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Back to the future: origins and directions of the “Agile Manifesto” – views of the originators
(2018)
In 2001, seventeen professionals set up the manifesto for agile software development. They wanted to define values and basic principles for better software development. On top of brought into focus, the manifesto has been widely adopted by developers, in software-developing organizations and outside the world of IT. Agile principles and their implementation in practice have paved the way for radical new and innovative ways of software and product development. In parallel, the understanding of the manifesto’s underlying principles evolved over time. This, in turn, may affect current and future applications of agile principles. This article presents results from a survey and an interview study in collaboration with the original contributors of the manifesto for agile software development. Furthermore, it comprises the results from a workshop with one of the original authors. This publication focuses on the origins of the manifesto, the contributors’ views from today’s perspective, and their outlook on future directions. We evaluated 11 responses from the survey and 14 interviews to understand the viewpoint of the contributors. They emphasize that agile methods need to be carefully selected and agile should not be seen as a silver bullet. They underline the importance of considering the variety of different practices and methods that had an influence on the manifesto. Furthermore, they mention that people should question their current understanding of "agile" and recommend reconsidering the core ideas of the manifesto.
Context: The current transformation of automotive development towards innovation, permanent learning and adapting to changes are directing various foci on the integration of agile methods. Although, there have been efforts to apply agile methods in the automotive domain for many years, a wide-spread adoption has not yet taken place.
Goal: This study aims to gain a better understanding of the forces that prevent the adoption of agile methods.
Method: Survey based on 16 semi-structured interviews from the automotive domain. The results are analyzed by means of thematic coding.
Results: Forces that prevent agile adoption are mainly of organizational, technical and social nature and address inertia, anxiety and context factors. Key challenges in agile adoption are related to transforming organizational structures and culture, achieving faster software release cycles without loss of quality, the importance of software reuse in combination with agile practices, appropriate quality assurance measures, and the collaboration with suppliers and other disciplines such as mechanics.
Conclusion: Significant challenges are imposed by specific characteristics of the automotive domain such as high quality requirements and many interfaces to surrounding rigid and inflexible processes. Several means are identified that promise to overcome these challenges.
Context: The current situation and future scenarios of the automotive domain require a new strategy to develop high quality software in a fast pace. In the automotive domain, it is assumed that a combination of agile development practices and software product lines is beneficial, in order to be capable to handle high frequency of improvements. This assumption is based on the understanding that agile methods introduce more flexibility in short development intervals. Software product lines help to manage the high amount of variants and to improve quality by reuse of software for long term development.
Goal: This study derives a better understanding of the expected benefits for a combination. Furthermore, it identifies the automotive specific challenges that prevent the adoption of agile methods within the software product line.
Method: Survey based on 16 semi structured interviews from the automotive domain, an internal workshop with 40 participants and a discussion round on ESE congress 2016. The results are analyzed by means of thematic coding.
Context: Software product lines are widely used in automotive embedded software development. This software paradigm improves the quality of software variants by reuse. The combination of agile software development practices with software product lines promises a faster delivery of high quality software. However, the set up of an agile software product line is still challenging, especially in the automotive domain. Goal: This publication aims to evaluate to what extend agility fits to automotive product line engineering. Method: Based on previous work and two workshops, agility is mapped to software product line concerns. Results: This publication presents important principles of software product lines, and examines how agile approaches fit to those principles. Additionally, the principles are related to one of the four major concerns of software product line engineering: Business, Architecture, Process, and Organization. Conclusion: Agile software product line engineering is promising and can add value to existing development approaches. The identified commonalities and hindering factors need to be considered when defining a combined agile product line engineering approach.
Due to digitalization, constant technological progress and ever shorter product life cycles, enterprises are currently facing major challenges. In order to succeed in the market, business models have to be adapted more often and more quickly to changing market conditions than they used to be. Fast adaptability, also called agility, is a decisive competitive factor in today’s world. Because of the ever-growing IT part of products and the fact that they are manufactured using IT, changing the business model has a major impact on the enterprise architecture (EA). However, developing EAs is a very complex task, because many stakeholders with conflicting interests are involved in the decision-making process. Therefore, a lot of collaboration is required. To support organizations in developing their EA, this article introduces a novel integrative method that systematically integrates stakeholder interests into decision-making activities. By using the method, collaboration between stakeholders involved is improved by identifying points of contact between them. Furthermore, standardized activities make decision-making more transparent and comparable without limiting creativity.
Die Digitalisierung, der ständige technologische Fortschritt und immer kürzere Produktlebenszyklen stellen Unternehmen derzeit vor große Herausforderungen. Um am Markt erfolgreich zu sein, müssen Geschäftsmodelle häufiger und schneller als früher an veränderte Marktbedingungen angepasst werden. Schnelle Anpassungsfähigkeit, auch Agilität genannt, ist in der heutigen Zeit ein entscheidender Wettbewerbsfaktor. Aufgrund des ständig wachsenden IT-Anteils von Produkten und der Tatsache, dass diese mit Hilfe von IT hergestellt werden, hat die Änderung des Geschäftsmodells große Auswirkungen auf die Unternehmensarchitektur (EA). Die Entwicklung von EAs ist jedoch eine sehr komplexe Aufgabe, da viele Beteiligte mit gegensätzlichen Interessen in den Entscheidungsprozess eingebunden sind. Daher ist ein hohes Maß an Zusammenarbeit erforderlich. Um Unternehmen bei der Entwicklung ihrer EA zu unterstützen, wird in diesem Artikel eine neuartige integrative Methode vorgestellt, die die Interessen der Stakeholder systematisch in die Entscheidungsfindung einbezieht. Durch die Anwendung der Methode wird die Zusammenarbeit zwischen den beteiligten Interessengruppen verbessert, indem Berührungspunkte zwischen ihnen identifiziert werden. Darüber hinaus machen die standardisierten Aktivitäten die Entscheidungsfindung transparenter und vergleichbarer, ohne die Kreativität einzuschränken.
