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Über dieses Buch

This book constitutes revised papers from the six workshops held at the 19th International Conference on Business Information Systems, BIS 2016, held in Leipzig, Germany, in July 2016.
The workshops included in this volume are:

* The 8th Workshop on Applications of Knowledge-Based Technologies in Business - AKTB2016 accepted 7 papers from 14 submissions and features 1 invited talk.
* The 7th Workshop on Business and IT Alignment - BITA 2016 selected 6 papers from 12 submissions.
* The Workshop on Big Data and Business Analytics Ecosystems - DeBASE 2016 has 4 papers in this volume.
* The First International Workshop on Intelligent Data Analysis in Integrated Social CRM - iCRM 2016 features 5 contributions.
* The Second International Workshop on Digital Enterprise Engineering and Architecture - IDEA 2016 contributes 4 papers to this volume.
* The First International Workshop on Integrative Analysis and Computation of Life Data for Smart Ecosystems - INCLuDE 2016 publishes 4 research papers.
In addition, BIS hosted a Doctoral Consortium which was organized in a workshop formula. The best papers from this event are included in the book.
In total, the workshops had 84 submissions of which 38 were accepted for publication.



Keynote Speech


Governmental IT – Challenges in a Federal State Setup and Possible Solutions

The Saxon IT Services (Staatsbetrieb Sächsische Informatik Dienste - SID) is a public agency and provides IT solutions in a federal organized state. Therefore some restrictions apply. For example, decreasing numbers of employees and an increasing average of age can lead to organizational problems in the long run. This paper gives a short overview on how to respond to new customer requirements from a public agency perspective.

Sebastian Kiebusch

AKTB Workshop


Exploring the Influence of the Use of an ERP System on Strategy Development in German and Polish Manufacturing Enterprises: An Empirical Investigation

This article aims to explore the effects of the use of an ERP system in a manufacturing company on strategy development as described by defined factors. The work is based on a survey and data obtained from 62 Polish manufacturing enterprises from the Lubuskie region, and from 23 German manufacturing enterprises from the Brandenburg region, in which the companies were categorised as either “construction” or “automotive” – a total of 85 manufacturing enterprises. Special attention was placed on the description of understanding the usage of an ERP system within a company. Nevertheless, relatively little information has been published that focuses on the post-implementation stages of ERP usage in a manufacturing company. In particular, this study pays attention to the likely consequences and results of the use of defined functionalities of an ERP system by employees. This is followed by a discussion of the results of the empirical studies and of key supporting literature. The summary indicates potential directions for further work.

Justyna Patalas-Maliszewska, Irene Krebs

Visual Language and Ontology Based Analysis: Using OWL for Relation Discovery and Query in 4EM

Usually, enterprise models consider different aspects and include different abstraction levels of enterprises. It is hence challenging to integrate these models and to maintain their consistency. In the light of these challenges, ontologies seem to be relevant to complement enterprise models since they are intended to support communication, computational inference, consistency checking, querying, and the organization of knowledge. In our contribution, we demonstrate that Enterprise modelling can benefit from these characteristics. In order to check feasibility and pertinence of ontology-based Enterprise Models, we selected the goal modelling part and its relations to actors and resources from the “For Enterprise Modelling” (4EM) method. In more detail, this paper provides (1) a formal OWL representation of the 4EM Goals meta-model; (2) a discussion of goal relations regarding transitivity and domain specific inference; (3) a formalization of the discussed inference rules; and (4) an analysis of an exemplary goals model instance. This paper extends earlier work on the topic by the introduction of inter-model relations, a discussion of formalization alternatives, and a comparison of query results with and without ontology-based reasoning.

Birger Lantow, Kurt Sandkuhl, Michael Fellmann

Targeting Advertising Scenarios for e-Shops Surfers

Buying goods in e-shops turns to be a very attractive activity for internet surfers. The shopping behaviour of online customers holds attention not only of e-shop businesses, but also the researchers analysing perspectives of online marketing. The most serious consideration is given to discovery of consumer interest patterns, visualization of customer online shopping behaviour or evaluation of advertising campaigns with the goal to attract more e-shop visitors and to grow sales. Unfortunately, selection of the most potentially promising customers draws less attention in the research works. The paper proposes new method of selecting the best e-shop clients for which we can offer the personalized advertising campaign. This study demonstrates how by using only e-shop clickstream data we can identify the potential buyers, select the best suitable advertising campaign and increase the e-shop sales level. The research is based on real clickstream data of two e-shops.

