business processes and disaster response processes at the general structure and goals. But up to now only a few approaches were able to handle the special characteristics of the DRM domain. Thus, the purpose of this paper is to identify the existing approaches and analyze them for the discussion of general requirements for applying methods and tools from business process management to DRM.

A structured literature review covering a wide field of information system-related publications (conferences and journals) is used to identify and classify general requirements discussed as the state of the art.

The work in this paper resulted in a suitable classification of requirements for the development of process-oriented DRM approaches deduced from the existing work. This was used to outline and analyze the current research landscape of this topic and identify research gaps as well as existing limitations.

Although the review of the state of the art is based on a wide set of publication databases, there may exist relevant research papers which have not been taken into consideration.

The elaborated requirements provide value for both the research community and practitioners. They can be considered to develop new or improve existing DRM systems and, thus, to exploit the potentials of process-oriented IT in supporting DRM in the case of disaster.

Changing scattered and dynamic business rules in business workflow systems has become a growing problem that hinders the use and configuration of workflow-based applications. There is a gap in the existing research studies which currently focus on solutions that are application specific, without accounting for the universal logical dependencies between the business rules and, as a result, do not support adaptation of the business rules in real time. The paper aims to discuss this issue.

To tackle the above problems, this paper adopts a bottom-up approach, which puts forward a component model of the business process workflows and then adds business rules which have clear logical semantics. This allows incremental development of the workflows and semantic indexing of the rules which govern them during the initial acquisition.

The paper introduces an event-driven model for development of business workflows which is purely logic-based and can be easily implemented using an object-oriented technology, together with a model of the business rules dependencies which supports incremental semantic indexing. It also proposes a two-level inference mechanism as a vehicle for controlling the business process execution and the process of adaptation of the business rules at real time based on propagating the dependencies.

The framework is strictly logical and completely domain-independent. It allows to account both synchronous and asynchronous triggering events as well as both qualitative and quantitative description of the conditions of the rules. Although our primary interest is to apply the framework to the business processes typical in the construction industry we believe our approach has much wider potential due to its strictly logical formalization and domain independence. In fact it can be used to control any business processes where the execution is governed by rules.

The framework could be applied to both large business process modelling tasks and small but very dynamic business processes like the typical digital business processes found in online banking or e-Commerce. For example, it can be used for adjusting security policies by adding the capability to adapt automatically the access rights to account for additional resources and new channels of operation which can be very interesting ion both B2C and B2B applications.

The potential scope of the impact of the research reported here is linked to the wide applicability of rule-based systems in business. Our approach makes it possible not only to control the execution of the processes, but also to identify problems in the control policies themselves from the point of view of their logical properties – consistency, redundancies and potential gaps in the logics. In addition to this, our approach not only increases the efficiency, but also provides flexibility for adaptation of the policies in real time and increases the security of the overall control which improves the overall quality of the automation.

The major achievement reported in this paper is the construction of a universal, strictly logic-based event-driven framework for business process modelling and control, which allows purely logical analysis and adaptation of the business rules governing the business workflows through accounting their dependencies. An added value is the support for object-oriented implementation and the incremental indexing which has been possible thanks to the bottom-up approach adopted in the construction of the framework.

Most literature on workflow (WF) adaptation considered the control flow correctness like absence of dead lock, live-lock, etc. during adaptation. The data aspect of WF adaptation like data flow, database schema changes and their correctness are less studied. When the WF schema is modified, their data flow and the database schema changes. The existing approaches used for adapting these data changes in the underlying database schema are time consuming and/or affect the old data persistence. The purpose of this paper is to concern the dynamic adaptation of the WF schema and implementing its data changes in the existing database schema.

A conceptual framework developed to adapt on-the-fly, the concomitant data changes during WF adaptation. The framework consists a set of data schema compliance criteria (DSC) which identify the data changes that can be directly accommodated in the existing database schema. Data adaptation algorithm (DAA) is developed to handle the data changes that does not conform to the DSC in the existing database schema.

In this approach the existing database schema is dynamically evolved without re-creating it, after WF schema adaptation. Therefore the WF schema changes can be implemented on-the-fly without stopping the running system. It also ensures the persistence of old data residing in the existing database.

A novel approach developed to adapt the data changes in the existing database schema, without requiring recreation or migration the data. This automated consistency checking of data attribute changes in the database schema and implement them dynamically.

This paper aims to propose a service-oriented framework for performing content annotation and search, adapted to the task context. Media production workflows are becoming increasingly distributed and heterogeneous.The tasks of professionals in media production can be supported by automatic content analysis and search and retrieval services.

The processes of the framework are derived top-down, starting from business goals and scenarios in audiovisual media production. Formal models of tasks in the production workflow are defined, and business processes are derived from the task models. A software framework enabling the orchestrated execution of these models is developed.

This paper presents a framework that implements the proposed approach called Metadata Production Management Framework (MPMF). The authors show how a media production workflow for a real-world scenario is implemented using the MPMF.

The authors have demonstrated the feasibility of a model-based approach for media processing. In the reification step, there is still information that needs to be provided in addition to the task models to obtain executable processes. Future research should target the further automation of this process.

By means of this approach, the implementation of the business process defines the workflow, whereas the services that are actually used are defined by the configuration. Thus, the processes are stable and, at the same time, the services can be managed very flexibly. If necessary, service implementations can also be completely replaced by others without changing the business process implementation.

The authors introduce a model-based approach to media processing and define a reification process from business-driven task models to executable workflows. This enables a more task-oriented design of media processing workflows and adaptive use of automatic information extraction tools.

Context-awareness has emerged as an important principle in the design of flexible business processes. The goal of the research is to develop an approach to extend context-aware business process modeling toward location-awareness. The purpose of this paper is to identify and conceptualize location-dependencies in process modeling.

This paper uses a pattern-based approach to identify location-dependency in process models. The authors design specifications for these patterns. The authors present illustrative examples and evaluate the identified patterns through a literature review of published process cases.

This paper introduces location-awareness as a new perspective to extend context-awareness in BPM research, by introducing relevant location concepts such as location-awareness and location-dependencies. The authors identify five basic location-dependent control-flow patterns that can be captured in process models. And the authors identify location-dependencies in several existing case studies of business processes.

The authors focus exclusively on the control-flow perspective of process models. Further work needs to extend the research to address location-dependencies in process data or resources. Further empirical work is needed to explore determinants and consequences of the modeling of location-dependencies.

As existing literature mostly focusses on the broad context of business process, location in process modeling still is treated as “second class citizen” in theory and in practice. This paper discusses the vital role of location-dependencies within business processes. The proposed five basic location-dependent control-flow patterns are novel and useful to explain location-dependency in business process models. They provide a conceptual basis for further exploration of location-awareness in the management of business processes.

Effective translation has become essential for seamless cross-cultural communication in an era of global interconnectedness. Translation management systems (TMS) have redefined the translation landscape, revolutionizing project management and execution. This study examines the attitudes of translation agencies and professional translators towards integrating and utilizing TMS, with a specific focus on Saudi Arabia.

The study's design was based on a thorough mixed-methods strategy that purposefully combined quantitative and qualitative procedures to create an array of findings. Through a survey involving 35 participants (both project managers and professional translators) and a series of interviews, this research explores the adoption of TMS, perceived benefits, influencing factors and future considerations. This integrated approach sought to investigate the nuanced perceptions of Saudi translation companies and expert translators about TMS. By combining the strengths of quantitative data's broad scopes and qualitative insights' depth, this mixed-methods approach sought to overcome the limitations of each method, ultimately resulting in a holistic understanding of the multifaceted factors shaping attitudes within Saudi Arabia's unique translation landscape.

Based on questionnaires and interviews, the study shows that 80% of participants were familiar with TMS, and 57% had adopted it in their work. Benefits included enhanced project efficiency, collaboration and quality assurance. Factors influencing adoption encompassed cost, compatibility and resistance to change. The study further delved into participants' demographic profiles and years of experience, with a notable concentration in the 6–10 years range. TMS adoption was linked to improved translation processes, and participants expressed interest in AI integration and mobile compatibility. Deployment models favored cloud-based solutions, and compliance with industry standards was deemed vital. The findings underscore the evolving nature of TMS adoption in Saudi Arabia, with diverse attitudes shaped by cultural influences, technological compatibility and awareness.