In times of dynamic markets, enterprises have to be agile to be able to quickly react to market influences. Due to the increasing digitization of products, the enterprise IT often is affected when business models change. Enterprise Architecture Management (EAM) targets a holistic view of the enterprise’ IT and their relations to the business. However, Enterprise Architectures (EA) are complex structures consisting of many layers, artifacts and relationships between them. Thus, analyzing EA is a very complex task for stakeholders. Visualizations are common vehicles to support analysis. However, in practice visualization capabilities lack flexibility and interactivity. A solution to improve the support of stakeholders in analyzing EAs might be the application of visual analytics. Starting from a systematic literature review, this article investigates the features of visual analytics relevant for the context of EAM.
New or adapted digital business models have huge impacts on Enterprise Architectures (EA) and require them to become more agile, flexible, and adaptable. All these changes are happening frequently and are currently not well documented. An EA consists of a lot of elements with manifold relationships between them. Thus changing the business model may have multiple impacts on other architectural elements. The EA engineering process deals with the development, change and optimization of architectural elements and their dependencies. Thus an EA provides a holistic view for both business and IT from the perspective of many stakeholders, which are involved in EA decision-making processes. Different stakeholders have specific concerns and are collaborating today in often unclear decision-making processes. In our research we are investigating information from collaborative decision-making processes to support stakeholders in taking current decisions. In addition we provide all information necessary to understand how and why decisions were taken. We are collecting the decision-related information automatically to minimize manual time intensive work as much as possible. The core contribution of our research extends a decisional metamodel, which links basic decisions with architectural elements and extends them with an associated decisional case context. Our aim is to support a new integral method for multi perspective and collaborative decision-making processes. We illustrate this by a practice-relevant decision-making scenario for Enterprise Architecture Engineering.
Companies are continuously changing their strategy, processes, and information systems to benefit from the digital transformation. Controlling the digital architecture and governance is the fundamental goal. Enterprise Governance, Risk and Compliance (GRC) systems are vital for managing digital risks threatening in modern enterprises from many different angles. The most significant constituent to GRC systems is the definition of controls that is implemented on different layers of a digital Enterprise Architecture (EA). As part of the compliant aspect of GRC, the effectiveness of these controls is assessed and reported to relevant management bodies within the enterprise. In this paper, we present a metamodel which links controls to the affected elements of a digital EA and supplies a way of expressing associated assessment techniques and results. We complement a metamodel with an expository instantiation of a control compliance cockpit in an international insurance enterprise.
Purpose
Context awareness in the operating room (OR) is important to realize targeted assistance to support actors during surgery. A situation recognition system (SRS) is used to interpret intraoperative events and derive an intraoperative situation from these. To achieve a modular system architecture, it is desirable to de-couple the SRS from other system components. This leads to the need of an interface between such an SRS and context-aware systems (CAS). This work aims to provide an open standardized interface to enable loose coupling of the SRS with varying CAS to allow vendor-independent device orchestrations.
Methods
A requirements analysis investigated limiting factors that currently prevent the integration of CAS in today's ORs. These elicited requirements enabled the selection of a suitable base architecture. We examined how to specify this architecture with the constraints of an interoperability standard. The resulting middleware was integrated into a prototypic SRS and our system for intraoperative support, the OR-Pad, as exemplary CAS for evaluating whether our solution can enable context-aware assistance during simulated orthopedical interventions.
Results
The emerging Service-oriented Device Connectivity (SDC) standard series was selected to specify and implement a middleware for providing the interpreted contextual information while the SRS and CAS are loosely coupled. The results were verified within a proof of concept study using the OR-Pad demonstration scenario. The fulfillment of the CAS’ requirements to act context-aware, conformity to the SDC standard series, and the effort for integrating the middleware in individual systems were evaluated. The semantically unambiguous encoding of contextual information depends on the further standardization process of the SDC nomenclature. The discussion of the validity of these results proved the applicability and transferability of the middleware.
Conclusion
The specified and implemented SDC-based middleware shows the feasibility of loose coupling an SRS with unknown CAS to realize context-aware assistance in the OR.
The focus of the developed maturity model was set on processes. The concept of the widespread CMM and its practices has been transferred to the perioperative domain and the concept of the new maturity model. Additional optimization goals and technological as well as networking-specific aspects enable a process- and object-focused view of the maturity model in order to ensure broad coverage of different subareas. The evaluation showed that the model is applicable to the perioperative field. Adjustments and extensions of the maturity model are future steps to improve the rating and classification of the new maturity model.
One of the key challenges for automatic assistance is the support of actors in the operating room depending on the status of the procedure. Therefore, context information collected in the operating room is used to gain knowledge about the current situation. In literature, solutions already exist for specific use cases, but it is doubtful to what extent these approaches can be transferred to other conditions. We conducted a comprehensive literature research on existing situation recognition systems for the intraoperative area, covering 274 articles and 95 cross-references published between 2010 and 2019. We contrasted and compared 58 identified approaches based on defined aspects such as used sensor data or application area. In addition, we discussed applicability and transferability. Most of the papers focus on video data for recognizing situations within laparoscopic and cataract surgeries. Not all of the approaches can be used online for real-time recognition. Using different methods, good results with recognition accuracies above 90% could be achieved. Overall, transferability is less addressed. The applicability of approaches to other circumstances seems to be possible to a limited extent. Future research should place a stronger focus on adaptability. The literature review shows differences within existing approaches for situation recognition and outlines research trends. Applicability and transferability to other conditions are less addressed in current work.
