Secondments

RISE_BPM's Innovation and Staff Exchange will be documentend in terms of secondments. They will be presented and archived within this section. 

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2016-08-30–2016-09-30: Wirtschaftsuniversität Wien (WU) to Universidade Federal do Estado do Rio de Janeiro (UNIRIO)

Saimir Bala

Researcher: Saimir Bala

Researcher Category: Early stage researcher
Website: https://www.wu.ac.at/en/infobiz/team/bala/en
Goal of the stay:

Software development projects often need to adhere to predefined guidelines or carried out according to a specific process. This is, for instance, when building software for human and data centric processes, which are subject to strict rules and regulations. However, normally the software development process is not managed by a process engine. To ease the burden of the monitoring or the retrospective analysis of its activities, an automated discovery of the software development process is required. The goal of this secondment is to research effective ways to discover clues of software development activities by analysing log data from Version Control Systems. Natural language processing (NLP) techniques will be used in order to classify user comments into specific activities of a software development process.

 


Work package addressed: WP1: Technological Enablers – Social Media (Phase 1)

2016-08-28–2016-09-27: Wirtschaftsuniversität Wien (WU) to Universidade Federal do Estado do Rio de Janeiro (UNIRIO)

Claudio Di Ciccio

Researcher: Claudio Di Ciccio

Researcher Category: Experienced researcher
Website: http://www.wu.ac.at/infobiz/team/diciccio/en/
Goal of the stay:

Knowledge-intensive Processes (KiPs) are business processes lying on the intersection between the BPM and the Knowledge Management (KM) fields . They are collaborative workflows which heavily depend on the tacit knowledge of the participants, which drives the decisions and strategies taken during the process life-cycle. Owing to that, they tend to be very flexible, as they can change at every instantiation. This characteristic suggests the utilisation of declarative specifications of their behaviour. In the light of the above, the objective of the secondment is to join the respective expertise acquired in the field by the partners in order to further advance in the investigation of KiP mining. In particular, studies will be conducted to enhance the declarative process discovery algorithms with Natural Language Processing techniques, both to aggregate the extracted information, and enlarge the possibility to mine KiPs out of partially structured or unstructured texts. The actors of a KiP cooperate by means of the exchange of information in the so-called knowledge items. Due to the prominent role that information and resource perspectives play in KiPs, it is of high interest and hence in the plans to devise new approaches capable of mining not only the control flow, but also the knowledge items and the active participants in the context of KiPs.  


Work package addressed: WP1: Technological Enablers – Social Media (Phase 1)

2016-08-22–2016-12-21: Westfälische Wilhelms-Universität Münster (WWU) to University of Liechtenstein (UNI-LI)

Markus Monhof

Researcher: Markus Monhof

Researcher Category: Early stage researcher
Website: http://www.erc.is/p/markus.monhof
Goal of the stay:

The goal of the secondment is to extend previous research on quality in smart service processes that was conducted during a previous secondment. Data from social media (WP1) is analyzed using big data technologies (WP4 ) to gain insights on influence factors and outcomes of service quality. Smart devices (WP2) as potential enablers of high quality in services processes are examined.

Furthermore, a business process for the reconfiguration of used electric vehicle batteries that is enabled by smart battery monitoring (WP2) soultions is developed.


Work packages addressed: WP1: Technological Enablers – Social Media (Phase 1), WP2: Technological Enablers – Smart Devices (Phase 1), WP4: Technological Enablers – Big Data Technology (Phase 1)

2016-08-05–2016-08-19: University of Liechtenstein (UNI-LI) to Wirtschaftsuniversität Wien (WU)

Bernd Schenk

Researcher: Bernd Schenk

Researcher Category: Experienced researcher
Website: https://www.uni.li/de/universitaet/institute/institut-fuer-wirtschaftsinformatik
Goal of the stay:

The goal of this secondment is to investigate the potential of Enterprise Systems for different kinds of innovations like process innovation and digital innovation. Due to latest technologies established in the field of Enterprise Systems (e.g. Big Data and In-Memory Computing) the role of Enterprise Systems changes to a more active one, being not just an enabler but driver of innovation for many companies.

