News
We are excited to announce Manfred Reichert as a keynote speaker!
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The deadline for the submission of papers has been extended to March 18, 2018.
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Glad to have BDA 2018 accepted as a workshop at CAiSE 2018
BDA 2018 - June 11, 2018
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Sunset over Tallinn by Ilya Khamushkin (CC BY-SA 2.0)
Programme
Monday, June 11 | ||||
09:00 – 09:15 | Welcome |
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Session I | 09:15 – 10:30 | Sanam Ahmad, Syed Irtaza Muzaffar, Khurram Shahzad | Using BPM Frameworks for Identifying Customer Feedback about Process Performance | |
Johannes Schneider, Joshua Handali and Jan Vom Brocke | Metrics for Increasing Trust in Big Data Analytics | |||
Coffee Break | ||||
Keynote | 11:00 – 12:00 | Manfred Reichert | Process-Driven Data Collection in Mobile and Distributed Environments: Challenges, Methods, Technologies | |
Session II | 12:00 – 12:30 | Artem Mateush, Rajesh Sharma, Marlon Dumas, | Building Payment Classification Models From Rules and Crowdsourced Labels: A Case Study Closing | |
12:30 – 12:45 | Closing | |||
Lunch Break |
Keynote
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Manfred Reichert (Ulm University) |
Process-Driven Data Collection in Mobile and Distributed Environments: Challenges, Methods, Technologies |
| Abstract: Data collection is the process of gathering and measuring information on targeted variables in a systematic manner, which then shall enable researchers to answer specific questions and to evaluate outcomes. Regardless of the field of study, accurate and honest data collection is crucial for maintaining the integrity of research. Both the selection of appropriate data collection instruments and clearly delineated instructions for their correct use (i.e. workflows) are essential. Due to the emergence of smart mobile devices, in addition, mobile crowdsensing has become an appealing method to collect data in the large scale. Finally, data collection increasingly draws on sensor data available through the Internet of Things. The goal for all kinds of data collection is to capture quality evidence such that data analyses lead to convincing and credible answers to the respective research questions. This keynote presentation deals with sophisticated data collection processes and data analysis scenarios from the real world (e.g., healthcare, Industry 4.0, and sustainability). It discusses characteristic challenges of these real-world applications and gives insights into selected technologies and methods (e.g., process-driven data collection instruments, mobile crowdsensing) for the support of advanced data collection processes. |
Bio: Manfred is Professor of Computer Science and Director of the Databases and Information Systems Institute at Ulm University, Germany. Prior to this appointment, he was Associate Professor at the University of Twente. His research interests span across the fields of digital services, information systems, business process management, and process automation. Amongst others, his ongoing projects deal with large-scale data collection and data analysis scenarios in domains like healthcare, industry, and sustainability. Currently, he collaborates with several large companies, including Daimler, BMW and Uhlmann Pac Systems. Manfred was PC co-chair of the BPM’08, CoopIS’11, and EDOC’13 conferences, and general chair of the BPM’09 and EDOC’14 conferences as well as the BPM’15 workshops. He is corecipient of several best paper awards (e.g. OTM’05, EDOC’08, AIMS‘17) and received the BPM Test of Time Award at the BPM’13 conference. Finally, he is co-founder of the AristaFlow Ltd. and co-author of a Springer book on process flexibility. |
About BDA
Objectives
Data analytics currently represents a revolution that cannot be missed. It is significantly transforming and changing various aspects of our modern life including the way we live, socialize, think, work, and do business. There is increasing interest in the application of data analytics in many industries (e.g., retail, manufacturing, finance) and business functions (e.g. marketing, customer relationship management, supply chain management). In fact, data is becoming a key ingredient for informing every step and element of modern business. According to market research by IBM and Gartner, business data analytics is today’s top priority for CIOs. IDC predicted that the worldwide market for big data and business analytics solutions will increase by more than 50 percent between 2015 and 2019, to more than $187 billion. And according to Gartner, by 2018 more than half of the world’s largest organizations will be applying advanced analytics solutions to large datasets by 2018. With the continued emergence and growth of massive and complex business data, the opportunities for applying data analytics for harnessing the knowledge inside the growing business data lakes – for example to improve service, reduce costs, enhance revenue, and manage risks – are expanding. At the same time, the adoption of analytics solutions for extracting value from big data is associated with enormous financial investments for firms, with a total-cost-of-ownership often ranging between $10-50 million.
The aim of this workshop is to discuss opportunities and challenges of applying data analytics in business. The workshop targets researchers interested in all aspects of developing effective data analytics solutions and evaluating applications in different business domains. The workshop invites original research contributions as well as reports on prototype systems from research communities and industry, dealing with different theoretical and applied aspects of business data analytics. Submitted papers will be evaluated on the basis of significance, originality, technical quality, and exposition. Papers should clearly establish the research contribution, and relation to previous research.
Subject and Topics
The workshop is open for a broad range of subjects around business data analytics. Possible topics include, but are not limited to:
- Models and methods for storing, managing and querying massive and heterogeneous business data.
- Models and methods for integrating and analyzing heterogeneous business data.
- Models and methods for continuous analysis of business data.
- Methods for deriving actionable insights from business data.
- Models and methods for exploiting big data systems on developing effective business data analytics.
- Methods for developing usable tools for business data analytics.
- Advanced applications and tools for business data analytics in different domains
Organization
BDA 2018 will take place in Tallinn, Estonia, as part of the workshop programme of the 30th International Conference on Advanced Information Systems Engineering (CAiSE).
Submissions
Submission Guidelines
BDA 2018 calls for research paper submissions of up to 15 pages. The paper shall be submitted as PDFs and follow Springer's LNBIP formatting guidelines. All accepted submissions will be published in the LNBIP volume of the CAiSE 2018 workshop proceedings.Submission Site
Submissions have to be made via easychair.org.
Important dates
Submission of papers
Notification of acceptance
Final version of papers
Workshop
People
Program Committee Co-Chairs
- Oliver Müller, IT University of Copenhagen, Denmark
- Sherif Sakr, King Saud bin Abdulaziz University for Health Sciences, Saudi Arabia
- Matthias Weidlich, Humboldt-Universität zu Berlin, Germany
Program Committee
- Ahmed Awad, Cairo University, Egypt
- Amin Beheshti, The University of New South Wales, Australia
- Florian Daniel, Politecnico di Milano, Italy
- Claudio Di Ciccio, WU Vienna, Austria
- Boudewijn Van Dongen, Eindhoven University of Technology, The Netherlands
- Marcelo Fantinato, University of São Paulo, Brasil
- Daniela Grigori, Laboratoire LAMSADE, University Paris-Dauphine, France
- Christian Janiesch, University of Würzburg, Germany
- Henrik Leopold, Vrije Universiteit Amsterdam, The Netherlands
- Fabrizio Maria Maggi, University of Tartu, Estonia
- Hamid Motahari, IBM Research, USA
- Raghava Rao Mukkamala, Copenhagen Business School, Denmark
- Manfred Reichert, University of Ulm, Germany
- Johannes Schneider, University of Liechtenstein, Liechtenstein
- Michael Sheng, Macquarie University, Australia
- Farouk Toumani, Blaise Pascal University, France