Purpose
For the modeling, execution, and control of complex, non-standardized intraoperative processes, a modeling language is needed that reflects the variability of interventions. As the established Business Process Model and Notation (BPMN) reaches its limits in terms of flexibility, the Case Management Model and Notation (CMMN) was considered as it addresses weakly structured processes.
Methods
To analyze the suitability of the modeling languages, BPMN and CMMN models of a Robot-Assisted Minimally Invasive Esophagectomy and Cochlea Implantation were derived and integrated into a situation recognition workflow. Test cases were used to contrast the differences and compare the advantages and disadvantages of the models concerning modeling, execution, and control. Furthermore, the impact on transferability was investigated.
Results
Compared to BPMN, CMMN allows flexibility for modeling intraoperative processes while remaining understandable. Although more effort and process knowledge are needed for execution and control within a situation recognition system, CMMN enables better transferability of the models and therefore the system. Concluding, CMMN should be chosen as a supplement to BPMN for flexible process parts that can only be covered insufficiently by BPMN, or otherwise as a replacement for the entire process.
Conclusion
CMMN offers the flexibility for variable, weakly structured process parts, and is thus suitable for surgical interventions. A combination of both notations could allow optimal use of their advantages and support the transferability of the situation recognition system.
Die rasante Entwicklung der Sensortechnik im Endverbraucherbereich lässt einen klinischen Nutzen der verfügbaren dezentral erhobenen Daten aus dem Patientenalltag zur Überwachung des individuellen Gesundheitszustands vermuten. Zur Überprüfung dieser Vermutung ist die Bereitstellung einer entsprechenden Plattform in den klinischen Alltag erforderlich. Hierzu wird die bwHealthApp entwickelt, mit der sowohl die aktuelle Bandbreite als auch die Evolution der Sensortechnik auf die klinische Anwendung abbildbar ist. Mit dem flexiblen Entwurf lässt sich der klinische Nutzen für die personalisierte Medizin evaluieren. Außerdem bietet die bwHealthApp einen an Machbarkeit orientierten Diskussionsbeitrag zu offenen rechtlichen, regulatorischen und ethischen Fragestellungen der Digitalisierung in der Medizin in Deutschland.
Intra-operative fluoroscopy-guided assistance system for transcatheter aortic valve implantation
(2014)
A new surgical assistance system has been developed to assist the correct positioning of the AVP during transapical TAVI. The developed assistance system automatically defines the target area for implanting the AVP under live 2-D fluoroscopy guidance. Moreover, this surgical assistance system works with low levels of contrast agent for the final deployment of AVP, reducing therefore long-term negative effects, such as renal failure in the elderly and high-risk patients.
Container virtualization evolved into a key technology for deployment automation in line with the DevOps paradigm. Whereas container management systems facilitate the deployment of cloud applications by employing container based artifacts, parts of the deployment logic have been applied before to build these artifacts. Current approaches do not integrate these two deployment phases in a comprehensive manner. Limited knowledge on application software and middleware encapsulated in container-based artifacts leads to maintainability and configuration issues. Besides, the deployment of cloud applications is based on custom orchestration solutions leading to lock in problems. In this paper, we propose a two-phase deployment method based on the TOSCA standard. We present integration concepts for TOSCA-based orchestration and deployment automation using container-based artifacts. Our two-phase deployment method enables capturing and aligning all the deployment logic related to a software release leading to better maintainability. Furthermore, we build a container management system, which is composed of a TOSCA-based orchestrator on Apache Mesos, to deploy container-based cloud applications automatically.
An important shift in software delivery is the definition of a cloud service as an independently deployable unit by following the microservices architectural style. Container virtualization facilitates development and deployment by ensuring independence from the runtime environment. Thus, cloud services are built as container based systems - a set of containers that control the lifecycle of software and middleware components. However, using containers leads to a new paradigm for service development and operation: Self service environments enable software developers to deploy and operate container based systems on their own - you build it, you run it. Following this approach, more and more operational aspects are transferred towards the responsibility of software developers. In this work, we propose a concept for self-adaptive cloud services based on container virtualization in line with the microservices architectural style and present a model-based approach that assists software developers in building these services. Based on operational models specified by developers, the mechanisms required for self-adaptation are automatically generated. As a result, each container automatically adapts itself in a reactive, decentralized manner. We evaluate a prototype which leverages the emerging TOSCA standard to specify operational behavior in a portable manner.
Parallel applications are the computational backbone of major industry trends and grand challenges in science. Whereas these applications are typically constructed for dedicated High Performance Computing clusters and supercomputers, the cloud emerges as attractive execution environment, which provides on-demand resource provisioning and a pay-per-use model. However, cloud environments require specific application properties that may restrict parallel application design. As a result, design trade-offs are required to simultaneously maximize parallel performance and benefit from cloud-specific characteristics.
In this paper, we present a novel approach to assess the cloud readiness of parallel applications based on the design decisions made. By discovering and understanding the implications of these parallel design decisions on an application’s cloud readiness, our approach supports the migration of parallel applications to the cloud.We introduce an assessment procedure, its underlying meta model, and a corresponding instantiation to structure this multi-dimensional design space. For evaluation purposes, we present an extensive case study comprising three parallel applications and discuss their cloud readiness based on our approach.
