Data Science in Health, Ecology and Commerce
(DSH)

Warsaw, Poland, 17–20 September, 2023

Data Science in Health, Ecology and Commerce is a forum on all forms of data analysis, data economics, information systems and data based research, focusing on the interaction of those three fields. Here, data-driven solutions can be generated by understanding complex real-world (health) related problems, critical thinking and analytics to derive knowledge from (big) data. The past years have shown a forthcoming interest on innovative data technology and analytics solutions that link and utilize large amounts of data across individual digital ecosystems. First applications scenarios in the field of health, smart cities or agriculture merge data from various IoT devices, social media or application systems and demonstrate the great potential for gaining new insights, supporting decisions or providing smarter services. Together with inexpensive sensors and computing power we are ahead of a world that bases its decisions on data. However, we are only at the beginning of this journey and we need to further explore the required methods and technologies as well as the potential application fields and the impact on society and economy. This endeavor needs the knowledge of researchers from different fields applying diverse perspectives and using different methodological directions to find a way to grasp and fully understand the power and opportunities of data science.

This Thematic Track is jointly organized by WIG2, the Scientific Institute for health economics and health service research, the Information Systems Institute of Leipzig University and the Helmholtz Center for Environmental Research.

Topics

We embrace a rich array of issues on data science and offer a platform for research from diverse methodological directions, including quantitative empirical research as well as qualitative contributions. We welcome research from a medical, technological, economic, political and societal perspective. The topics of interest therefore include but are not limited to:

Data analysis in health, ecology and commerce
Data analysis in climate change adaptation
Data analysis in commerce
(Health) Data management
Health economics
5G(/6G) in health
Data economics
Data integration
Semantic data analysis
AI based data analysis
Data based health service research
Smart Service Engineering
Integrating data in integrated care
AI in integrated care
Spatial health economics
Risk adjustment and Predictive modelling
Privacy in data science

Thematic Track organizers

Franczyk, Bogdan, University of Leipzig, Germany
Militzer-Horstmann, Carsta, WIG2 Institute for health economics and health service research, Leipzig, Germany
Häckl, Dennis, University of Leipzig, Germany and WIG2 Institute for health economics and health service research, Leipzig, Germany
Bumberger, Jan, Helmholtz‐Centre for Environmental Research – UFZ, Germany
Reinhold, Olaf, University of Leipzig / Social CRM Research Center, Germany

Contact: dsh@fedcsis.org

Submission rules

Authors should submit their papers as Postscript, PDF or MSWord files.
The total length of a paper should not exceed 12 pages IEEE style (including tables, figures and references). More pages can be added, for an additional fee (see details). IEEE style templates are available here.
Papers will be refereed and accepted on the basis of their scientific merit and relevance to the Topical Area.
Preprints containing accepted papers will be published online.
Only papers presented at the conference will be published in Conference Proceedings and submitted for inclusion in the IEEE Xplore® database.
Conference proceedings will be published in a volume with ISBN, ISSN and DOI numbers and posted at the conference WWW site.
Conference proceedings will be submitted for indexation according to information here.
Organizers reserve right to move accepted papers between FedCSIS Tracks.