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Abstract This document presents a practice-oriented framework for understanding research data environments within academic departments. It is designed for situations in which a Data Steward or similar research support role enters a department without prior domain familiarity and must develop an accurate, practice-based understanding of how research data is generated, used, managed, and interpreted. The framework emphasizes structured engagement with researchers and leadership, focusing on observed workflows, tool usage, and data realities rather than formal policy descriptions alone. It supports the development of a stakeholder-informed overview, a synthesized map of practices and challenges, and a preliminary basis for prioritizing targeted support. Applied within the Department of Mechanical Engineering at TU/e, this approach reflects the need to bridge institutional research data management (RDM) services with the actual conditions of research practice. The framework provides a repeatable method for aligning support structures with research workflows while remaining sensitive to disciplinary diversity, technical variation, and organizational complexity. Authorship and Provenance Statement This document is based on applied professional experience across multiple institutional contexts and reflects a synthesized account of observed research data practices. It is grounded in direct engagement with researchers, research support staff, and institutional systems, rather than purely theoretical construction.