Elasticity is considered to be the most beneficial characteristic of cloud environments, which distinguishes the cloud from clusters and grids. Whereas elasticity has become mainstream for web-based, interactive applications, it is still a major research challenge how to leverage elasticity for applications from the high-performance computing (HPC) domain, which heavily rely on efficient parallel processing techniques. In this work, we specifically address the challenges of elasticity for parallel tree search applications. Well-known meta-algorithms based on this parallel processing technique include branch-and-bound and backtracking search. We show that their characteristics render static resource provisioning inappropriate and the capability of elastic scaling desirable. Moreover, we discuss how to construct an elasticity controller that reasons about the scaling behavior of a parallel system at runtime and dynamically adapts the number of processing units according to user-defined cost and efficiency thresholds. We evaluate a prototypical elasticity controller based on our findings by employing several benchmarks for parallel tree search and discuss the applicability of the proposed approach. Our experimental results show that, by means of elastic scaling, the performance can be controlled according to user-defined thresholds, which cannot be achieved with static resource provisioning.
Cloud resources can be dynamically provisioned according to application-specific requirements and are payed on a per-use basis. This gives rise to a new concept for parallel processing: Elastic parallel computations. However, it is still an open research question to which extent parallel applications can benefit from elastic scaling, which requires resource adaptation at runtime and corresponding coordination mechanisms. In this work, we analyze how to address these system-level challenges in the context of developing and operating elastic parallel tree search applications. Based on our findings, we discuss the design and implementation of TASKWORK, a cloud-aware runtime system specifically designed for elastic parallel tree search, which enables the implementation of elastic applications by means of higher-level development frameworks. We show how to implement an elastic parallel branch-and-bound application based on an exemplary development framework and report on our experimental evaluation that also considers several benchmarks for parallel tree search.
The cloud evolved into an attractive execution environment for parallel applications, which make use of compute resources to speed up the computation of large problems in science and industry. Whereas Infrastructure as a Service (IaaS) offerings have been commonly employed, more recently, serverless computing emerged as a novel cloud computing paradigm with the goal of freeing developers from resource management issues. However, as of today, serverless computing platforms are mainly used to process computations triggered by events or user requests that can be executed independently of each other and benefit from on-demand and elastic compute resources as well as per-function billing. In this work, we discuss how to employ serverless computing platforms to operate parallel applications. We specifically focus on the class of parallel task farming applications and introduce a novel approach to free developers from both parallelism and resource management issues. Our approach includes a proactive elasticity controller that adapts the physical parallelism per application run according to user-defined goals. Specifically, we show how to consider a user-defined execution time limit after which the result of the computation needs to be present while minimizing the associated monetary costs. To evaluate our concepts, we present a prototypical elastic parallel system architecture for self-tuning serverless task farming and implement two applications based on our framework. Moreover, we report on performance measurements for both applications as well as the prediction accuracy of the proposed proactive elasticity control mechanism and discuss our key findings.
The Internet of Things (IoT) is coined by many different standards, protocols, and data formats that are often not compatible to each other. Thus, the integration of different heterogeneous (IoT) components into a uniform IoT setup can be a time-consuming manual task. This lacking interoperability between IoT components has been addressed with different approaches in the past. However, only very few of these approaches rely on Machine Learning techniques. In this work, we present a new way towards IoT interoperability based on Deep Reinforcement Learning (DRL). In detail, we demonstrate that DRL algorithms, which use network architectures inspired by Natural Language Processing (NLP), can be applied to learn to control an environment by merely taking raw JSON or XML structures, which reflect the current state of the environment, as input. Applied to IoT setups, where the current state of a component is often reflected by features embedded into JSON or XML structures and exchanged via messages, our NLP DRL approach eliminates the need for feature engineering and manually written code for pre-processing of data, feature extraction, and decision making.
Background: Internationally, teledermatology has proven to be a viable alternative to conventional physical referrals. Travel cost and referral times are reduced while patient safety is preserved. Especially patients from rural areas benefit from this healthcare innovation. Despite these established facts and positive experiences from EU neighboring countries like the Netherlands or the United Kingdom, Germany has not yet implemented store-and-forward teledermatology in routine care.
Methods: The TeleDerm study will implement and evaluate store-and-forward teledermatology in 50 general practitioner (GP) practices as an alternative to conventional referrals. TeleDerm aims to confirm that the possibility of store-and-forward teledermatology in GP practices is going to lead to a 15% (n = 260) reduction in referrals in the intervention arm. The study uses a cluster-randomized controlled trial design. Randomization is planned for the cluster “county”. The main observational unit is the GP practice. Poisson distribution of referrals is assumed. The evaluation of secondary outcomes like acceptance, enablers and barriers uses a mixed methods design with questionnaires and interviews.
Discussion: Due to the heterogeneity of GP practice organization, patient management software, information technology service providers, GP personal technical affinity and training, we expect several challenges in implementing teledermatology in German GP routine care. Therefore, we plan to recruit 30% more GPs than required by the power calculation. The implementation design and accompanying evaluation is expected to deliver vital insights into the specifics of implementing telemedicine in German routine care.