This research provides a holistic and profound perspective on the integration of TMS, fostering a more comprehensive understanding of the opportunities, obstacles and potential pathways to success. As the translation landscape continues to evolve, the findings from this study will serve as a valuable compass guiding practitioners and researchers towards effectively harnessing the power of technology for enhanced translation outcomes.

The purpose of this paper is to investigate the feasibility of an end-to-end simplified and automated reconstruction pipeline for digital building assets using the design science research approach. Current methods to create digital assets by capturing the state of existing buildings can provide high accuracy but are time-consuming, expensive and difficult.

Using design science research, this research identifies the need for a crowdsourced and cloud-based approach to reconstruct digital building assets. The research then develops and tests a fully functional smartphone application prototype. The proposed end-to-end smartphone workflow begins with data capture and ends with user applications.

The resulting implementation can achieve a realistic three-dimensional (3D) model characterized by different typologies, minimal trade-off in accuracy and low processing costs. By crowdsourcing the images, the proposed approach can reduce costs for asset reconstruction by an estimated 93% compared to manual modeling and 80% compared to locally processed reconstruction algorithms.

The resulting implementation achieves “good enough” reconstruction of as-is 3D models with minimal tradeoffs in accuracy compared to automated approaches and 15× cost savings compared to a manual approach. Potential facility management use cases include the issue and information tracking, 3D mark-up and multi-model configurators.

Through user engagement, development, testing and validation, this work demonstrates the feasibility and impact of a novel crowdsourced and cloud-based approach for the reconstruction of digital building assets.

This paper aims to clarify how affect-based adaptation can improve implicit recognition of playing style of individuals during game sessions. This study presents the “Rush for Gold” game using dynamic difficulty adjustment of tasks based on both player performance and affectation inferred through electrodermal activity and facial expressions of the player. The game applies linear regression for calculating playing styles to be applied for achieving a style-based adaptation in other educational video games.

The experimental procedure included subject selection, demonstration, informed consent procedure, two game sessions in random order – one without and another with affective adaptation control – and post-game self-report. The experiment was conducted with participation of 30 master students and university lecturers in informatics.

This study presents experimental results concerning the impact of affective adaptation over playing style recognition, game session time, task’s effectiveness, efficiency and difficulty and, as well, player’s assessment of affectively adaptive gameplay obtained by an adaptation control panel embedded into the game and by post-game self-report.

The proposed adaptive game limits recognised styles to such based on the Kolb’s Learning Style Inventory model. Another limitation of the study is the relatively small number of participants constrained by the extended experimental procedure and the desktop game version.

The paper presents an original research on the effect of affect-based adaptation on a novel approach for implicit recognition of playing styles.

The purpose of this study is to explore how demolition contractors coordinate project activities for buildings at their end-of-life. The organizations are thereby conceptualized as information processing systems facing uncertainty.

A multiple-case study methodology was selected to gain in-depth insights from three projects with different end-of-life strategies: a faculty building (material recycling), a nursing home (component reuse) and a psychiatric hospital (element reuse). Using a theory elaboration approach, the authors sought to explain how and why demolition contractors process information for end-of-life coordination.

End-of-life strategies differ in the degree of building, workflow and environmental uncertainty posed to the demolition contractor. Whether or not a strategy is effective depends on the (mis)match between the specific levels of uncertainty and the adopted coordination mechanisms.

The explanatory account on end-of-life coordination refines information processing theory for the context of (selective) demolition projects.

The detailed case descriptions and information processing perspective enable practitioners to select, implement and reflect on coordination mechanisms for demolition/deconstruction projects at hand.

Reflecting its dual conceptual-empirical and inductive-deductive focus, this study contributes with new opportunities to explain building end-of-life coordination with a refined theory.