For a data-driven economy, digitization of product information throughout the entire product lifecycle is key to agility and efficiency of product-related processes. Documenting products and their development, e.g., creating requirement specifications, is an indispensable, time-consuming and resource-intensive activity in large organizations. A vast amount of related information often emerges across several siloing lifecycle tools, and only a portion of it is available in the post-hoc documentation. Additionally, numerous product lines and versions additionally increase the documentation effort. To tackle these issues in a research project, we developed a semi-automatic end-to-end documentation system, able to generate documents based on templates and structured data. As a use case for document generation, we employ the RDF-based lifecycle tool integration standard OSLC and add extended publishing information. In order to generate target documents, we leverage DITA, an established digital publishing standard. A pilot implementation demonstrates that the approach is able to extract distributed lifecycle data and to generate several types of documents in multiple formats. Since the method can also be used to generate documents from arbitrary RDF graphs, the results can be generalized to other domains beyond software development. We believe that the results support the change from a document-driven to a data-driven documentation paradigm in large organizations.

Globalization and digitization of the economy increase the demand for fast and precise positioning services. Existing and new global navigation satellite systems (GNSS) add flexibility and adaptability to the list of requirements. To cope with these demands GNSS receivers have been built as software solutions. For software receivers satellite signal acquisition is a hard problem. In this paper we have focused on improving the efficiency of the acquisition in the receiver. The proposed method combines multiple frequency steps into a single one to acquire the satellites. By this means we reduce memory demand and the number of FFT /IFFT calculations for correlation calculation, which is crucial for the performance of a software receiver, in particular on an embedded platform. To eliminate the influence and ambiguity of the multi-frequency approach, we introduce a correction procedure after the basic acquisition process. In our approach we choose several candidate results to implement a more precise acquisition. Our experiments show that the multi-frequency acquisition method saves a significant amount of resources in the acquisition phase, even in a weak GPS signal environment.

Digitization is a megatrend which affects all industries. But how does this affect learning on the job scenarios. The research project HANDELkompetent aims at digitization of work process integrated informal learning in retail with a methodological approach and a supporting digital learning environment. The method consists of an accompanied learning approach, where a dedicated person schedules the development of competences of staff in dialog. Learning content consists of small web-based trainings, i.e. learning-nuggets, which can be consumed in a few minutes. The learning environment is enhanced with a tablet pc app, which presents learning content to a learner. The app is enabled to deliver appropriate content to the learner by recognizing the learning situation by making use of device sensors, the actual competences of a learner and the target competences as registered in the learning environment. That means in detail that a learning position, e.g. cash point, warehouse or sales floor is tagged with iBeacons. Those iBeacons broadcast their identification via Bluetooth Low Energy. The tablet PCof a learner can identify these iBeacons and thus, the app determines the physical location of the learner. Besides the position the app can utilize microphone, camera or a brightness sensor for gathering context information, to derive the learning situation and to deliver appropriate content. We make use of the Digital Business Engineering Framework to structure our work. Digital Business Engineering is a methodological framework to deliver sustainable solutions for Digital Transformation. This paper shows our structural approach and first results of the development phase of the HANDELkompetent project.

Asymmetric information between logistics service demanders and logistics service providers may lead to poor service or high service price, and thus cause losses for logistics service demanders. However, a logistics contract is difficult to monitor as a service process in real time. In this paper, SLA management is introduced into business process management of third-party logistics services. Measurement methods for SLA metrics in logistics are analyzed and a monitoring mechanism is proposed as a control program whose main task is to realize the instantiation of SLA metrics. The mechanism is demonstrated by a typical transportation service process of a third party logistics service provider. The measurement process of an SLA metric is then described in detail and the compliance of the logistics SLA is also analyzed and discussed. In the end, the delivery process of a logistics SLA report is given. The proposed monitoring mechanism is an effective method for the monitoring of service level parameters to deliver a proper level of logistics service based on customer requirements. Quality of service can be monitored in real time.

The Logistics Mall extends the cloud service model from Software-as-a-Service (SaaS) to Business Process-as-a-Service (BPaaS). Its architecture, hence, spans from a web-based public B2B marketplace for simple apps, traditional applications and even logistics process templates to customer-specific cloud based execution environments for instantiated process models and therein included applications. For communication with the mall outside world a specific gateway is provided that controls inbound and outbound message flow.

Common characteristics of all logistics processes are individuality and dynamically changing requirements of the customers’ business. Cloud computing enables new business models to provide highly individual IT services that fit the needs of logistics customers. After outlining logistics specific cloud service requirements and the results of a study about the acceptance of cloud computing in logistics domain this paper presents the Logistics Mall, an approach for a domain specific cloud platform for the trading and usage of logistics IT services and logistics processes.