Dalia Kriksciuniene, Virgilijus Sakalauskas

A Proposal of an Academic Library Management System Based on an RDF Repository

The application of Semantic Web technologies has the potential to overcome the limitations of classic WWW architectures and can be used to build Web portals with enhanced semantic interoperability. This paper proposes an innovative approach to implement e-learning portals components using state of the art Semantic Web technologies. We propose a new architecture in which a number of components are to be described and modeled using the Linked Data technological space built around RDF [24]. Creating and incorporating a virtual library based on RDF allows the combination of semantic links between resources, with the possibility of extending these semantics. At the application level, there will be entities capable of processing information in an intelligent manner and capable of reasoning, thus offering complex services like data search, resources retrieval, monitoring applications’ activities or information filtering for both machines and people.

Loredana Mocean, Vasile Paul Bresfelean, Mara Hajdu Macelaru

The Paradigm of Relatedness

This paper introduces the paradigm of relatedness, the generalization of the paradigm of user interest. Relatedness is typically interpreted in a graph based information representation environment, where the content-based and collaborative information is treated at the same abstraction level. To demonstrate the effectiveness of the paradigm, various graph based recommendation methods are evaluated on standard datasets, as MovieLens and MovieTweetings. In our experiment, we focus on the information sparse environment and measure coverage, precision, recall and nDCG on top-N recommendation lists. The primary conclusion of our work is that the paradigm of relatedness is a promising direction as the evaluation results show a significant increase in the recommendation quality of the method implementing the paradigm.

László Grad-Gyenge, Peter Filzmoser

Enterprise Model Based UML Interaction Overview Model Generation Process

The main scope of the research is to analyse Unified Modelling Language (UML) models generation process from Enterprise Model (EM) in Information Systems (IS) development process by using knowledge-based subsystem. The knowledge-based subsystem is proposed as an additional computer aided software engineering (CASE) tool component to avoid IS development process based on empirics. For comprehensible perception there is also presented relation between EM and ontologies and its use in generation process.As the result of this part of research transformation algorithms are presented and described. These algorithms are capable of whole UML models elements generation from Enterprise Model. Example of UML Interaction Overview model generation illustrates full process.

Audrius Lopata, Ilona Veitaite, Neringa Zemaityte

Speaker Authentication System Based on Voice Biometrics and Speech Recognition

In this paper we are analyzing possibility to authenticate speaker by using user voice biometrics and speech recognition. Process of authentication is simple: user says his personal ID number, then system makes prediction of users’ identity and compares it to claimed ID. If these two parameters are equal system makes a positive decision. Using proposed algorithms we managed to achieve 70.45% accuracy for system, with identification module accuracy of 100% and recognition module accuracy of 70.45%.

Laurynas Dovydaitis, Tomas Rasymas, Vytautas Rudžionis

Decision Support System for Foreign Exchange Markets

Selection of the right decision strategy is a crucial factor to success in the foreign exchange market. This article presents an innovative approach how to support related decision steps by means of suitable data mining methods applied on collected data from the market. The motivation is a trading under the best conditions, i.e. with the highest chance to be successful. To meet this requirement, we designed and implemented a decision support system (DSS) for trading on the foreign exchange market which uses a possibility to speculate on this market and in line with extracted rules, economic news and outputs of the technical analysis recommend the future trading direction. We extracted the rules from the historical Forex data with the C5.0 and CART algorithms for decision trees generation. The best achieved accuracy was 56.03% that is typical for this type of data. We used the best rules to design a dynamic trading strategy, which we experimentally verified as profitable.

Róbert Magyar, František Babič, Ján Paralič

BITA Workshop


Visual Analytics in Enterprise Architecture Management: A Systematic Literature Review

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.

