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Research Projects

BOSS

Behavior Oriented Service Substitution

Description

The Service Oriented Computing (SOC) paradigm aims at building complex systems by composing them from less complex systems, called services. Such a (complex) system is a distributed application often involving several cooperating enterprises. As a system is usually subject to change, individual services will be substituted by other services during the system's life-cycle. Substituting one service by another one should not affect the correctness of the overall system. Verification of correctness is challenging, as the overall system is usually not known to any of the involved enterprises. The focus of the BOSS project is to study service substitution for a set of practical relevant correctness notions. The project is funded by NWO.

Staff involved

CoSeLoG

Configurable Services for Local Governments

Description

The Software as a Service (SaaS) paradigm is particularly interesting for situations where many organizations need to support similar processes. Since there are 441 municipalities in the Netherlands and they are all providing similar services and are executing similar processes, the use of SaaS technology could potentially be very beneficial for these local governments. Therefore, the aim of the CoSeLoG project is to create a cloud infrastructure for municipalities. Such a cloud would offer services for handling various types of permits, taxes, certificates, and licences.

Although municipalities are similar, their internal processes are typically different. Within the constraints of national laws and regulations, municipalities can differentiate because of differences in size, demographics, problems, and policies. Therefore, the cloud should provide configurable services such that products and processes can be customized while sharing a common infrastructure. The CoSeLoG project aims at the development and analysis of such services. For this we want to use earlier work on configurable process models done at TU/e, QUT, and UT.

One challenge is to actually describe the different variants of a particular municipal service in a single model that can be used to generate the actual configured services. Note that many different variants of a particular service may run in parallel in our cloud. Such a cloud infrastructure for municipalities enables new types of analysis as there is detailed data about the execution of different variants of a given process in different organizations.

A challenge is to develop new process mining techniques that allow for the comparison of event logs of different variants of the same process. Such techniques should highlight differences and commonalities and should assist municipalities in configuring services in a better manner.

The following municipalities are involved in this so-called Jacquard project: Bergeijk, Bladel, Coevorden, Eersel, Emmen, Gemert-Bakel, Hellendoorn, Reusel de Mierden, and Zwolle.

Staff involved

DeLiBiDa

Desire Lines in Big Data

Description

The goal of process mining is to extract process-related information from event logs, e.g., to automatically discover a process model by observing events recorded by some information system. Despite recent advances in process mining there are still important challenges that need to be addressed. In particular with respect to handling large-scale event logs. DeLiBiDa aims to develop new techniques to deal with massive event data. There are various settings where it is impossible to store events over an extended period. Therefore, we want to develop techniques for storing large event logs efficiently, for example in databases. Furthermore, we aim to develop in-database (pre)processing techniques to facilitate existing as well as new to be developed process mining technology. Finally, we plan to develop query techniques to make event-data quickly accessible for processing.

Links

Staff involved

DSC/e & NWO Graduate Program

Data Science Center Eindhoven

Description

Recent technological and societal changes led to an explosion of digitally available data. Exploiting the available data to its fullest extent, in order to improve decision making, increase productivity, and deepen our understanding of scientific questions, is one of today's key challenges. Data science is an emerging area that aims to address this challenge. It is a multi-disciplinary area, where computer science and mathematics play crucial roles. The Graduate Program on Data Science leverages the presence at the TU/e of excellent research groups in the data-science area, and to give highly talented students the opportunity to be educated in and contribute to this exciting area. The positions are funded by the NWO Graduate Program.

The Graduate Program on Data Science is part of the Data Science Center Eindhoven (DSC/e), launched in December 2013. It builds on the excellence of several research groups within the department that together cover many of the core topics in data science: algorithms, visualization, data mining, process mining, statistics and probability, stochastics, operations research, and optimization. This ensures a stimulating and excellent environment for the selected students.

The projects fall at the intersection of computer science and mathematics, and are expected to open up promising connections between these fields. Together with the intended supervisors from the relevant research group(s), the students will have the opportunity to define their own research project. The overall aim is to make fundamental advances in the area of Data Science.

Links

Staff involved

EDSA

European Data Science Academy

Description

The European Data Science Academy (EDSA) will establish a virtuous learning production cycle whereby we: a) analyse the required sector specific skillsets for data analysts across the main industrial sectors in Europe; b) develop modular and adaptable data science curricula to meet these needs; and c) deliver training supported by multi-platform and multilingual learning resources based on our curricula. The curricula and learning resources will be continuously evaluated by pedagogical and data science experts during both development and deployment.

Links

Staff involved

Fluxicon

X-ray for Business Processes

Description

Fluxicon is a spin-off of the process mining research done at TU/e. Two STW Valorisation Grants (Phase 1 & 2) have been granted to set up a process mining company that will develop easy-to-use process mining software.

Links

Staff involved

RISE BPM

“Propelling Business Process Management by Research and Innovation Staff Exchange”

Description

RISE_BPM is the first favourably evaluated project proposal submitted by the University of Münster in cooperation with ERCIS partners within the Horizon 2020 EU funding programme. The RISE_BPM project is aimed at networking world-leading research institutions and corporate innovators to develop new horizons for Business Process Management (BPM). The project consortium, besides the University of Münster as the coordinator, includes partners from Australia, South Korea, Brazil, Austria, Spain, the Netherlands, and Liechtenstein.

RISE_BPM was set up to ensure the sustainability and further extension of the collaboration ties established during the Networked Service Society (NSS) project. NSS (Project number: APR 10/805) is a multi-national project funded by the International Bureau of the German Federal Ministry of Education and Research (BMBF). The project was conducted from July 2010 until the end of 2014 and was aimed at establishing and strengthening long-term collaboration structures with institutions in the Asian-Pacific region in the areas of Joint Research, Joint Education and Joint Industry Projects.

RISE_BPM will last for four years and started May 1st 2015.

Links

Staff involved


If you have a project item for this page, please send it to Eric Verbeek.