Interactive Business Intelligence & Analytics Systems

 

Research Activities

 
Multimodal COVID-19 Dashboards

Dashboards became very popular during the COVID-19 pandemic to help people better understand the spread of the virus. But dashboards are complex user interfaces and less tech-savvy users may struggle to access the information they need. Why not give users the opportunity to use both mouse and natural language to navigate the dashboard?

 

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Conversational Assistance in Forecasting Support Systems

Accurate forecasting decisions are important for many supply chain-based companies. However, decision makers often tend to trust their own beliefs more than advice from forecasting support systems (FSS), which prepare forecasts and support the forecasting process. Therefore, we explore how providing conversational assistance can help decision makers better understand the FSS and its forecasts in order to make more accurate forecasting decisions.

 

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Demystifying Job Roles in Data Science: A Text Mining Approach

The continuing proliferation of data science these days is causing organizations to reassess their workforce demands. Simultaneously, it is unclear what types of job roles, knowledge, skills, and abilities make up this field and how they differ. This ambiguity is generating a misleading myth around the data scientist’s role.

 

 

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Designing a Self-Service Analytics System for Supply Base Optimization

Reducing the number of suppliers – a process known as supply base optimization – is crucial for organizations to achieve better quality, higher service levels, and lower prices. The buyers in the role of the business analyst in corporate purchasing departments are responsible for this process and usually consider various selection criteria.

 

 

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Self-Service Data Provisioning and Preparation in Data Lakes

With the ongoing trend of building central data lakes in enterprises, it is unclear how data is replicated from source systems. Often, data analysts have to rebuild SAP transactions to analyze data from the central data lake. In doing so, they must identify column names from SAP in the data lake and join tables.

 

 

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Does This Explanation Help? How Lay Users Visually Attend, Trust, and Understand Local Explanations of Model-agnostic XAI Methods

Artificial Intelligence (AI) is playing an increasingly important role in high-stake domains. Nevertheless, the effectiveness of AI systems in these domains is limited by their inability to explain their decisions to human users. Recently, there has been a surge of interest in Explainable Artificial Intelligence (XAI) by researchers and practitioners seeking to increase the transparency of AI. In particular, extensive research in XAI has focused on developing model-agnostic methods that are capable of explaining local instances of any predictive model, which provides higher applicability and scalability due to their decoupling from the predictive model. However, the user perspective has played a less important role so far in XAI research resulting in a lack of understanding of how users visually attended and perceived model-agnostic local explanations.

 

 

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Professor

Alexander Mädche  Prof. Dr. Alexander Mädche

 

Team Lead

Dr. Ulrich Gnewuch  Dr. Ulrich Gnewuch

 

Doctoral Researchers

Miguel Angel Meza Martinez  Miguel Martinez

 

Jonas Gunklach  Jonas Gunklach

 

Marcel Ruoff  Marcel Ruoff

 

Research Assistants

Interested in our topics? Send us an email now and join our team as a research assistant!

 

 

Partners

 

 

 

 

 

 

