We invite applications for a
PhD position (100%) at HEC Lausanne
in the Competence Center Corporate Data Quality (CDQ)
Data sharing platforms and open/external data services
The PhD position will contribute to the design, implementation and evaluation of a Data App Store that supports businesses in the discovery, integration and use of external data. The PhD candidate will be employed at HEC Lausanne and work in the Competence Center Corporate Data Quality (CC CDQ – cc-cdq.ch). CC CDQ is an industry-funded research consortium that is researching, developing and testing solutions that advance data management in digital and data-driven enterprises. CC CDQ is being conducted between the Universities of Lausanne and St. Gallen and 20 renowned European companies (Bosch, Merck, Nestlé, PMI, SBB, Siemens etc.).
- Master’s degree in Information Systems, Computer Science or related field
- Strong interest in one or more of the following topics: data catalogs, data sharing platforms, linked and open data, semantic Web and ontologies
- Professional experience (e.g. as consultant) and/or relevant internships
- Excellent analytical and communication skills
- Good writing skills and fluency in English; German and/or French are a plus
Employment rate is 100% with a competitive salary and maximum contract duration isfive years. Starting date is negotiable from October 2018 until the position is filled.
The PhD candidate is expected to enrol in the doctoral school in information systems at HEC Lausanne and will be supervised by Prof. Christine Legner.
Job announcement: UNIL-CDQ-PhD_201809_cle.pdf
Informal inquiries and how to apply:
For any inquiry about the PhD positions, please contact Prof. Christine Legner:
firstname.lastname@example.org or +41 21 692 3432.
Competence Center CDQ www.cc-cdq.ch
HEC Lausanne, hec.unil.ch
Prof. Christine Legner, www.unil.ch/bisa
We welcome Matthieu Harbich as new researcher in our team!
Matthieu received his M.Sc. in Information Systems at the Faculty of Business and Economics (HEC), University of Lausanne. Previously, he worked at the Kudelski Group as a Data Scientist intern. His Master’s thesis suggested a generative clustering algorithm to understand customer’s behaviors in the Pay-TV industry and reduce churn. He completed his B.Sc. in Media engineering at the HES-SO with a Bachelor’s thesis on building and designing a web-based interactive video editing product, based on an open-source JS library written for this purpose.
Matthieu is currently working in the CTI project “Open Data to Business – Data App Store for the discovery, integration and use of open data in business environments”. Its aim is to link heterogeneous open datasets in a knowledge graph to increase quality and trust and to unlock the potential of open data for companies.
Our paper “Leveraging Market Research Techniques in IS – A Review of Conjoint Analysis in IS Research” co-authored by Dana Naous and Christine Legner was nominated as Best Theory Development Paper at the International Conference on Information Systems (ICIS 2017) in Seoul. The paper summarizes results of the SNF project “Don’t Guess, Simulate! – Understanding User Preferences for Cloud Services”.
ICIS is the most prestigious international conference in the Information Systems discipline, and provides a forum for networking and sharing of latest ideas and highest calibre scientific work amongst the IS profession. The ICIS Conference Proceedings are available for download in the AIS Electronic Library.
With the increasing importance of mass-market information systems (IS), understanding individual user preferences for IS design and adoption is essential. However, this has been a challenging task due to the complexity of balancing functional, non-functional, and economic requirements. Conjoint analysis (CA), from marketing research, estimates user preferences by measuring tradeoffs between products attributes. Although the number of studies applying CA in IS has increased in the past years, we still lack fundamental discussion on its use in our discipline. We review the existing CA studies in IS with regard to the application areas and methodological choices along the CA procedure. Based on this review, we develop a reference framework for application areas in IS that serves as foundation for future studies. We argue that CA can be leveraged in requirements management, business model design, and systems evaluation. As future research opportunities, we see domain-specific adaptations e.g., user preference models.
On December 5, Kenny Lienhard successfully defended his PhD thesis entitled “Routines in Patient Care: Essays on the Design and Use of the Information Technology Artifact”. Members of the jury were Prof. Christine Legner as supervisor, Prof. Mauro Cherubini as internal expert, Prof. Tobias Mettler (IDHEAP) and Prof. Albert Boonstra (University of Groningen) as external expert, and Prof. Olivier Cadot as president of the jury. Kenny’s dissertation comprises 6 essays, thereof 5 published conference articles (among them 1 x ECIS and 2 x ICIS) as well as 1 manuscript for an IS journal.
The BISA team congratulates Kenny on his successful PhD defense!
More than 250 participants attended the first Swiss Data Day on November 9, 2017 at EPFL in Lausanne. Professor Christine Legner held a keynote presentation on “Managing Data as a Strategic Resource – Foundation of the Digital and Data-Driven Enterprise”. She addressed the need for organisations to think about data and its management in new ways, as they engage in the digital and data-driven transformation of their business. The presentation concludes with three recommendations: (1) assess data’s business value and impact, (2) measure and improve data quality, and (3) democratize data and support data citizenship.
The presentation is available for download on Slideshare.
The partnership between HEC Lausanne, CDQ AG, Nestlé and Swisscom on the project “Open Data to Business – Data App Store for the discovery, integration and use of open data in business environments” has been granted a research & development fund by the Commission of Technology and Innovation (CTI) of the Swiss Confederation. This innovative R&D project starts in January 2018 and will be finalized in December 2019.