Decentralized energy systems are characterized by an ad hoc planing. The missing integration of energy objectives into business strategy creates difficulties resulting in inefficient energy architectures and decisions. Practice-proven methods such as balanced scorecard, enterprise architecture management and value network approach supports the transformation path towards an effective decentralized system. The methods are evaluated based on a case study. Managing multi-dimensionality, high complexity and multiple actors are the main drivers for an effective and efficient energy management system. The underlying basis to gain the positive impacts of these methods on decentralized corporate energy systems is digitization of energy data and processes.
Several studies analyzed existing Web APIs against the constraints of REST to estimate the degree of REST compliance among state-of-the-art APIs. These studies revealed that only a small number of Web APIs are truly RESTful. Moreover, identified mismatches between theoretical REST concepts and practical implementations lead us to believe that practitioners perceive many rules and best practices aligned with these REST concepts differently in terms of their importance and impact on software quality. We therefore conducted a Delphi study in which we confronted eight Web API experts from industry with a catalog of 82 REST API design rules. For each rule, we let them rate its importance and software quality impact. As consensus, our experts rated 28 rules with high, 17 with medium, and 37 with low importance. Moreover, they perceived usability, maintainability, and compatibility as the most impacted quality attributes. The detailed analysis revealed that the experts saw rules for reaching Richardson maturity level 2 as critical, while reaching level 3 was less important. As the acquired consensus data may serve as valuable input for designing a tool-supported approach for the automatic quality evaluation of RESTful APIs, we briefly discuss requirements for such an approach and comment on the applicability of the most important rules.
Hypermedia as the Engine of Application State (HATEOAS) is one of the core constraints of REST. It refers to the concept of embedding hyperlinks into the response of a queried or manipulated resource to show a client possible follow-up actions and transitions to related resources. Thus, this concept aims to provide a client with a navigational support when interacting with a Web-based application. Although HATEOAS should be implemented by any Web-based API claiming to be RESTful, API providers tend to offer service descriptions in place of embedding hyperlinks into responses. Instead of relying on a navigational support, a client developer has to read the service description and has to identify resources and their URIs that are relevant for the interaction with the API. In this paper, we introduce an approach that aims to identify transitions between resources of a Web-based API by systematically analyzing the service description only. We devise an algorithm that automatically derives a URI Model from the service description and then analyzes the payload schemas to identify feasible values for the substitution of path parameters in URI Templates. We implement this approach as a proxy application, which injects hyperlinks representing transitions into the response payload of a queried or manipulated resource. The result is a HATEOAS-like navigational support through an API. Our first prototype operates on service descriptions in the OpenAPI format. We evaluate our approach using ten real-world APIs from different domains. Furthermore, we discuss the results as well as the observations captured in these tests.
Menopause is the permanent cessation of menstruation occurring naturally in women's aging. The most frequent symptoms associated with menopausal phases are mucosal dryness, increased weight and body fat, and changes in sleep patterns. Oral symptoms in menopause derived from saliva flow reduction can lead to dry mouth, ulcers, and alterations of taste and swallowing patterns. However, the oral health phenotype of postmenopausal women has not been characterized. The aim of the study was to determine postmenopausal women's oral phenotype, including medical history, lifestyle, and oral assessment through artificial intelligence algorithms. We enrolled 100 postmenopausal women attending the Dental School of the University of Seville were included in the study. We collected an extensive questionnaire, including lifestyle, medication, and medical history. We used an unsupervised k-means algorithm to cluster the data following standard features for data analysis. Our results showed the main oral symptoms in our postmenopausal cohort were reduced salivary flow and periodontal disease. Relying on the classical assessment of the collected data, we might have a biased evaluation of postmenopausal women. Then, we used artificial intelligence analysis to evaluate our data obtaining the main features and providing a reduced feature defining the oral health phenotype. We found 6 clusters with similar features, including medication affecting salivation or smoking as essential features to obtain different phenotypes. Thus, we could obtain main features considering differential oral health phenotypes of postmenopausal women with an integrative approach providing new tools to assess the women in the dental clinic.
Companies are constantly changing their business process models. In team environments, different versions of a process model are created at the same time. These versions of a process model need to be merged from time to time to consolidate changes and create a new common version.
In this short paper, we propose a solution for modifying a merge result. The goal is to create a meaningful merge result by adding connector nodes to the model at specific locations. This increases the amount of possible result models and reduces additional implementation effort.
Software and system development is complex and diverse, and a multitude of development approaches is used and combined with each other to address the manifold challenges companies face today. To study the current state of the practice and to build a sound understanding about the utility of different development approaches and their application to modern software system development, in 2016, we launched the HELENA initiative. This paper introduces the 2nd HELENA workshop and provides an overview of the current project state. In the workshop, six teams present initial findings from their regions, impulse talk are given, and further steps of the HELENA roadmap are discussed.
In this presentation the audience will be: (a) introduced to the aims and objectives of the DBTechNet initiative, (b) briefed on the DBTech EXT virtual laboratory workshops (VLW), i.e. the educational and training (E&T) content which is freely available over the internet and includes vendor-neutral hands-on laboratory training sessions on key database technology topics, and (c) informed on some of the practical problems encountered and the way they have been addressed. Last but not least, the audience will be invited to consider incorporating some or all of the DBTech EXT VLW content into their higher education (HE), vocational education and training (VET), and/or lifelong learning/training type course curricula. This will come at no cost and no commitment on behalf of the teacher/trainer; the latter is only expected to provide his/her feedback on the pedagogical value and the quality of the E&T content received/used.
Context: Agile practices as well as UX methods are nowadays well-known and often adopted to develop complex software and products more efficiently and effectively. However, in the so called VUCA environment, which many companies are confronted with, the sole use of UX research is not sufficient to find the best solutions for customers. The implementation of Design Thinking can support this process. But many companies and their product owners don’t know how much resources they should spend for conducting Design Thinking.