 


Work package addressed: WP4: Technological Enablers – Big Data Technology (Phase 1)

2016-08-04–2016-09-05: Wirtschaftsuniversität Wien (WU) to University of Liechtenstein (UNI-LI)

Gerhard Wohlgenannt

Researcher: Gerhard Wohlgenannt

Researcher Category: Experienced researcher
Website: http://www.wu.ac.at/infobiz/team/wohlgenannt
Goal of the stay:

With the exponential growth of data available on the Web, especially in the from of unstructured natural language text, text mining technologies are crucial components in business analytics and big data analysis. Obviously, BPM can benefit from text mining methods and tools, too.
In the from of a use-case study, we will apply state-of-the-art text mining methods to extract opinions and topics in the 2016 US presidential election campains. More precisely, we analyse data from the Twitter Streaming API about the presidential candidates, and use methods such as topic modeling and word embeddings to gain insights about the motivations and opinions of social media users. For topic modeling we apply Latent Dirichlet Allocation (LDA), and for word embeddings the word2vec toolkit. We also develop a Web interface to present and visualize the results of the various analysis components like LDA topic modelling and word embeddings. The Web interface builds on existing tools such as pyLDAvis and the Webvectors (RusVectōrēs) toolkit.


Work packages addressed: WP1: Technological Enablers – Social Media (Phase 1), WP4: Technological Enablers – Big Data Technology (Phase 1)

2016-08-01–2016-08-12: University of Liechtenstein (UNI-LI) to Westfälische Wilhelms-Universität Münster (WWU)

Isabell Wohlgenannt

Researcher: Isabell Wohlgenannt

Researcher Category: Early stage researcher
Website: https://www.uni.li/isabell.wohlgenannt
Goal of the stay:

The goal of the secondment is to cooperate on data analysis in the field of gamification with researchers from University of Münster. Goal of the research project is the identification of gaming mechanisms and skills which might be relevant for showing high performance in strategy games and in work life. Companies could modify their way of assessing applicants in accordance to the results of this research project.


Work package addressed: WP1: Technological Enablers – Social Media (Phase 1)

2016-08-01–2016-08-12: University of Liechtenstein (UNI-LI) to Westfälische Wilhelms-Universität Münster (WWU)

Alexander Simons

Researcher: Alexander Simons

Researcher Category: Experienced researcher
Website: https://www.uni.li/de/universitaet/institute/institut-fuer-wirtschaftsinformatik
Goal of the stay:

The goal of the secondment is to cooperate on data analysis in the field of gamification with researchers from University of Münster. Goal of the research project is the identification of gaming mechanisms and skills which might be relevant for showing high performance in strategy games and in work life. Companies could modify their way of assessing applicants in accordance to the results of this research project.


Work package addressed: WP1: Technological Enablers – Social Media (Phase 1)

2016-08-01–2016-08-12: University of Liechtenstein (UNI-LI) to Westfälische Wilhelms-Universität Münster (WWU)

Markus Weinmann

Researcher: Markus Weinmann

Researcher Category: Experienced researcher
Website: https://www.uni.li/markus.weinmann
Goal of the stay:

The goal of the secondment is to cooperate on data analysis in the field of gamification with researchers from University of Münster. Goal of the research project is the identification of gaming mechanisms and skills which might be relevant for showing high performance in strategy games and in work life. Companies could modify their way of assessing applicants in accordance to the results of this research project.


Work package addressed: WP1: Technological Enablers – Social Media (Phase 1)

2016-07-29–2016-08-31: Wirtschaftsuniversität Wien (WU) to Queensland University of Technology (QUT)

Jan Mendling

Researcher: Jan Mendling

Researcher Category: Experienced researcher > 10 years
Website: http://www.wu.ac.at/infobiz/team/mendling/en/
Goal of the stay:

This research visit to QUT Brisbane is dedicated to the investigation of process query languages for managing process-related event data such as from RFID readers, GPS signals, AIS transponders of other sorts of event data. In order to analyze such data, it is typically required to conduct various steps of pre-processing including filtering, aggregation and matching. Todays process mining tools do not directly support such operations, but rather assume that the process-related event log data is harmonized and integrated. The objective of ongoing research with QUT is to develop a process query language for handling process-related event log data that supports all these pre-processing operations.


Work package addressed: WP1: Technological Enablers – Social Media (Phase 1)

2016-07-10–2016-07-16: Wirtschaftsuniversität Wien (WU) to CUPENYA B.V. (CUP)

Manuel Raffel

Researcher: Manuel Raffel

Researcher Category: Early stage researcher
Website: http://www.wu.ac.at/infobiz/team/raffel/en/
Goal of the stay:

the last part consists of summarization and feedback rounds aimed at evaluating the collaborative performance as well as decide upon possible future collaborations, including but not limited to finding master’s thesis or dissertation topics relevant for the industry to be conducted with the Institute for Information Business.


