A Literature Survey on Information Logistics

Michelberger, Bernd; Andris, Ralph-Josef; Girit, Hasan; Mutschler, Bela

doi:10.1007/978-3-642-38366-3_12

Cited by 9 publications

(7 citation statements)

References 23 publications

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“…These requirements were derived in the context of two case studies in the automotive and healthcare domain [7,8]. Their generalizability was confirmed by a literature study [9]. Finally, Table 1 summarizes the derived requirements.…”

Section: Requirementsmentioning

confidence: 63%

Enabling a User-Friendly Visualization of Business Process Models

Hipp

Strauß

Michelberger

et al. 2015

Business Process Management Workshops

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Abstract. Enterprises are facing increasingly complex business processes. Engineering processes in the automotive domain, for example, may comprise hundreds or thousands of process tasks. In such a scenario, existing modeling notations do not always allow for a user-friendly process visualization. In turn, this hampers the comprehensibility of business processes, especially for non-experienced process participants. This paper tackles this challenge by suggesting alternative ways of visualizing large and complex process models. A controlled experiment with 22 subjects provides first insights into how users perceive these approaches.

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Section: Requirementsmentioning

confidence: 63%

Enabling a User-Friendly Visualization of Business Process Models

Hipp

Strauß

Michelberger

et al. 2015

Business Process Management Workshops

Self Cite

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“…The goal of information logistics is to enable the effective and efficient delivery of needed information in the right format, granularity and quality, at the right place, at the right point in time to the right actors [12]. This system uses method of''user-demand Information-supply'' [13] and Semantic technology to map information to information demands.…”

Section: Information Overload Filteringmentioning

confidence: 99%

Multiple views system to support awareness for cooperative design

Chen

Zhao

et al. 2015

Computer-Aided Design

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“…Focusing on the optimization of the data movement, it is fundamental to properly manage the information logistics (Michelberger et al, 2013 ), i.e., the delivery of information at the right time, in the right place, and with the right quality and format to the user (D'Andria et al, 2015 ). As a consequence, user requirements can be defined in terms of functional aspects, i.e., contents, and non-functional ones, i.e., time, location, representation, and quality (Plebani et al, 2017 ).…”

Section: Fog Computingmentioning

confidence: 99%

Improving Health Monitoring With Adaptive Data Movement in Fog Computing

et al. 2020

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Pervasive sensing is increasing our ability to monitor the status of patients not only when they are hospitalized but also during home recovery. As a result, lots of data are collected and are available for multiple purposes. If operations can take advantage of timely and detailed data, the huge amount of data collected can also be useful for analytics. However, these data may be unusable for two reasons: data quality and performance problems. First, if the quality of the collected values is low, the processing activities could produce insignificant results. Second, if the system does not guarantee adequate performance, the results may not be delivered at the right time. The goal of this document is to propose a data utility model that considers the impact of the quality of the data sources (e.g., collected data, biographical data, and clinical history) on the expected results and allows for improvement of the performance through utility-driven data management in a Fog environment. Regarding data quality, our approach aims to consider it as a context-dependent problem: a given dataset can be considered useful for one application and inadequate for another application. For this reason, we suggest a context-dependent quality assessment considering dimensions such as accuracy, completeness, consistency, and timeliness, and we argue that different applications have different quality requirements to consider. The management of data in Fog computing also requires particular attention to quality of service requirements. For this reason, we include QoS aspects in the data utility model, such as availability, response time, and latency. Based on the proposed data utility model, we present an approach based on a goal model capable of identifying when one or more dimensions of quality of service or data quality are violated and of suggesting which is the best action to be taken to address this violation. The proposed approach is evaluated with a real and appropriately anonymized dataset, obtained as part of the experimental procedure of a research project in which a device with a set of sensors (inertial, temperature, humidity, and light sensors) is used to collect motion and environmental data associated with the daily physical activities of healthy young volunteers.

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A Literature Survey on Information Logistics

Cited by 9 publications

References 23 publications

Enabling a User-Friendly Visualization of Business Process Models

Enabling a User-Friendly Visualization of Business Process Models

Multiple views system to support awareness for cooperative design

Improving Health Monitoring With Adaptive Data Movement in Fog Computing

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