Objective: This paper aims at suggesting a supportive tool, the “Discovery Effort Worthiness (DEW) Index”, for product owners and agile teams to determine a suitable amount of effort that should be spent for Design Thinking activities.
Method: A case study was conducted for the development of the DEW index. Design Thinking was introduced into the regular development cycle of an industry Scrum team. With the support of UX and Design Thinking experts, a formula was developed to determine the appropriate effort for Design Thinking.
Results: The developed “Discovery Effort Worthiness Index” provides an easy-to-use tool for companies and their product owners to determine how much effort they should spend on Design Thinking methods to discover and validate requirements. A company can map the corresponding Design Thinking methods to the results of the DEW Index calculation, and product owners can select the appropriate measures from this mapping. Therefore, they can optimize the effort spent for discovery and validation.
Analysis is an important part of the enterprise architecture management process. Prior to decisions regarding transformation of the enterprise architecture, the current situation and the outcomes of alternative action plans have to be analysed. Many analysis approaches have been proposed by researchers and current enterprise architecture management tools implement analysis functionalities. However, few work has been done structuring and classifying enterprise architecture analysis approaches. This paper collects and extends existing classification schemes, presenting a framework for enterprise architecture analysis classification. For evaluation, a collection of enterprise architecture analysis approaches has been classified based on this framework. As a result, the description of these approaches has been assessed, a common set of important categories for enterprise architecture analysis classification has been derived and suggestions for further development are drawn.
Rapid prototyping platforms reduce development time by allowing quick prototyping of a prototype idea and achieve more time for actual application development with user interfaces. This approach has long been followed in technical platforms, such as the Arduino. To transfer this form of prototyping to wearables, WearIT is presented in this paper.WearIT consists of four components as a wearable prototyping platform: (1) a vest, (2) sensor and actuator shields, (3) its own library and (4) a motherboard consisting of Arduino, Raspberry Pi, a board and a GPS module. As a result, a wearable prototype can be quickly developed by attaching sensor and actuator shields to the WearIT vest. These sensor and actuator shields can then be programmed through the WearIT library. Via Virtual Network Computing (VNC) with a remote computer, the screen contents of the Raspberry Pi can be accessed and the Arduino be programmed.
Software development as an experiment system : a qualitative survey on the state of the practice
(2015)
An experiment-driven approach to software product and service development is gaining increasing attention as a way to channel limited resources to the efficient creation of customer value. In this approach, software functionalities are developed incrementally and validated in continuous experiments with stakeholders such as customers and users. The experiments provide factual feedback for guiding subsequent development. Although case studies on experimentation in industry exist, the understanding of the state of the practice and the encountered obstacles is incomplete. This paper presents an interview-based qualitative survey exploring the experimentation experiences of ten software development companies. The study found that although the principles of continuous experimentation resonated with industry practitioners, the state of the practice is not yet mature. In particular, experimentation is rarely systematic and continuous. Key challenges relate to changing organizational culture, accelerating development cycle speed, and measuring customer value and product
success.
Enterprises and societies currently face essential challenges, and digital transformation can contribute to their resolution. Enterprise architecture (EA) is useful for promoting digital transformation in global companies and information societies covering ecosystem partners. The advancement of new business models can be promoted with digital platforms and architectures for Industry 4.0 and Society 5.0. Therefore, products from the sector of healthcare, manufacturing and energy, etc. can increase in value. The adaptive integrated digital architecture framework (AIDAF) for Industry 4.0 and the design thinking approach is expected to promote and implement the digital platforms and digital products for healthcare, manufacturing and energy communities more efficiently. In this paper, we propose various cases of digital transformation where digital platforms and products are designed and evaluated for digital IT, digital manufacturing and digital healthcare with Industry 4.0 and Society 5.0. The vision of AIDAF applications to perform digital transformation in global companies is explained and referenced, extended toward the digitalized ecosystems such as Society 5.0 and Industry 4.0.
Enterprises and societies currently face crucial challenges, while Society 5.0 can contribute to a supersmart society, especially for manufacturing and healthcare, and Industry 4.0 becomes important in the global manufacturing industry. Smart energy digital platforms are architected to manage energy supply efficiently. Furthermore, the above digital platforms are expected to collect various kinds of data and analyze Big Data for the trends in the sharing economy in ecosystems. The adaptive integrated digital architecture framework (AIDAF) for Design Thinking Approach with Risk Management is expected to make an alignment with digital IT strategy. In this paper, we propose that various energy management systems and related digital platforms are designed and implemented in an alignment to digital IT strategy for sharing economy toward Society 5.0, with the AIDAF framework for Design Thinking Approach with Risk Management. The vision of AIDAF applications to enable sharing economy and digital platforms is explained and extended in the context of Society 5.0. In addition, challenges and future activities for this area are discussed that cover the directions of smart energy for Society 5.0.
Enterprises and societies currently face crucial challenges, while Industry 4.0 becomes important in the global manufacturing industry all the more. Industry 4.0 offers a range of opportunities for companies to increase the flexibility and efficiency of production processes. The development of new business models can be promoted with digital platforms and architectures for Industry 4.0. Therefore, products from the healthcare sector can increase in value. The adaptive integrated digital architecture framework (AIDAF) for Industry 4.0 is expected to promote and implement the digital platforms and robotics for healthcare and medical communities efficiently. In this paper, we propose that various digital platforms and robotics are designed and evaluated for digital healthcare as for manufacturing industry with Industry 4.0. We argue that the design of an open healthcare platform “Open Healthcare Platform 2030 - OHP2030” for medical product design and robotics can be developed with AIDAF. The vision of AIDAF applications to enable Industry 4.0 in the OHP2030 research initiative is explained and referenced, extended in the context of Society 5.0.
