Conceptualizing Data Ecosystems for Industrial Food Production

Calvin Rix; Hannah Stein; Qiang Chen; Jana Frank; Wolfgang Maaß

In: 23rd IEEE International Conference on Business Informatics. IEEE Conference on Business Informatics (CBI-2021), Leading the Digital Transformation, September 1-3, Bolzano/Virtual, Italy, Springer, 2021.


Industrial food production represents one of the largest industries, accounting for a share of ten percent of the world's gross domestic product. At the same time, it is responsible for 26 percent of global greenhouse gas emissions. Due to increasing CO2 taxes and population's call for sustainability and CO2 reduction, it is facing challenges in terms of economic profitability and stakeholder demands. These challenges could partly be overcome by participating in data ecosystems in which data are refined as data products, understood, exchanged and monetized as economic goods. Despite large amounts of data, collected parenthetically along the value chain in food production, potentials of data analytics and data ecosystems are only marginally exploited. Food production mainly focuses on traditional, product-centric business models. This work shows the conceptualization of a data ecosystem for food production, enabling data-based business models. Therefore, resources, actors, roles and underlying relationships of future ecosystem are analyzed. Building on these, corresponding architectural and analytical artifacts that support data ecosystem exploitation are presented. The profitability of a food production data ecosystem is exemplified by applying data analytics to compressor data, which reveals high potentials for CO2 reduction.


Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence