Competitive Niche of Archival Data and Its Optimization Strategies

Abstract: In the era of big data, the value and significance of archival data have become increasingly prominent. However, the explicit or implicit competition among different types of archival data hinders the full realization of their value as a production factor. Based on niche theory, this study investigates the competitive niche of archival data from three fundamental dimensions—resources, functions, and time-space, through two core indicators: niche breadth and niche overlap. This approach enables a comprehensive understanding of the “ecostate”, “ecorole”, and “capability” of archival data competition. In response to current challenges, such as insufficient archival data resources, high overlap of interdisciplinary talent, weak value realization of archival data as a productive factor, regional disparities, and digital space barriers, this paper proposes optimization strategies led by archival institutions to systematically adjust the niche of archival data across the dimensions of resources, functions, and time-space. Ultimately, the goal is to enhance the co-opetitive capacity of archival data populations, thereby facilitating the adaptation and evolution of archival data species at a higher level.