@inproceedings{ThelenEderMelzeretal., author = {Thelen, Simon and Eder, Friedrich and Melzer, Matthias and Nunes, Danilo Weber and Stadler, Michael and Rechenauer, Christian and Obergrießer, Mathias and Jubeh, Ruben and Volbert, Klaus and D{\"u}nnweber, Jan}, title = {A Slim Digital Twin For A Smart City And Its Residents}, series = {SOICT '23: Proceedings of the 12th International Symposium on Information and Communication Technology, 2023, Hi Chi Minh, Vietnam}, booktitle = {SOICT '23: Proceedings of the 12th International Symposium on Information and Communication Technology, 2023, Hi Chi Minh, Vietnam}, publisher = {ACM}, isbn = {979-8-4007-0891-6}, doi = {10.1145/3628797.3628936}, pages = {8 -- 15}, abstract = {In the engineering domain, representing real-world objects using a body of data, called a digital twin, which is frequently updated by "live" measurements, has shown various advantages over tradi- tional modelling and simulation techniques. Consequently, urban planners have a strong interest in digital twin technology, since it provides them with a laboratory for experimenting with data before making far-reaching decisions. Realizing these decisions involves the work of professionals in the architecture, engineering and construction (AEC) domain who nowadays collaborate via the methodology of building information modeling (BIM). At the same time, the citizen plays an integral role both in the data acquisition phase, while also being a beneficiary of the improved resource management strategies. In this paper, we present a prototype for a "digital energy twin" platform we designed in cooperation with the city of Regensburg. We show how our extensible platform de- sign can satisfy the various requirements of multiple user groups through a series of data processing solutions and visualizations, in- dicating valuable design and implementation guidelines for future projects. In particular, we focus on two example use cases concern- ing building electricity monitoring and BIM. By implementing a flexible data processing architecture we can involve citizens in the data acquisition process, meeting the demands of modern users regarding maximum transparency in the handling of their data.}, language = {en} } @book{ScheidVogl, author = {Scheid, Sandro and Vogl, Stefanie}, title = {Data Science: Grundlagen, Methode und Modelle der Statistik}, publisher = {Hanser}, isbn = {978-3-446-46663-0}, doi = {10.3139/9783446470019}, pages = {359}, subject = {Big Data}, language = {de} } @article{KratzerWestnerStrahringer, author = {Kratzer, Simon and Westner, Markus and Strahringer, Susanne}, title = {Traction with fraction: Strategic IS management in SMEs through Fractional CIOs}, series = {International Journal of Information Systems and Project Management}, volume = {12}, journal = {International Journal of Information Systems and Project Management}, number = {1}, issn = {2182-7788}, doi = {10.12821/ijispm120101}, pages = {5 -- 16}, abstract = {Small and medium-sized enterprises (SMEs) increasingly need to manage nformation technology (IT) effectively in order to remain competitive. However, compared to larger organizations, SMEs often face challenges in terms of resources and employer attractiveness, and regularly do not have the need to employ a Chief Information Officer (CIO) on a full-time basis. To address this issue, a growing number of global experts have begun to provide CIO services on a part-time basis for multiple clients simultaneously. This approach allows SMEs to tap into the expertise of experienced IT leaders at a fraction of the cost and without committing to long-term arrangements. While these professionals, known as "Fractional CIOs", have proven their value in the field, there has been a lack of academic research on this emerging trend. Therefore, we carried out a comprehensive research project between 2020 and 2023, involving 62 Fractional CIOs from 10 countries. The research produced a definition, different types of engagements, and success factors for Fractional CIOs and their engagements. This paper summarizes these findings for a wider audience of academics and practitioners.}, language = {en} } @article{DahmenWeiklBogenberger, author = {Dahmen, Victoria and Weikl, Simone and Bogenberger, Klaus}, title = {Interpretable Machine Learning for Mode Choice Modeling on Tracking-Based Revealed Preference Data}, series = {Transportation Research Record: Journal of the Transportation Research Board}, volume = {2678}, journal = {Transportation Research Record: Journal of the Transportation Research Board}, number = {11}, publisher = {SAGE Publications}, issn = {0361-1981}, doi = {10.1177/03611981241246973}, pages = {2075 -- 2091}, abstract = {Mode choice modeling is imperative for predicting and understanding travel behavior. For this purpose, machine learning (ML) models have increasingly been applied to stated preference and traditional self-recorded revealed preference data with promising results, particularly for extreme gradient boosting (XGBoost) and random forest (RF) models. Because of the rise in the use of tracking-based smartphone applications for recording travel behavior, we address the important and unprecedented task of testing these ML models for mode choice modeling on such data. Furthermore, as ML approaches are still criticized for leading to results that are hard to understand, we consider it essential to provide an in-depth interpretability analysis of the best-performing model. Our results show that the XGBoost and RF models far outperform a conventional multinomial logit model, both overall and for each mode. The interpretability analysis using the Shapley additive explanations approach reveals that the XGBoost model can be explained well at the overall and mode level. In addition, we demonstrate how to analyze individual predictions. Lastly, a sensitivity analysis gives insight into the relative importance of different data sources, sample size, and user involvement. We conclude that the XGBoost model performs best, while also being explainable. Insights generated by such models can be used, for instance, to predict mode choice decisions for arbitrary origin-destination pairs to see which impacts infrastructural changes would have on the mode share.