Dierk Jugel, Kurt Sandkuhl, Alfred Zimmermann

Modeling Alignment as a Higher Order Nomological Framework

Achieving Business/IT-alignment (BITA) and pursuing intended goals within organizations seems an intricate and poorly examined process. We argue that without proper theories concerning BITA, the ‘mapping’ of theoretical constructs onto empirical phenomena, is ambiguous. In this paper we synthesize a higher order nomological framework for BITA with a considerable degree of complexity, coherence and causality. We aim to extend and generalize previous work on BITA within the healthcare domain, drawing on principles of complexity science. Our framework explains how BITA is related to firm performance. Using this knowledge, organizations can define improvement activities that can be executed along five organizational dimensions that best meets a organizations’ current and future needs; done simultaneously and hence by an integrated management perspective. This work contributes to academia by using a modeling approach that overcomes acknowledged limitations of existing approaches. Doing so, the outcomes of this study also offer many opportunities for future research.

Rogier van de Wetering

Multi-touch Table or Plastic Wall? Design of a Study for the Comparison of Media in Modeling

An important aspect of participatory enterprise modeling is the work in a group. However, does the collaboration of the group members change depending on which medium is used to generate the models? Are there for example differences in the group’s behavior when working with a plastic wall, similar to a whiteboard, or with a multi-touch table? Based on the state of research and theoretical foundations of group work as well as previous research, relevant research issues are raised and an experimental design will be described in order to examine possible differences in the group work depending on the medium. Relevant aspects will be forms of cooperation, i.e. verbal and nonverbal contributions of the participants, but also territorial behavior and group performance.

Anne Gutschmidt, Kurt Sandkuhl, Ulrike Borchardt

The Communicative Nature of Information Systems Integration as an Enabler for Business IT Alignment

Patterns of systems integration strive to accommodate the diversity of business ecosystems, including novel Web- and cloud-based services. In this paper, we apply the principles of the language/action paradigm (LAP) to develop a decentralized integration pattern that supports dynamic integration of services. A model is proposed for designing the interacting systems as active and independent entities that seek to communicate with each other. Two modes are enabled in the communication model: an indirect mode, where systems interact via business processes; and a direct mode, where systems directly interface with each other, following four categories. The communication perspective of the proposed integration pattern contributes to realizing the vision of a marketplace for cloud services. It supports a more flexible alternative to centralized integration patterns. The communication model builds on the improved alignment between system design models and the overall organizational design offered by the unifying meta-model for enterprise modeling.

Iyad Zikra

From Products to Product-Service Systems: Business and Information System Changes

Due to increasing competition in globalized markets companies are forced to search for new business models to get a competitive advantage. One of the trends is to shift from selling products to offering product-service systems. However, such shift requires significant changes in the business processes and related information systems. The paper is based on the analysis and modification of the information management processes related to Product Service Systems (PSS). It investigates the problem of PSS engineering information management in a customer-oriented way. Implementing such an application-system view addresses the problem of designing the customer view on PSS selection, configuration and usage. Though the research results are based on the analysis of one company, the presented work can give significant input to achieve benefits for component manufacturers that tend to become system vendors in general.

Alexander Smirnov, Nikolay Shilov, Andreas Oroszi, Mario Sinko, Thorsten Krebs

Information Quality Framework for the Design and Validation of Data Flow Within Business Processes - Position Paper

Poor data quality may be a cause for problems in organizational processes. There are numerous methods to assess and improve quality of data within information systems, however they often do not address the original source of these problems. This paper presents a conceptual solution for dealing with the data quality issue within information systems. It focuses on analysis of business processes being a source of requirements for information systems design and development. This analysis benefits information quality requirements, in order to improve data quality within systems emerging from these requirements.

Michael Vaknin, Agata Filipowska

DeBASE Workshop


Do You Write What You Are in Business Communications? Deriving Psychometrics from Enterprise Social Networks

In this paper, we explore the discriminability of psychometrics derived from an automated linguistic analysis within a business setting. To this end, a commercial natural language processing application is used to analyse messages posted to the Enterprise Social Network (ESN) of an Australian professional services firm. Comparing the psychometrics derived for individual users with those of other users, we find that the text posted to the ESN facilitates the detection of distinguishable personality profiles. Also, our analysis indicates the derived psychometrics to remain stable from year to year.

