Abstract. The research focuses on the challenges and requirements of heterogeneous research data management in environmental sciences. Environmental research involves diverse data types, and effective management and integration of these data sets are crucial in managing heterogeneous environmental research data. The issue at hand is the lack of specific guidance on how to select and plan an appropriate data management practice to address the challenges of handling and integrating diverse data types in environmental research. The objective of the research is to identify the issues associated with the current data storage approach in research data management and determine the requirements for an appropriate system to address these challenges. The research adopts a qualitative approach, utilizing semi-structured interviews to collect data. Content analysis is employed to analyze the gathered data and identify relevant issues and requirements.

The study reveals various issues in the current data management process, including inconsistencies in data treatment, the risk of unintentional data deletion, loss of knowledge due to staff turnover, lack of guidelines, and data scattered across multiple locations. The requirements identified through interviews emphasize the need for a data management system that integrates automation, open access, centralized storage, online electronic lab notes, systematic data management, secure repositories, reduced hardware storage, and version control with metadata support. The research identifies the current challenges faced by researchers in heterogeneous data management and compiles a list of requirements for an effective solution. The findings contribute to existing knowledge on research-related problems and provide a foundation for developing tailored solutions to meet the specific needs of researchers in environmental sciences.