Publications


2022
The Impact of Conversational Assistance on the Effective Use of Forecasting Support Systems: A Framed Field Experiment : Short Paper
Haug, S.; Ruoff, M.; Gnewuch, U.
2022. ICIS 2022 Proceedings. Vol.: 2, 1–9, AIS eLibrary (AISeL)
Designing a Self-Service Analytics System for Transportation Supplier Selection
Michalczyk, S.; Breitling, N.; Mädche, A.
2022. Intelligent Information Systems : CAiSE Forum 2022, Leuven, Belgium, June 6–10, 2022, Proceedings. Ed.: J. De Weerdt, 64–72, Springer
ONYX - User Interfaces for Assisting in Interactive Task Learning for Natural Language Interfaces of Data Visualization Tools
Ruoff, M.; Myers, B. A.; Maedche, A.
2022. CHI EA ’22: CHI Conference on Human Factors in Computing Systems Extended Abstracts: April 30–May 5, 2022 ; New Orleans, LA, USA. Ed.: S. Barbosa, Art.-Nr.: 433, Association for Computing Machinery (ACM). doi:10.1145/3491101.3519793
Towards Automatic Parsing of Structured Visual Content through the Use of Synthetic Data
Scholch, L.; Steinhauser, J.; Beichter, M.; Seibold, C.; Yang, K.; Knaeble, M.; Schwarz, T.; Maedche, A.; Stiefelhagen, R.
2022. 2022 26th International Conference on Pattern Recognition (ICPR), 1607–1613, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICPR56361.2022.9956453
Multiexperience
Gnewuch, U.; Ruoff, M.; Peukert, C.; Maedche, A.
2022. Business & Information Systems Engineering. doi:10.1007/s12599-022-00766-8
Accessible Chemical Structural Formulas Through Interactive Document Labeling
Knaeble, M.; Chen, Z.; Schwarz, T.; Sailer, G.; Yang, K.; Stiefelhagen, R.; Maedche, A.
2022. Computers Helping People with Special Needs – 18th International Conference, ICCHP-AAATE 2022, Lecco, Italy, July 11–15, 2022, Proceedings, Part I. Ed.: K. Miesenberger, 38–46, Springer International Publishing. doi:10.1007/978-3-031-08648-9_6
Paintings, not Noise - The Role of Variety and Self-Determination in Labeling Work and its Effects on Psychological and Performance Outcomes
Knaeble, M.; Nadj, M.; Maedche, A.
2022. CHI 2022 Workshop - Self-Determination Theory in HCI: Shaping a Research Agenda
Toward User-adaptive Interactive Labeling on Crowdsourcing Platforms
Knaeble, M.; Nadj, M.; Maedche, A.; Loewe, N.
2022. CHI 2022 Workshop - REGROW: Reimagining Global Crowdsourcing for Better Human-AI Collaboration
2021
Designing a Self-service Analytics System for Supply Base Optimization
Michalczyk, S.; Nadj, M.; Beier, H.; Mädche, A.
2021. CAiSE ’21- 33rd International Conference on Advanced Information Systems Engineering, MELBOURNE, 28 JUNE 2021 - 2 JULY 2021, 154–161. doi:10.1007/978-3-030-79108-7_18
Ensuring a Robust Multimodal Conversational User Interface during Maintenance Work
Fleiner, C.; Riedel, T.; Beigl, M.; Ruoff, M.
2021. MuC ’21: Mensch und Computer 2021. Ed.: S. Schneegass, 79–91, Association for Computing Machinery (ACM). doi:10.1145/3473856.3473871
An Interactive Machine Learning System for Image Advertisements
Foerste, M.; Nadj, M.; Knaeble, M.; Maedche, A.; Gehrmann, L.; Stahl, F.
2021. Mensch und Computer 2021 (MuC ’21), Ingolstadt, 5.-8.9.2021, 574–577, Association for Computing Machinery (ACM). doi:10.1145/3473856.3474027
Designing Conversational Dashboards for Effective Use in Crisis Response
Ruoff, M.; Gnewuch, U.
2021. ECIS 2021 Proceedings - European Conference on Information Systems. Human Values Crisis in a Digitizing World, Article no: 1698, Association for Information Systems (AIS)
Designing Multimodal BI&A Systems for Co-Located Team Interactions
Ruoff, M.; Gnewuch, U.
2021. ECIS 2021 Proceedings - European Conference on Information Systems. Human Values Crisis in a Digitizing World, Article no: 1610, Association for Information Systems (AIS)
Demystifying Job Roles in Data Science: A Text Mining Approach
Michalczyk, S.; Nadj, M.; Mädche, A.; Gröger, C.
2021. ECIS 2021 Proceedings - European Conference on Information Systems. Human Values Crisis in a Digitizing World, Paper Number: 1622, Association for Information Systems (AIS)
2020
The effect of interactive analytical dashboard features on situation awareness and task performance
Nadj, M.; Maedche, A.; Schieder, C.
2020. Decision support systems, 135, Art.Nr.: 113322. doi:10.1016/j.dss.2020.113322
Oracle or Teacher? A Systematic Overview of Research on Interactive Labeling for Machine Learning
Knaeble, M.; Nadj, M.; Maedche, A.
2020. 15. Internationale Tagung Wirtschaftsinformatik (WI 2020), Potsdam, 9 - 11 März 2020, 2–16, GITO Verlag. doi:10.30844/wi_2020_a1-knaeble
Designing Multimodal BI&A Systems for Face-to-Face Team Interactions
Ruoff, M.; Gnewuch, U.; Alexander Maedche
2020. HCI/MIS Workshop 2020 – The 19th Annual Pre-ICIS Workshop on HCI Research in MIS, December 12, 2020, (One-Day Online Workshop), AIS eLibrary (AISeL)
Designing an Analytical Information Systems Engineering Method
Michalczyk, S.; Scheu, S.
2020. Proceedings of the 28th European Conference on Information Systems (ECIS), An Online AIS Conference (Marrakesh, Marokko), June 15-17, 2020, Art.Nr. 57, AIS eLibrary (AISeL)
A State-of-the-Art Overview and Future Research Avenues of Self-Service Business Intelligence and Analytics
Michalczyk, S.; Nadj, M.; Azarfar, D.; Mädche, A.; Gröger, C.
2020. Proceedings of the 28th European Conference on Information Systems (ECIS), An Online AIS Conference (Marrakesh, Marokko), June 15-17, 2020, Art.Nr. 46, AIS eLibrary (AISeL)
Power to the Oracle? Design Principles for Interactive Labeling Systems in Machine Learning
Nadj, M.; Knaeble, M.; Li, M. X.; Maedche, A.
2020. Künstliche Intelligenz, 34, 131–142. doi:10.1007/s13218-020-00634-1
2019
Towards an Integrative Theoretical Framework of Interactive Machine Learning Systems
Meza Martínez, M. A.; Nadj, M.; Maedche, A.
2019. ECIS 2019 proceedings . 27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden, June 8-14, 2019. Research Papers, Paper: 172, AIS eLibrary (AISeL)
2018
Designing Uncertainty-Aware Dashboards for Software Development Projects
Knaeble, M.; Nadj, M.; Maedche, A.
2018. 13th International Conference on Design Science Research in Information Systems and Technology (DESRIST), Chennai, IND, June 3-6, 2018, 1–15