Janine Viol Hacker, Alexander Piazza, Trevor Kelley

A Framework for Describing Big Data Projects

With the ability to collect, store and analyze an ever-growing diversity of data generated with ever-increasing frequency, Big Data is a rapidly growing field. While tremendous strides have been made in the algorithms and technologies that are used to perform the analytics, much less has been done to determine how the team should work together to do a Big Data project. Our research reports on a set of case studies, where researchers were embedded within Big Data teams. Since project methodologies will likely depend on the attributes of a Big Data effort, we focus our analysis on defining a framework to describe a Big Data project. We then use this framework to describe the organizations we studied and some of the socio-technical challenges linked to these newly defined project characteristics.

Jeffrey Saltz, Ivan Shamshurin, Colin Connors

Sequential Anomaly Detection Techniques in Business Processes

Many companies use information systems to manage their business processes and thereby collect large amounts of transactional data. The analysis of this data offers the possibility of automated detection of anomalies, i.e. flaws and faults, in the execution of the process. The anomalies can be related not only to the sequence of executed activities but also to other dimensions like the organization or the person performing the respective activity. This paper discusses two approaches of detecting the different anomalies types using basic sequential analysis techniques. Besides the classical one-dimensional approach, a simple approach to use multiple dimensions of the process information in the sequential analysis is discussed and evaluated on a simulated artificial business process.

Christian Linn, Dirk Werth

Social Media and Analytics for Competitive Performance: A Conceptual Research Framework

Social media websites have managed in a very short period of time to attract and maintain a massive user. Recognizing their potential, the vast majority of companies are deploying strategies in order to harness their potential in various ways, and ultimately, to establish their competitive position. Nonetheless, being relevantly novel, it still remains unclear as to how it is possible to make the most out of social media, especially in competitive and highly dynamic environments. As with any new technology, it is important to understand the mechanisms and processes through which social media can be of business value for companies in order to incorporate them into their competitive strategies. To this end, the present paper aims to provide a theoretical discussion leading up to a conceptual research framework that can help explain the mechanisms through which social media and analytics lead to competitive performance gains. The conceptual research framework builds on the resource-based view (RBV) and dynamic capabilities view (DCV) of the firm, and provides a synthesis of the two theoretical perspectives.

Ilias O. Pappas, Patrick Mikalef, Michail N. Giannakos, John Krogstie, George Lekakos

iCRM Workshop


Social CRM: Biggest Challenges to Make it Work in the Real World

The ways of communication and social interactions are changing and web users are becoming increasingly engaged with Online Social Networks (OSN). This fact has significantly impact in the relationship mechanisms between companies and customers. Thus, a new approach to perform Customer Relationship Management (CRM) is arising, the Social CRM (SCRM). Aiming to identify state of art, a literature review was conducted to demonstrate the current state of knowledge about the topic. In addition, expert interviews and events organized by researchers involved in this project, helped in challenges validation. As main contributions, it is possible to highlight: (i) identification, categorization and discussion of SCRM most prominent challenges; and (ii) construction of a SCRM service portfolio; (iii) estimation of the distance between state of art and state of practice. Therefore, the results obtained point out a number of future research directions, demonstrating that Social Customer Relationship Management is an emerging and promising research topic.

Fábio Lobato, Márcia Pinheiro, Antonio Jacob, Olaf Reinhold, Ádamo Santana

Emotions in Online Reviews to Better Understand Customers’ Brand Perception

Measuring customers’ opinions based on online customer reviews pose an integral part of Social CRM. However, polarity analysis, i.e., positive vs. negative opinion, fails to map the emotional mindset of customers. To complement existing Social CRM tools with a comprehensible, yet efficient way of measuring emotions towards brands, a model is presented to differentiate eight basic human emotions. Emotion terms get extracted and categorized review-wise by an eight dimensional emotion lexicon into eight dimensional feature vectors. These vectors train the random forest classifier to distinguish positive helpful from negative helpful reviews. The classifiers inherent ability to display single feature importance enables marketers to infer the importance of each basic emotion. The ability to measure the interrelationship of emotions towards brands equips marketers with a powerful tool to better understand consumers and to adapt CRM campaigns accordingly. Along with the technicalities of the model a way of interpreting results is presented.