Work package addressed: WP1: Technological Enablers – Social Media (Phase 1)

2016-07-01–2016-11-01: Westfälische Wilhelms-Universität Münster (WWU) to Universidade Federal do Estado do Rio de Janeiro (UNIRIO)

Friedrich Chasin

Researcher: Friedrich Chasin

Researcher Category: Early stage researcher
Website: http://erc.is/p/chasin
Goal of the stay:

Uber, the world’s largest taxi company, owns no vehicles and And Airbnb, the world’s largest accommodation provider, owns no real estate. There are areas of goods and services, where consumers needs can be satisfied by mere access to a resource instead of actual ownership. These markets for peer-to-peer (P2P) sharing and collaborative consumption (SCC) gathered under the to share term of the sharing economy describe a phenomenon, that has experienced strong growth in the past years. As of today, there are more than 10.000 web platforms that consider themselves part of the sharing economy. These platforms depend on the efficient execution of Smart-IT-enabled processes. However, neither reference processes exist for P2P SCC platforms nor the role of smart devices in the establishment and management of these processes is yet understood.

The goal of the secondment is to build upon the research outcomes of a previous RISE_BPM collaboration between the University of Muenster and Pohang University of Science and Technology. The analysis of the processes and the structures of the P2P SCC enterprises under the umbrella of the Sharing City Seoul Initiative provided first reference materials and hypotheses in regard to how P2P SCC platforms manage their processes and build upon the use of smart devices such as location-based sensors for efficient match-making between peers. A particular goal is to improve the understanding of how smart devices are utilised by these sharing businesses in order to facilitate the sharing between individuals. We plan to do it by extending the scope of the analyzed P2P SCC platforms specifically looking at the corresponding enterprises located in Brazil. By means of semi-structured interviews and platform analyses, we aim at enriching our understanding of BP references models in the domain of P2P SCC.  As the individual behavior of peers is decisive for the success of any P2P SCC enterprise we furthermore analyze the social impact factors on the BPM of sharing economy businesses. A look at different social environments such as Europe, South Korea, and Brazil gives us a unique opportunity to understand the differences and similarities in the social impact on P2P SCC BPM.

This stay addresses WP2: Technological Enablers – Smart Devices (Phase 1), WP5: Analysis of Societal Impact Factors (Phase 1) 


Work packages addressed: WP2: Technological Enablers – Smart Devices (Phase 1), WP5: Analysis of Societal Impact Factors (Phase 1)

2016-06-28–2016-07-15: Universidad de Sevilla (USE) to Universidade Federal do Estado do Rio de Janeiro (UNIRIO)

Adela del-Rio-Ortega

Researcher: Adela del-Rio-Ortega

Researcher Category: Experienced researcher
Website: http://www.isa.us.es/adela.delrio
Goal of the stay:

The goals of this secondment are framed into two contexts: Process model understandability and validation and Business Process-Oriented Knowledge Management (BPO-KM). In the following we introduce them and set the goals:

  1. Business process models are artifacts that can be used to support the understanding of how to obtain a service or product. However, the misunderstanding produced by “hard” process model notations prevents not only the understanding of the process, but also the implementation of appropriate tools to support them and the current practice of a service. One goal of this secondment is to build upon previous research results of the collaborating groups (from UNIRIO and USE) and other existing approaches to investigate possible mechanisms to automatically obtain highly understandable process models from existing BPMN models.
  2. Knowledge Management aims to promote the growth, communication and preservation of knowledge within an organization, which includes managing the appropriate resources to facilitate knowledge sharing and reuse. Business Process-Oriented Knowledge Management (BPO-KM) focuses on discovering and representing the dynamic conversion of existing knowledge among participants involved in executing business processes. In this context, Knowledge-Intensive Processes (KPIs) are a very important and challenging specific subclass of processes, since they strongly involve socialization and informal exchanges of knowledge among participants. BPO-KM aims at identifying, modeling, analyzing and refining KIPs. As part of this, the performance measurement of KIPs plays a key role for their holistic management and improvement. In this secondment we plan to investigate how existing approaches for the definition of process performance indicators can be adapted or extended to measure the performance of KIPs.