Internet of Things (IoT) provides a strong platform for computer users to connect objects, devices, and people to the Internet for exchanging or sharing of information with each other. IoT is growing rapidly and is expected to adapt to disciplines such as manufacturing, agriculture, healthcare, and robotics. Furthermore, the new concept of IoT is proposed and shown, especially for robotics areas as Internet of Robotics Things (IoRT). IoRT is a mixed structure of diverse technologies such as cloud computing, artificial intelligence, and machine learning. However, to promote and realize IoRT, digitization and digital transformation should be proceeded and implemented in the robotics enterprise. In this paper, we propose and architecture framework for IoRT-based digital platforms an verify it using a planned case in a global robotics enterprise. The associated challenges and future research directions in this field are also presented.
The increasing heterogenecity of students at German Universities of Applied Sciences and the growing importance of digitization call for a rethinking of teaching and learning within higher education. In the next years, changing the learning ecosystem by developing and reflecting upon new teaching and learning techniques using methods of digitalization will be both - most relevant and very challenging. The following article introduces two different learning scenarios, which exemplify the implementation of new educational models that allow discontinuity of time and place, technology and process in teaching and learning. Within a blended learning apporach, the first learning scenario aims at adapting and individualizing the knowledge transfer in the course Foundations of Computer Science by providing knowledge individually and situation-specifically. The second learning scenario proposes a web-based tool to facilitate digital learning environments and thus digital learning communities and the possibility of computer-supported learning. The overall aim of both learning scenarios is to enhance learning for diverse groups by providing a different smart learning ecosystem in stepping away from a teacher-based to a student-centered approach. Both learning scenarios exemplarily represent the educational vision of Reutlingen University - its development into an interactive university.
The livestock sector is growing steadily and is responsible for around 18% of global greenhouse‐gas‐emissions, which is more than the global transport sec-tor (Steinfeld et al. 2006). This paper examines the potential of social marketing to reduce meat consumption. The aim is to understand consumers’ motivation in diet choices and to learn what opportunities social marketing can provide to counteract negative environmental and health trends. The authors believe that research to answer this question should start in metropolitan areas, be-cause measures should be especially effective there. Based on the Theory of Planned Behaviour (TPB, Ajzen 1991) and the Technology‐Acceptance‐Model by Huijts et al. (2012), an online‐study with participants from the metropolitan region (n = 708) was conducted in which central socio‐psychological constructs for a meat consumption reduction were examined. It was shown that attitude, personal norm and habit have a critical influence on the intention to reduce meat consumption. A segmentation of consumers based on these factors led to three consumer clusters: vegetarians/flexitarians, potential flexitarians and convinced meat eaters. Potential flexitarians are an especially relevant target group for the development of social‐marketing‐measures to reduce meat consumption. In co‐creation‐workshops with potential flexitarians from the metropolitan region, barriers and benefits of reducing meat consumption were identified. The factors of environmental protection, animal welfare and desire for variety turn out to be the most relevant motivational factors. Based on these factors, consumers proposed a variety of social marketing measures, such as applications and labels to inform about the environmental impact of meat products.
Digitalization and enterprise architecture management: a perspective on benefits and challenges
(2023)
Many companies digitally transform their business models, processes, and services. They have also been using Enterprise Architecture Management approaches for a long time to synchronize corporate strategy and information technology. Such digitalization projects bring different challenges for Enterprise Architecture Management. Without understanding and addressing them, Enterprise Architecture Management projects will fail or not deliver the expected value. Since existing research has not yet addressed these challenges, they were investigated based on a qualitative expert study with leading industry experts from Europe. Furthermore, potential benefits of digitalization projects for Enterprise Architecture Management were researched. Our results provide a theoretical framework consisting of five identified challenges, triggers and a number of benefits. Furthermore, we discuss in what ways digitalization and EAM is a promising topic for future research.
Data analysis is becoming increasingly important to pursue organizational goals, especially in the context of Industry 4.0, where a wide variety of data is available. Here numerous challenges arise, especially when using unstructured data. However, this subject has not been focused by research so far. This research paper addresses this gap, which is interesting for science and practice as well. In a study three major challenges of using unstructured data has been identified: analytical know-how, data issues, variety. Additionally, measures how to improve the analysis of unstructured data in the industry 4.0 context are described. Therefore, the paper provides empirical insights about challenges and potential measures when analyzing unstructured data. The findings are presented in a framework, too. Hence, next steps of the research project and future research points become apparent.
Revenue management information systems are very important in the hospitality sector. Revenue decisions can be better prepared based on different information from different information systems and decision strategies. There is a lack of research about the usage of such systems in small and medium-sized hotels and architectural configurations. Our paper empirically shows the current development of revenue information systems. Furthermore, we define future developments and requirements to improve such systems and the architectural base.
New business concepts such as Enterprise 2.0 foster the use of social software in enterprises. Especially social production significantly increases the amount of data in the context of business processes. Unfortunately, these data are still an unearthed treasure in many enterprises. Due to advances in data processing such as Big Data, the exploitation of context data becomes feasible. To provide a foundation for the methodical exploitation of context data, this paper introduces a classification, based on two classes, intrinsic and extrinsic data.