This paper describes an approach for the development of a logistics cloud as a “vertical cloud”. In contrast to a generic or “horizontal cloud” components of the cloud platform are custom tailored to the specific needs of the logistics application area. The NIST cloud services model serves as a basis for structuring logistics specific cloud service requirements. In the next step the domain specific model is used as a basis for the development of Logistics Mall, a domain specific cloud platform for the trading and usage of logistics IT services and logistics processes. The paper closes with an overview of the implementation status and an outlook to future work.

Logistics demand forecasting is important for investment decision-making of infrastructure and strategy programming of the logistics industry. In this paper, a hybrid method which combines the Grey Model, artificial neural networks and other techniques in both learning and analyzing phases is proposed to improve the precision and reliability of forecasting. After establishing a learning model GNNM(1,8) for road logistics demand forecasting, we chose road freight volume as target value and other economic indicators, i.e. GDP, production value of primary industry, total industrial output value, outcomes of tertiary industry, retail sale of social consumer goods, disposable personal income, and total foreign trade value as the seven key influencing factors for logistics demand. Actual data sequences of the province of Zhejiang from years 1986 to 2008 were collected as training and test-proof samples. By comparing the forecasting results, it turns out that GNNM(1,8) is an appropriate forecasting method to yield higher accuracy and lower mean absolute percentage errors than other individual models for short-term logistics demand forecasting.

This chapter describes the use of ontologies for personalized situation-aware information and service supply of mobile users in different application domains. A modular application ontology, composed of upper-level ontologies such as location and time ontologies and of domain-specific ontologies, acts as a semantic reference model for a compatible description of user demands and service offers in a service-oriented information-logistical platform. The authors point out that the practical deployment of the platform proved the viability of the conceptual approach and exhibited the need for a more performant implementation of inference engines in mobile multi-user scenarios. Furthermore, the authors hope that understanding the underlying concepts and domain-specific application constraints will help researchers and practitioners building more sophisticated applications not only in the domains tackled in this chapter but also transferring the concepts to other domains.

The virtualization of IT services by using software-as-a-service offers imposes the problem of correct service usage. Often an application level protocol has to be followed to assure logically correct workflows. This paper presents a domain-specific approach for the specification of such application level protocols. A domain ontology is combined with a formal protocol specification language to enable correct usage patterns even for dynamically adapted workflows to support individual needs.

We will describe a field test and its evaluation of a truly novel type of mobile computer programs that will assist foreign tourists in their communication with Chinese people. The software is an electronic phrase book and a translation aid but at the same time a powerful multilingual information system connected to numerous services via the Internet. It effectively helps visitors to navigate through the streets, temples and shopping centres of the Beijing megalopolis. It was developed in the German-Chinese project COMPASS 2008, a research action within the Digital Olympics framework. The subjects of the field test were fifteen tourists from seven countries. The test concentrated on usability and acceptance. The applied methodology adapts recognized standards and widely accepted best practice to the specific application type.

A growing number of frameworks and middleware for context aware application exists as prototypes. Only little information with practical deployment is available. The COMPASS system has been developed as a platform for multilingual, personalized and situation aware provision of mobile services to help visitors of the Olympic Games 2008 in Beijing. In a field test a group of external users tested the COMPASS system in its target environment. This paper describes some results of the field test regarding situation aware service provision.

The dynamic characteristics of business processes and network computing environments bring new challenges to distributed applications. As an approach to solve the adaptation problem of service-oriented applications, caused by changes of service resources and user requirements in such dynamic network computing environments, we present an open and adaptive software architecture model in this paper. We also discuss the deployment of the model in a real project. An analysis and evaluation of the model's capability to improve software adaptability shows that the model can improve service-oriented applications regarding change awareness, continuous evolution and self-organization.

Although the demand for context-aware applications seems very high, not many applications are in real use. Besides the strenuosity, their insufficient adaptability to changing environment is a major reason. To address the issue, we proposed a VINCA-cc approach and a context middleware to support business-level dynamic configuration of context-aware service. In our approach, all kinds of context information are abstracted to standardized context business objects (CBO), registered in the context middleware. The business-level context model, CBO, represents a set of business-level properties and abstract unified operations that are applicable to all context information. Based on the visual business-level service composition language-VINCA and CBO model, context-aware services can be visually (re-)configured at the business-level. The paper focuses on the context middleware, CBO model and its application.

In this paper we present a decision support system for emergency situations for mobile use. MONA filters from the abundance of altogether available information and services those relevant for the operation situation and puts them to the operation control at the spot and also the directing center at the disposal. Long delays, caused by complex procurement processes for relevant information, can increase risk for lives and for the environment and can be reduced by using a system like MONA.