Work package addressed: WP3: Technological Enablers – Real-time Computing (Phase 1)

2016-06-02–2016-08-10: Westfälische Wilhelms-Universität Münster (WWU) to Universidade Federal do Estado do Rio de Janeiro (UNIRIO)

Benjamin Klör

Researcher: Benjamin Klör

Researcher Category: Experienced researcher
Website: https://www.wi.uni-muenster.de/de/institut/gruppen/is/personen/benjamin-kloer
Goal of the stay:

„Smart Business Process for Reconfiguring Electric Vehicle Batteries“

Motivation

Electric vehicle batteries (EVBs) are large energy storage facilities to propel electric vehicles (EVs) over significant distances. EVBs are designed for modularity and comprise of parallel connected battery modules (increase total amperage), which again consist of plenty of serially connected battery cells (increase total voltage). Due to degradation effects (calendric and cyclic aging), the quality of EVBs decreases over time, which necessitates their removal from the EVs (first life application) after approximately ten years of usage. However, the batteries still provide enough energy to be repurposed in various second life scenarios, e.g., as buffer storages in smart homes or solar plants.

Like many other used products that are intended for a second life, EVBs must be handled by a dedicated business process to organize, e.g., their take back, refurbishment, reconfiguration, and redistribution. Because of the specific characteristics and properties of EVBs as a cyber-physical system (integrated battery management system (BMS), which is a “smart device”), the business process for giving batteries a second life may become “smart(er)”.

Research Endeavor

To design such a business process, it is necessary to review current process instances of reconfiguring/repurposing used products/goods to analyze possible activities, which can become smart. We define “smart” by the degree of business process automation and efficiency that can be reached by using smart devices and IS. Then, based on the findings of the process instances, the repurposing process for used EVBs is derived with a special focus on their reconfiguration, since this activity is considered to be one block in the process chain that may become smart(er).

As yet, we think that the reconfiguration of EVBs can become smart due to the EVBs’ modular design and the included smart device (BMS), which can provide comprehensive data about the status and usage history of the battery. This data can be used to feed decision models for optimizing the reconfiguration process. The decision models shall make use of linear programming to generate a set of feasible reconfigured batteries that optimally satisfy the requirements of second life scenarios, which could not be supplied with a battery in the first round of battery matching. Consequently, by reconfiguring batteries on pack and module levels, battery systems can be supplied to more or less demanding second life scenarios.


Work package addressed: WP2: Technological Enablers – Smart Devices (Phase 1)

2016-05-26–2016-06-24: Universidade Federal do Estado do Rio de Janeiro (UNIRIO) to Universidad de Sevilla (USE)

Flavia Maria Santoro

Researcher: Flavia Maria Santoro

Researcher Category: Experienced researcher
Website: http://lattes.cnpq.br/5377746284077362
Goal of the stay:

The main goal of this secondment is to analyze computing concepts to real-time monitoring and control of business processes. This goal is aligned with WP3: Technological Enablers – Real-time Computing (Phase 1). Specifically, a study on the discovery of relevant context information for modeling the business process will be done. The approach to be adopted will: propose and create mechanisms to support an organization to adapt and dynamic evolution of its processes, automatically or semi-automatically based on context information. This support is accomplished through the analysis of the current context and also the reasoning of the historical process of events in previous instances.

The other goal of this second is to identify potential interests and possibilities of integrating the research on BPM related to RISE-BPM of both groups.


Work package addressed: WP3: Technological Enablers – Real-time Computing (Phase 1)

2016-04-05–2016-05-05: Technische Universiteit Eindhoven (TU/e) to Ulsan National Institute of Science and Technology (UNIST)

Sebastiaan Zelst, van

Researcher: Sebastiaan Zelst, van

Researcher Category: Early stage researcher
Website: http://www.win.tue.nl/~svzelst/
Goal of the stay:

Resource Network analysis in data intensive environments. Given the omnipresence of data, and, the high velocity at which data is produced within business processes, interesting questions arise such as: what resources are currently active? what resource is causing problems? What clusters of resources can we identify? etc. During the research visit we focus on discovering, visualizing analyzing such information, using a process mining focus. We investigate the intersection of existing (process mining based) social network analysis techniques, and, techniques aiming at handling huge amounts of (streaming) data.


Work package addressed: WP4: Technological Enablers – Big Data Technology (Phase 1)

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