}, language = {en} } @article{BrosigGraeubigStrahringeretal., author = {Brosig, Christoph and Gr{\"a}ubig, Dix M. and Strahringer, Susanne and Westner, Markus}, title = {Prerequisites and Causal Recipes for Manufacturers' IT-Enabled Service Innovation Success}, series = {Communications of the Association for Information Systems}, volume = {55}, journal = {Communications of the Association for Information Systems}, publisher = {Association for Information Systems, AIS}, issn = {1529-3181}, doi = {10.17705/1CAIS.05509}, pages = {205 -- 256}, abstract = {For manufacturing firms, success in innovating IT-enabled services is a critical antecedent to benefit from digital servitization of their business models. Digital servitization literature has explored mechanisms for success in innovating IT-enabled services, indicating that the phenomenon is multifaceted and needs to be explained from multiple theoretical perspectives. We derive a conceptual model for success in innovating IT-enabled services covering its multifaceted nature by referring to knowledge-based and organizational control theory. We test this model using qualitative cases of IT-enabled service innovation initiatives in manufacturing firms and use set-theoretic analyses to account for the multifaceted nature of the phenomenon. The necessary condition analysis yields that a certain degree of service innovation capabilities is a prerequisite for success. With the results of a qualitative comparative analysis, we obtain five solution terms as causal recipes for success in innovating IT-enabled services. Our results contribute to research by offering a theory-based approach that explains the multiplicity of success in IT-enabled service innovation. Practitioners benefit from our results by understanding prerequisites and causal recipes for success while learning from unsuccessful initiatives in innovating IT-enabled services of manufacturing firms. Our study is also an example of how to rigorously calibrate qualitative data using a structured approach.}, language = {en} } @inproceedings{LeglerJajjaVolbert, author = {Legler, Katharina and Jajja, Muhammad Sheheryar and Volbert, Klaus}, title = {Analysis and Design of Smart Components in Digital Energy Twins}, series = {Proceedings of the 10th International Conference on Internet of Things, Big Data and Security., Porto, Portugal April 6-8, 2025}, booktitle = {Proceedings of the 10th International Conference on Internet of Things, Big Data and Security., Porto, Portugal April 6-8, 2025}, publisher = {SciTePress - Science and Technology Publications}, address = {Set{\´u}bal, Portugal}, isbn = {978-989-758-750-4}, doi = {10.5220/0013289900003944}, pages = {263 -- 272}, abstract = {The energy crisis, energy demand growth, and dependence on fossil fuels worldwide have made urgent action necessary for us to seek sustainability in energy production and use. Digital technologies, especially Digital Energy Twins, have immense potential to reduce energy consumption, thereby reducing environmental impacts, particularly in the building sector. This paper presents the development of a digital energy twin that supports sustainable energy consumption analysis and optimization. Our study begins with a comprehensive analysis of the energy consumption data, the weather data, and the building plans as a solid basis for the analysis. We identify key energy consumption trends and patterns across different timescales and device-specific details that could be optimized, such as base load consumption and device-specific inefficiencies. A key part of our work is forecasting energy consumption using time series models, such as the ARIMA model, which promises to be useful in identify ing patterns for improving energy efficiency. Overall, our study provides valuable insights into energy optimization and could form the base for further advances in digital energy twins at OTH Regensburg, helping to contribute to its sustainable development goals and smart campus initiatives.}, language = {en} } @inproceedings{SchildgenHeinz, author = {Schildgen, Johannes and Heinz, Florian}, title = {A Showcase of LLMs in Action: SQL Generation from Natural Language (Demo Paper)}, series = {Datenbanksysteme f{\"u}r Business, Technologie und Web - Workshopband (BTW 2025)}, booktitle = {Datenbanksysteme f{\"u}r Business, Technologie und Web - Workshopband (BTW 2025)}, publisher = {Gesellschaft f{\"u}r Informatik}, address = {Bonn}, doi = {10.18420/BTW2025-47}, pages = {819 -- 825}, abstract = {Today, large language models are a very efficient tool for human-computer interaction using natural language. Chatbots like ChatGPT and their corresponding APIs can be used to solve a large variety of tasks that are provided in human-comprehensible sentences, for example generating SQL queries. Executing spoken SQL queries in a database system poses a challenge, because the various syntactical details of SQL are usually not provided verbally. Here, the LLM can help to augment the recognized raw query with the syntax elements needed for successful execution. Furthermore, the correct spelling of table and column names can be derived from the database schema provided in the LLM prompt. This work showcases four use cases in which LLMs assist in querying database systems: (1) A plugin for phpMyAdmin for voice-query input in natural language, (2) a chart generator, (3) an Alexa skill, and (4) a speech-controlled action game SQL Invaders.