Context: Organizations are increasingly challenged by dynamic and technical market environments. Traditional product roadmapping practices such as detailed and fixed long-term planning typically fail in such environments. Therefore, companies are actively seeking ways to improve their product roadmapping approach. Goal: This paper aims at identifying problems and challenges with respect to product roadmapping. In addition, it aims at understanding how companies succeed in improving their roadmapping practices in their respective company contexts. The study focuses on mid-sized and large companies developing software-intensive products in dynamic and technical market environments. Method: We conducted semi structured expert interviews with 15 experts from 13 German companies and conducted a thematic data analysis. Results: The analysis showed that a significant number of companies is still struggling with traditional feature based product-roadmapping and opinion based prioritization of features. The most promising areas for improvement are stating the outcomes a company is trying to achieve and making them part of the roadmap, sharing or co-developing the roadmap with stakeholders, and the establishing discovery activities.
Context: Organizations are increasingly challenged by high market dynamics, rapidly evolving technologies and shifting user expectations. In consequence, many organizations are struggling with their ability to provide reliable product roadmaps by applying traditional roadmapping approaches. Currently, many companies are seeking opportunities to improve their product roadmapping practices and strive for new roadmapping approaches. A typical first step towards advancing the roadmapping capabilities of an organization is to assess the current situation. Therefore, the so-called maturity model DEEP for assessing the product roadmapping capabilities of companies operating in dynamic and uncertain environments has been developed and published by the authors.
Objective: The aim of this article is to conduct an initial validation of the DEEP model in order to understand its applicability better and to see if important concepts are missing. In addition, the aim of this article is to evolve the model based on the findings from the initial validation.
Method: The model has been given to practitioners such as product managers with the request to perform a self-assessment of the current product roadmapping practices in their company. Afterwards, interviews with each participant have been conducted in order to gain insights.
Results: The initial validation revealed that some of the stages of the model need to be rearranged and minor usability issues were found. The overall structure of the model was well received. The study resulted in the development of the version 1.1 of the DEEP product roadmap maturity model which is also presented in this article.
Workshops and tutorials
(2018)
The 19th International Conference on Product-Focused Software Process Improvement (PROFES 2018) hosted two workshops and three tutorials. The workshops and tutorials complemented and enhanced the main conference program, offering a wider knowledge perspective around the conference topics. The topics of the two workshops were Hybrid Development Approaches in Software Systems Development (HELENA) and Managing Quality in Agile & Rapid Software Development Processes (QUaSD). The topics of the tutorials were The human factor in agile transitions – using the personas concept in agile oaching, Process Management 4.0 – Best Practices, and Domain-specific languages for specification, development, and testing of autonomous systems.
The use of Wireless Sensor and Actuator Networks (WSAN) as an enabling technology for Cyber-Physical Systems has increased significantly in recent past. The challenges that arise in different application areas of Cyber- Physical Systems, in general, and in WSAN in particular, are getting the attention of academia and industry both. Since reliability issues for message delivery in wireless communication are of critical importance for certain safety related applications, it is one of the areas that has received significant focus in the research community. Additionally, the diverse needs of different applications put different demands on the lower layers in the protocol stack, thus necessitating such mechanisms in place in the lower layers which enable them to dynamically adapt. Another major issue in the realization of networked wirelessly communicating cyber-physical systems, in general, and WSAN, in particular, is the lack of approaches that tackle the reliability, configurability and application awareness issues together. One could consider tackling these issues in isolation. However, the interplay between these issues create such challenges that make the application developers spend more time on meeting these challenges, and that too not in very optimal ways, than spending their time on solving the problems related to the application being developed. Starting from some fundamental concepts, general issues and problems in cyber-physical systems, this chapter discusses such issues like energy-efficiency, application and channel-awareness for networked wirelessly communicating cyber-physical systems. Additionally, the chapter describes a middleware approach called CEACH, which is an acronym for Configurable, Energy-efficient, Application- and Channel-aware Clustering based middleware service for cyber-physical systems. The state of-the art in the area of cyberphysical systems with a special focus on communication reliability, configurability, application- and channel-awareness is described in the chapter. The chapter also describes how these features have been considered in the CEACH approach. Important node level and network level characteristics and their significance vis-àvis the design of applications for cyber physical systems is also discussed. The issue of adaptively controlling the impact of these factors vis-à-vis the application demands and network conditions is also discussed. The chapter also includes a description of Fuzzy-CEACH which is an extension of CEACH middleware service and which uses fuzzy logic principles. The fuzzy descriptors used in different stages of Fuzzy-CEACH have also been described. The fuzzy inference engine used in the Fuzzy-CEACH cluster head election process is described in detail. The Rule-Bases used by fuzzy inference engine in different stages of Fuzzy-CEACH is also included to show an insightful description of the protocol. The chapter also discusses in detail the experimental results validating the authenticity of the presented concepts in the CEACH approach. The applicability of the CEACH middleware service in different application scenarios in the domain of cyberphysical systems is also discussed. The chapter concludes by shedding light on the Publish-Subscribe mechanisms in distributed event-based systems and showing how they can make use of the CEACH middleware to reliably communicate detected events to the event-consumers or the actuators if the WSAN is modeled as a distributed event-based system.
In this paper a method for the generation of gSPM with ontology-based generalization was presented. The resulting gSPM was modeled with BPMN/BPMNsix in an efficient way and could be executed with BPMN workflow engines. In the next step the implementation of resource concepts, anatomical structures, and transition probabilities for workflow execution will be realized.