For more information about the project, please check out the project description or contact Andreas Lang.
We welcome two new researchers in our team – Andreas Lang and Martin Fadler!
Andreas Lang joined the CC CDQ research team on May 1, 2017. Previously, he worked at the European Research Council of the European Commission in the support to the Scientific Council. Andreas received his M.Sc. in Life Sciences and Technologies at the EPFL and proposed in his Master’s thesis a computational model for explaining the psychological phenomenon of illusory conjunctions. Before, he completed his B.Sc. in Computer Science at the University of Geneva with a Bachelor’s thesis on Neuro Evolutionary Meta-Optimization.
Andreas is currently working in the CTI project “Open Data to Business – Data App Store for the discovery, integration and use of open data in business environments”. Its aim is to link heterogeneous open datasets in a knowledge graph in order to increase quality and trust and to unlock the potential of open data for companies.
Martin Fadler started on September 1, 2017 as PhD student in the CC CDQ research team. Previously, he worked in a data-driven startup as a Data Scientist where he learned to manage and build data products with advanced analysis methods and technologies. Mr. Fadler received a M.Sc. in ICT Systems and Management from the Technical University of Berlin, Germany, and a B.Sc. in Industrial Engineering from the Technical University of Clausthal, Germany.
In his research, Martin Fadler will focus on data management for Big Data and AI. He also investigates machine learning techniques within the data management lifecycle.
In a joint effort, comprising more than 15 European companies as well as researchers from three European universities, the Competence Center Corporate Data Quality (CC CDQ) has developed a reference model for data management in the digital economy: the Data Excellence Model. It offers support and guidance for practitioners in the implementation of data management by defining major design areas, while at the same time supporting the transformation into a digital and data-driven company.
Given the understanding of data as a strategic resource for the digital economy, the reference model specifies design areas of data management in three categories: goals, enablers, and results, which are interlinked in a continuous improvement cycle.
- goals break down the overall aim and purpose of data management by outlining necessary business capabilities and data management capabilities and explicating them in the form of a data strategy;
- enablers help to achieve the goals specified with regard to six design areas: people, roles and responsibilities; performance management; processes and methods; data architecture; data lifecycle; and data applications;
- results indicate to what extent the goals are achieved in terms of two quanti-fiable aspects: data excellence and business value; and
- continuous improvement allows adjustment of goals and enablers, ensuring the dynamic nature of the model.
More information can be found on the CC CDQ website.
Schaeffler, the German technology company and automotive
supplier, is the winner of the 2016 CDQ Good Practice Award.
The CDQ Good Practice Award was launched in 2013 as a joint initiative of the Competence Center Corporate Data Quality (CC CDQ) and the European Foundation for Quality Management (EFQM) for acknowledging world-class corporate data management initiatives. The international jury, consisting of data management experts from research and practice, ranked Schaeffler’s good practice top. Joining Schaeffler in this year’s final round of the competition were Emmi, the leading milk processing company in Switzerland, presenting their approach
towards an integrated master data management, and Merck, the German healthcare and life science specialist, showcasing their concept of exploiting the benefits of data analytics for data management.
The good practice presented by Schaeffler illustrates how the company systematically evolved its master data management initiative starting in 2009. A self-assessment conducted two years ago revealed that Schaeffler had successfully built up capabilities and raised the level of maturity in all relevant areas of master data management. Aspects still demanding for substantial improvement were successfully tackled by Schaeffler during the past two years. The company has continued to develop its data management strategy further and communicate this strategy across the entire group. Among other things, Schaeffler uses performance indicators to measure and sustainably improve the quality of its data. Furthermore, the company defined clear roles and processes for data maintenance and implemented appropriate data models and metadata models. All these measures combined have led to a reduction in service processing time and to a continuous improvement of data quality (customer master data processing time has been reduced by 60 %, for example). “Schaeffler is pursuing a strategy of profitable growth, based on key success factors such as quality, technology, and innovation. The mission of our master data management department is to support this endeavor by providing data of high quality in order to ensure efficient business processes,” said Markus Rahm.
We are proud to announce that the manuscript “Designing Business Models for cloud platforms” co-authored by Andrea Giessmann and Christine Legner has been published in the Information Systems Journal (ISJ). ISJ is one of the top IS management journals and part of the Senior Scholars’ Basket of Journals.
Abstract: Platform as a service (PaaS) has become a strategic option for software vendors who expect to benefit from value co-creation with partners by developing complementary components and applications. In reality, however, established and new software vendors are battling to redefine their offering to embrace PaaS. They face the challenges of transforming, configuring and calibrating their PaaS business models to align them with existing business models, customer expectations and competitive pressures. This motivates our research question: How can software providers design viable business models for PaaS? Our study develops a design theory for PaaS business models. This theory is grounded on a 12-month action design research study at one of the largest global software companies (here called Alpha) with mixed PaaS experiences in the past. Our primary research contribution is a set of design principles that guide software providers to define a viable PaaS business model in order to create a flourishing software ecosystem for their cloud platform. By synthesizing prescriptive knowledge related to business model design for emerging cloud platforms, our study advances PaaS research towards the existing body of research on software platforms and business models.
The full article is available here.