}, language = {en} } @inproceedings{HeinzSchildgen, author = {Heinz, Florian and Schildgen, Johannes}, title = {SQLinked - A Hybrid Approach for Local and Database-Remote Program Execution}, series = {Datenbanksysteme f{\"u}r Business, Technologie und Web - Workshopband (BTW 2025)}, booktitle = {Datenbanksysteme f{\"u}r Business, Technologie und Web - Workshopband (BTW 2025)}, publisher = {Gesellschaft f{\"u}r Informatik}, address = {Bonn}, doi = {10.18420/BTW2025-128}, pages = {257 -- 263}, abstract = {When working with today's relational databases, there is usually a clear boundary between the database server and the application, that interfaces with the database system using the query language SQL. The concept of stored procedures allows to move complex parts of the business logic into the database server for various reasons, as, for instance, to reduce the latency of ELT processes that involve several database queries building on each other like distributing records into tables according to their attribute values. Creating and maintaining such stored procedures can be a challenging task, however. The idea pursued in this paper is to create a programming language, as well as a compilation and execution environment that allows the user to mark parts of the application code for being automatically compiled to and later be executed as a stored procedure in the database instead of the execution environment of the actual application. This blurs the border between database and application and provides a natural and maintenance-friendly way for offloading latency sensitive parts of the code to the database system.}, language = {en} } @inproceedings{PenzkoferBaumann, author = {Penzkofer, Vinzent and Baumann, Timo}, title = {Evaluating and Fine-Tuning Retrieval-Augmented Language Models to Generate Text With Accurate Citations}, series = {Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024), September 10-13, 2024, Vienna, Austria}, booktitle = {Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024), September 10-13, 2024, Vienna, Austria}, publisher = {Association for Computational Linguistics}, organization = {Austrian Research Institute for Artificial Intelligence}, pages = {57 -- 64}, abstract = {Retrieval Augmented Generation (RAG) is becoming an essential tool for easily accessing large amounts of textual information. However, it is often challenging to determine whether the information in a given response originates from the retrieved context, the training, or is a result of hallucination. Our contribution in this area is twofold. Firstly, we demonstrate how existing datasets for information retrieval evaluation can be used to assess the ability of Large Language Models (LLMs) to correctly identify relevantsources. Our findings indicate that there are notable discrepancies in the performance of different current LLMs in this task. Secondly, we utilise the datasets and metrics for citation evaluation to enhance the citation quality of small open-weight LLMs through fine-tuning. We achieve significant performance gains in this task, matching the results of much larger models.}, language = {en} } @inproceedings{BaumannEllerGagarina, author = {Baumann, Timo and Eller, Korbinian and Gagarina, Natalia}, title = {BERT-based Annotation of Oral Texts Elicited via Multilingual Assessment Instrument for Narratives}, series = {Proceedings of the the 6th Workshop on Narrative Understanding (WNU), November 12th to November 16th 2024, Miami, Florida, USA}, booktitle = {Proceedings of the the 6th Workshop on Narrative Understanding (WNU), November 12th to November 16th 2024, Miami, Florida, USA}, editor = {Lal, Yash Kumar and Clark, Elizabeth and Iyyer, Mohit and Chaturvedi, Snigdha and Brei, Anneliese and Brahman, Faeze and Chandu, Khyathi Raghavi}, publisher = {Association for Computational Linguistics}, address = {Stroudsburg, PA, USA}, doi = {10.18653/v1/2024.wnu-1.16}, pages = {99 -- 104}, abstract = {We investigate how NLP can help annotate the structure and complexity of oral narrative texts elicited via the Multilingual Assessment Instrument for Narratives (MAIN). MAIN is a theory-based tool designed to evaluate the narrative abilities of children who are learning one or more languages from birth or early in their development. It provides a standardized way to measure how well children can comprehend and produce stories across different languages and referential norms for children between 3 and 12 years old. MAIN has been adapted to over ninety languages and is used in over 65 countries. The MAIN analysis focuses on story structure and story complexity which are typically evaluated manually based on scoring sheets. We here investigate the automation of this process using BERT-based classification which already yields promising results.}, language = {en} }