Workshop content:
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Data analytics is becoming increasingly important in science and practice. However, organisations and companies are increasingly facing challenges as well as opportunities. In particular, the combination of structured and unstructured data, data engineering and different analysis and visualisation methods are major challenges. The frequent lack of expertise in these areas is also a critical stumbling block. By using and analysing data, processes in various areas can be improved or even newly implemented, but often only with the help of external service providers or internal competence centres. Newer technologies, e.g. from the field of Generative AI / Large Language Models and the combination with established approaches (e.g. agents, ontologies, etc.) represent further new opportunities and challenges for companies. The workshop aims to present and discuss scientific findings on the opportunities and challenges to show the community a contribution to this important topic in science and practice.


Possible topics or subject areas (not limited to these):
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- Development and utilisation of data analytics solutions
- Opportunities and challenges of data analytics in service and production companies
- Organisational anchoring of the development and operation of data analytics solutions (analytics centre of excellence, data science teams, external service providers)
- Utilisation of differently structured data (unstructured, semi-structured, structured) in data analytics projects
- Usage of Agentic AI
- Use of NLP, generative AI / LLMs, chatbots, Q&A systems, object recognition, voice analytics, simulation for data analysis
- Process Mining and Process Intelligence
- Adoption, acceptance and comprehensibility of data analytics solutions, explainable AI
- Ensuring data quality in analytics projects
- Data visualisation, communication and data storytelling in data analytics projects
- Experiences with Vibe Coding and AI Slop in Data Analytics
- Use of synthetic data for training data analytics solutions
- Compliance and legal aspects of data analytics solutions
- Specifics of data analytics for SMEs
- Going live and operation, maintenance of data analytics solutions
- Aspects of project management for data analytics projects (e.g. agile, PoC, MVP, lighthouse projects, etc.)
- Technological aspects of data analytics (e.g. new database technologies or access methods)
- Ecological impact and sustainability aspects and resource consumption of data analytics, Green AI
-Etc.

Both theoretical and practice-oriented contributions related to data analytics are welcome.


Dates and deadlines:
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May 7, 2026: Deadline for the submission of contributions
July 1, 2026: Notification
July 12, 2026: Submission of the revised contributions
September 2026 (22-25) tbd: Workshop (planned in presence and hybrid)


Submissions and contribution formats:
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Full paper (max. 10 pages)
Short paper (max. 6 pages)
Practical contributions / discussion papers / demo papers / vision papers (4 pages)

All information incl. references, title page, etc.

The contributions can be submitted either in English or in German.

Blind Review – Please do not add author information for the initial submission.


Publication:
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After successful peer-reviewed review, a publication in the conference proceedings of Informatik 2026 is planned. The planned proceedings will be published in the ranked series „Lecture Notes in Informatics“ (LNI) of the Gesellschaft für Informatik (GI).

The LNI series of the GI is listed in relevant rankings (e.g. VHB JQ3: C; WKWI Orientierungsliste B; SJR).

The author template and guidelines can be found here:
https://data-analytics-research.de/

Following the author’s template and guidelines is mandatory. Unfortunately, deviations from them cannot be considered.

Blind Review – Please do not add author information for the initial submission.


Conference information:
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Informatiktagung 2026 of the GI (Annual Meeting of the German Computer Science Society (GI))– „Informatik Festival“ @ the university of Dresden:

https://informatik2026.gi.de

Venue is at the University of Dresden, Germany.

Some sessions of the conference will be only in German.


Organizers:
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Prof. Dr. Barbara Keller, DHBW Stuttgart, Germany
Prof. Dr. Friedrich Augenstein, DHBW Stuttgart, Germany
Prof. Dr.-Ing. Michael Möhring, Reutlingen University, Germany


PC Members:
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see: https://data-analytics-research.de/