Armin Felbermayr

Performance Evaluation of Sentiment Analysis Methods for Brazilian Portuguese

Daily, a big data of media, thoughts and opinions can be noticed on Online Social Networks (OSN), resulting from their user’s interaction and sharing of information. In Brazil, this is strongly observed, as Brazilians are often active on the Internet. The business and academic communities around the world are aware of these events, due their possibilities to improve social customer relationship management. Therefore, this work aims to show a performance comparison between algorithms for Sentiment Analysis (SA), in their Portuguese and English versions, with datasets composed of Brazilian Portuguese comments from OSN, and their translations. The results highlight the need for proposals in specific language and Social Media context, given the performance presented by Portuguese version methods.

Douglas Cirqueira, Antonio Jacob, Fábio Lobato, Adamo Lima de Santana, Márcia Pinheiro

Social Media Analytics Using Business Intelligence and Social Media Tools – Differences and Implications

The increasing amount of content created in Social Media platforms is calling for sophisticated filters that separate relevant from non-relevant content. Social Media Analytics (SMA) is a field that addresses this challenge by the development of strategies, methods and technologies to automate this filtering process. This work in progress paper presents an experiment, which examined two Social Media (SM) applications as well as two Business Intelligence (BI) applications for the analysis of tweets. The overall goal is to identify differences of these tool categories with regard to the analytics process itself as well as the obtained results. Using the scenario of a fitness tracking application for smartphones, data from Twitter was collected and analyzed with applications of both categories. The findings show (1) differences between BI and SM application, (2) challenges resulting from the different analytics processes, and (3) hints for decision makers as well as data analysts when to use which category for analyzing social content.

Matthias Wittwer, Olaf Reinhold, Rainer Alt, Finn Jessen, Richard Stüber

Assessment of Business Benefits for the Operation of a Smart City Energy Management Platform

Managing energy production and consumption on a city level is an important, yet challenging task, since an increasing number of volatile renewable energies are being connected to the grid. Smart city energy management platforms could constitute a powerful tool for the involved market actors to effectively integrate renewable energies and thereby to refine existing business models. However, the implementation of such energy management tools is often hindered by privacy concerns or the lack of awareness about connected business benefits. In this paper, we present the concept for a decision support system that is tested in two pilot cities in Croatia and Bulgaria. Furthermore, we present a framework for the identification of the business benefits that are connected with the implementation of such a tool.

Stefan Reichert, Jens Strüker

IDEA Workshop


A Meta-Framework for Efficacious Adaptive Enterprise Architectures

Tuning enterprise architectures to stay competitive and fit is an enduring challenge for organizations. This study postulates a meta-framework for Efficacious Adaptive Enterprise Architectures (EA), the 2EA framework. We use fundamental long-standing principles found in complex adaptive systems. These principles explain adaptive success. Also, we set forward managerial implications about the dynamics of EA to function effectively on four architectural levels, i.e. enterprise environment, enterprise, enterprise systems and infrastructure. Principles of efficacious adaptation have not been incorporated into current EA frameworks and methods underlining an improvement area. Subsequently, we extend baseline work into a meta-framework and evaluate it accordingly following the design science method. Our meta-framework supports organizations to assess and adapt EA capabilities – modular units of functionality within the organization – to the continuously changing environment, stakeholder interests and internal organizational dynamics. Our research contributes to foundational work on EA and can be used for strategic EA development and maturation.

Rogier van de Wetering, Rik Bos

Multi-perspective Digitization Architecture for the Internet of Things

Social networks, smart portable devices, Internet of Things (IoT) on base of technologies like analytics for big data and cloud services are emerging to support flexible connected products and agile services as the new wave of digital transformation. Biological metaphors of living and adaptable ecosystems with service-oriented enterprise architectures provide the foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems. We are extending Enterprise Architecture (EA) with mechanisms for flexible adaptation and evolution of information systems having distributed IoT and other micro-granular digital architecture to support next digitization products, services, and processes. Our aim is to support flexibility and agile transformation for both IT and business capabilities through adaptive digital enterprise architectures. The present research paper investigates additionally decision mechanisms in the context of multi-perspective explorations of enterprise services and Internet of Things architectures by extending original enterprise architecture reference models with state of art elements for architectural engineering and digitization.

