Deutsch Intern
Lernen. Wissen. Daten. Analysen. (LWDA) 2024

CfP for Business Intelligence and Analytics (WSBIA 2024)

of the GI e.V. Specialist Group Business Intelligence & Analytics as part of the conference Learning.Knowledge.Data.Analyses. LWDA 2024 23 th of September 2024 – 25th of September 2024 at the Julius-Maximilians-University (JMU) on the topic

New impulses from the interplay of data management and artificial intelligence

Description of the contents

More than a year after the ChatGPT moment, the dust is beginning to settle and first insights into the business potential and the limitations of generative artificial intelligence (GenAI) are beginning to emerge. One of the first lessons is the an old one: As with other analytical techniques, a reliable data management is a critical factor for the successful application of the technology. Even the best AI cannot fix unclear, contradictory, outdated, or erroneous data. Going even further, a clean metadata, well-designed data models, clear semantics and transformation paths as well as a comprehensive data and analytics governance are no longer only crucial for human actors, but also for new AI-based solutions and agents. In principle, these findings can be applied to all types of analytical solutions. And new solutions increase the pressure to open domains that have so far eluded an analytical access due to their high degree of technical specificity, their complex or missing structure or their low accessibility. If you combine these developments with the rise of self-service analytics solutions and federated approaches to both data management (data mesh, data fabric, data spaces) and data analysis (federated machine learning), the considerable challenges - but also the significant potential - that successful data management has for AI and analytics become apparent.

Conversely, AI and analytics technologies are increasingly becoming enablers for handling and analysing data. Whether for the interpretation of reports and analyses or the design of the queries and analyses s behind them, an automated development of analysis solutions, the handling of data quality management, or the automatic generation and interpretation of metadata, AI promises considerable gains in efficiency and effectiveness. At the same time, it opens up a previously untapped field of completely new analytical applications, the development and evaluation of which, however, also require new concepts for management and governance. The workshop is dedicated to these and neighbouring topics.

Aim of the workshop and submission formats

The aim of the workshop is to present, discuss and compare innovative research approaches and research results from the field of Business Intelligence and Analytics/AI (BIA) (full paper). In addition to original research results, interim results from research projects, concrete research ideas and new methodological approaches (research in progress) can also be presented. Previously published contributions and interim results (re-submissions) that are presented for further development and to find partners for follow-up work can also be submitted. Independent of this, poster submissions on prototypes, design artefacts and practical contributions are welcome.

Orientation and target group

This year's workshop is once again focused on supporting the initiation of new research projects, the active preparation of high-quality publications and the initiation of possible collaborations. The target group includes doctoral students in particular. An exchange with the parallel events is explicitly desired and encouraged.

Examples of relevant topics:

  • The interaction between GenAI and data management/BIA

  • Concepts for integrating AI and data management - in terms of content, technology and organisation

  • AI-supported BIA - new approaches for data management and data analysis

  • BIA and AI as the basis of digital business models / BIA in the digital transformation / BIA in the innovation process

  • Business applications of artificial intelligence and deep learning: mono- and multimodal large language models (transformer networks, JAMBA models, KANs etc.), convolutional neural networks, deep recurrent neural networks and LSTMs, deep reinforcement learning, deep autoencoder, generative adversarial networks, capsule networks, etc.

  • Innovative applications of natural language processing/large language models/text mining, process mining, social network analysis, geo-analysis and co.

  • Design, management and governance of agent-based AI solutions

  • Integration and evaluation of customer data; GDPR-compliant BIA, concepts for anonymisation and pseudonomisation in the BIA & AI context

  • Integration of analytics and AI in business processes and integrated approaches for the management of corresponding solutions

  • Innovative BIA application domains (e.g. BIA in logistics, BIA and smart farming, BIA in the energy sector / internet of energy, in the water industry, BIA and healthcare, BIA in public administration)

  • BIA in the context of the ‘Internet of Things’ and ‘Industry 4.0’ topics

  • Organisation of BIA and AI, data science teams, BIA & AI Competence Center

  • Agility for BIA and AI and agility through BIA and AI

  • BIA and AI governance, development and operational concepts and tool support

  • Self-service analytics/self-service ML and sourcing concepts

  • Operationalisation and operation of ML models; model lifecycle management

  • Cloud-based BIA: BIA with microservices, containers, function as a service / serverless computing, Model-asaS

  • DataOps, MLOps and AIOps

  • AutoML and augmented analytics

  • Explainable AI, ethical AI and compliance-compliant AI

  • BIA and Big Data / NoSQL

  • Metadata management, data quality and master data management in the BIA environment

  • BIA across company boundaries, data sharing & data brokers, data cooperatives

Further additions are welcome.

Important dates

  • Submissions until: 01/07/2024

  • Notification of acceptance / review: 31/07/2024

  • Camera-ready versions of the accepted paper 20 August 2024

  • Workshop and presentation at the LWDA conference: from 23 to 25 September 2024

Submissions

  • All submissions must be based on the CEUR-WS format guidelines: ceur-ws.org/Vol-XXX/CEURART.zip.

  • German-language and English-language contributions are both welcome.

  • Full paper comprise 10-12 pages (without bibliography) and contain (mostly) completed research activities.

  • Research in progress papers (short paper) comprise 4-9 pages (without bibliography) in which research ideas and new design projects are presented. The procedure, method and data basis should be explained. Initial results should be recognisable.

  • In the case of poster papers on prototypes and design artefacts and for practical contributions, the creation process should be completed and the assumptions should be presented transparently.

  • Re-submissions are summarised on a total of 1-2 pages, in which reference is made to the existing publication(s).

  • Each submission will be reviewed twice.

  • Submissions are made via EasyChair easychair.org/account2/signin

  • If a paper is accepted for presentation and publication (optional), at least one author must register for the LDWA 2024 conference and present the paper in person.

Publication

Full and short papers with a length of at least 5 pages can be published in the LWDA proceedings (excluding re-submissions): CEUR-Workshop-Proceedings: http://ceur-ws.org

Programme Committee

  • Dr Henning Baars, University of Stuttgart

  • Prof. Dr Carsten Felden, TU Bergakademie Freiberg

  • Dr Ralf Finger, Information Works

  • PD Dr Sebastian Olbrich, Deloitte

Track Chair

Dr Henning Baars

Chair of ABWL and Business Informatics I - University of Stuttgart

Keplerstr. 17 - 70174 Stuttgart, Phone: 0711 - 685 83037

E-mail: henning.baars@bwi.uni-stuttgart.de