Open Digital Platform For Smart Honey Value Chains: Identifying Data Through Beekeeping Expertise

The necessity for research on smart honey value chains is increasingly evident as consumer demand for transparency, quality, and sustainability grows (Dossou et al., 2022; Hidalgo et al., 2020; Rünzel et al., 2021). Advances in digital technology are transforming the ways in which trust is built and sustained within value chain relationships, including in the honey sector (Finlay-Smits et al., 2023; Rünzel et al., 2021). Within the international project "Trustworthy and Sustainable Open Platform for Smart Honey Value Chains ," efforts are being made to develop a reliable, sustainable, and adaptive digital open data platform to facilitate the efficient implementation of smart honey value chains. Stakeholders and the data they provide and utilize are crucial components of these chains, highlighting the importance of thorough data mapping and analysis (Dossou et al., 2022; Sparacino et al., 2022). Despite the recognized need, existing literature lacks research on data mapping in smart honey value chains and the creation of a comprehensive data value map (Agerskans e al., 2023; Dossou et al., 2022) that includes data acquisition, data integration, data analysis, and data delivery (Nagle & Sammon, 2017). This gap underscores the importance of developing a detailed understanding of the types of data necessary for these chains and the methods for effectively acquiring and managing this data. This article focuses on the first component of the data value map: data acquisition. The primary objective is to identify the types of data related to beekeeping activities that need to be acquired and collected within the honey value chain. By addressing this objective, the research aims to provide a foundational framework for future studies and practical applications in smart honey value chains. The research methodology involved a comprehensive review of scientific and grey literature and the application of design thinking principles to develop an initial framework for data acquisition in the honey value chain. This preliminary framework was then validated through qualitative research, specifically interviews conducted with 30 beekeeping experts in Poland. The interviews aimed to gather detailed insights into the specific data required for a robust and transparent honey value chain. The key findings of the study confirmed that all collected data in a smart honey value chain can be categorized into four main groups: Beekeeper Description, Apiary Description, Honey Description and Quality, Apiary Management, and Beekeeping Regulations and Standards. Within each group, specific data points were identified that need to be collected to ensure transparency and trust among stakeholders, and to enhance the quality of honey. The research contributes to the academic field by providing a structured framework for data acquisition in smart honey value chains, addressing a significant gap in the literature. This framework serves as a basis for further research on data integration, analysis, and delivery within the value chain. In practical terms, the findings offer valuable insights for stakeholders involved in honey production, enabling them to implement more effective data collection and management practices. By adopting these practices, the honey industry can improve product quality, ensure regulatory compliance, and build greater trust with consumers.

Acknowledgment The TOP4HoneyChains: Trustable and Sustainable Open Platform for Smart Honey Value Chains project has received funding from the European Union's Horizon 2020 research and innovation programme under the ERA-NET CO-FUND ICT-AGRI-FOOD (2022 Joint Call), under Grant Agreement No. 862665. The project is co-funded by: 1. The National Centre for Research and Development (NCBIR) in Poland, under the agreement ICTAGRIFOOD/II/67/TOP4HoneyChain/2023; 2. Türkiye–TÜBİTAK, under the agreement 123N225; 3. The National Institute of Agricultural Technology (INTA) in Argentina, under the agreement Smart Honey Value Chain Analysis; 4. Ministry of Education and Science, Republic of Latvia.