Alfred Zimmermann, Rainer Schmidt, Kurt Sandkuhl, Dierk Jugel, Justus Bogner, Michael Möhring

Data-Centered Platforms in Tourism: Advantages and Challenges for Digital Enterprise Architecture

Digitization changes business processes and enterprise architectures in many sectors. In the Tourism sector more and more data must be analyzed and integrated into business processes. Therefore, the current architecture must be changed to a more flexible, data-driven one. Besides the basements of current Tourism application, we investigate which scenarios are possible via data-centered platforms in Tourism and how this transformation can be done.

Barbara Keller, Michael Möhring, Martina Toni, Laura Di Pietro, Rainer Schmidt

Applying the Research on Product-Service Systems to Smart and Connected Products

Digitalization has changed media and retail industry in the last decades dramatically. Currently the focus switched to physical products enhanced or completely re-thought by digitalization. These products are called smart and connected products by Porter and Heppelmann, as they have smart components (i.e. computing power) in the product and are connected to a product cloud. By that, the products are enhanced with a strong service component. Since the late 90’s, there was a substantial amount of research on product-service systems (PSS). In this position paper we analyze the research on PSS and apply it to smart and connected products.

Lars Brehm, Barbara Klein

INCLuDE Workshop


An Architectural Model for High Performance Pattern Matching in Linked Historical Data

In times of global digitalization and interconnectedness the virtual Cyber Physical Systems (CPS) are getting more and more on importance. These CPS and their relations among themselves can be investigated using appropriate data acquired by the inherent sensors. The multivariate, multiscale, multimodal sensor data can be modeled and analyzed as a dynamically evolving spatio-temporal complex network. These graphs as well as the patterns estimated in historical data can then be used for real time comparison with momentary computed patterns. Therefore providing linked data from memory is an important need to accomplish real time constraints especially in case of CPS in critical medical systems. Since the handling of graphs in the traditional relational database systems is problematic an encouraging approach is the storage of these data in graph databases which are appropriate for the handling of linked data. Therefore we propose the graph database Neo4J and demonstrate first applications of the approach within medical use-cases.

Michael Aleithe, Ulrich Hegerl, Galina Ivanova

Research in Progress: Implementation of an Integrated Data Model for an Improved Monitoring of Environmental Processes

How can we benefit from innovative open-source technologies such as mobile sensors and open data platforms in the field of environmental monitoring? Due to the fact that we are facing challenging problems in terms of climate change, urbanization and a growing world population, new strategies for a more comprehensive environmental monitoring have to be developed. Here, we need to create user-specific and easy to use infrastructures as assistance tools for a comprehensive and mobile data acquisition, data processing and data provision. With regard to the variety of existing data sources, data acquisition tools and scales, this paper is focused on strategies and methods for an service oriented monitoring approach based on an integrated data model. To this end, a formal connection was defined by combining spatial, temporal and contextual information of sensor readings into one measure called the individual specific exposure (ISE), which will be later extended to a predictive individual exposure by using historical data.

Robert Schima, Tobias Goblirsch, Christoph Salbach, Bogdan Franczyk, Michael Aleithe, Jan Bumberger, Peter Dietrich

Exploring Context from the Consumer Perspective: Insights from eBusiness and Health Care

Many electronic services are not used in isolation, but in the context of a specific user. This user, customer or patient perspective is different from the perspective of service providers since customer processes usually involve multiple service providers. Information on the context helps to understand these user needs and to improve the coordination among services. This research in progress paper examines existing contributions as a basis towards an understanding of the concept and modeling of “context” from a context provider’s perspective and proposes a preliminary model, which also serves to analyze four use cases. The paper summarizes challenges observed in these cases and presents an agenda for further research.

Olaf Reinhold, Matthias Wittwer, Rainer Alt, Toralf Kirsten, Wieland Kiess

Research in Progress on Integrating Health and Environmental Data in Epidemiological Studies

Epidemiological studies analyze and monitor the health state of a population. They typically use different methods and techniques to capture and to integrate data of interest before they can be analyzed. As new technologies and, thus, devices are available for data capturing, such as wearables, new requirements arise for current data integration approaches. In this paper, we review current techniques and approaches as well as new trends in data capturing and the resulting requirement for its integration.

Toralf Kirsten, Jan Bumberger, Galina Ivanova, Peter Dietrich, Christoph Engel, Markus Loeffler, Wieland Kiess

Doctoral Consortium


Decision Support Enhancement for Player Substitution in Football: A Design Science Approach

Football players are constantly being tracked during the live games by means of automated tracking technologies. Every event that happens on the field is recorded in a who-what-where-when fashion. These data are used in pre- and post-match analyses to improve strategies and tactics. To date such data have not yet been used for in-game decision making. Considering the impact of the substitute players on the final outcome of the game, this paper proposes an approach for enhancing the substitution decision. The goal is to support the coach and his staff during live matches by developing an algorithm or using an existing analytic method which will evaluate and rate the players’ performance and recommend a player that should leave the game.

Pavlina Kröckel

A Bayesian Network Approach to Assessing the Risk and Reliability of Maritime Transport

The paper presents a conception of a doctoral dissertation, which concerns the problem of estimation of maritime risk and reliability of maritime transport services. In the dissertation a method for dynamic risk assessment based on the Bayesian Network approach is presented. The method concern the risk of an individual ship and its aim is to identify ships, which pose a potential threat due to their individual behaviour and characteristics. Within the article, the following aspects of the dissertation are presented: motivation standing behind the research, main assumptions for the proposed method, its novelty in comparison to existing solutions as well as preliminary results.

Milena Stróżyna

Development of an Information System Architecture for Online Surgery Scheduling

This work presents the current state of a PhD thesis about optimizing decision-making in operating room management with an integrated information systems architecture for a decision support system. A design-science research approach is used to develop an architecture that fills the gap for operational decision support by integrating data sources, decision support models and real-time information. After identifying the current state-of-the-art in operational decision support systems, a requirements analysis was started. The first results lead to an architecture in development status. Future work will complete requirements and architecture model and further in a prototypical implementation for evaluation.

Norman Spangenberg

Towards Automatic Business Networks Identification

Dynamic changes on of the business environment force business experts to continuously monitor and analyze situation and relations on the market. Due to the volume of available data and huge number of entities that operates on most markets, it is very time and cost consuming to perform the analysis manually. The paper presents an outline of analysis method that focus on identification on business networks and analysis of business environment of the specific business entity. The method operates on a set of semantically described profiles that are automatically processed and analyzed according the to user’s criteria.

Elżbieta Lewańska

Classification of Data Analysis Tasks for Production Environments

In the age of “Industry 4.0”, the rising amount of data from production environments is primarily used to control the operational production environment. However, companies frequently do not exploit the data’s potential for strategic and tactical decision making. A possible reason is that many data analysis tools follow a method-centric perspective, which is not compatible with the problem-centric view of the tasks of a particular department. This dissertation project investigates the theoretical and practical improvement of data analysis processes in industrial corporations. To overcome these often distinct perspectives and foster the implementation of state-of-the-art methods of data analysis such as data mining, we propose the standardization of data analysis tasks in industrial corporations by construction of a reference model that can help building data analysis tools. As a first step, we survey different types of analysis tasks arising in the environment of the automotive industry, namely the AUDI AG.

Sebastian Eckert, Jan Fabian Ehmke

Toward a Configuration Model for User-Oriented Representations of Analytical Services

Currently there is insufficient support regarding the user-oriented modeling of analytical information systems. More precisely, there is a lack of semiformal and detailed conceptual models, which could represent the functional and nonfunctional requirements of analytical users. Addressing this issue, this article motivates the development of a conceptual analytical service configuration model, gives a short insight into previous research and describes the range of necessary modeling content, which contains functional and nonfunctional requirements of the user context. Then, this article presents first ideas concerning the model structures and discusses potential application areas.

Christian Hrach

Improving the Quality of Art Market Data Using Linked Open Data and Machine Learning

Among numerous research studies devoted to art markets, very little attention is given to the quality of the data. Availability of a decent amount of observations is a problem in many fields; the art market is no different, especially in Poland. Therefore, it constitutes a severe obstacle in explaining the market behaviour. The use of Linked Open Data and Machine Learning can pave the way to improve the quality of data and enrich results of other art market research as a consequence, such as building indices. This paper is an outline of the method for combining such fields and summarises effort already made to achieve that.

Dominik Filipiak, Agata Filipowska


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